var bibbase_data = {"data":"<img src=\"//bibbase.org/img/ajax-loader.gif\" id=\"spinner\"\n  style=\"display: none;\" alt=\"Loading..\" />\n\n<div id=\"bibbase\">\n\n  <script type=\"text/javascript\">\n    var bibbase = {\n      params: {\"jsonp\":\"1\",\"host\":\"bibbase.org\"},\n      data: [{\"title\":\"Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"homogeneous turbulence,isotropic turbulence,turbulence theory\",\"volume\":\"900\",\"websites\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F\",\"publisher\":\"Cambridge University Press\",\"id\":\"8cc0f47e-27fc-38bb-a4af-8911bc26fe10\",\"created\":\"2021-04-09T15:22:51.557Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:22:51.557Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic differential equation. In comparison with previously proposed stochastic models, the obtained process is infinitely differentiable at a given finite Reynolds number, and its second-order statistical properties converge to those of an Ornstein-Uhlenbeck process in the infinite Reynolds number limit. In this limit, it exhibits furthermore intermittent scaling properties, as they can be quantified using higher-order statistics. To achieve this, we begin with generalizing the two-layered embedded stochastic process of Sawford (Phys. Fluids A, vol. 3 (6), 1991, pp. 1577-1586) by considering an infinite number of layers. We then study, both theoretically and numerically, the convergence towards a smooth (i.e. infinitely differentiable) Gaussian process. To include intermittent corrections, we follow similar considerations as for the multifractal random walk of Bacry et al. (Phys. Rev. E, vol. 64, 2001, 026103). We derive in an exact manner the statistical properties of this process, and compare them with those estimated from Lagrangian trajectories extracted from numerically simulated turbulent flows. Key predictions of the multifractal formalism regarding the acceleration correlation function and high-order structure functions are also derived. Through these predictions, we understand phenomenologically peculiar behaviours of the fluctuations in the dissipative range, that are not reproduced by our stochastic process. The proposed theoretical method regarding the modelling of infinitely differentiability opens the route to the full stochastic modelling of velocity, including the peculiar action of viscosity on the very fine scales.\",\"bibtype\":\"article\",\"author\":\"Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent\",\"doi\":\"10.1017/jfm.2020.495\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes},\\n type = {article},\\n year = {2020},\\n keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},\\n volume = {900},\\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F},\\n publisher = {Cambridge University Press},\\n id = {8cc0f47e-27fc-38bb-a4af-8911bc26fe10},\\n created = {2021-04-09T15:22:51.557Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:22:51.557Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic differential equation. In comparison with previously proposed stochastic models, the obtained process is infinitely differentiable at a given finite Reynolds number, and its second-order statistical properties converge to those of an Ornstein-Uhlenbeck process in the infinite Reynolds number limit. In this limit, it exhibits furthermore intermittent scaling properties, as they can be quantified using higher-order statistics. To achieve this, we begin with generalizing the two-layered embedded stochastic process of Sawford (Phys. Fluids A, vol. 3 (6), 1991, pp. 1577-1586) by considering an infinite number of layers. We then study, both theoretically and numerically, the convergence towards a smooth (i.e. infinitely differentiable) Gaussian process. To include intermittent corrections, we follow similar considerations as for the multifractal random walk of Bacry et al. (Phys. Rev. E, vol. 64, 2001, 026103). We derive in an exact manner the statistical properties of this process, and compare them with those estimated from Lagrangian trajectories extracted from numerically simulated turbulent flows. Key predictions of the multifractal formalism regarding the acceleration correlation function and high-order structure functions are also derived. Through these predictions, we understand phenomenologically peculiar behaviours of the fluctuations in the dissipative range, that are not reproduced by our stochastic process. The proposed theoretical method regarding the modelling of infinitely differentiability opens the route to the full stochastic modelling of velocity, including the peculiar action of viscosity on the very fine scales.},\\n bibtype = {article},\\n author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},\\n doi = {10.1017/jfm.2020.495},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Viggiano,  B.\",\"Friedrich,  J.\",\"Volk,  R.\",\"Bourgoin,  M.\",\"Cal,  R., B.\",\"Chevillard,  L.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\",\"role\":\"author\",\"keyword\":[\"homogeneous turbulence\",\"isotropic turbulence\",\"turbulence theory\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":11,\"html\":\"\"},{\"title\":\"Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data\",\"pages\":\"45-56\",\"volume\":\"88\",\"month\":\"5\",\"publisher\":\"Elsevier Ltd\",\"day\":\"1\",\"id\":\"2163eeea-5277-3538-b932-9bca1745b1b6\",\"created\":\"2021-04-09T15:22:57.667Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:22:57.667Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.\",\"bibtype\":\"article\",\"author\":\"Díaz, Jose and Marton, Fabio and Gobbetti, Enrico\",\"doi\":\"10.1016/j.cag.2020.03.002\",\"journal\":\"Computers and Graphics (Pergamon)\",\"bibtex\":\"@article{\\n title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},\\n type = {article},\\n year = {2020},\\n keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},\\n pages = {45-56},\\n volume = {88},\\n month = {5},\\n publisher = {Elsevier Ltd},\\n day = {1},\\n id = {2163eeea-5277-3538-b932-9bca1745b1b6},\\n created = {2021-04-09T15:22:57.667Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:22:57.667Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},\\n bibtype = {article},\\n author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},\\n doi = {10.1016/j.cag.2020.03.002},\\n journal = {Computers and Graphics (Pergamon)}\\n}\",\"author_short\":[\"Díaz,  J.\",\"Marton,  F.\",\"Gobbetti,  E.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Compression\",\"Direct volume rendering\",\"Learned dictionary\",\"Sparse coding\",\"Time-varying data\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":7,\"html\":\"\"},{\"title\":\"ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER\",\"type\":\"techreport\",\"year\":\"2020\",\"month\":\"2\",\"day\":\"26\",\"id\":\"11ddc1a2-9ba3-3585-8fff-4772389fff79\",\"created\":\"2021-04-09T15:22:58.110Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:07.834Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions. Many systems in the physical sciences are governed by Partial Differential Equations (PDEs). Enforcing these as hard constraints, we show, are inefficient in conventional frameworks due to the high dimensionality of the generated fields. To this end, we propose the use of a novel differentiable spectral projection layer for neural networks that efficiently enforces spatial PDE constraints using spectral methods, yet is fully differentiable, allowing for its use as a layer within Convolutional Neural Networks (CNNs) during end-to-end training. We show that its computational cost is cheaper than a single convolution layer. We apply it to an important class of physical systems-incompressible turbulent flows, where the divergence-free PDE constraint is required. We train a 3D Conditional Generative Adversarial Network (CGAN) for turbulent flow superresolution efficiently, while guaranteeing the spatial PDE constraint of zero divergence. Furthermore, our empirical results show that the model produces realistic flow statistics when trained with hard constraints imposed via the proposed novel differentiable spectral projection layer, as compared to soft constrained and unconstrained counterparts.\",\"bibtype\":\"techreport\",\"author\":\"Kashinath, Karthik and Marcus, Philip\",\"bibtex\":\"@techreport{\\n title = {ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER},\\n type = {techreport},\\n year = {2020},\\n month = {2},\\n day = {26},\\n id = {11ddc1a2-9ba3-3585-8fff-4772389fff79},\\n created = {2021-04-09T15:22:58.110Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:07.834Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions. Many systems in the physical sciences are governed by Partial Differential Equations (PDEs). Enforcing these as hard constraints, we show, are inefficient in conventional frameworks due to the high dimensionality of the generated fields. To this end, we propose the use of a novel differentiable spectral projection layer for neural networks that efficiently enforces spatial PDE constraints using spectral methods, yet is fully differentiable, allowing for its use as a layer within Convolutional Neural Networks (CNNs) during end-to-end training. We show that its computational cost is cheaper than a single convolution layer. We apply it to an important class of physical systems-incompressible turbulent flows, where the divergence-free PDE constraint is required. We train a 3D Conditional Generative Adversarial Network (CGAN) for turbulent flow superresolution efficiently, while guaranteeing the spatial PDE constraint of zero divergence. Furthermore, our empirical results show that the model produces realistic flow statistics when trained with hard constraints imposed via the proposed novel differentiable spectral projection layer, as compared to soft constrained and unconstrained counterparts.},\\n bibtype = {techreport},\\n author = {Kashinath, Karthik and Marcus, Philip}\\n}\",\"author_short\":[\"Kashinath,  K.\",\"Marcus,  P.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/354e1d2d-d745-37f7-0d56-c9b7a49cd905/full_text.pdf.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Speed-direction description of turbulent flows\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"115128\",\"volume\":\"32\",\"websites\":\"http://aip.scitation.org/doi/10.1063/5.0031218\",\"month\":\"11\",\"publisher\":\"American Institute of Physics Inc.\",\"day\":\"1\",\"id\":\"61e5a178-e0bc-3b06-82b2-2ec7fe5c9107\",\"created\":\"2021-04-09T15:22:58.545Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:08.486Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this note, we introduce speed and direction variables to describe the motion of incompressible viscous fluid. Fluid velocity u is decomposed into u = ur, with u = |u| and r = u/|u|. We consider a directional split of the Navier-Stokes equations into a coupled system of equations for u and for r. The equation for u is particularly simple but solely maintains the energy balance of the system. Under the assumption of a weak correlation between fluctuations in speed and direction in a developed turbulent flow, we further illustrate the application of u-r variables to describe mean statistics of a shear turbulence. The standard (full) Reynolds stress tensor does not appear in a resulting equation for the mean flow profile.\",\"bibtype\":\"article\",\"author\":\"Olshanskii, Maxim A.\",\"doi\":\"10.1063/5.0031218\",\"journal\":\"Physics of Fluids\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Speed-direction description of turbulent flows},\\n type = {article},\\n year = {2020},\\n pages = {115128},\\n volume = {32},\\n websites = {http://aip.scitation.org/doi/10.1063/5.0031218},\\n month = {11},\\n publisher = {American Institute of Physics Inc.},\\n day = {1},\\n id = {61e5a178-e0bc-3b06-82b2-2ec7fe5c9107},\\n created = {2021-04-09T15:22:58.545Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:08.486Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this note, we introduce speed and direction variables to describe the motion of incompressible viscous fluid. Fluid velocity u is decomposed into u = ur, with u = |u| and r = u/|u|. We consider a directional split of the Navier-Stokes equations into a coupled system of equations for u and for r. The equation for u is particularly simple but solely maintains the energy balance of the system. Under the assumption of a weak correlation between fluctuations in speed and direction in a developed turbulent flow, we further illustrate the application of u-r variables to describe mean statistics of a shear turbulence. The standard (full) Reynolds stress tensor does not appear in a resulting equation for the mean flow profile.},\\n bibtype = {article},\\n author = {Olshanskii, Maxim A.},\\n doi = {10.1063/5.0031218},\\n journal = {Physics of Fluids},\\n number = {11}\\n}\",\"author_short\":[\"Olshanskii,  M., A.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0f028845-ab84-e2a7-3c74-426d30dcddb5/full_text.pdf.pdf\",\"Website\":\"http://aip.scitation.org/doi/10.1063/5.0031218\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"olshanskii-speeddirectiondescriptionofturbulentflows-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A take on wake modeling of turbines based on deep learning\",\"type\":\"inproceedings\",\"year\":\"2020\",\"keywords\":\"CNN,Computational fluid dynamics,GAN,Offshore renewable energy systems,Reduced-order modeling,Turbulent flow field,Unsupervised learning\",\"volume\":\"2020-August\",\"month\":\"10\",\"publisher\":\"American Society of Mechanical Engineers (ASME)\",\"day\":\"13\",\"id\":\"7aafb4af-eba4-32ce-a7dc-e2914e92ed36\",\"created\":\"2021-04-09T15:22:59.016Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:22:59.016Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Analyzing real-world engineering problems such as wake modeling of wind/ocean current turbines are known to be complex and challenging. The multivariable nature of these problems requires either the implementation of computational analyses under certain simplifying assumptions or conducting experiments for a limited number of scenarios. Hence, there is always several fundamental features missed in understanding the key players in determining the complex turbulent velocity fields within the wake of turbines. It becomes more critical when studying the optimization of wind/ocean renewable farms with more than one turbine to determine the true power density or cost of energy. Machine learning (ML) algorithms suggest promising complementary solutions to the existing physics-based (e.g. wind farm wake modeling) techniques. Implementation of conventional ML algorithms that require long-term historical data is either not feasible in many real-case applications or very expensive and time-consuming. Moreover, there are often infinite features in dataset with complex relation between them. It makes the tasks of feature selection and model tuning more challenging. In this work, a cross-domain study of physics and ML models is performed to show the need of integration of these domains. The key achievement of this work is two-fold: first, suggesting a group of emerging generative models (e.g. Generative Adversarial Networks) in the wake modeling domain; second, reducing the computational cost by demanding either smaller or no simulation dataset.\",\"bibtype\":\"inproceedings\",\"author\":\"Ziaei, Dorsa and Goudarzi, Navid\",\"doi\":\"10.1115/POWER2020-16950\",\"booktitle\":\"American Society of Mechanical Engineers, Power Division (Publication) POWER\",\"bibtex\":\"@inproceedings{\\n title = {A take on wake modeling of turbines based on deep learning},\\n type = {inproceedings},\\n year = {2020},\\n keywords = {CNN,Computational fluid dynamics,GAN,Offshore renewable energy systems,Reduced-order modeling,Turbulent flow field,Unsupervised learning},\\n volume = {2020-August},\\n month = {10},\\n publisher = {American Society of Mechanical Engineers (ASME)},\\n day = {13},\\n id = {7aafb4af-eba4-32ce-a7dc-e2914e92ed36},\\n created = {2021-04-09T15:22:59.016Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:22:59.016Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Analyzing real-world engineering problems such as wake modeling of wind/ocean current turbines are known to be complex and challenging. The multivariable nature of these problems requires either the implementation of computational analyses under certain simplifying assumptions or conducting experiments for a limited number of scenarios. Hence, there is always several fundamental features missed in understanding the key players in determining the complex turbulent velocity fields within the wake of turbines. It becomes more critical when studying the optimization of wind/ocean renewable farms with more than one turbine to determine the true power density or cost of energy. Machine learning (ML) algorithms suggest promising complementary solutions to the existing physics-based (e.g. wind farm wake modeling) techniques. Implementation of conventional ML algorithms that require long-term historical data is either not feasible in many real-case applications or very expensive and time-consuming. Moreover, there are often infinite features in dataset with complex relation between them. It makes the tasks of feature selection and model tuning more challenging. In this work, a cross-domain study of physics and ML models is performed to show the need of integration of these domains. The key achievement of this work is two-fold: first, suggesting a group of emerging generative models (e.g. Generative Adversarial Networks) in the wake modeling domain; second, reducing the computational cost by demanding either smaller or no simulation dataset.},\\n bibtype = {inproceedings},\\n author = {Ziaei, Dorsa and Goudarzi, Navid},\\n doi = {10.1115/POWER2020-16950},\\n booktitle = {American Society of Mechanical Engineers, Power Division (Publication) POWER}\\n}\",\"author_short\":[\"Ziaei,  D.\",\"Goudarzi,  N.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ziaei-goudarzi-atakeonwakemodelingofturbinesbasedondeeplearning-2020\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"CNN\",\"Computational fluid dynamics\",\"GAN\",\"Offshore renewable energy systems\",\"Reduced-order modeling\",\"Turbulent flow field\",\"Unsupervised learning\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Physics-informed machine learning,Separated flows,Turbulence modeling\",\"pages\":\"104431\",\"volume\":\"200\",\"month\":\"3\",\"publisher\":\"Elsevier Ltd\",\"day\":\"30\",\"id\":\"d382f22a-060d-3a0c-948f-2de090393e2d\",\"created\":\"2021-04-09T15:22:59.647Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:22:59.647Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Computational fluid dynamics models based on Reynolds-averaged Navier–Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant for decades. With recent advances in machine learning, data-driven turbulence models have become attractive alternatives worth further explorations. However, a major obstacle in the development of data-driven turbulence models is the lack of training data. In this work, we survey currently available public turbulent flow databases and conclude that they are inadequate for developing and validating data-driven models. Rather, we need more benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space for this purpose. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations. We further demonstrate the use of such a dataset by training a machine learning model that predicts Reynolds stress anisotropy based on a set of mean flow features. We expect the generated dataset, along with its design methodology and the example application presented herein, will facilitate development and comparison of future data-driven turbulence models.\",\"bibtype\":\"article\",\"author\":\"Xiao, Heng and Wu, Jin Long and Laizet, Sylvain and Duan, Lian\",\"doi\":\"10.1016/j.compfluid.2020.104431\",\"journal\":\"Computers and Fluids\",\"bibtex\":\"@article{\\n title = {Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations},\\n type = {article},\\n year = {2020},\\n keywords = {Physics-informed machine learning,Separated flows,Turbulence modeling},\\n pages = {104431},\\n volume = {200},\\n month = {3},\\n publisher = {Elsevier Ltd},\\n day = {30},\\n id = {d382f22a-060d-3a0c-948f-2de090393e2d},\\n created = {2021-04-09T15:22:59.647Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:22:59.647Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Computational fluid dynamics models based on Reynolds-averaged Navier–Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant for decades. With recent advances in machine learning, data-driven turbulence models have become attractive alternatives worth further explorations. However, a major obstacle in the development of data-driven turbulence models is the lack of training data. In this work, we survey currently available public turbulent flow databases and conclude that they are inadequate for developing and validating data-driven models. Rather, we need more benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space for this purpose. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations. We further demonstrate the use of such a dataset by training a machine learning model that predicts Reynolds stress anisotropy based on a set of mean flow features. We expect the generated dataset, along with its design methodology and the example application presented herein, will facilitate development and comparison of future data-driven turbulence models.},\\n bibtype = {article},\\n author = {Xiao, Heng and Wu, Jin Long and Laizet, Sylvain and Duan, Lian},\\n doi = {10.1016/j.compfluid.2020.104431},\\n journal = {Computers and Fluids}\\n}\",\"author_short\":[\"Xiao,  H.\",\"Wu,  J., L.\",\"Laizet,  S.\",\"Duan,  L.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"xiao-wu-laizet-duan-flowsoverperiodichillsofparameterizedgeometriesadatasetfordatadriventurbulencemodelingfromdirectsimulations-2020\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Physics-informed machine learning\",\"Separated flows\",\"Turbulence modeling\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing particle image velocimetry software based on a deep neural network\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Deep neural networks,Estimation of fluid motion,Particle image velocimetry\",\"pages\":\"359-376\",\"volume\":\"27\",\"websites\":\"http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\",\"publisher\":\"Begell House Inc.\",\"id\":\"855967e5-91dd-34db-92b6-6aa75f42ee99\",\"created\":\"2021-04-09T15:23:00.253Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:00.253Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"As an experimental technique for fluid mechanics, particle image velocimetry (PIV) can extract global and quantitative velocity field from images. With the development of artificial intelligence, designing PIV method based on deep learning is quite promising and worth exploring. First, in this paper, the authors introduce the optical flow neural network based on one proposed in the computer vision community. Second, a data set including particle images and the ground truth fluid motion is generated to train the parameters of the networks. This leads to a deep neural network for PIV which can provide estimation of dense motion (down to maximum one vector for one pixel) with the high degree of efficiency. The featuring of particle image extracted by the neural network is also investigated in this paper. It is found that feature matching improves the accuracy of esti-mation. The proposed network model is firstly evaluated by a synthetic image sequence of turbulent flow. An experiment measuring the flow over an aerofoil is used to validate the practicability. The experimental results indicate that compared with the traditional cross correlation method, the proposed deep neural network has advantages in accuracy, spatial resolution, and efficiency.\",\"bibtype\":\"article\",\"author\":\"Majewski, Wojciech and Wei, Runjie and Kumar, Vivek\",\"doi\":\"10.1615/JFlowVisImageProc.2020033180\",\"journal\":\"Journal of Flow Visualization and Image Processing\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Developing particle image velocimetry software based on a deep neural network},\\n type = {article},\\n year = {2020},\\n keywords = {Deep neural networks,Estimation of fluid motion,Particle image velocimetry},\\n pages = {359-376},\\n volume = {27},\\n websites = {http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},\\n publisher = {Begell House Inc.},\\n id = {855967e5-91dd-34db-92b6-6aa75f42ee99},\\n created = {2021-04-09T15:23:00.253Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:00.253Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {As an experimental technique for fluid mechanics, particle image velocimetry (PIV) can extract global and quantitative velocity field from images. With the development of artificial intelligence, designing PIV method based on deep learning is quite promising and worth exploring. First, in this paper, the authors introduce the optical flow neural network based on one proposed in the computer vision community. Second, a data set including particle images and the ground truth fluid motion is generated to train the parameters of the networks. This leads to a deep neural network for PIV which can provide estimation of dense motion (down to maximum one vector for one pixel) with the high degree of efficiency. The featuring of particle image extracted by the neural network is also investigated in this paper. It is found that feature matching improves the accuracy of esti-mation. The proposed network model is firstly evaluated by a synthetic image sequence of turbulent flow. An experiment measuring the flow over an aerofoil is used to validate the practicability. The experimental results indicate that compared with the traditional cross correlation method, the proposed deep neural network has advantages in accuracy, spatial resolution, and efficiency.},\\n bibtype = {article},\\n author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},\\n doi = {10.1615/JFlowVisImageProc.2020033180},\\n journal = {Journal of Flow Visualization and Image Processing},\\n number = {4}\\n}\",\"author_short\":[\"Majewski,  W.\",\"Wei,  R.\",\"Kumar,  V.\"],\"urls\":{\"Website\":\"http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\",\"role\":\"author\",\"keyword\":[\"Deep neural networks\",\"Estimation of fluid motion\",\"Particle image velocimetry\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":12,\"html\":\"\"},{\"title\":\"Dual channels of helicity cascade in turbulent flows\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"homogeneous turbulence,isotropic turbulence,turbulence theory\",\"volume\":\"894\",\"websites\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF\",\"publisher\":\"Cambridge University Press\",\"id\":\"08eeb047-4cd5-346d-9698-456857823601\",\"created\":\"2021-04-09T15:23:00.826Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:00.826Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulent flows. Through theoretical analyses, we find that there are two channels in the helicity cascade process, which differs dramatically from the traditional viewpoint. In this paper, we have conducted important research on the newly proposed dual-channel helicity cascade theory, including vortex dynamic processes, intermittent discrepancies, tensor geometries, etc. The first channel mainly originates from the vortex twisting process, and the second channel mainly originates from the vortex stretching process. Antisymmetric tensors are introduced to the derivations of dual-channel helicity cascade theory, and a complex rotation frame leads to a higher helicity transfer efficiency. By analysing data from direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other types of turbulent flows. The intermittency of the second channel is stronger than that of the first channel. In addition, we find a novel mechanism of hindered or even inverse energy cascades, which could be attributed to the second-channel helicity flux.\",\"bibtype\":\"article\",\"author\":\"Yan, Zheng and Li, Xinliang and Yu, Changping and Wang, Jianchun and Chen, Shiyi\",\"doi\":\"10.1017/jfm.2020.289\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Dual channels of helicity cascade in turbulent flows},\\n type = {article},\\n year = {2020},\\n keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},\\n volume = {894},\\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF},\\n publisher = {Cambridge University Press},\\n id = {08eeb047-4cd5-346d-9698-456857823601},\\n created = {2021-04-09T15:23:00.826Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:00.826Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulent flows. Through theoretical analyses, we find that there are two channels in the helicity cascade process, which differs dramatically from the traditional viewpoint. In this paper, we have conducted important research on the newly proposed dual-channel helicity cascade theory, including vortex dynamic processes, intermittent discrepancies, tensor geometries, etc. The first channel mainly originates from the vortex twisting process, and the second channel mainly originates from the vortex stretching process. Antisymmetric tensors are introduced to the derivations of dual-channel helicity cascade theory, and a complex rotation frame leads to a higher helicity transfer efficiency. By analysing data from direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other types of turbulent flows. The intermittency of the second channel is stronger than that of the first channel. In addition, we find a novel mechanism of hindered or even inverse energy cascades, which could be attributed to the second-channel helicity flux.},\\n bibtype = {article},\\n author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Wang, Jianchun and Chen, Shiyi},\\n doi = {10.1017/jfm.2020.289},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Yan,  Z.\",\"Li,  X.\",\"Yu,  C.\",\"Wang,  J.\",\"Chen,  S.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020\",\"role\":\"author\",\"keyword\":[\"homogeneous turbulence\",\"isotropic turbulence\",\"turbulence theory\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Data compression for turbulence databases using spatiotemporal subsampling and local resimulation\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"064607\",\"volume\":\"5\",\"websites\":\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607\",\"month\":\"6\",\"publisher\":\"American Physical Society\",\"day\":\"1\",\"id\":\"6ce865be-a713-3e73-83dc-be3fbb8bd04b\",\"created\":\"2021-04-09T15:23:01.423Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:01.423Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.\",\"bibtype\":\"article\",\"author\":\"Wu, Zhao and Zaki, Tamer A. and Meneveau, Charles\",\"doi\":\"10.1103/PhysRevFluids.5.064607\",\"journal\":\"Physical Review Fluids\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Data compression for turbulence databases using spatiotemporal subsampling and local resimulation},\\n type = {article},\\n year = {2020},\\n pages = {064607},\\n volume = {5},\\n websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607},\\n month = {6},\\n publisher = {American Physical Society},\\n day = {1},\\n id = {6ce865be-a713-3e73-83dc-be3fbb8bd04b},\\n created = {2021-04-09T15:23:01.423Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:01.423Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.},\\n bibtype = {article},\\n author = {Wu, Zhao and Zaki, Tamer A. and Meneveau, Charles},\\n doi = {10.1103/PhysRevFluids.5.064607},\\n journal = {Physical Review Fluids},\\n number = {6}\\n}\",\"author_short\":[\"Wu,  Z.\",\"Zaki,  T., A.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"16\",\"volume\":\"31\",\"websites\":\"https://doi.org/10.1088/1361-6501/ab848d\",\"month\":\"9\",\"publisher\":\"Institute of Physics Publishing\",\"day\":\"1\",\"id\":\"65d799a3-d02e-31c4-bf57-e23d965b9285\",\"created\":\"2021-04-09T15:23:01.980Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:10.041Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.\",\"bibtype\":\"article\",\"author\":\"Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian\",\"doi\":\"10.1088/1361-6501/ab848d\",\"journal\":\"Measurement Science and Technology\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},\\n type = {article},\\n year = {2020},\\n pages = {16},\\n volume = {31},\\n websites = {https://doi.org/10.1088/1361-6501/ab848d},\\n month = {9},\\n publisher = {Institute of Physics Publishing},\\n day = {1},\\n id = {65d799a3-d02e-31c4-bf57-e23d965b9285},\\n created = {2021-04-09T15:23:01.980Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:10.041Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},\\n bibtype = {article},\\n author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},\\n doi = {10.1088/1361-6501/ab848d},\\n journal = {Measurement Science and Technology},\\n number = {9}\\n}\",\"author_short\":[\"Ehlers,  F.\",\"Schröder,  A.\",\"Gesemann,  S.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5d5a4e3b-6739-43f7-3594-0abb38acecf1/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1088/1361-6501/ab848d\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":14,\"html\":\"\"},{\"title\":\"Learning dominant physical processes with data-driven balance models\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Applied mathematics,Computational science,Physics\",\"pages\":\"1-10\",\"volume\":\"12\",\"websites\":\"https://doi.org/10.1038/s41467-021-21331-z\",\"month\":\"12\",\"publisher\":\"Nature Research\",\"day\":\"1\",\"id\":\"65773184-a381-3802-8cef-979c7b013b38\",\"created\":\"2021-04-09T15:23:02.935Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:10.405Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only applies in asymptotic regimes where there is a strict separation of scales in the physics. Here, we automate and generalize this approach to non-asymptotic regimes by introducing the idea of an equation space, in which different local balances appear as distinct subspace clusters. Unsupervised learning can then automatically identify regions where groups of terms may be neglected. We show that our data-driven balance models successfully delineate dominant balance physics in a much richer class of systems. In particular, this approach uncovers key mechanistic models in turbulence, combustion, nonlinear optics, geophysical fluids, and neuroscience.\",\"bibtype\":\"article\",\"author\":\"Callaham, Jared L. and Koch, James V. and Brunton, Bingni W. and Kutz, J. Nathan and Brunton, Steven L.\",\"doi\":\"10.1038/s41467-021-21331-z\",\"journal\":\"Nature Communications\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Learning dominant physical processes with data-driven balance models},\\n type = {article},\\n year = {2021},\\n keywords = {Applied mathematics,Computational science,Physics},\\n pages = {1-10},\\n volume = {12},\\n websites = {https://doi.org/10.1038/s41467-021-21331-z},\\n month = {12},\\n publisher = {Nature Research},\\n day = {1},\\n id = {65773184-a381-3802-8cef-979c7b013b38},\\n created = {2021-04-09T15:23:02.935Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:10.405Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only applies in asymptotic regimes where there is a strict separation of scales in the physics. Here, we automate and generalize this approach to non-asymptotic regimes by introducing the idea of an equation space, in which different local balances appear as distinct subspace clusters. Unsupervised learning can then automatically identify regions where groups of terms may be neglected. We show that our data-driven balance models successfully delineate dominant balance physics in a much richer class of systems. In particular, this approach uncovers key mechanistic models in turbulence, combustion, nonlinear optics, geophysical fluids, and neuroscience.},\\n bibtype = {article},\\n author = {Callaham, Jared L. and Koch, James V. and Brunton, Bingni W. and Kutz, J. Nathan and Brunton, Steven L.},\\n doi = {10.1038/s41467-021-21331-z},\\n journal = {Nature Communications},\\n number = {1}\\n}\",\"author_short\":[\"Callaham,  J., L.\",\"Koch,  J., V.\",\"Brunton,  B., W.\",\"Kutz,  J., N.\",\"Brunton,  S., L.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/6f43832b-e4b2-6c9f-215b-68e89bbcee1d/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1038/s41467-021-21331-z\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021\",\"role\":\"author\",\"keyword\":[\"Applied mathematics\",\"Computational science\",\"Physics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Ill-posed problems,PINNs,Transfer learning,Turbulence,Velocity-pressure formulation,Vorticity-velocity formulation\",\"pages\":\"109951\",\"volume\":\"426\",\"month\":\"2\",\"publisher\":\"Academic Press Inc.\",\"day\":\"1\",\"id\":\"e3efa042-5d37-39e7-bce7-85eb007e210c\",\"created\":\"2021-04-09T15:23:03.649Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:03.649Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at Reτ∼1,000, but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. We also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.\",\"bibtype\":\"article\",\"author\":\"Jin, Xiaowei and Cai, Shengze and Li, Hui and Karniadakis, George Em\",\"doi\":\"10.1016/j.jcp.2020.109951\",\"journal\":\"Journal of Computational Physics\",\"bibtex\":\"@article{\\n title = {NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations},\\n type = {article},\\n year = {2021},\\n keywords = {Ill-posed problems,PINNs,Transfer learning,Turbulence,Velocity-pressure formulation,Vorticity-velocity formulation},\\n pages = {109951},\\n volume = {426},\\n month = {2},\\n publisher = {Academic Press Inc.},\\n day = {1},\\n id = {e3efa042-5d37-39e7-bce7-85eb007e210c},\\n created = {2021-04-09T15:23:03.649Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:03.649Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at Reτ∼1,000, but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. We also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.},\\n bibtype = {article},\\n author = {Jin, Xiaowei and Cai, Shengze and Li, Hui and Karniadakis, George Em},\\n doi = {10.1016/j.jcp.2020.109951},\\n journal = {Journal of Computational Physics}\\n}\",\"author_short\":[\"Jin,  X.\",\"Cai,  S.\",\"Li,  H.\",\"Karniadakis,  G., E.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Ill-posed problems\",\"PINNs\",\"Transfer learning\",\"Turbulence\",\"Velocity-pressure formulation\",\"Vorticity-velocity formulation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"As a matter of tension - kinetic energy spectra in MHD turbulence\",\"type\":\"misc\",\"year\":\"2020\",\"source\":\"arXiv\",\"keywords\":\"MHD,Methods: numerical,Turbulence\",\"pages\":\"148\",\"volume\":\"909\",\"issue\":\"2\",\"websites\":\"https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta\",\"month\":\"9\",\"publisher\":\"arXiv\",\"day\":\"7\",\"id\":\"46aa6f81-0116-3381-9a45-cb8ae1a65f65\",\"created\":\"2021-04-09T15:23:04.161Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:04.161Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Magnetized turbulence is ubiquitous in many astrophysical and terrestrial systems but no complete, uncontested theory even in the simplest form, magnetohydrodynamics (MHD), exists. Many theories and phenomenologies focus on the joint (kinetic and magnetic) energy fluxes and spectra. We highlight the importance of treating kinetic and magnetic energies separately to shed light on MHD turbulence dynamics. We conduct an implicit large eddy simulation of subsonic, super-Alfvénic MHD turbulence and analyze the scale-wise energy transfer over time. Our key finding is that the kinetic energy spectrum develops a scaling of approximately k−4/3 in the stationary regime as the kinetic energy cascade is suppressed by magnetic tension. This motivates a reevaluation of existing MHD turbulence theories with respect to a more differentiated modeling of the energy fluxes.\",\"bibtype\":\"misc\",\"author\":\"Grete, Philipp and O’Shea, Brian W. and Beckwith, Kris\",\"doi\":\"10.3847/1538-4357/abdd22\",\"bibtex\":\"@misc{\\n title = {As a matter of tension - kinetic energy spectra in MHD turbulence},\\n type = {misc},\\n year = {2020},\\n source = {arXiv},\\n keywords = {MHD,Methods: numerical,Turbulence},\\n pages = {148},\\n volume = {909},\\n issue = {2},\\n websites = {https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta},\\n month = {9},\\n publisher = {arXiv},\\n day = {7},\\n id = {46aa6f81-0116-3381-9a45-cb8ae1a65f65},\\n created = {2021-04-09T15:23:04.161Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:04.161Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Magnetized turbulence is ubiquitous in many astrophysical and terrestrial systems but no complete, uncontested theory even in the simplest form, magnetohydrodynamics (MHD), exists. Many theories and phenomenologies focus on the joint (kinetic and magnetic) energy fluxes and spectra. We highlight the importance of treating kinetic and magnetic energies separately to shed light on MHD turbulence dynamics. We conduct an implicit large eddy simulation of subsonic, super-Alfvénic MHD turbulence and analyze the scale-wise energy transfer over time. Our key finding is that the kinetic energy spectrum develops a scaling of approximately k−4/3 in the stationary regime as the kinetic energy cascade is suppressed by magnetic tension. This motivates a reevaluation of existing MHD turbulence theories with respect to a more differentiated modeling of the energy fluxes.},\\n bibtype = {misc},\\n author = {Grete, Philipp and O’Shea, Brian W. and Beckwith, Kris},\\n doi = {10.3847/1538-4357/abdd22}\\n}\",\"author_short\":[\"Grete,  P.\",\"O’Shea,  B., W.\",\"Beckwith,  K.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020\",\"role\":\"author\",\"keyword\":[\"MHD\",\"Methods: numerical\",\"Turbulence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"103627\",\"websites\":\"https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756\",\"month\":\"3\",\"publisher\":\"Pergamon\",\"day\":\"13\",\"id\":\"f2cc069f-bc29-3f68-8cc6-734cd5d5244a\",\"created\":\"2021-04-09T15:23:04.654Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:04.654Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Jie, Yucheng and Andersson, Helge I. and Zhao, Lihao\",\"doi\":\"10.1016/j.ijmultiphaseflow.2021.103627\",\"journal\":\"International Journal of Multiphase Flow\",\"bibtex\":\"@article{\\n title = {Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles},\\n type = {article},\\n year = {2021},\\n pages = {103627},\\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756},\\n month = {3},\\n publisher = {Pergamon},\\n day = {13},\\n id = {f2cc069f-bc29-3f68-8cc6-734cd5d5244a},\\n created = {2021-04-09T15:23:04.654Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:04.654Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Jie, Yucheng and Andersson, Helge I. and Zhao, Lihao},\\n doi = {10.1016/j.ijmultiphaseflow.2021.103627},\\n journal = {International Journal of Multiphase Flow}\\n}\",\"author_short\":[\"Jie,  Y.\",\"Andersson,  H., I.\",\"Zhao,  L.\"],\"urls\":{\"Website\":\"https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Optimal clipping of the gradient model for subgrid stress closure\",\"type\":\"inproceedings\",\"year\":\"2021\",\"pages\":\"1-16\",\"websites\":\"https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665\",\"publisher\":\"American Institute of Aeronautics and Astronautics Inc, AIAA\",\"id\":\"2a8d900a-b84e-3601-9ead-56f37770b12a\",\"created\":\"2021-04-09T15:23:05.122Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:05.122Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Large Eddy Simulation (LES) involves modeling of the Subgrid Stress (SGS) tensor to close the set of filtered Navier-Stokes equations. The gradient model is a well-known candidate for SGS closure. Stresses obtained using the gradient model have high structural accuracy, that is, these stresses are in high correlation with those from the filtered DNS data in a priori studies. However, a posteriori simulations at a high Reynolds number are subject to energy pileup at small resolved scales due in part to model backscatter that often cascades to numerical instabilities. The modeled stresses are often clipped to eliminate model backscatter and, thereby, improve the dissipative performance and stability of these simulations. However, this comes at the cost of reduced structural accuracy. In this paper, we propose an optimal clipping procedure that recasts the operation as a minimization problem. The proposed clipping ensures that the impact of clipping on the structural accuracy is minimal and, at the same time, there is no model backscatter. We demonstrate the resulting model form is similar to that of mixed models. We conduct a series of a priori and a posteriori tests to investigate the impact of the traditional and optimal clipping procedures. We observe that optimal clipping leads to a significant improvement in model predictions as compared to the traditional clipping procedure for select forced homogeneous isotropic turbulence, Taylor-Green vortex, and channel flow cases.\",\"bibtype\":\"inproceedings\",\"author\":\"Prakash, Aviral and Jansen, Kenneth E. and Evans, John A.\",\"doi\":\"10.2514/6.2021-1665\",\"booktitle\":\"AIAA Scitech 2021 Forum\",\"bibtex\":\"@inproceedings{\\n title = {Optimal clipping of the gradient model for subgrid stress closure},\\n type = {inproceedings},\\n year = {2021},\\n pages = {1-16},\\n websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665},\\n publisher = {American Institute of Aeronautics and Astronautics Inc, AIAA},\\n id = {2a8d900a-b84e-3601-9ead-56f37770b12a},\\n created = {2021-04-09T15:23:05.122Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:05.122Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Large Eddy Simulation (LES) involves modeling of the Subgrid Stress (SGS) tensor to close the set of filtered Navier-Stokes equations. The gradient model is a well-known candidate for SGS closure. Stresses obtained using the gradient model have high structural accuracy, that is, these stresses are in high correlation with those from the filtered DNS data in a priori studies. However, a posteriori simulations at a high Reynolds number are subject to energy pileup at small resolved scales due in part to model backscatter that often cascades to numerical instabilities. The modeled stresses are often clipped to eliminate model backscatter and, thereby, improve the dissipative performance and stability of these simulations. However, this comes at the cost of reduced structural accuracy. In this paper, we propose an optimal clipping procedure that recasts the operation as a minimization problem. The proposed clipping ensures that the impact of clipping on the structural accuracy is minimal and, at the same time, there is no model backscatter. We demonstrate the resulting model form is similar to that of mixed models. We conduct a series of a priori and a posteriori tests to investigate the impact of the traditional and optimal clipping procedures. We observe that optimal clipping leads to a significant improvement in model predictions as compared to the traditional clipping procedure for select forced homogeneous isotropic turbulence, Taylor-Green vortex, and channel flow cases.},\\n bibtype = {inproceedings},\\n author = {Prakash, Aviral and Jansen, Kenneth E. and Evans, John A.},\\n doi = {10.2514/6.2021-1665},\\n booktitle = {AIAA Scitech 2021 Forum}\\n}\",\"author_short\":[\"Prakash,  A.\",\"Jansen,  K., E.\",\"Evans,  J., A.\"],\"urls\":{\"Website\":\"https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Unsupervised deep learning for super-resolution reconstruction of turbulence\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"turbulence simulation\",\"volume\":\"910\",\"websites\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6\",\"publisher\":\"Cambridge University Press\",\"id\":\"27c4e2e7-9c31-38fb-a542-9c5db2bdcdeb\",\"created\":\"2021-04-09T15:23:05.570Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:05.570Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.\",\"bibtype\":\"article\",\"author\":\"Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon\",\"doi\":\"10.1017/jfm.2020.1028\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},\\n type = {article},\\n year = {2020},\\n keywords = {turbulence simulation},\\n volume = {910},\\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6},\\n publisher = {Cambridge University Press},\\n id = {27c4e2e7-9c31-38fb-a542-9c5db2bdcdeb},\\n created = {2021-04-09T15:23:05.570Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:05.570Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},\\n bibtype = {article},\\n author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},\\n doi = {10.1017/jfm.2020.1028},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Kim,  H.\",\"Kim,  J.\",\"Won,  S.\",\"Lee,  C.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020\",\"role\":\"author\",\"keyword\":[\"turbulence simulation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows\",\"type\":\"misc\",\"year\":\"2020\",\"source\":\"arXiv\",\"keywords\":\"turbulence modelling,turbulence theory †\",\"pages\":\"6\",\"volume\":\"914\",\"websites\":\"https://doi.org/10.1017/jfm.2020.977\",\"month\":\"6\",\"publisher\":\"arXiv\",\"day\":\"3\",\"id\":\"70465517-279e-3fdb-9989-01d5df030e63\",\"created\":\"2021-04-09T15:23:06.069Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:11.909Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"By analyzing the Karman-Howarth equation for filtered velocity fields in turbulent flows, we show that the two-point correlation between filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlations-based statistical priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence we show that local eddy viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows.\",\"bibtype\":\"misc\",\"author\":\"Clark Di Leoni, Patricio and Zaki, Tamer A. and Karniadakis, George and Meneveau, Charles\",\"doi\":\"10.1017/jfm.2020.977\",\"bibtex\":\"@misc{\\n title = {Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows},\\n type = {misc},\\n year = {2020},\\n source = {arXiv},\\n keywords = {turbulence modelling,turbulence theory †},\\n pages = {6},\\n volume = {914},\\n websites = {https://doi.org/10.1017/jfm.2020.977},\\n month = {6},\\n publisher = {arXiv},\\n day = {3},\\n id = {70465517-279e-3fdb-9989-01d5df030e63},\\n created = {2021-04-09T15:23:06.069Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:11.909Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {By analyzing the Karman-Howarth equation for filtered velocity fields in turbulent flows, we show that the two-point correlation between filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlations-based statistical priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence we show that local eddy viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows.},\\n bibtype = {misc},\\n author = {Clark Di Leoni, Patricio and Zaki, Tamer A. and Karniadakis, George and Meneveau, Charles},\\n doi = {10.1017/jfm.2020.977}\\n}\",\"author_short\":[\"Clark Di Leoni,  P.\",\"Zaki,  T., A.\",\"Karniadakis,  G.\",\"Meneveau,  C.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/70c270b0-be18-a15d-13ce-fc26512cf651/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1017/jfm.2020.977\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020\",\"role\":\"author\",\"keyword\":[\"turbulence modelling\",\"turbulence theory †\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A study of inner-outer interactions in turbulent channel flows by interactive POD\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"100222\",\"month\":\"2\",\"publisher\":\"Elsevier BV\",\"day\":\"17\",\"id\":\"277fb85f-9a1c-3648-bf9c-83b446322b79\",\"created\":\"2021-04-09T15:23:06.538Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:12.377Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Wang, Hongping and Gao, Qi\",\"doi\":\"10.1016/j.taml.2021.100222\",\"journal\":\"Theoretical and Applied Mechanics Letters\",\"bibtex\":\"@article{\\n title = {A study of inner-outer interactions in turbulent channel flows by interactive POD},\\n type = {article},\\n year = {2021},\\n pages = {100222},\\n month = {2},\\n publisher = {Elsevier BV},\\n day = {17},\\n id = {277fb85f-9a1c-3648-bf9c-83b446322b79},\\n created = {2021-04-09T15:23:06.538Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:12.377Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Wang, Hongping and Gao, Qi},\\n doi = {10.1016/j.taml.2021.100222},\\n journal = {Theoretical and Applied Mechanics Letters}\\n}\",\"author_short\":[\"Wang,  H.\",\"Gao,  Q.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0d1359ff-3618-0b5d-7f96-5a53b43cf77d/full_text.pdf.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R <sub>eτ</sub> = 150, 400 and 1020\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra\",\"pages\":\"36-50\",\"volume\":\"59\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\",\"month\":\"1\",\"publisher\":\"Taylor and Francis Ltd.\",\"day\":\"2\",\"id\":\"bff8a865-3735-375b-b7b6-a81a95dfcd66\",\"created\":\"2021-04-09T15:23:07.047Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:12.855Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.\",\"bibtype\":\"article\",\"author\":\"Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran\",\"doi\":\"10.1080/00221686.2020.1729265\",\"journal\":\"Journal of Hydraulic Research\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R <sub>eτ</sub> = 150, 400 and 1020},\\n type = {article},\\n year = {2021},\\n keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},\\n pages = {36-50},\\n volume = {59},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},\\n month = {1},\\n publisher = {Taylor and Francis Ltd.},\\n day = {2},\\n id = {bff8a865-3735-375b-b7b6-a81a95dfcd66},\\n created = {2021-04-09T15:23:07.047Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:12.855Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},\\n bibtype = {article},\\n author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},\\n doi = {10.1080/00221686.2020.1729265},\\n journal = {Journal of Hydraulic Research},\\n number = {1}\\n}\",\"author_short\":[\"Ahmed,  U.\",\"Apsley,  D.\",\"Stallard,  T.\",\"Stansby,  P.\",\"Afgan,  I.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/099473ef-efff-cf7b-6b5d-b881174cf8a9/full_text.pdf.pdf\",\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021\",\"role\":\"author\",\"keyword\":[\"Anisotropy\",\"budgets\",\"open-channel flow\",\"tidal stream turbines\",\"turbulence length scales\",\"turbulence spectra\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Construction of urban turbulent flow database with wavelet-based compression: A study with large-eddy simulation of flow and dispersion in block-arrayed building group model\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Computational fluid dynamics,Data compression,Dispersion simulation,Large-eddy simulation,Urban flow database,Wavelet transform\",\"pages\":\"104433\",\"volume\":\"208\",\"month\":\"1\",\"publisher\":\"Elsevier B.V.\",\"day\":\"1\",\"id\":\"e2b98148-30c1-35b0-a10e-b9b35cd10e46\",\"created\":\"2021-04-09T15:23:07.512Z\",\"accessed\":\"2021-04-08\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:07.512Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Urban Turbulent flow database, which includes accurately simulated velocity field with full spatial distribution and time-dependent dynamics, is beneficial for fast analysis of pollutant dispersion and comprehensive validation. However, the enormous data volume makes storage and sharing difficult. This research investigated the feasibility of constructing a small-sized database by compression. A wavelet-based compression method was selected because of its light calculation burden and independence of time series data. The database of the flow field in urban-like arrayed blocks was obtained by large-eddy simulation, and then the velocity and diffusion coefficient fields were compressed with different error controls to construct databases. The compression ability of the wavelet-based method was evaluated, and it was found that the maximum compression ratio is reached when most information in the wavelet coefficients is discarded. The effects of compression error on both the single snapshot and the time-series results were studied. The applicability of the compressed database was verified by the resimulation of passive scalar dispersion in the flow. According to results, the database with approximately 100-times compression is suitable for such applications as the visualization and dispersion simulation of passive scalars with sufficient accuracy.\",\"bibtype\":\"article\",\"author\":\"Jia, Hongyuan and Kikumoto, Hideki\",\"doi\":\"10.1016/j.jweia.2020.104433\",\"journal\":\"Journal of Wind Engineering and Industrial Aerodynamics\",\"bibtex\":\"@article{\\n title = {Construction of urban turbulent flow database with wavelet-based compression: A study with large-eddy simulation of flow and dispersion in block-arrayed building group model},\\n type = {article},\\n year = {2021},\\n keywords = {Computational fluid dynamics,Data compression,Dispersion simulation,Large-eddy simulation,Urban flow database,Wavelet transform},\\n pages = {104433},\\n volume = {208},\\n month = {1},\\n publisher = {Elsevier B.V.},\\n day = {1},\\n id = {e2b98148-30c1-35b0-a10e-b9b35cd10e46},\\n created = {2021-04-09T15:23:07.512Z},\\n accessed = {2021-04-08},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:07.512Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Urban Turbulent flow database, which includes accurately simulated velocity field with full spatial distribution and time-dependent dynamics, is beneficial for fast analysis of pollutant dispersion and comprehensive validation. However, the enormous data volume makes storage and sharing difficult. This research investigated the feasibility of constructing a small-sized database by compression. A wavelet-based compression method was selected because of its light calculation burden and independence of time series data. The database of the flow field in urban-like arrayed blocks was obtained by large-eddy simulation, and then the velocity and diffusion coefficient fields were compressed with different error controls to construct databases. The compression ability of the wavelet-based method was evaluated, and it was found that the maximum compression ratio is reached when most information in the wavelet coefficients is discarded. The effects of compression error on both the single snapshot and the time-series results were studied. The applicability of the compressed database was verified by the resimulation of passive scalar dispersion in the flow. According to results, the database with approximately 100-times compression is suitable for such applications as the visualization and dispersion simulation of passive scalars with sufficient accuracy.},\\n bibtype = {article},\\n author = {Jia, Hongyuan and Kikumoto, Hideki},\\n doi = {10.1016/j.jweia.2020.104433},\\n journal = {Journal of Wind Engineering and Industrial Aerodynamics}\\n}\",\"author_short\":[\"Jia,  H.\",\"Kikumoto,  H.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jia-kikumoto-constructionofurbanturbulentflowdatabasewithwaveletbasedcompressionastudywithlargeeddysimulationofflowanddispersioninblockarrayedbuildinggroupmodel-2021\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Computational fluid dynamics\",\"Data compression\",\"Dispersion simulation\",\"Large-eddy simulation\",\"Urban flow database\",\"Wavelet transform\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics\",\"pages\":\"84\",\"volume\":\"62\",\"websites\":\"http://link.springer.com/10.1007/s00348-021-03156-0\",\"month\":\"4\",\"publisher\":\"Springer\",\"day\":\"31\",\"id\":\"96e37199-25a7-3e0b-849d-8fbb8637bf75\",\"created\":\"2021-04-09T15:23:08.214Z\",\"accessed\":\"2021-04-08\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:13.472Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor's hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian-Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor's hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier-Stokes equations compared to the mean flow convective method.\",\"bibtype\":\"article\",\"author\":\"Fratantonio, Dominique and Lai, Chris C. K. and Charonko, John and Prestridge, Kathy\",\"doi\":\"10.1007/s00348-021-03156-0\",\"journal\":\"Experiments in Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows},\\n type = {article},\\n year = {2021},\\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\\n pages = {84},\\n volume = {62},\\n websites = {http://link.springer.com/10.1007/s00348-021-03156-0},\\n month = {4},\\n publisher = {Springer},\\n day = {31},\\n id = {96e37199-25a7-3e0b-849d-8fbb8637bf75},\\n created = {2021-04-09T15:23:08.214Z},\\n accessed = {2021-04-08},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:13.472Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor's hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian-Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor's hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier-Stokes equations compared to the mean flow convective method.},\\n bibtype = {article},\\n author = {Fratantonio, Dominique and Lai, Chris C. K. and Charonko, John and Prestridge, Kathy},\\n doi = {10.1007/s00348-021-03156-0},\\n journal = {Experiments in Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Fratantonio,  D.\",\"Lai,  C., C., K.\",\"Charonko,  J.\",\"Prestridge,  K.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5a1e3df4-a7be-35cb-1a7b-3136a38cfd59/full_text.pdf.pdf\",\"Website\":\"http://link.springer.com/10.1007/s00348-021-03156-0\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021\",\"role\":\"author\",\"keyword\":[\"Engineering Fluid Dynamics\",\"Engineering Thermodynamics\",\"Fluid\",\"Heat and Mass Transfer\",\"and Aerodynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Stochastic Lagrangian dynamics of vorticity. Part 1. General theory for viscous, incompressible fluids\",\"type\":\"article\",\"year\":\"2020\",\"volume\":\"901\",\"month\":\"10\",\"day\":\"25\",\"id\":\"31cff53d-f2e9-385b-bee6-263cf1d5df55\",\"created\":\"2021-04-09T15:23:08.688Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:08.688Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Prior mathematical work of Constantin & Iyer (Commun. Pure Appl. Maths, vol. 61, 2008, pp. 330–345; Ann. Appl. Probab., vol. 21, 2011, pp. 1466–1492) has shown that incompressible Navier–Stokes solutions possess infinitely many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the invariants of Cauchy (Sciences mathématiques et physique, vol. I, 1815, pp. 33–73) for smooth Euler solutions. We reformulate this theory for the case of wall-bounded flows by appealing to the Kuz'min (Phys. Lett. A, vol. 96, 1983, pp. 88–90)–Oseledets (Russ. Math. Surv., vol. 44, 1989, p. 210) representation of Navier–Stokes dynamics, in terms of the vortex-momentum density associated to a continuous distribution of infinitesimal vortex rings. The Constantin–Iyer theory provides an exact representation for vorticity at any interior point as an average over stochastic vorticity contributions transported from the wall. We point out relations of this Lagrangian formulation with the Eulerian theory of Lighthill (Boundary layer theory. In Laminar Boundary Layers (ed. L. Rosenhead), 1963, pp. 46–113)–Morton (Geophys. Astrophys. Fluid Dyn., vol. 28, 1984, pp. 277–308) for vorticity generation at solid walls, and also with a statistical result of Taylor (Proc. R. Soc. Lond. A, vol. 135, 1932, pp. 685–702)–Huggins (J. Low Temp. Phys., vol. 96, 1994, pp. 317–346), which connects dissipative drag with organized cross-stream motion of vorticity and which is closely analogous to the ‘Josephson–Anderson relation’ for quantum superfluids. We elaborate a Monte Carlo numerical Lagrangian scheme to calculate the stochastic Cauchy invariants and their statistics, given the Eulerian space–time velocity field. The method is validated using an online database of a turbulent channel-flow simulation (Graham et al., J. Turbul., vol. 17, 2016, pp. 181–215), where conservation of the mean Cauchy invariant is verified for two selected buffer-layer events corresponding to an ‘ejection’ and a ‘sweep’. The variances of the stochastic Cauchy invariants grow exponentially backward in time, however, revealing Lagrangian chaos of the stochastic trajectories undergoing both fluid advection and viscous diffusion.\",\"bibtype\":\"article\",\"author\":\"Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.\",\"doi\":\"10.1017/jfm.2020.491\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Stochastic Lagrangian dynamics of vorticity. Part 1. General theory for viscous, incompressible fluids},\\n type = {article},\\n year = {2020},\\n volume = {901},\\n month = {10},\\n day = {25},\\n id = {31cff53d-f2e9-385b-bee6-263cf1d5df55},\\n created = {2021-04-09T15:23:08.688Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:08.688Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Prior mathematical work of Constantin & Iyer (Commun. Pure Appl. Maths, vol. 61, 2008, pp. 330–345; Ann. Appl. Probab., vol. 21, 2011, pp. 1466–1492) has shown that incompressible Navier–Stokes solutions possess infinitely many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the invariants of Cauchy (Sciences mathématiques et physique, vol. I, 1815, pp. 33–73) for smooth Euler solutions. We reformulate this theory for the case of wall-bounded flows by appealing to the Kuz'min (Phys. Lett. A, vol. 96, 1983, pp. 88–90)–Oseledets (Russ. Math. Surv., vol. 44, 1989, p. 210) representation of Navier–Stokes dynamics, in terms of the vortex-momentum density associated to a continuous distribution of infinitesimal vortex rings. The Constantin–Iyer theory provides an exact representation for vorticity at any interior point as an average over stochastic vorticity contributions transported from the wall. We point out relations of this Lagrangian formulation with the Eulerian theory of Lighthill (Boundary layer theory. In Laminar Boundary Layers (ed. L. Rosenhead), 1963, pp. 46–113)–Morton (Geophys. Astrophys. Fluid Dyn., vol. 28, 1984, pp. 277–308) for vorticity generation at solid walls, and also with a statistical result of Taylor (Proc. R. Soc. Lond. A, vol. 135, 1932, pp. 685–702)–Huggins (J. Low Temp. Phys., vol. 96, 1994, pp. 317–346), which connects dissipative drag with organized cross-stream motion of vorticity and which is closely analogous to the ‘Josephson–Anderson relation’ for quantum superfluids. We elaborate a Monte Carlo numerical Lagrangian scheme to calculate the stochastic Cauchy invariants and their statistics, given the Eulerian space–time velocity field. The method is validated using an online database of a turbulent channel-flow simulation (Graham et al., J. Turbul., vol. 17, 2016, pp. 181–215), where conservation of the mean Cauchy invariant is verified for two selected buffer-layer events corresponding to an ‘ejection’ and a ‘sweep’. The variances of the stochastic Cauchy invariants grow exponentially backward in time, however, revealing Lagrangian chaos of the stochastic trajectories undergoing both fluid advection and viscous diffusion.},\\n bibtype = {article},\\n author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},\\n doi = {10.1017/jfm.2020.491},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Eyink,  G., L.\",\"Gupta,  A.\",\"Zaki,  T., A.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart1generaltheoryforviscousincompressiblefluids-2020\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Stochastic Lagrangian dynamics of vorticity. Part 2. Application to near-wall channel-flow turbulence\",\"type\":\"article\",\"year\":\"2020\",\"volume\":\"901\",\"month\":\"10\",\"day\":\"25\",\"id\":\"f4a750c4-3dce-3e29-b0ae-ae027506a6da\",\"created\":\"2021-04-09T15:23:09.180Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:09.180Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"We use an online database of a turbulent channel-flow simulation at 𝑅𝑒𝜏=1000 (Graham et al. J. Turbul., vol. 17, issue 2, 2016, pp. 181–215) to determine the origin of vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (J. Fluid Mech., vol. 633, 2009, pp.17–60), we identify typical ‘ejection’ and ‘sweep’ events in the buffer layer by local minima/maxima of the wall stress. In contrast to their conjecture, however, we find that vortex lifting from the wall is not a discrete event requiring ∼ 1 viscous time and ∼ 10 wall units, but is instead a distributed process over a space–time region at least 1∼2 orders of magnitude larger in extent. To reach this conclusion, we exploit a rigorous mathematical theory of vorticity dynamics for Navier–Stokes solutions, in terms of stochastic Lagrangian flows and stochastic Cauchy invariants, conserved on average backward in time. This theory yields exact expressions for vorticity inside the flow domain in terms of vorticity at the wall, as transported by viscous diffusion and by nonlinear advection, stretching and rotation. We show that Lagrangian chaos observed in the buffer layer can be reconciled with saturated vorticity magnitude by ‘virtual reconnection’: although the Eulerian vorticity field in the viscous sublayer has a single sign of spanwise component, opposite signs of Lagrangian vorticity evolve by rotation and cancel by viscous destruction. Our analysis reveals many unifying features of classical fluids and quantum superfluids. We argue that ‘bundles’ of quantized vortices in superfluid turbulence will also exhibit stochastic Lagrangian dynamics and satisfy stochastic conservation laws resulting from particle relabelling symmetry.\",\"bibtype\":\"article\",\"author\":\"Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.\",\"doi\":\"10.1017/jfm.2020.492\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Stochastic Lagrangian dynamics of vorticity. Part 2. Application to near-wall channel-flow turbulence},\\n type = {article},\\n year = {2020},\\n volume = {901},\\n month = {10},\\n day = {25},\\n id = {f4a750c4-3dce-3e29-b0ae-ae027506a6da},\\n created = {2021-04-09T15:23:09.180Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:09.180Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We use an online database of a turbulent channel-flow simulation at 𝑅𝑒𝜏=1000 (Graham et al. J. Turbul., vol. 17, issue 2, 2016, pp. 181–215) to determine the origin of vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (J. Fluid Mech., vol. 633, 2009, pp.17–60), we identify typical ‘ejection’ and ‘sweep’ events in the buffer layer by local minima/maxima of the wall stress. In contrast to their conjecture, however, we find that vortex lifting from the wall is not a discrete event requiring ∼ 1 viscous time and ∼ 10 wall units, but is instead a distributed process over a space–time region at least 1∼2 orders of magnitude larger in extent. To reach this conclusion, we exploit a rigorous mathematical theory of vorticity dynamics for Navier–Stokes solutions, in terms of stochastic Lagrangian flows and stochastic Cauchy invariants, conserved on average backward in time. This theory yields exact expressions for vorticity inside the flow domain in terms of vorticity at the wall, as transported by viscous diffusion and by nonlinear advection, stretching and rotation. We show that Lagrangian chaos observed in the buffer layer can be reconciled with saturated vorticity magnitude by ‘virtual reconnection’: although the Eulerian vorticity field in the viscous sublayer has a single sign of spanwise component, opposite signs of Lagrangian vorticity evolve by rotation and cancel by viscous destruction. Our analysis reveals many unifying features of classical fluids and quantum superfluids. We argue that ‘bundles’ of quantized vortices in superfluid turbulence will also exhibit stochastic Lagrangian dynamics and satisfy stochastic conservation laws resulting from particle relabelling symmetry.},\\n bibtype = {article},\\n author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},\\n doi = {10.1017/jfm.2020.492},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Eyink,  G., L.\",\"Gupta,  A.\",\"Zaki,  T., A.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart2applicationtonearwallchannelflowturbulence-2020\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations\",\"type\":\"article\",\"year\":\"2018\",\"websites\":\"http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262\",\"month\":\"4\",\"id\":\"b3715914-ba21-3486-84e7-5f2b72759a86\",\"created\":\"2021-04-09T15:23:09.679Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:09.679Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynolds number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a sixty-seven percent accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.\",\"bibtype\":\"article\",\"author\":\"McCracken, Megan\",\"doi\":\"10.1145/3219104.3229262\",\"bibtex\":\"@article{\\n title = {Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations},\\n type = {article},\\n year = {2018},\\n websites = {http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262},\\n month = {4},\\n id = {b3715914-ba21-3486-84e7-5f2b72759a86},\\n created = {2021-04-09T15:23:09.679Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:09.679Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynolds number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a sixty-seven percent accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.},\\n bibtype = {article},\\n author = {McCracken, Megan},\\n doi = {10.1145/3219104.3229262}\\n}\",\"author_short\":[\"McCracken,  M.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1902.09929\",\"month\":\"4\",\"id\":\"281385a6-8a49-3483-95e5-d151e1a57bd5\",\"created\":\"2021-04-09T15:23:10.129Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:10.129Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We perform direct numerical simulations (DNSs) of emulsions in homogeneous, isotropic turbulence using a pseudopotential lattice-Boltzmann (PP-LB) method. Improving on previous literature by minimizing droplet dissolution and spurious currents, we show that the PP-LB technique is capable of long, stable simulations in certain parameter regions. Varying the dispersed phase volume fraction φ, we demonstrate that droplet breakup extracts kinetic energy from the larger scales while injecting energy into the smaller scales, increasingly with higher φ, with the Hinze scale dividing the two effects. Droplet size (d) distribution was found to follow the d^-10/3 scaling (Deane & Stokes 2002). We show the need to maintain a separation of the turbulence forcing scale and domain size to prevent the formation of large connected regions of the dispersed phase. For the first time, we show that turbulent emulsions evolve into a quasi-equilibrium cycle of alternating coalescence and breakup dominated processes. Studying the system in its state-space comprising kinetic energy E_k, enstrophy ω^2 and the droplet number density N_d, we find that their dynamics resemble limit-cycles with a time delay. Extreme values in the evolution of E_k manifest in the evolution of ω^2 and N_d with a delay of ~0.3T and ~0.9T respectively (with T the large eddy timescale). Lastly, we also show that flow topology of turbulence in an emulsion is significantly more different than single-phase turbulence than previously thought. In particular, vortex compression and axial straining mechanisms become dominant in the droplet phase, a consequence of the elastic behaviour of droplet interfaces.\",\"bibtype\":\"article\",\"author\":\"Mukherjee, Siddhartha and Safdari, Arman and Shardt, Orest and Kenjeres, Sasa and den Akker, Harry E A Van\",\"bibtex\":\"@article{\\n title = {Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1902.09929},\\n month = {4},\\n id = {281385a6-8a49-3483-95e5-d151e1a57bd5},\\n created = {2021-04-09T15:23:10.129Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:10.129Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We perform direct numerical simulations (DNSs) of emulsions in homogeneous, isotropic turbulence using a pseudopotential lattice-Boltzmann (PP-LB) method. Improving on previous literature by minimizing droplet dissolution and spurious currents, we show that the PP-LB technique is capable of long, stable simulations in certain parameter regions. Varying the dispersed phase volume fraction φ, we demonstrate that droplet breakup extracts kinetic energy from the larger scales while injecting energy into the smaller scales, increasingly with higher φ, with the Hinze scale dividing the two effects. Droplet size (d) distribution was found to follow the d^-10/3 scaling (Deane & Stokes 2002). We show the need to maintain a separation of the turbulence forcing scale and domain size to prevent the formation of large connected regions of the dispersed phase. For the first time, we show that turbulent emulsions evolve into a quasi-equilibrium cycle of alternating coalescence and breakup dominated processes. Studying the system in its state-space comprising kinetic energy E_k, enstrophy ω^2 and the droplet number density N_d, we find that their dynamics resemble limit-cycles with a time delay. Extreme values in the evolution of E_k manifest in the evolution of ω^2 and N_d with a delay of ~0.3T and ~0.9T respectively (with T the large eddy timescale). Lastly, we also show that flow topology of turbulence in an emulsion is significantly more different than single-phase turbulence than previously thought. In particular, vortex compression and axial straining mechanisms become dominant in the droplet phase, a consequence of the elastic behaviour of droplet interfaces.},\\n bibtype = {article},\\n author = {Mukherjee, Siddhartha and Safdari, Arman and Shardt, Orest and Kenjeres, Sasa and den Akker, Harry E A Van}\\n}\",\"author_short\":[\"Mukherjee,  S.\",\"Safdari,  A.\",\"Shardt,  O.\",\"Kenjeres,  S.\",\"den Akker,  H., E., A., V.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1902.09929\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Techniques for 3D-PIV\",\"type\":\"misc\",\"year\":\"2018\",\"source\":\"Particle Image Velocimetry\",\"pages\":\"309-365\",\"websites\":\"http://link.springer.com/10.1007/978-3-319-68852-7_9\",\"publisher\":\"Springer International Publishing\",\"id\":\"8ee722fd-7e42-38e2-a51f-5d6d07406d7e\",\"created\":\"2021-04-09T15:23:10.924Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:10.924Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"book_section\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Raffel, Markus and Willert, Christian E and Scarano, Fulvio and Kähler, Christian J and Wereley, Steven T and Kompenhans, Jürgen\",\"doi\":\"10.1007/978-3-319-68852-7_9\",\"bibtex\":\"@misc{\\n title = {Techniques for 3D-PIV},\\n type = {misc},\\n year = {2018},\\n source = {Particle Image Velocimetry},\\n pages = {309-365},\\n websites = {http://link.springer.com/10.1007/978-3-319-68852-7_9},\\n publisher = {Springer International Publishing},\\n id = {8ee722fd-7e42-38e2-a51f-5d6d07406d7e},\\n created = {2021-04-09T15:23:10.924Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:10.924Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {book_section},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Raffel, Markus and Willert, Christian E and Scarano, Fulvio and Kähler, Christian J and Wereley, Steven T and Kompenhans, Jürgen},\\n doi = {10.1007/978-3-319-68852-7_9}\\n}\",\"author_short\":[\"Raffel,  M.\",\"Willert,  C., E.\",\"Scarano,  F.\",\"Kähler,  C., J.\",\"Wereley,  S., T.\",\"Kompenhans,  J.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-319-68852-7_9\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"34101\",\"volume\":\"4\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"cdf950fb-cf1c-354d-b297-b77c65b772e1\",\"created\":\"2021-04-09T15:23:11.553Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:11.553Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Ge, M.-W. and Yang, Xiang I A and Marusic, Ivan\",\"doi\":\"10.1103/PhysRevFluids.4.034101\",\"journal\":\"Physical Review Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers},\\n type = {article},\\n year = {2019},\\n pages = {34101},\\n volume = {4},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {cdf950fb-cf1c-354d-b297-b77c65b772e1},\\n created = {2021-04-09T15:23:11.553Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:11.553Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Ge, M.-W. and Yang, Xiang I A and Marusic, Ivan},\\n doi = {10.1103/PhysRevFluids.4.034101},\\n journal = {Physical Review Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Ge,  M.\",\"Yang,  X., I., A.\",\"Marusic,  I.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations\",\"type\":\"inproceedings\",\"year\":\"2017\",\"pages\":\"2584-2592\",\"websites\":\"http://ieeexplore.ieee.org/document/8237542/\",\"month\":\"4\",\"publisher\":\"IEEE\",\"id\":\"3f68124b-812f-3e04-a39c-7163dc10e60e\",\"created\":\"2021-04-09T15:23:12.026Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:12.026Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"In experimental fluid dynamics, the flow in a volume of fluid is observed by injecting high-contrast tracer particles and tracking them in multi-view video. Fluid dynamics re-searchers have developed variants of space-carving to re-construct the 3D particle distribution at a given time-step, and then use relatively simple local matching to recover the motion over time. On the contrary, estimating the opti-cal flow between two consecutive images is a long-standing standard problem in computer vision, but only little work exists about volumetric 3D flow. Here, we propose a varia-tional method for 3D fluid flow estimation from multi-view data. We start from a 3D version of the standard varia-tional flow model, and investigate different regularization schemes that ensure divergence-free flow fields, to account for the physics of incompressible fluids. Moreover, we pro-pose a semi-dense formulation, to cope with the computa-tional demands of large volumetric datasets. Flow is esti-mated and regularized at a lower spatial resolution, while the data term is evaluated at full resolution to preserve the discriminative power and geometric precision of the local particle distribution. Extensive experiments reveal that a simple sum of squared differences (SSD) is the most suit-able data term for our application. For regularization, an energy whose Euler-Lagrange equations correspond to the stationary Stokes equations leads to the best results. This strictly enforces a divergence-free flow and additionally pe-nalizes the squared gradient of the flow.\",\"bibtype\":\"inproceedings\",\"author\":\"Lasinger, Katrin and Vogel, Christoph and Schindler, Konrad\",\"doi\":\"10.1109/ICCV.2017.280\",\"booktitle\":\"2017 IEEE International Conference on Computer Vision (ICCV)\",\"bibtex\":\"@inproceedings{\\n title = {Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations},\\n type = {inproceedings},\\n year = {2017},\\n pages = {2584-2592},\\n websites = {http://ieeexplore.ieee.org/document/8237542/},\\n month = {4},\\n publisher = {IEEE},\\n id = {3f68124b-812f-3e04-a39c-7163dc10e60e},\\n created = {2021-04-09T15:23:12.026Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:12.026Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {In experimental fluid dynamics, the flow in a volume of fluid is observed by injecting high-contrast tracer particles and tracking them in multi-view video. Fluid dynamics re-searchers have developed variants of space-carving to re-construct the 3D particle distribution at a given time-step, and then use relatively simple local matching to recover the motion over time. On the contrary, estimating the opti-cal flow between two consecutive images is a long-standing standard problem in computer vision, but only little work exists about volumetric 3D flow. Here, we propose a varia-tional method for 3D fluid flow estimation from multi-view data. We start from a 3D version of the standard varia-tional flow model, and investigate different regularization schemes that ensure divergence-free flow fields, to account for the physics of incompressible fluids. Moreover, we pro-pose a semi-dense formulation, to cope with the computa-tional demands of large volumetric datasets. Flow is esti-mated and regularized at a lower spatial resolution, while the data term is evaluated at full resolution to preserve the discriminative power and geometric precision of the local particle distribution. Extensive experiments reveal that a simple sum of squared differences (SSD) is the most suit-able data term for our application. For regularization, an energy whose Euler-Lagrange equations correspond to the stationary Stokes equations leads to the best results. This strictly enforces a divergence-free flow and additionally pe-nalizes the squared gradient of the flow.},\\n bibtype = {inproceedings},\\n author = {Lasinger, Katrin and Vogel, Christoph and Schindler, Konrad},\\n doi = {10.1109/ICCV.2017.280},\\n booktitle = {2017 IEEE International Conference on Computer Vision (ICCV)}\\n}\",\"author_short\":[\"Lasinger,  K.\",\"Vogel,  C.\",\"Schindler,  K.\"],\"urls\":{\"Website\":\"http://ieeexplore.ieee.org/document/8237542/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"Hybrid LES/RANS,OpenFOAM,Turbulence modelling,Wall-bounded flows\",\"pages\":\"73-83\",\"volume\":\"157\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0045793017302852\",\"month\":\"4\",\"publisher\":\"Pergamon\",\"id\":\"8dde42f9-59e0-384e-8274-2b5e9502d15e\",\"created\":\"2021-04-09T15:23:12.565Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:12.565Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper presents a combined RANS and LES methodology, which automates the dual-mesh hybrid LES/RANS approach and circumvents the need for wall-functions. Unlike RANS, wall-resolved LES is still unaffordable for studying high Reynolds number complex flows in industry and requires much user expertise when turbulence features are unknown a priori. The present approach avoids these issues by concurrently solving the LES and unsteady RANS equations on separate meshes, which are adapted to each model and are overlapping over the entire domain. The RANS solution guides the LES where its mesh is too coarse, and vice-versa where the LES is well-resolved. The driver- and driven-simulation locally swap roles automatically, depending on which one is deemed more reliable by a blending function. Consistency between the RANS solution and a temporal average of the LES solution is enforced by drift terms, whose strength depend on relaxation times-scales that are provided by the RANS model. Predictions for fully-developed channel flows and the flow through periodic hills are shown to be in excellent agreement with reference data. The LES grids are deliberately too coarse for wall-resolved LES, while the independent RANS mesh uses high aspect-ratio cells to economically resolve the near-wall layer.\",\"bibtype\":\"article\",\"author\":\"Tunstall, R and Laurence, D and Prosser, R and Skillen, A\",\"doi\":\"10.1016/j.compfluid.2017.08.002\",\"journal\":\"Computers and Fluids\",\"bibtex\":\"@article{\\n title = {Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency},\\n type = {article},\\n year = {2017},\\n keywords = {Hybrid LES/RANS,OpenFOAM,Turbulence modelling,Wall-bounded flows},\\n pages = {73-83},\\n volume = {157},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0045793017302852},\\n month = {4},\\n publisher = {Pergamon},\\n id = {8dde42f9-59e0-384e-8274-2b5e9502d15e},\\n created = {2021-04-09T15:23:12.565Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:12.565Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper presents a combined RANS and LES methodology, which automates the dual-mesh hybrid LES/RANS approach and circumvents the need for wall-functions. Unlike RANS, wall-resolved LES is still unaffordable for studying high Reynolds number complex flows in industry and requires much user expertise when turbulence features are unknown a priori. The present approach avoids these issues by concurrently solving the LES and unsteady RANS equations on separate meshes, which are adapted to each model and are overlapping over the entire domain. The RANS solution guides the LES where its mesh is too coarse, and vice-versa where the LES is well-resolved. The driver- and driven-simulation locally swap roles automatically, depending on which one is deemed more reliable by a blending function. Consistency between the RANS solution and a temporal average of the LES solution is enforced by drift terms, whose strength depend on relaxation times-scales that are provided by the RANS model. Predictions for fully-developed channel flows and the flow through periodic hills are shown to be in excellent agreement with reference data. The LES grids are deliberately too coarse for wall-resolved LES, while the independent RANS mesh uses high aspect-ratio cells to economically resolve the near-wall layer.},\\n bibtype = {article},\\n author = {Tunstall, R and Laurence, D and Prosser, R and Skillen, A},\\n doi = {10.1016/j.compfluid.2017.08.002},\\n journal = {Computers and Fluids}\\n}\",\"author_short\":[\"Tunstall,  R.\",\"Laurence,  D.\",\"Prosser,  R.\",\"Skillen,  A.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0045793017302852\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017\",\"role\":\"author\",\"keyword\":[\"Hybrid LES/RANS\",\"OpenFOAM\",\"Turbulence modelling\",\"Wall-bounded flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"turbulence simulation,turbulent boundary layers,turbulent flows\",\"pages\":\"356-394\",\"volume\":\"803\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112016005048\",\"month\":\"4\",\"id\":\"7e9d65e4-b575-3200-b915-dd2f7127ea25\",\"created\":\"2021-04-09T15:23:13.084Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:13.084Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The invariants of the velocity gradient tensor, R and Q, and their enstrophy and strain components are studied in the logarithmic layer of an incompressible turbulent channel flow. The velocities are filtered in the three spatial directions and the results analyzed at different scales. We show that the R–Q plane does not capture the changes undergone by the flow as the filter width increases, and that the enstrophy/enstrophy-production and strain/strain-production planes represent better choices. We also show that the conditional mean trajectories may differ significantly from the instantaneous behavior of the flow since they are the result of an averaging process where the mean is 3-5 times smaller than the corresponding standard deviation. The orbital periods in the R–Q plane are shown to be independent of the intensity of the events, and of the same order of magnitude than those in the enstrophy/enstrophy-production and strain/strain-production planes. Our final goal is to test whether the dynamics of the flow are self-similar in the inertial range, and the answer turns out to be no. The mean shear is found to be responsible for the absence of self-similarity and progressively controls the dynamics of the eddies observed as the filter width increases. However, a self-similar behavior emerges when the calculations are repeated for the fluctuating velocity gradient tensor. Finally, the turbulent cascade in terms of vortex stretching is considered by computing the alignment of the vorticity at a given scale with the strain at a different one. These results generally support a non-negligible role of the phenomenological energy-cascade model formulated in terms of vortex stretching.\",\"bibtype\":\"article\",\"author\":\"Lozano-Durán, A and Holzner, M and Jiménez, J\",\"doi\":\"10.1017/jfm.2016.504\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932},\\n type = {article},\\n year = {2016},\\n keywords = {turbulence simulation,turbulent boundary layers,turbulent flows},\\n pages = {356-394},\\n volume = {803},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005048},\\n month = {4},\\n id = {7e9d65e4-b575-3200-b915-dd2f7127ea25},\\n created = {2021-04-09T15:23:13.084Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:13.084Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The invariants of the velocity gradient tensor, R and Q, and their enstrophy and strain components are studied in the logarithmic layer of an incompressible turbulent channel flow. The velocities are filtered in the three spatial directions and the results analyzed at different scales. We show that the R–Q plane does not capture the changes undergone by the flow as the filter width increases, and that the enstrophy/enstrophy-production and strain/strain-production planes represent better choices. We also show that the conditional mean trajectories may differ significantly from the instantaneous behavior of the flow since they are the result of an averaging process where the mean is 3-5 times smaller than the corresponding standard deviation. The orbital periods in the R–Q plane are shown to be independent of the intensity of the events, and of the same order of magnitude than those in the enstrophy/enstrophy-production and strain/strain-production planes. Our final goal is to test whether the dynamics of the flow are self-similar in the inertial range, and the answer turns out to be no. The mean shear is found to be responsible for the absence of self-similarity and progressively controls the dynamics of the eddies observed as the filter width increases. However, a self-similar behavior emerges when the calculations are repeated for the fluctuating velocity gradient tensor. Finally, the turbulent cascade in terms of vortex stretching is considered by computing the alignment of the vorticity at a given scale with the strain at a different one. These results generally support a non-negligible role of the phenomenological energy-cascade model formulated in terms of vortex stretching.},\\n bibtype = {article},\\n author = {Lozano-Durán, A and Holzner, M and Jiménez, J},\\n doi = {10.1017/jfm.2016.504},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Lozano-Durán,  A.\",\"Holzner,  M.\",\"Jiménez,  J.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112016005048\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016\",\"role\":\"author\",\"keyword\":[\"turbulence simulation\",\"turbulent boundary layers\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"The anisotropic structure of turbulence and its energy spectrum\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"11701\",\"volume\":\"28\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.4939471\",\"month\":\"4\",\"id\":\"15cb2dab-6eab-3807-90eb-f579a18bc5c5\",\"created\":\"2021-04-09T15:23:13.967Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:13.967Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The spectral energy distribution in turbulent flows is observed to follow a k−5/3 power scaling, as originally predicted by Kolmogorov’s theory. However, the underlying assumptions in Kolmogorov’s theory appear not to hold with most experimental and numerical data showing evidence of small-scale anisotropy and significant direct energy transfer between the large- and the small-scales. Here, we present a flow structure that reconciles the k−5/3 spectrum with small-scale universality, small-scale anisotropy, and direct scale interactions. The flow structure is a shear layer, which contains the small-scales of motion and is bounded by the large-scales. The anisotropic shear layer reveals the expected scaling of the energy spectrum in nearly all directions.\",\"bibtype\":\"article\",\"author\":\"Elsinga, G E and Marusic, I\",\"doi\":\"10.1063/1.4939471\",\"journal\":\"Physics of Fluids\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {The anisotropic structure of turbulence and its energy spectrum},\\n type = {article},\\n year = {2016},\\n pages = {11701},\\n volume = {28},\\n websites = {http://aip.scitation.org/doi/10.1063/1.4939471},\\n month = {4},\\n id = {15cb2dab-6eab-3807-90eb-f579a18bc5c5},\\n created = {2021-04-09T15:23:13.967Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:13.967Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The spectral energy distribution in turbulent flows is observed to follow a k−5/3 power scaling, as originally predicted by Kolmogorov’s theory. However, the underlying assumptions in Kolmogorov’s theory appear not to hold with most experimental and numerical data showing evidence of small-scale anisotropy and significant direct energy transfer between the large- and the small-scales. Here, we present a flow structure that reconciles the k−5/3 spectrum with small-scale universality, small-scale anisotropy, and direct scale interactions. The flow structure is a shear layer, which contains the small-scales of motion and is bounded by the large-scales. The anisotropic shear layer reveals the expected scaling of the energy spectrum in nearly all directions.},\\n bibtype = {article},\\n author = {Elsinga, G E and Marusic, I},\\n doi = {10.1063/1.4939471},\\n journal = {Physics of Fluids},\\n number = {1}\\n}\",\"author_short\":[\"Elsinga,  G., E.\",\"Marusic,  I.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.4939471\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Hierarchical models for financial markets and turbulence\",\"type\":\"misc\",\"year\":\"2018\",\"websites\":\"https://repositorio.ufpe.br/handle/123456789/31035\",\"month\":\"4\",\"publisher\":\"Universidade Federal de Pernambuco\",\"id\":\"8417a4a2-5d9f-349f-ad47-0263483f4ee4\",\"created\":\"2021-04-09T15:23:14.900Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:14.900Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"thesis\",\"private_publication\":false,\"abstract\":\"CAPES\",\"bibtype\":\"misc\",\"author\":\"Correa, William Oswaldo Sosa\",\"bibtex\":\"@misc{\\n title = {Hierarchical models for financial markets and turbulence},\\n type = {misc},\\n year = {2018},\\n websites = {https://repositorio.ufpe.br/handle/123456789/31035},\\n month = {4},\\n publisher = {Universidade Federal de Pernambuco},\\n id = {8417a4a2-5d9f-349f-ad47-0263483f4ee4},\\n created = {2021-04-09T15:23:14.900Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:14.900Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {thesis},\\n private_publication = {false},\\n abstract = {CAPES},\\n bibtype = {misc},\\n author = {Correa, William Oswaldo Sosa}\\n}\",\"author_short\":[\"Correa,  W., O., S.\"],\"urls\":{\"Website\":\"https://repositorio.ufpe.br/handle/123456789/31035\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Applied mathematics,Astronomy and astrophysics,Astrophysical plasmas,Information technology\",\"pages\":\"466-469\",\"volume\":\"497\",\"websites\":\"http://www.nature.com/articles/nature12128\",\"month\":\"4\",\"publisher\":\"Nature Publishing Group\",\"id\":\"6a88f6fa-126a-376e-be84-8a2f914b8b62\",\"created\":\"2021-04-09T15:23:16.064Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:16.064Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The idea of 'frozen-in' magnetic field lines for ideal plasmas is useful to explain diverse astrophysical phenomena, for example the shedding of excess angular momentum from protostars by twisting of field lines frozen into the interstellar medium. Frozen-in field lines, however, preclude the rapid changes in magnetic topology observed at high conductivities, as in solar flares. Microphysical plasma processes are a proposed explanation of the observed high rates, but it is an open question whether such processes can rapidly reconnect astrophysical flux structures much greater in extent than several thousand ion gyroradii. An alternative explanation is that turbulent Richardson advection brings field lines implosively together from distances far apart to separations of the order of gyroradii. Here we report an analysis of a simulation of magnetohydrodynamic turbulence at high conductivity that exhibits Richardson dispersion. This effect of advection in rough velocity fields, which appear non-differentiable in space, leads to line motions that are completely indeterministic or 'spontaneously stochastic', as predicted in analytical studies. The turbulent breakdown of standard flux freezing at scales greater than the ion gyroradius can explain fast reconnection of very large-scale flux structures, both observed (solar flares and coronal mass ejections) and predicted (the inner heliosheath, accretion disks, γ-ray bursts and so on). For laminar plasma flows with smooth velocity fields or for low turbulence intensity, stochastic flux freezing reduces to the usual frozen-in condition.\",\"bibtype\":\"article\",\"author\":\"Eyink, Gregory and Vishniac, Ethan and Lalescu, Cristian and Aluie, Hussein and Kanov, Kalin and Bürger, Kai and Burns, Randal and Meneveau, Charles and Szalay, Alexander\",\"doi\":\"10.1038/nature12128\",\"journal\":\"Nature\",\"number\":\"7450\",\"bibtex\":\"@article{\\n title = {Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence},\\n type = {article},\\n year = {2013},\\n keywords = {Applied mathematics,Astronomy and astrophysics,Astrophysical plasmas,Information technology},\\n pages = {466-469},\\n volume = {497},\\n websites = {http://www.nature.com/articles/nature12128},\\n month = {4},\\n publisher = {Nature Publishing Group},\\n id = {6a88f6fa-126a-376e-be84-8a2f914b8b62},\\n created = {2021-04-09T15:23:16.064Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:16.064Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The idea of 'frozen-in' magnetic field lines for ideal plasmas is useful to explain diverse astrophysical phenomena, for example the shedding of excess angular momentum from protostars by twisting of field lines frozen into the interstellar medium. Frozen-in field lines, however, preclude the rapid changes in magnetic topology observed at high conductivities, as in solar flares. Microphysical plasma processes are a proposed explanation of the observed high rates, but it is an open question whether such processes can rapidly reconnect astrophysical flux structures much greater in extent than several thousand ion gyroradii. An alternative explanation is that turbulent Richardson advection brings field lines implosively together from distances far apart to separations of the order of gyroradii. Here we report an analysis of a simulation of magnetohydrodynamic turbulence at high conductivity that exhibits Richardson dispersion. This effect of advection in rough velocity fields, which appear non-differentiable in space, leads to line motions that are completely indeterministic or 'spontaneously stochastic', as predicted in analytical studies. The turbulent breakdown of standard flux freezing at scales greater than the ion gyroradius can explain fast reconnection of very large-scale flux structures, both observed (solar flares and coronal mass ejections) and predicted (the inner heliosheath, accretion disks, γ-ray bursts and so on). For laminar plasma flows with smooth velocity fields or for low turbulence intensity, stochastic flux freezing reduces to the usual frozen-in condition.},\\n bibtype = {article},\\n author = {Eyink, Gregory and Vishniac, Ethan and Lalescu, Cristian and Aluie, Hussein and Kanov, Kalin and Bürger, Kai and Burns, Randal and Meneveau, Charles and Szalay, Alexander},\\n doi = {10.1038/nature12128},\\n journal = {Nature},\\n number = {7450}\\n}\",\"author_short\":[\"Eyink,  G.\",\"Vishniac,  E.\",\"Lalescu,  C.\",\"Aluie,  H.\",\"Kanov,  K.\",\"Bürger,  K.\",\"Burns,  R.\",\"Meneveau,  C.\",\"Szalay,  A.\"],\"urls\":{\"Website\":\"http://www.nature.com/articles/nature12128\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013\",\"role\":\"author\",\"keyword\":[\"Applied mathematics\",\"Astronomy and astrophysics\",\"Astrophysical plasmas\",\"Information technology\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking\",\"type\":\"inproceedings\",\"year\":\"2018\",\"websites\":\"https://www.research-collection.ethz.ch/handle/20.500.11850/279200\",\"month\":\"4\",\"publisher\":\"ETH Zurich\",\"id\":\"a51771b0-62fb-346c-bdc2-bb3045c1a60b\",\"created\":\"2021-04-09T15:23:17.163Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:17.163Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Huhn, F and Schröder, Andreas and Schanz, D and Gesemann, S and Manovski, P\",\"editor\":\"Rösgen, Thomas\",\"doi\":\"10.3929/ETHZ-B-000279200\",\"booktitle\":\"18th International Symposium on Flow Visualization (ISFV18)\",\"bibtex\":\"@inproceedings{\\n title = {Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking},\\n type = {inproceedings},\\n year = {2018},\\n websites = {https://www.research-collection.ethz.ch/handle/20.500.11850/279200},\\n month = {4},\\n publisher = {ETH Zurich},\\n id = {a51771b0-62fb-346c-bdc2-bb3045c1a60b},\\n created = {2021-04-09T15:23:17.163Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:17.163Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Huhn, F and Schröder, Andreas and Schanz, D and Gesemann, S and Manovski, P},\\n editor = {Rösgen, Thomas},\\n doi = {10.3929/ETHZ-B-000279200},\\n booktitle = {18th International Symposium on Flow Visualization (ISFV18)}\\n}\",\"author_short\":[\"Huhn,  F.\",\"Schröder,  A.\",\"Schanz,  D.\",\"Gesemann,  S.\",\"Manovski,  P.\"],\"editor_short\":[\"Rösgen,  T.\"],\"urls\":{\"Website\":\"https://www.research-collection.ethz.ch/handle/20.500.11850/279200\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis\",\"type\":\"inproceedings\",\"year\":\"2017\",\"keywords\":\"Floating-point compression,GPU video encoding,Volume compression\",\"pages\":\"64-73\",\"volume\":\"2017-Decem\",\"websites\":\"http://ieeexplore.ieee.org/document/8231852/\",\"month\":\"4\",\"publisher\":\"IEEE\",\"id\":\"ae2fd0e8-eb3b-34bb-ae02-c84319d53fb9\",\"created\":\"2021-04-09T15:23:18.258Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:18.258Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.\",\"bibtype\":\"inproceedings\",\"author\":\"Leaf, Nick and Miller, Bob and Ma, Kwan Liu\",\"doi\":\"10.1109/LDAV.2017.8231852\",\"booktitle\":\"2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017\",\"bibtex\":\"@inproceedings{\\n title = {In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis},\\n type = {inproceedings},\\n year = {2017},\\n keywords = {Floating-point compression,GPU video encoding,Volume compression},\\n pages = {64-73},\\n volume = {2017-Decem},\\n websites = {http://ieeexplore.ieee.org/document/8231852/},\\n month = {4},\\n publisher = {IEEE},\\n id = {ae2fd0e8-eb3b-34bb-ae02-c84319d53fb9},\\n created = {2021-04-09T15:23:18.258Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:18.258Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.},\\n bibtype = {inproceedings},\\n author = {Leaf, Nick and Miller, Bob and Ma, Kwan Liu},\\n doi = {10.1109/LDAV.2017.8231852},\\n booktitle = {2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017}\\n}\",\"author_short\":[\"Leaf,  N.\",\"Miller,  B.\",\"Ma,  K., L.\"],\"urls\":{\"Website\":\"http://ieeexplore.ieee.org/document/8231852/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017\",\"role\":\"author\",\"keyword\":[\"Floating-point compression\",\"GPU video encoding\",\"Volume compression\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"A uniform momentum zone–vortical fissure model of the turbulent boundary layer\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"boundary layer structure,turbulence modelling,turbulent boundary layers\",\"pages\":\"609-633\",\"volume\":\"858\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"ee6df86a-88f6-3f40-8c15-a9446fb35c8a\",\"created\":\"2021-04-09T15:23:19.246Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:19.246Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Recent studies reveal that at large friction Reynolds number [STIX]x1D6FF^+ the inertially dominated region of the turbulent boundary layer is composed of large-scale zones of nearly uniform momentum segregated by narrow fissures of concentrated vorticity. Experiments show that, when scaled by the boundary-layer thickness, the fissure thickness is O(1/[STIX]x1D6FF^+) , while the dimensional jump in streamwise velocity across each fissure scales in proportion to the friction velocity u_[STIX]x1D70F . A simple model that exploits these essential elements of the turbulent boundary-layer structure at large [STIX]x1D6FF^+ is developed. First, a master wall-normal profile of streamwise velocity is constructed by placing a discrete number of fissures across the boundary layer. The number of fissures and their wall-normal locations follow scalings informed by analysis of the mean momentum equation. The fissures are then randomly displaced in the wall-normal direction, exchanging momentum as they move, to create an instantaneous velocity profile. This process is repeated to generate ensembles of streamwise velocity profiles from which statistical moments are computed. The modelled statistical profiles are shown to agree remarkably well with those acquired from direct numerical simulations of turbulent channel flow at large [STIX]x1D6FF^+ . In particular, the model robustly reproduces the empirically observed sub-Gaussian behaviour for the skewness and kurtosis profiles over a large range of input parameters.\",\"bibtype\":\"article\",\"author\":\"Bautista, Juan Carlos Cuevas and Ebadi, Alireza and White, Christopher M and Chini, Gregory P and Klewicki, Joseph C\",\"doi\":\"10.1017/jfm.2018.769\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {A uniform momentum zone–vortical fissure model of the turbulent boundary layer},\\n type = {article},\\n year = {2019},\\n keywords = {boundary layer structure,turbulence modelling,turbulent boundary layers},\\n pages = {609-633},\\n volume = {858},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {ee6df86a-88f6-3f40-8c15-a9446fb35c8a},\\n created = {2021-04-09T15:23:19.246Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:19.246Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Recent studies reveal that at large friction Reynolds number [STIX]x1D6FF^+ the inertially dominated region of the turbulent boundary layer is composed of large-scale zones of nearly uniform momentum segregated by narrow fissures of concentrated vorticity. Experiments show that, when scaled by the boundary-layer thickness, the fissure thickness is O(1/[STIX]x1D6FF^+) , while the dimensional jump in streamwise velocity across each fissure scales in proportion to the friction velocity u_[STIX]x1D70F . A simple model that exploits these essential elements of the turbulent boundary-layer structure at large [STIX]x1D6FF^+ is developed. First, a master wall-normal profile of streamwise velocity is constructed by placing a discrete number of fissures across the boundary layer. The number of fissures and their wall-normal locations follow scalings informed by analysis of the mean momentum equation. The fissures are then randomly displaced in the wall-normal direction, exchanging momentum as they move, to create an instantaneous velocity profile. This process is repeated to generate ensembles of streamwise velocity profiles from which statistical moments are computed. The modelled statistical profiles are shown to agree remarkably well with those acquired from direct numerical simulations of turbulent channel flow at large [STIX]x1D6FF^+ . In particular, the model robustly reproduces the empirically observed sub-Gaussian behaviour for the skewness and kurtosis profiles over a large range of input parameters.},\\n bibtype = {article},\\n author = {Bautista, Juan Carlos Cuevas and Ebadi, Alireza and White, Christopher M and Chini, Gregory P and Klewicki, Joseph C},\\n doi = {10.1017/jfm.2018.769},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Bautista,  J., C., C.\",\"Ebadi,  A.\",\"White,  C., M.\",\"Chini,  G., P.\",\"Klewicki,  J., C.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019\",\"role\":\"author\",\"keyword\":[\"boundary layer structure\",\"turbulence modelling\",\"turbulent boundary layers\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Fluctuation dynamos and their Faraday rotation signatures\",\"type\":\"article\",\"year\":\"2013\",\"pages\":\"2469-2481\",\"volume\":\"429\",\"websites\":\"http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation\",\"month\":\"4\",\"publisher\":\"Oxford University Press\",\"id\":\"411f3d9f-938e-3b01-9d5d-a75cabb68633\",\"created\":\"2021-04-09T15:23:19.834Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:19.834Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Bhat, Pallavi and Subramanian, Kandaswamy\",\"doi\":\"10.1093/mnras/sts516\",\"journal\":\"Monthly Notices of the Royal Astronomical Society\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Fluctuation dynamos and their Faraday rotation signatures},\\n type = {article},\\n year = {2013},\\n pages = {2469-2481},\\n volume = {429},\\n websites = {http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation},\\n month = {4},\\n publisher = {Oxford University Press},\\n id = {411f3d9f-938e-3b01-9d5d-a75cabb68633},\\n created = {2021-04-09T15:23:19.834Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:19.834Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Bhat, Pallavi and Subramanian, Kandaswamy},\\n doi = {10.1093/mnras/sts516},\\n journal = {Monthly Notices of the Royal Astronomical Society},\\n number = {3}\\n}\",\"author_short\":[\"Bhat,  P.\",\"Subramanian,  K.\"],\"urls\":{\"Website\":\"http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"On PIV random error minimization with optimal POD-based low-order reconstruction\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"75\",\"volume\":\"56\",\"websites\":\"http://link.springer.com/10.1007/s00348-015-1940-8\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"e02969e8-fdd8-3b3d-8ee5-c7c59492f1d8\",\"created\":\"2021-04-09T15:23:20.692Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:20.692Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© 2015, Springer-Verlag Berlin Heidelberg. Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows.\",\"bibtype\":\"article\",\"author\":\"Raiola, Marco and Discetti, Stefano and Ianiro, Andrea\",\"doi\":\"10.1007/s00348-015-1940-8\",\"journal\":\"Experiments in Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {On PIV random error minimization with optimal POD-based low-order reconstruction},\\n type = {article},\\n year = {2015},\\n pages = {75},\\n volume = {56},\\n websites = {http://link.springer.com/10.1007/s00348-015-1940-8},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {e02969e8-fdd8-3b3d-8ee5-c7c59492f1d8},\\n created = {2021-04-09T15:23:20.692Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:20.692Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© 2015, Springer-Verlag Berlin Heidelberg. Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows.},\\n bibtype = {article},\\n author = {Raiola, Marco and Discetti, Stefano and Ianiro, Andrea},\\n doi = {10.1007/s00348-015-1940-8},\\n journal = {Experiments in Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Raiola,  M.\",\"Discetti,  S.\",\"Ianiro,  A.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-015-1940-8\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows\",\"type\":\"misc\",\"year\":\"2015\",\"websites\":\"http://www.osti.gov/servlets/purl/1221181/\",\"month\":\"4\",\"institution\":\"Sandia National Laboratories (SNL)\",\"id\":\"92304c26-4a57-3361-b9af-462cc2475259\",\"created\":\"2021-04-09T15:23:21.473Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:21.473Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"report\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Templeton, Jeremy Alan and Blaylock, Myra L and Domino, Stefan P and Hewson, John C and Kumar, Pritvi Raj and Ling, Julia and Najm, Habib N and Ruiz, Anthony and Safta, Cosmin and Sargsyan, Khachik and Stewart, Alessia and Wagner, Gregory\",\"doi\":\"10.2172/1221181\",\"bibtex\":\"@misc{\\n title = {Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows},\\n type = {misc},\\n year = {2015},\\n websites = {http://www.osti.gov/servlets/purl/1221181/},\\n month = {4},\\n institution = {Sandia National Laboratories (SNL)},\\n id = {92304c26-4a57-3361-b9af-462cc2475259},\\n created = {2021-04-09T15:23:21.473Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:21.473Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {report},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Templeton, Jeremy Alan and Blaylock, Myra L and Domino, Stefan P and Hewson, John C and Kumar, Pritvi Raj and Ling, Julia and Najm, Habib N and Ruiz, Anthony and Safta, Cosmin and Sargsyan, Khachik and Stewart, Alessia and Wagner, Gregory},\\n doi = {10.2172/1221181}\\n}\",\"author_short\":[\"Templeton,  J., A.\",\"Blaylock,  M., L.\",\"Domino,  S., P.\",\"Hewson,  J., C.\",\"Kumar,  P., R.\",\"Ling,  J.\",\"Najm,  H., N.\",\"Ruiz,  A.\",\"Safta,  C.\",\"Sargsyan,  K.\",\"Stewart,  A.\",\"Wagner,  G.\"],\"urls\":{\"Website\":\"http://www.osti.gov/servlets/purl/1221181/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence\",\"type\":\"article\",\"year\":\"2011\",\"pages\":\"261-268\",\"volume\":\"18\",\"websites\":\"https://www.nonlin-processes-geophys.net/18/261/2011/\",\"month\":\"4\",\"id\":\"8f32c50d-8599-33b6-a5d8-0a33019102dd\",\"created\":\"2021-04-09T15:23:22.180Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:22.180Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.\",\"bibtype\":\"article\",\"author\":\"Wu, C C and Chang, T\",\"doi\":\"10.5194/npg-18-261-2011\",\"journal\":\"Nonlinear Processes in Geophysics\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence},\\n type = {article},\\n year = {2011},\\n pages = {261-268},\\n volume = {18},\\n websites = {https://www.nonlin-processes-geophys.net/18/261/2011/},\\n month = {4},\\n id = {8f32c50d-8599-33b6-a5d8-0a33019102dd},\\n created = {2021-04-09T15:23:22.180Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:22.180Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.},\\n bibtype = {article},\\n author = {Wu, C C and Chang, T},\\n doi = {10.5194/npg-18-261-2011},\\n journal = {Nonlinear Processes in Geophysics},\\n number = {2}\\n}\",\"author_short\":[\"Wu,  C., C.\",\"Chang,  T.\"],\"urls\":{\"Website\":\"https://www.nonlin-processes-geophys.net/18/261/2011/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder\",\"type\":\"inproceedings\",\"year\":\"2016\",\"websites\":\"http://arc.aiaa.org/doi/10.2514/6.2016-1048\",\"month\":\"4\",\"publisher\":\"American Institute of Aeronautics and Astronautics\",\"id\":\"064e72ac-06e5-3458-8c9e-86c71f12040e\",\"created\":\"2021-04-09T15:23:22.630Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:22.630Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"© 2016, American Institute of Aeronautics and Astronautics Inc, AIAA . All rights reserved. Instantaneous and time-resolved pressure is evaluated in a 6-liter measurement volume by making use of tomographic PTV with Helium-filled soap bubbles (HFSB) as tracers. This volume is two orders of magnitude larger than conventional tomographic experiments. The experiment considers the near-wake of a surface mounted cylinder (Re D = 3.6×10 4 ), which is highly unsteady and fully three-dimensional. Pressure is calculated from the tomographic velocity measurement by invoking the incompressible momentum equation. The time-averaged, RMS and instantaneous pressure is validated against simultaneous and independent pressure measurements made by pressure transducers in the surface. The mean and RMS pressure is in good correspondence to the reference measurements. Cross-correlation of the instantaneous pressure time-series with the reference measurement signal yields a cross-correlation coefficient peak value of 0.6. The present study shows that instantaneous pressure can be measured non-intrusively in a large measurement volume by making use of tomographic PTV with HFSB as tracers, which allows significantly reduced model complexity as the use of pressure transducers is avoided.\",\"bibtype\":\"inproceedings\",\"author\":\"Schneiders, Jan and Caridi, Giuseppe Carlo Alp and Sciacchitano, Andrea and Scarano, Fulvio\",\"doi\":\"10.2514/6.2016-1048\",\"booktitle\":\"54th AIAA Aerospace Sciences Meeting\",\"bibtex\":\"@inproceedings{\\n title = {Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder},\\n type = {inproceedings},\\n year = {2016},\\n websites = {http://arc.aiaa.org/doi/10.2514/6.2016-1048},\\n month = {4},\\n publisher = {American Institute of Aeronautics and Astronautics},\\n id = {064e72ac-06e5-3458-8c9e-86c71f12040e},\\n created = {2021-04-09T15:23:22.630Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:22.630Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {© 2016, American Institute of Aeronautics and Astronautics Inc, AIAA . All rights reserved. Instantaneous and time-resolved pressure is evaluated in a 6-liter measurement volume by making use of tomographic PTV with Helium-filled soap bubbles (HFSB) as tracers. This volume is two orders of magnitude larger than conventional tomographic experiments. The experiment considers the near-wake of a surface mounted cylinder (Re D = 3.6×10 4 ), which is highly unsteady and fully three-dimensional. Pressure is calculated from the tomographic velocity measurement by invoking the incompressible momentum equation. The time-averaged, RMS and instantaneous pressure is validated against simultaneous and independent pressure measurements made by pressure transducers in the surface. The mean and RMS pressure is in good correspondence to the reference measurements. Cross-correlation of the instantaneous pressure time-series with the reference measurement signal yields a cross-correlation coefficient peak value of 0.6. The present study shows that instantaneous pressure can be measured non-intrusively in a large measurement volume by making use of tomographic PTV with HFSB as tracers, which allows significantly reduced model complexity as the use of pressure transducers is avoided.},\\n bibtype = {inproceedings},\\n author = {Schneiders, Jan and Caridi, Giuseppe Carlo Alp and Sciacchitano, Andrea and Scarano, Fulvio},\\n doi = {10.2514/6.2016-1048},\\n booktitle = {54th AIAA Aerospace Sciences Meeting}\\n}\",\"author_short\":[\"Schneiders,  J.\",\"Caridi,  G., C., A.\",\"Sciacchitano,  A.\",\"Scarano,  F.\"],\"urls\":{\"Website\":\"http://arc.aiaa.org/doi/10.2514/6.2016-1048\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows\",\"type\":\"article\",\"year\":\"2014\",\"pages\":\"14501\",\"volume\":\"112\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevLett.112.014501\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"3894f9ae-c4f5-365a-9482-522b9a30d427\",\"created\":\"2021-04-09T15:23:23.153Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:23.153Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of Lagrangian correlation functions. These capture preferential sampling of the fluid gradients which in turn can give rise to differences in the tumbling rates of disks and rods. We show that this is a weak effect in Gaussian random flows. But in turbulent flows persistent regions of high vorticity cause disks to tumble much faster than rods, as observed in direct numerical simulations [Parsa et al., Phys. Rev. Lett. 109 (2012) 134501]. For larger particles (at finite Stokes numbers), rotational and translational inertia affects the tumbling rate and the angle at which particles collide, due to the formation of rotational caustics.\",\"bibtype\":\"article\",\"author\":\"Gustavsson, K and Einarsson, J and Mehlig, B\",\"doi\":\"10.1103/PhysRevLett.112.014501\",\"journal\":\"Physical Review Letters\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows},\\n type = {article},\\n year = {2014},\\n pages = {14501},\\n volume = {112},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.112.014501},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {3894f9ae-c4f5-365a-9482-522b9a30d427},\\n created = {2021-04-09T15:23:23.153Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:23.153Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of Lagrangian correlation functions. These capture preferential sampling of the fluid gradients which in turn can give rise to differences in the tumbling rates of disks and rods. We show that this is a weak effect in Gaussian random flows. But in turbulent flows persistent regions of high vorticity cause disks to tumble much faster than rods, as observed in direct numerical simulations [Parsa et al., Phys. Rev. Lett. 109 (2012) 134501]. For larger particles (at finite Stokes numbers), rotational and translational inertia affects the tumbling rate and the angle at which particles collide, due to the formation of rotational caustics.},\\n bibtype = {article},\\n author = {Gustavsson, K and Einarsson, J and Mehlig, B},\\n doi = {10.1103/PhysRevLett.112.014501},\\n journal = {Physical Review Letters},\\n number = {1}\\n}\",\"author_short\":[\"Gustavsson,  K.\",\"Einarsson,  J.\",\"Mehlig,  B.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevLett.112.014501\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Complex Networks Unveiling Spatial Patterns in Turbulence\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"Complex networks,spatial correlation,spatiotemporal patterns,time series analysis,turbulent flows\",\"pages\":\"1650223\",\"volume\":\"26\",\"websites\":\"http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230\",\"month\":\"4\",\"publisher\":\"World Scientific Publishing Company\",\"id\":\"90dfeab9-ddc5-3436-b6a3-2af6cf730f25\",\"created\":\"2021-04-09T15:23:23.612Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:23.612Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.\",\"bibtype\":\"article\",\"author\":\"Scarsoglio, Stefania and Iacobello, Giovanni and Ridolfi, Luca\",\"doi\":\"10.1142/S0218127416502230\",\"journal\":\"International Journal of Bifurcation and Chaos\",\"number\":\"13\",\"bibtex\":\"@article{\\n title = {Complex Networks Unveiling Spatial Patterns in Turbulence},\\n type = {article},\\n year = {2016},\\n keywords = {Complex networks,spatial correlation,spatiotemporal patterns,time series analysis,turbulent flows},\\n pages = {1650223},\\n volume = {26},\\n websites = {http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230},\\n month = {4},\\n publisher = {World Scientific Publishing Company},\\n id = {90dfeab9-ddc5-3436-b6a3-2af6cf730f25},\\n created = {2021-04-09T15:23:23.612Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:23.612Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.},\\n bibtype = {article},\\n author = {Scarsoglio, Stefania and Iacobello, Giovanni and Ridolfi, Luca},\\n doi = {10.1142/S0218127416502230},\\n journal = {International Journal of Bifurcation and Chaos},\\n number = {13}\\n}\",\"author_short\":[\"Scarsoglio,  S.\",\"Iacobello,  G.\",\"Ridolfi,  L.\"],\"urls\":{\"Website\":\"http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016\",\"role\":\"author\",\"keyword\":[\"Complex networks\",\"spatial correlation\",\"spatiotemporal patterns\",\"time series analysis\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"remesh smoothed particle hydrodynamics,three-dimensional isotropic decaying turbulence,turbulent flow\",\"pages\":\"1-19\",\"volume\":\"86\",\"websites\":\"http://doi.wiley.com/10.1002/fld.4405\",\"month\":\"4\",\"publisher\":\"Wiley-Blackwell\",\"id\":\"51235906-1632-379f-8de3-6d3c18134f8b\",\"created\":\"2021-04-09T15:23:24.693Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:24.693Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Copyright © 2017 John Wiley & Sons, Ltd. We present a remeshed particle-mesh method for the simulation of three-dimensional compressible turbulent flow. The method is related to the meshfree smoothed particle hydrodynamics method, but the present method introduces a mesh for efficient calculation of the pressure gradient, and laminar and turbulent diffusion. In addition, the mesh is used to remesh (reorganise uniformly) the particles to ensure a regular particle distribution and convergence of the method. The accuracy of the presented methodology is tested for a number of benchmark problems involving two- and three-dimensional Taylor-Green flow, thin double shear layer, and three-dimensional isotropic turbulence. Two models were implemented, direct numerical simulations, and Smagorinsky model. Taking advantage of the Lagrangian advection, and the finite difference efficiency, the method is capable of providing quality simulations while maintaining its robustness and versatility.\",\"bibtype\":\"article\",\"author\":\"Obeidat, Anas and Bordas, Stéphane P A\",\"doi\":\"10.1002/fld.4405\",\"journal\":\"International Journal for Numerical Methods in Fluids\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {remesh smoothed particle hydrodynamics,three-dimensional isotropic decaying turbulence,turbulent flow},\\n pages = {1-19},\\n volume = {86},\\n websites = {http://doi.wiley.com/10.1002/fld.4405},\\n month = {4},\\n publisher = {Wiley-Blackwell},\\n id = {51235906-1632-379f-8de3-6d3c18134f8b},\\n created = {2021-04-09T15:23:24.693Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:24.693Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Copyright © 2017 John Wiley & Sons, Ltd. We present a remeshed particle-mesh method for the simulation of three-dimensional compressible turbulent flow. The method is related to the meshfree smoothed particle hydrodynamics method, but the present method introduces a mesh for efficient calculation of the pressure gradient, and laminar and turbulent diffusion. In addition, the mesh is used to remesh (reorganise uniformly) the particles to ensure a regular particle distribution and convergence of the method. The accuracy of the presented methodology is tested for a number of benchmark problems involving two- and three-dimensional Taylor-Green flow, thin double shear layer, and three-dimensional isotropic turbulence. Two models were implemented, direct numerical simulations, and Smagorinsky model. Taking advantage of the Lagrangian advection, and the finite difference efficiency, the method is capable of providing quality simulations while maintaining its robustness and versatility.},\\n bibtype = {article},\\n author = {Obeidat, Anas and Bordas, Stéphane P A},\\n doi = {10.1002/fld.4405},\\n journal = {International Journal for Numerical Methods in Fluids},\\n number = {1}\\n}\",\"author_short\":[\"Obeidat,  A.\",\"Bordas,  S., P., A.\"],\"urls\":{\"Website\":\"http://doi.wiley.com/10.1002/fld.4405\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018\",\"role\":\"author\",\"keyword\":[\"remesh smoothed particle hydrodynamics\",\"three-dimensional isotropic decaying turbulence\",\"turbulent flow\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Kolmogorov spectrum consistent optimization for multi-scale flow decomposition\",\"type\":\"article\",\"year\":\"2014\",\"pages\":\"55106\",\"volume\":\"26\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.4871106\",\"month\":\"4\",\"id\":\"489c5ab7-e1ff-3915-994f-e4aae3de0d50\",\"created\":\"2021-04-09T15:23:25.571Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:25.571Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide ...\",\"bibtype\":\"article\",\"author\":\"Mishra, M and Liu, X and Skote, M and Fu, C W\",\"doi\":\"10.1063/1.4871106\",\"journal\":\"Physics of Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Kolmogorov spectrum consistent optimization for multi-scale flow decomposition},\\n type = {article},\\n year = {2014},\\n pages = {55106},\\n volume = {26},\\n websites = {http://aip.scitation.org/doi/10.1063/1.4871106},\\n month = {4},\\n id = {489c5ab7-e1ff-3915-994f-e4aae3de0d50},\\n created = {2021-04-09T15:23:25.571Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:25.571Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide ...},\\n bibtype = {article},\\n author = {Mishra, M and Liu, X and Skote, M and Fu, C W},\\n doi = {10.1063/1.4871106},\\n journal = {Physics of Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Mishra,  M.\",\"Liu,  X.\",\"Skote,  M.\",\"Fu,  C., W.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.4871106\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"experimental fluid mechanics,image processing,outlier detection,particle image velocimetry,proper orthogonal decomposition\",\"pages\":\"125303\",\"volume\":\"27\",\"websites\":\"http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b\",\"month\":\"4\",\"id\":\"dba5bfce-3af7-344f-b0c3-c53a04d6e84e\",\"created\":\"2021-04-09T15:23:26.054Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:26.054Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.\",\"bibtype\":\"article\",\"author\":\"Higham, J E and Brevis, W and Keylock, C J\",\"doi\":\"10.1088/0957-0233/27/12/125303\",\"journal\":\"Measurement Science and Technology\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data},\\n type = {article},\\n year = {2016},\\n keywords = {experimental fluid mechanics,image processing,outlier detection,particle image velocimetry,proper orthogonal decomposition},\\n pages = {125303},\\n volume = {27},\\n websites = {http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b},\\n month = {4},\\n id = {dba5bfce-3af7-344f-b0c3-c53a04d6e84e},\\n created = {2021-04-09T15:23:26.054Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:26.054Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.},\\n bibtype = {article},\\n author = {Higham, J E and Brevis, W and Keylock, C J},\\n doi = {10.1088/0957-0233/27/12/125303},\\n journal = {Measurement Science and Technology},\\n number = {12}\\n}\",\"author_short\":[\"Higham,  J., E.\",\"Brevis,  W.\",\"Keylock,  C., J.\"],\"urls\":{\"Website\":\"http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016\",\"role\":\"author\",\"keyword\":[\"experimental fluid mechanics\",\"image processing\",\"outlier detection\",\"particle image velocimetry\",\"proper orthogonal decomposition\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"58\",\"volume\":\"60\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2700-y\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"d7556610-b073-3556-97e4-8438c2bb3eb2\",\"created\":\"2021-04-09T15:23:26.564Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:26.564Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Wang, Jin and Zhang, Cao and Katz, Joseph\",\"doi\":\"10.1007/s00348-019-2700-y\",\"journal\":\"Experiments in Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution},\\n type = {article},\\n year = {2019},\\n pages = {58},\\n volume = {60},\\n websites = {http://link.springer.com/10.1007/s00348-019-2700-y},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {d7556610-b073-3556-97e4-8438c2bb3eb2},\\n created = {2021-04-09T15:23:26.564Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:26.564Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Wang, Jin and Zhang, Cao and Katz, Joseph},\\n doi = {10.1007/s00348-019-2700-y},\\n journal = {Experiments in Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Wang,  J.\",\"Zhang,  C.\",\"Katz,  J.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2700-y\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Local and nonlocal dynamics in superfluid turbulence\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"104517\",\"volume\":\"91\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevB.91.104517\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"7bb1275f-e165-3b14-a23e-732c494ccda4\",\"created\":\"2021-04-09T15:23:27.432Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:27.432Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Turbulence in superfluid helium~II is a tangle of quantized vortex lines which interact via the classical Biot-Savart law. We show that vortex tangles with the same vortex line density will have different energy spectra, depending on the normal fluid which feeds energy into the superfluid component, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the 'worms` of ordinary turbulence.\",\"bibtype\":\"article\",\"author\":\"Sherwin-Robson, L K and Barenghi, C F and Baggaley, A W\",\"doi\":\"10.1103/PhysRevB.91.104517\",\"journal\":\"Physical Review B\",\"number\":\"10\",\"bibtex\":\"@article{\\n title = {Local and nonlocal dynamics in superfluid turbulence},\\n type = {article},\\n year = {2015},\\n pages = {104517},\\n volume = {91},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevB.91.104517},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {7bb1275f-e165-3b14-a23e-732c494ccda4},\\n created = {2021-04-09T15:23:27.432Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:27.432Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Turbulence in superfluid helium~II is a tangle of quantized vortex lines which interact via the classical Biot-Savart law. We show that vortex tangles with the same vortex line density will have different energy spectra, depending on the normal fluid which feeds energy into the superfluid component, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the 'worms` of ordinary turbulence.},\\n bibtype = {article},\\n author = {Sherwin-Robson, L K and Barenghi, C F and Baggaley, A W},\\n doi = {10.1103/PhysRevB.91.104517},\\n journal = {Physical Review B},\\n number = {10}\\n}\",\"author_short\":[\"Sherwin-Robson,  L., K.\",\"Barenghi,  C., F.\",\"Baggaley,  A., W.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevB.91.104517\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"On coarse-grained simulations of turbulent material mixing\",\"type\":\"article\",\"year\":\"2012\",\"pages\":\"58203\",\"volume\":\"86\",\"websites\":\"http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27\",\"month\":\"4\",\"publisher\":\"IOP Publishing\",\"id\":\"b59e8f66-df49-356c-9971-4e3390d30396\",\"created\":\"2021-04-09T15:23:28.097Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:28.097Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.\",\"bibtype\":\"article\",\"author\":\"Grinstein, F F and Gowardhan, A A and Ristorcelli, J R and Wachtor, A J\",\"doi\":\"10.1088/0031-8949/86/05/058203\",\"journal\":\"Physica Scripta\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {On coarse-grained simulations of turbulent material mixing},\\n type = {article},\\n year = {2012},\\n pages = {58203},\\n volume = {86},\\n websites = {http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27},\\n month = {4},\\n publisher = {IOP Publishing},\\n id = {b59e8f66-df49-356c-9971-4e3390d30396},\\n created = {2021-04-09T15:23:28.097Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:28.097Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.},\\n bibtype = {article},\\n author = {Grinstein, F F and Gowardhan, A A and Ristorcelli, J R and Wachtor, A J},\\n doi = {10.1088/0031-8949/86/05/058203},\\n journal = {Physica Scripta},\\n number = {5}\\n}\",\"author_short\":[\"Grinstein,  F., F.\",\"Gowardhan,  A., A.\",\"Ristorcelli,  J., R.\",\"Wachtor,  A., J.\"],\"urls\":{\"Website\":\"http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Full-field pressure from snapshot and time-resolved volumetric PIV\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"1-14\",\"volume\":\"57\",\"websites\":\"http://link.springer.com/10.1007/s00348-016-2129-5\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"7301db0a-bf15-37e9-a0f6-62747dd8aaab\",\"created\":\"2021-04-09T15:23:29.050Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:29.050Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Laskari, A and de Kat, R and Ganapathisubramani, B\",\"doi\":\"10.1007/s00348-016-2129-5\",\"journal\":\"Experiments in Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Full-field pressure from snapshot and time-resolved volumetric PIV},\\n type = {article},\\n year = {2016},\\n pages = {1-14},\\n volume = {57},\\n websites = {http://link.springer.com/10.1007/s00348-016-2129-5},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {7301db0a-bf15-37e9-a0f6-62747dd8aaab},\\n created = {2021-04-09T15:23:29.050Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:29.050Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Laskari, A and de Kat, R and Ganapathisubramani, B},\\n doi = {10.1007/s00348-016-2129-5},\\n journal = {Experiments in Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Laskari,  A.\",\"de Kat,  R.\",\"Ganapathisubramani,  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In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. 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In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. 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We show here that this irreversibility can be quantified by following the relative motion of several Lagrangian tracers. We find by analytical calculation, numerical analysis and experimental observation that the existence of the energy flux implies that, at short times, two particles separate temporally slower forwards than backwards, and the difference between forward and backward dispersion grows as t^3. We also find the geometric deformation of material volumes, surrogated by four points spanning an initially regular tetrahedron, to show sensitivity to the time-reversal with an effect growing linearly in t. We associate this with the structure of the strain rate in the flow.\",\"bibtype\":\"article\",\"author\":\"Jucha, Jennifer and Xu, Haitao and Pumir, Alain and Bodenschatz, Eberhard\",\"doi\":\"10.1103/PhysRevLett.113.054501\",\"journal\":\"Physical Review Letters\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Time-reversal-symmetry breaking in turbulence},\\n type = {article},\\n year = {2014},\\n pages = {54501},\\n volume = {113},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.113.054501},\\n month = {4},\\n id = {63563e3e-b931-33fc-928b-86829f9249e1},\\n created = {2021-04-09T15:23:32.941Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:32.941Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In three-dimensional turbulent flows, the flux of energy from large to small scales breaks time symmetry. We show here that this irreversibility can be quantified by following the relative motion of several Lagrangian tracers. We find by analytical calculation, numerical analysis and experimental observation that the existence of the energy flux implies that, at short times, two particles separate temporally slower forwards than backwards, and the difference between forward and backward dispersion grows as t^3. We also find the geometric deformation of material volumes, surrogated by four points spanning an initially regular tetrahedron, to show sensitivity to the time-reversal with an effect growing linearly in t. We associate this with the structure of the strain rate in the flow.},\\n bibtype = {article},\\n author = {Jucha, Jennifer and Xu, Haitao and Pumir, Alain and Bodenschatz, Eberhard},\\n doi = {10.1103/PhysRevLett.113.054501},\\n journal = {Physical Review Letters},\\n number = {5}\\n}\",\"author_short\":[\"Jucha,  J.\",\"Xu,  H.\",\"Pumir,  A.\",\"Bodenschatz,  E.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevLett.113.054501\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"45302\",\"volume\":\"30\",\"websites\":\"http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c\",\"month\":\"4\",\"publisher\":\"IOP Publishing\",\"id\":\"6f742a18-ef05-39f4-8e72-5916fb799b83\",\"created\":\"2021-04-09T15:23:33.577Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:33.577Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Clark, A and Machicoane, N and Aliseda, A\",\"doi\":\"10.1088/1361-6501/ab0786\",\"journal\":\"Measurement Science and Technology\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking},\\n type = {article},\\n year = {2019},\\n pages = {45302},\\n volume = {30},\\n websites = {http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c},\\n month = {4},\\n publisher = {IOP Publishing},\\n id = {6f742a18-ef05-39f4-8e72-5916fb799b83},\\n created = {2021-04-09T15:23:33.577Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:33.577Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Clark, A and Machicoane, N and Aliseda, A},\\n doi = {10.1088/1361-6501/ab0786},\\n journal = {Measurement Science and Technology},\\n number = {4}\\n}\",\"author_short\":[\"Clark,  A.\",\"Machicoane,  N.\",\"Aliseda,  A.\"],\"urls\":{\"Website\":\"http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Flight-crash events in turbulence\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Lagrangian description,direct and inverse turbulent energy cascades,nonequilibrium statistical mechanics,nonequilibrium systems,turbulent mixing\",\"pages\":\"7558-7563\",\"volume\":\"111\",\"websites\":\"http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111\",\"month\":\"4\",\"publisher\":\"National Academy of Sciences\",\"id\":\"fda3961e-245e-3a03-a910-a65e04ccf982\",\"created\":\"2021-04-09T15:23:34.122Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:34.122Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The statistical properties of turbulence differ in an essential way from those of systems in or near thermal equilibrium because of the flux of energy between vastly different scales at which energy is supplied and at which it is dissipated. We elucidate this difference by studying experimentally and numerically the fluctuations of the energy of a small fluid particle moving in a turbulent fluid. We demonstrate how the fundamental property of detailed balance is broken, so that the probabilities of forward and backward transitions are not equal for turbulence. In physical terms, we found that in a large set of flow configurations, fluid elements decelerate faster than accelerate, a feature known all too well from driving in dense traffic. The statistical signature of rare \\\"flight-crash\\\" events, associated with fast particle deceleration, provides a way to quantify irreversibility in a turbulent flow. Namely, we find that the third moment of the power fluctuations along a trajectory, nondimensionalized by the energy flux, displays a remarkable power law as a function of the Reynolds number, both in two and in three spatial dimensions. This establishes a relation between the irreversibility of the system and the range of active scales. We speculate that the breakdown of the detailed balance characterized here is a general feature of other systems very far from equilibrium, displaying a wide range of spatial scales.\",\"bibtype\":\"article\",\"author\":\"Xu, Haitao and Pumir, Alain and Falkovich, Gregory and Bodenschatz, Eberhard and Shats, Michael and Xia, Hua and Francois, Nicolas and Boffetta, Guido\",\"doi\":\"10.1073/pnas.1321682111\",\"journal\":\"Proceedings of the National Academy of Sciences\",\"number\":\"21\",\"bibtex\":\"@article{\\n title = {Flight-crash events in turbulence},\\n type = {article},\\n year = {2014},\\n keywords = {Lagrangian description,direct and inverse turbulent energy cascades,nonequilibrium statistical mechanics,nonequilibrium systems,turbulent mixing},\\n pages = {7558-7563},\\n volume = {111},\\n websites = {http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111},\\n month = {4},\\n publisher = {National Academy of Sciences},\\n id = {fda3961e-245e-3a03-a910-a65e04ccf982},\\n created = {2021-04-09T15:23:34.122Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:34.122Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The statistical properties of turbulence differ in an essential way from those of systems in or near thermal equilibrium because of the flux of energy between vastly different scales at which energy is supplied and at which it is dissipated. We elucidate this difference by studying experimentally and numerically the fluctuations of the energy of a small fluid particle moving in a turbulent fluid. We demonstrate how the fundamental property of detailed balance is broken, so that the probabilities of forward and backward transitions are not equal for turbulence. In physical terms, we found that in a large set of flow configurations, fluid elements decelerate faster than accelerate, a feature known all too well from driving in dense traffic. The statistical signature of rare \\\"flight-crash\\\" events, associated with fast particle deceleration, provides a way to quantify irreversibility in a turbulent flow. Namely, we find that the third moment of the power fluctuations along a trajectory, nondimensionalized by the energy flux, displays a remarkable power law as a function of the Reynolds number, both in two and in three spatial dimensions. This establishes a relation between the irreversibility of the system and the range of active scales. We speculate that the breakdown of the detailed balance characterized here is a general feature of other systems very far from equilibrium, displaying a wide range of spatial scales.},\\n bibtype = {article},\\n author = {Xu, Haitao and Pumir, Alain and Falkovich, Gregory and Bodenschatz, Eberhard and Shats, Michael and Xia, Hua and Francois, Nicolas and Boffetta, Guido},\\n doi = {10.1073/pnas.1321682111},\\n journal = {Proceedings of the National Academy of Sciences},\\n number = {21}\\n}\",\"author_short\":[\"Xu,  H.\",\"Pumir,  A.\",\"Falkovich,  G.\",\"Bodenschatz,  E.\",\"Shats,  M.\",\"Xia,  H.\",\"Francois,  N.\",\"Boffetta,  G.\"],\"urls\":{\"Website\":\"http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014\",\"role\":\"author\",\"keyword\":[\"Lagrangian description\",\"direct and inverse turbulent energy cascades\",\"nonequilibrium statistical mechanics\",\"nonequilibrium systems\",\"turbulent mixing\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Deformation of a compliant wall in a turbulent channel flow\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"Turbulent boundary Layers,Turbulent flows\",\"pages\":\"345-390\",\"volume\":\"823\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"b7254578-dcde-3f36-a742-ff0536faf242\",\"created\":\"2021-04-09T15:23:34.928Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:34.928Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Interaction of a compliant wall with a turbulent channel flow is investigated experimentally by simultaneously measuring the time-resolved, three-dimensional (3D) flow field and the two-dimensional (2D) surface deformation. The optical set-up integrates tomographic particle image velocimetry to measure the flow with Mach–Zehnder interferometry to map the deformation. The Reynolds number is Re_[STIX]x1D70F=2300 , and the Young’s modulus of the wall is 0.93 MPa, resulting in a ratio of shear speed to the centreline velocity ( U_0 ) of 6.8. The wavenumber–frequency spectra of deformation show the surface motions consist of a non-advected low-frequency component and advected modes, some travelling downstream at approximately U_0 and others at ~0.72U_0 . The r.m.s. values of the advected and non-advected modes are 0.04~[STIX]x03BCm (0.004[STIX]x1D6FF_[STIX]x1D708) and 0.2~[STIX]x03BCm ( 0.02[STIX]x1D6FF_[STIX]x1D708 ), respectively, much smaller than the wall unit ( [STIX]x1D6FF_[STIX]x1D708 ), hence they do not affect the flow. Trends in the wall dynamics are elucidated by correlating the deformation with flow variables, including the 3D pressure distribution calculated by spatially integrating the material acceleration. Predictions by the Chase [ J. Acoust. Soc. Am. , vol. 89 (6), pp. 2589–2596] linear model are also calculated and compared to the measured trends. The spatial deformation–pressure correlations peak at y/h 0.12 ( h is half channel height), the elevation of Reynolds shear stress maximum in the log-layer. Streamwise lagging of the deformation behind the pressure is caused in part by phase lag of the pressure with decreasing distance from the wall, and in part by material damping. Positive deformations (bumps) caused by negative pressure fluctuations are preferentially associated with ejections involving spanwise vortices located downstream and quasi-streamwise vortices with spanwise offset. Results of conditional correlations are consistent with the presence of hairpin-like structures. The negative deformations (dimples) are preferentially associated with positive pressure fluctuations at the transition between an upstream sweep to a downstream ejection.\",\"bibtype\":\"article\",\"author\":\"Zhang, Cao and Wang, Jin and Blake, William and Katz, Joseph\",\"doi\":\"10.1017/jfm.2017.299\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Deformation of a compliant wall in a turbulent channel flow},\\n type = {article},\\n year = {2017},\\n keywords = {Turbulent boundary Layers,Turbulent flows},\\n pages = {345-390},\\n volume = {823},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {b7254578-dcde-3f36-a742-ff0536faf242},\\n created = {2021-04-09T15:23:34.928Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:34.928Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Interaction of a compliant wall with a turbulent channel flow is investigated experimentally by simultaneously measuring the time-resolved, three-dimensional (3D) flow field and the two-dimensional (2D) surface deformation. The optical set-up integrates tomographic particle image velocimetry to measure the flow with Mach–Zehnder interferometry to map the deformation. The Reynolds number is Re_[STIX]x1D70F=2300 , and the Young’s modulus of the wall is 0.93 MPa, resulting in a ratio of shear speed to the centreline velocity ( U_0 ) of 6.8. The wavenumber–frequency spectra of deformation show the surface motions consist of a non-advected low-frequency component and advected modes, some travelling downstream at approximately U_0 and others at ~0.72U_0 . The r.m.s. values of the advected and non-advected modes are 0.04~[STIX]x03BCm (0.004[STIX]x1D6FF_[STIX]x1D708) and 0.2~[STIX]x03BCm ( 0.02[STIX]x1D6FF_[STIX]x1D708 ), respectively, much smaller than the wall unit ( [STIX]x1D6FF_[STIX]x1D708 ), hence they do not affect the flow. Trends in the wall dynamics are elucidated by correlating the deformation with flow variables, including the 3D pressure distribution calculated by spatially integrating the material acceleration. Predictions by the Chase [ J. Acoust. Soc. Am. , vol. 89 (6), pp. 2589–2596] linear model are also calculated and compared to the measured trends. The spatial deformation–pressure correlations peak at y/h 0.12 ( h is half channel height), the elevation of Reynolds shear stress maximum in the log-layer. Streamwise lagging of the deformation behind the pressure is caused in part by phase lag of the pressure with decreasing distance from the wall, and in part by material damping. Positive deformations (bumps) caused by negative pressure fluctuations are preferentially associated with ejections involving spanwise vortices located downstream and quasi-streamwise vortices with spanwise offset. Results of conditional correlations are consistent with the presence of hairpin-like structures. The negative deformations (dimples) are preferentially associated with positive pressure fluctuations at the transition between an upstream sweep to a downstream ejection.},\\n bibtype = {article},\\n author = {Zhang, Cao and Wang, Jin and Blake, William and Katz, Joseph},\\n doi = {10.1017/jfm.2017.299},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Zhang,  C.\",\"Wang,  J.\",\"Blake,  W.\",\"Katz,  J.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017\",\"role\":\"author\",\"keyword\":[\"Turbulent boundary Layers\",\"Turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1902.07358\",\"month\":\"4\",\"id\":\"bf1067d7-1a27-31e0-9024-7edb31cc4c99\",\"created\":\"2021-04-09T15:23:35.428Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:35.428Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance with traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.\",\"bibtype\":\"article\",\"author\":\"Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan\",\"bibtex\":\"@article{\\n title = {Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1902.07358},\\n month = {4},\\n id = {bf1067d7-1a27-31e0-9024-7edb31cc4c99},\\n created = {2021-04-09T15:23:35.428Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:35.428Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance with traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.},\\n bibtype = {article},\\n author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan}\\n}\",\"author_short\":[\"Erichson,  N., B.\",\"Mathelin,  L.\",\"Yao,  Z.\",\"Brunton,  S., L.\",\"Mahoney,  M., W.\",\"Kutz,  J., N.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1902.07358\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"intermittency,isotropic turbulence,particle/fluid flows\",\"pages\":\"465-486\",\"volume\":\"860\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"0aeeba05-23f0-32cf-918a-2aeba6c223e8\",\"created\":\"2021-04-09T15:23:36.064Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:36.064Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We examine the dynamics of slender, rigid rods in direct numerical simulation of isotropic turbulence. The focus is on the statistics of three quantities and how they vary as rod length increases from the dissipation range to the inertial range. These quantities are (i) the steady-state rod alignment with respect to the perceived velocity gradients in the surrounding flow, (ii) the rate of rod reorientation (tumbling) and (iii) the rate at which the rod end points move apart (stretching). Under the approximations of slender-body theory, the rod inertia is neglected and rods are modelled as passive particles in the flow that do not affect the fluid velocity field. We find that the average rod alignment changes qualitatively as rod length increases from the dissipation range to the inertial range. While rods in the dissipation range align most strongly with fluid vorticity, rods in the inertial range align most strongly with the most extensional eigenvector of the perceived strain-rate tensor. For rods in the inertial range, we find that the variance of rod stretching and the variance of rod tumbling both scale as l^-4/3 , where l is the rod length. However, when rod dynamics are compared to two-point fluid velocity statistics (structure functions), we see non-monotonic behaviour in the variance of rod tumbling due to the influence of small-scale fluid motions. Additionally, we find that the skewness of rod stretching does not show scale invariance in the inertial range, in contrast to the skewness of longitudinal fluid velocity increments as predicted by Kolmogorov’s 4/5 law. Finally, we examine the power-law scaling exponents of higher-order moments of rod tumbling and rod stretching for rods with lengths in the inertial range and find that they show anomalous scaling. We compare these scaling exponents to predictions from Kolmogorov’s refined similarity hypotheses.\",\"bibtype\":\"article\",\"author\":\"Pujara, Nimish and Voth, Greg A and Variano, Evan A\",\"doi\":\"10.1017/jfm.2018.866\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence},\\n type = {article},\\n year = {2019},\\n keywords = {intermittency,isotropic turbulence,particle/fluid flows},\\n pages = {465-486},\\n volume = {860},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {0aeeba05-23f0-32cf-918a-2aeba6c223e8},\\n created = {2021-04-09T15:23:36.064Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:36.064Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We examine the dynamics of slender, rigid rods in direct numerical simulation of isotropic turbulence. The focus is on the statistics of three quantities and how they vary as rod length increases from the dissipation range to the inertial range. These quantities are (i) the steady-state rod alignment with respect to the perceived velocity gradients in the surrounding flow, (ii) the rate of rod reorientation (tumbling) and (iii) the rate at which the rod end points move apart (stretching). Under the approximations of slender-body theory, the rod inertia is neglected and rods are modelled as passive particles in the flow that do not affect the fluid velocity field. We find that the average rod alignment changes qualitatively as rod length increases from the dissipation range to the inertial range. While rods in the dissipation range align most strongly with fluid vorticity, rods in the inertial range align most strongly with the most extensional eigenvector of the perceived strain-rate tensor. For rods in the inertial range, we find that the variance of rod stretching and the variance of rod tumbling both scale as l^-4/3 , where l is the rod length. However, when rod dynamics are compared to two-point fluid velocity statistics (structure functions), we see non-monotonic behaviour in the variance of rod tumbling due to the influence of small-scale fluid motions. Additionally, we find that the skewness of rod stretching does not show scale invariance in the inertial range, in contrast to the skewness of longitudinal fluid velocity increments as predicted by Kolmogorov’s 4/5 law. Finally, we examine the power-law scaling exponents of higher-order moments of rod tumbling and rod stretching for rods with lengths in the inertial range and find that they show anomalous scaling. We compare these scaling exponents to predictions from Kolmogorov’s refined similarity hypotheses.},\\n bibtype = {article},\\n author = {Pujara, Nimish and Voth, Greg A and Variano, Evan A},\\n doi = {10.1017/jfm.2018.866},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Pujara,  N.\",\"Voth,  G., A.\",\"Variano,  E., A.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019\",\"role\":\"author\",\"keyword\":[\"intermittency\",\"isotropic turbulence\",\"particle/fluid flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"Compressible flows,DNS,Density fluctuations,Favre average,Homogeneous turbulence,Linear Interaction Approximation,Mixing,RANS,Rayleigh-Taylor,Reynolds stress,Richtmyer-Meshkov,Shear,Turbulence,Two-length scale,Two-time scale,Variable density\",\"pages\":\"1-43\",\"volume\":\"96\",\"websites\":\"http://link.springer.com/10.1007/s10494-015-9643-z\",\"month\":\"4\",\"publisher\":\"Springer Netherlands\",\"id\":\"cbacad99-a22a-316d-ba88-7841c0cd0d26\",\"created\":\"2021-04-09T15:23:36.618Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:36.618Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.\",\"bibtype\":\"article\",\"author\":\"Schwarzkopf, J D and Livescu, D and Baltzer, J R and Gore, R A and Ristorcelli, J R\",\"doi\":\"10.1007/s10494-015-9643-z\",\"journal\":\"Flow, Turbulence and Combustion\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing},\\n type = {article},\\n year = {2016},\\n keywords = {Compressible flows,DNS,Density fluctuations,Favre average,Homogeneous turbulence,Linear Interaction Approximation,Mixing,RANS,Rayleigh-Taylor,Reynolds stress,Richtmyer-Meshkov,Shear,Turbulence,Two-length scale,Two-time scale,Variable density},\\n pages = {1-43},\\n volume = {96},\\n websites = {http://link.springer.com/10.1007/s10494-015-9643-z},\\n month = {4},\\n publisher = {Springer Netherlands},\\n id = {cbacad99-a22a-316d-ba88-7841c0cd0d26},\\n created = {2021-04-09T15:23:36.618Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:36.618Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.},\\n bibtype = {article},\\n author = {Schwarzkopf, J D and Livescu, D and Baltzer, J R and Gore, R A and Ristorcelli, J R},\\n doi = {10.1007/s10494-015-9643-z},\\n journal = {Flow, Turbulence and Combustion},\\n number = {1}\\n}\",\"author_short\":[\"Schwarzkopf,  J., D.\",\"Livescu,  D.\",\"Baltzer,  J., R.\",\"Gore,  R., A.\",\"Ristorcelli,  J., R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s10494-015-9643-z\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016\",\"role\":\"author\",\"keyword\":[\"Compressible flows\",\"DNS\",\"Density fluctuations\",\"Favre average\",\"Homogeneous turbulence\",\"Linear Interaction Approximation\",\"Mixing\",\"RANS\",\"Rayleigh-Taylor\",\"Reynolds stress\",\"Richtmyer-Meshkov\",\"Shear\",\"Turbulence\",\"Two-length scale\",\"Two-time scale\",\"Variable density\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"TTHRESH: Tensor Compression for Multidimensional Visual Data\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"1\",\"websites\":\"http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/\",\"month\":\"4\",\"id\":\"42be9489-0a16-33a0-83cb-d7f6a51e32f6\",\"created\":\"2021-04-09T15:23:37.189Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:37.189Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression algorithm for N-dimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to 3 and more dimensions, together with adaptive quantization, run-length and arithmetic coding to store the HOSVD transform coefficients' relative positions as sorted by their absolute magnitude. Our scheme degrades the data particularly smoothly and outperforms other state-of-the-art volume compressors at low-to-medium bit rates, as required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include extremely fine bit rate selection granularity, bounded resulting l^2 error, and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct subsampled or filtered-resampled versions of all (or selected parts) of the data set.\",\"bibtype\":\"article\",\"author\":\"Ballester-Ripoll, Rafael and Lindstrom, Peter and Pajarola, Renato\",\"doi\":\"10.1109/TVCG.2019.2904063\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"bibtex\":\"@article{\\n title = {TTHRESH: Tensor Compression for Multidimensional Visual Data},\\n type = {article},\\n year = {2019},\\n pages = {1},\\n websites = {http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/},\\n month = {4},\\n id = {42be9489-0a16-33a0-83cb-d7f6a51e32f6},\\n created = {2021-04-09T15:23:37.189Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:37.189Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression algorithm for N-dimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to 3 and more dimensions, together with adaptive quantization, run-length and arithmetic coding to store the HOSVD transform coefficients' relative positions as sorted by their absolute magnitude. Our scheme degrades the data particularly smoothly and outperforms other state-of-the-art volume compressors at low-to-medium bit rates, as required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include extremely fine bit rate selection granularity, bounded resulting l^2 error, and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct subsampled or filtered-resampled versions of all (or selected parts) of the data set.},\\n bibtype = {article},\\n author = {Ballester-Ripoll, Rafael and Lindstrom, Peter and Pajarola, Renato},\\n doi = {10.1109/TVCG.2019.2904063},\\n journal = {IEEE Transactions on Visualization and Computer Graphics}\\n}\",\"author_short\":[\"Ballester-Ripoll,  R.\",\"Lindstrom,  P.\",\"Pajarola,  R.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"The spanwise spectra in wall-bounded turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Inner/outer peak,Scale separation,Streamwise/spanwise spectra,Wall-bounded turbulence\",\"pages\":\"452-461\",\"volume\":\"34\",\"websites\":\"http://link.springer.com/10.1007/s10409-017-0731-2\",\"month\":\"4\",\"publisher\":\"The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences\",\"id\":\"bb01c65f-b97c-3004-b791-211a96563468\",\"created\":\"2021-04-09T15:23:37.690Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:37.690Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Wang, Hong-Ping and Wang, Shi-Zhao and He, Guo-Wei\",\"doi\":\"10.1007/s10409-017-0731-2\",\"journal\":\"Acta Mechanica Sinica\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {The spanwise spectra in wall-bounded turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {Inner/outer peak,Scale separation,Streamwise/spanwise spectra,Wall-bounded turbulence},\\n pages = {452-461},\\n volume = {34},\\n websites = {http://link.springer.com/10.1007/s10409-017-0731-2},\\n month = {4},\\n publisher = {The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences},\\n id = {bb01c65f-b97c-3004-b791-211a96563468},\\n created = {2021-04-09T15:23:37.690Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:37.690Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Wang, Hong-Ping and Wang, Shi-Zhao and He, Guo-Wei},\\n doi = {10.1007/s10409-017-0731-2},\\n journal = {Acta Mechanica Sinica},\\n number = {3}\\n}\",\"author_short\":[\"Wang,  H.\",\"Wang,  S.\",\"He,  G.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s10409-017-0731-2\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-wang-he-thespanwisespectrainwallboundedturbulence-2018\",\"role\":\"author\",\"keyword\":[\"Inner/outer peak\",\"Scale separation\",\"Streamwise/spanwise spectra\",\"Wall-bounded turbulence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Beyond Kolmogorov cascades\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"intermittency,turbulence theory\",\"pages\":\"P1\",\"volume\":\"867\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"1012b117-456b-32d9-b1ba-3795e219b594\",\"created\":\"2021-04-09T15:23:38.322Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:38.322Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The large-scale structure of many turbulent flows encountered in practical situations such as aeronautics, industry, meteorology is nowadays successfully computed using the Kolmogorov–Kármán–Howarth energy cascade picture. This theory appears increasingly inaccurate when going down the energy cascade that terminates through intermittent spots of energy dissipation, at variance with the assumed homogeneity. This is problematic for the modelling of all processes that depend on small scales of turbulence, such as combustion instabilities or droplet atomization in industrial burners or cloud formation. This paper explores a paradigm shift where the homogeneity hypothesis is replaced by the assumption that turbulence contains singularities, as suggested by Onsager. This paradigm leads to a weak formulation of the Kolmogorov–Kármán–Howarth–Monin equation (WKHE) that allows taking into account explicitly the presence of singularities and their impact on the energy transfer and dissipation. It provides a local in scale, space and time description of energy transfers and dissipation, valid for any inhomogeneous, anisotropic flow, under any type of boundary conditions. The goal of this article is to discuss WKHE as a tool to get a new description of energy cascades and dissipation that goes beyond Kolmogorov and allows the description of small-scale intermittency. It puts the problem of intermittency and dissipation in turbulence into a modern framework, compatible with recent mathematical advances on the proof of Onsager’s conjecture.\",\"bibtype\":\"article\",\"author\":\"Dubrulle, Bérengère\",\"doi\":\"10.1017/jfm.2019.98\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Beyond Kolmogorov cascades},\\n type = {article},\\n year = {2019},\\n keywords = {intermittency,turbulence theory},\\n pages = {P1},\\n volume = {867},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {1012b117-456b-32d9-b1ba-3795e219b594},\\n created = {2021-04-09T15:23:38.322Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:38.322Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The large-scale structure of many turbulent flows encountered in practical situations such as aeronautics, industry, meteorology is nowadays successfully computed using the Kolmogorov–Kármán–Howarth energy cascade picture. This theory appears increasingly inaccurate when going down the energy cascade that terminates through intermittent spots of energy dissipation, at variance with the assumed homogeneity. This is problematic for the modelling of all processes that depend on small scales of turbulence, such as combustion instabilities or droplet atomization in industrial burners or cloud formation. This paper explores a paradigm shift where the homogeneity hypothesis is replaced by the assumption that turbulence contains singularities, as suggested by Onsager. This paradigm leads to a weak formulation of the Kolmogorov–Kármán–Howarth–Monin equation (WKHE) that allows taking into account explicitly the presence of singularities and their impact on the energy transfer and dissipation. It provides a local in scale, space and time description of energy transfers and dissipation, valid for any inhomogeneous, anisotropic flow, under any type of boundary conditions. The goal of this article is to discuss WKHE as a tool to get a new description of energy cascades and dissipation that goes beyond Kolmogorov and allows the description of small-scale intermittency. It puts the problem of intermittency and dissipation in turbulence into a modern framework, compatible with recent mathematical advances on the proof of Onsager’s conjecture.},\\n bibtype = {article},\\n author = {Dubrulle, Bérengère},\\n doi = {10.1017/jfm.2019.98},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Dubrulle,  B.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"dubrulle-beyondkolmogorovcascades-2019\",\"role\":\"author\",\"keyword\":[\"intermittency\",\"turbulence theory\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow\",\"type\":\"misc\",\"year\":\"2019\",\"keywords\":\"analysis,computational fluid dynamics,reference turbine,simulations,wind energy\",\"websites\":\"http://www.osti.gov/servlets/purl/1493479/\",\"month\":\"4\",\"institution\":\"National Renewable Energy Laboratory (NREL)\",\"id\":\"70cedc58-3373-3d60-afe1-61d2bbed6131\",\"created\":\"2021-04-09T15:23:38.930Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:38.930Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"report\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Lawson, Michael J and Melvin, Jeremy and Ananthan, Shreyas and Gruchalla, Kenny M and Rood, Jonathan S and Sprague, Michael A\",\"doi\":\"10.2172/1493479\",\"bibtex\":\"@misc{\\n title = {Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow},\\n type = {misc},\\n year = {2019},\\n keywords = {analysis,computational fluid dynamics,reference turbine,simulations,wind energy},\\n websites = {http://www.osti.gov/servlets/purl/1493479/},\\n month = {4},\\n institution = {National Renewable Energy Laboratory (NREL)},\\n id = {70cedc58-3373-3d60-afe1-61d2bbed6131},\\n created = {2021-04-09T15:23:38.930Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:38.930Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {report},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Lawson, Michael J and Melvin, Jeremy and Ananthan, Shreyas and Gruchalla, Kenny M and Rood, Jonathan S and Sprague, Michael A},\\n doi = {10.2172/1493479}\\n}\",\"author_short\":[\"Lawson,  M., J.\",\"Melvin,  J.\",\"Ananthan,  S.\",\"Gruchalla,  K., M.\",\"Rood,  J., S.\",\"Sprague,  M., A.\"],\"urls\":{\"Website\":\"http://www.osti.gov/servlets/purl/1493479/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019\",\"role\":\"author\",\"keyword\":[\"analysis\",\"computational fluid dynamics\",\"reference turbine\",\"simulations\",\"wind energy\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Analysis of geometrical and statistical features of Lagrangian stretching in turbulent channel flow using a database task-parallel particle tracking algorithm\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"14605\",\"volume\":\"2\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605\",\"month\":\"4\",\"publisher\":\"American Physical 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= {4},\\n publisher = {American Physical Society},\\n id = {e74b8566-4274-3b1a-a739-79796c7ef4f6},\\n created = {2021-04-09T15:23:39.680Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:39.680Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Johnson, Perry L and Hamilton, Stephen S and Burns, Randal and Meneveau, Charles},\\n doi = {10.1103/PhysRevFluids.2.014605},\\n journal = {Physical Review Fluids},\\n number = {1}\\n}\",\"author_short\":[\"Johnson,  P., L.\",\"Hamilton,  S., S.\",\"Burns,  R.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Compression and heuristic caching for GPU particle tracing in turbulent vector fields\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"Data compression,Data streaming,Particle tracing,Turbulence,Vector fields\",\"pages\":\"144-165\",\"volume\":\"598\",\"websites\":\"http://link.springer.com/10.1007/978-3-319-29971-6_8\",\"publisher\":\"Springer, Cham\",\"id\":\"c967ab18-170c-3561-9b15-cf0969b9566f\",\"created\":\"2021-04-09T15:23:40.216Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:40.216Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© Springer International Publishing Switzerland 2016. Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.\",\"bibtype\":\"article\",\"author\":\"Treib, Marc and Bürger, Kai and Wu, Jun and Westermann, Rüdiger\",\"doi\":\"10.1007/978-3-319-29971-6_8\",\"journal\":\"Communications in Computer and Information Science\",\"bibtex\":\"@article{\\n title = {Compression and heuristic caching for GPU particle tracing in turbulent vector fields},\\n type = {article},\\n year = {2016},\\n keywords = {Data compression,Data streaming,Particle tracing,Turbulence,Vector fields},\\n pages = {144-165},\\n volume = {598},\\n websites = {http://link.springer.com/10.1007/978-3-319-29971-6_8},\\n publisher = {Springer, Cham},\\n id = {c967ab18-170c-3561-9b15-cf0969b9566f},\\n created = {2021-04-09T15:23:40.216Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:40.216Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© Springer International Publishing Switzerland 2016. Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.},\\n bibtype = {article},\\n author = {Treib, Marc and Bürger, Kai and Wu, Jun and Westermann, Rüdiger},\\n doi = {10.1007/978-3-319-29971-6_8},\\n journal = {Communications in Computer and Information Science}\\n}\",\"author_short\":[\"Treib,  M.\",\"Bürger,  K.\",\"Wu,  J.\",\"Westermann,  R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-319-29971-6_8\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016\",\"role\":\"author\",\"keyword\":[\"Data compression\",\"Data streaming\",\"Particle tracing\",\"Turbulence\",\"Vector fields\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Dynamic estimation,Linear stochastic estimation,PIV,Proper orthogonal decomposition\",\"pages\":\"119-130\",\"volume\":\"93\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"cdac6288-8a17-349d-91de-b4fe36f68248\",\"created\":\"2021-04-09T15:23:40.778Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:40.778Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"A method for the estimation of time-resolved turbulent fields from the combination of non-time-resolved field measurements and time-resolved point measurements is proposed. The approach poses its fundaments on a stochastic estimation based on the Proper Orthogonal Decomposition (POD) of the field measurements and of the time-resolved point measurements. The correlation between the temporal modes of the field measurements and the temporal modes of the point measurements at synchronized instants is evaluated; this correlation is extended to the “out-of-sample” time instants for the field measurements, i.e. those in which field data are not available. In the “out-of-sample” instants, POD modes time coefficients are estimated and the flow fields are reconstructed. The proposed method extends the work by Hosseini et al. (Experiments in fluids, 56, 2015) by proposing a truncation criterion which allows removing the uncorrelated part of the signal from the reconstruction of the flow fields. The truncation is fundamental in case of turbulent flow fields, in which a great wealth of scales is involved, thus reducing the correlation between the probe signal and the field measurements. The threshold selection is based on the random distribution of the uncorrelated signal. Additionally, the selection of the probe time-span to perform the POD analysis on the probe signal is discussed. The method is validated with a synthetic test case and an experimental one. A Direct Numerical Simulation database of a channel flow is selected since its spectral richness is expected to represent a significant challenge for this method. This dataset allows isolating the effects of correlation between field measurements and point measurements, removing issues connected to noise contamination or to the finite spatial resolution which would inevitably affect experimental data. The experimental test case is the wake-flow behind a high-angle-of-attack airfoil with a relatively small number of samples, affected by significant noise. The quality of the dynamic estimation is found to be affected by the noise contamination of the data and by the poor convergence of the POD modes, which add on the effect of the probe location, i.e. on the correlation between probe events and flow features. The squared correlation coefficient between reconstructed data and in-sample data is proposed as an assessment of the flow fields estimation quality. The use of the squared correlation coefficient directly on in-sample data is allowed by the truncation itself.\",\"bibtype\":\"article\",\"author\":\"Discetti, Stefano and Raiola, Marco and Ianiro, Andrea\",\"doi\":\"10.1016/j.expthermflusci.2017.12.011\",\"journal\":\"Experimental Thermal and Fluid Science\",\"bibtex\":\"@article{\\n title = {Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements},\\n type = {article},\\n year = {2018},\\n keywords = {Dynamic estimation,Linear stochastic estimation,PIV,Proper orthogonal decomposition},\\n pages = {119-130},\\n volume = {93},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941},\\n month = {4},\\n publisher = {Elsevier},\\n id = {cdac6288-8a17-349d-91de-b4fe36f68248},\\n created = {2021-04-09T15:23:40.778Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:40.778Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {A method for the estimation of time-resolved turbulent fields from the combination of non-time-resolved field measurements and time-resolved point measurements is proposed. The approach poses its fundaments on a stochastic estimation based on the Proper Orthogonal Decomposition (POD) of the field measurements and of the time-resolved point measurements. The correlation between the temporal modes of the field measurements and the temporal modes of the point measurements at synchronized instants is evaluated; this correlation is extended to the “out-of-sample” time instants for the field measurements, i.e. those in which field data are not available. In the “out-of-sample” instants, POD modes time coefficients are estimated and the flow fields are reconstructed. The proposed method extends the work by Hosseini et al. (Experiments in fluids, 56, 2015) by proposing a truncation criterion which allows removing the uncorrelated part of the signal from the reconstruction of the flow fields. The truncation is fundamental in case of turbulent flow fields, in which a great wealth of scales is involved, thus reducing the correlation between the probe signal and the field measurements. The threshold selection is based on the random distribution of the uncorrelated signal. Additionally, the selection of the probe time-span to perform the POD analysis on the probe signal is discussed. The method is validated with a synthetic test case and an experimental one. A Direct Numerical Simulation database of a channel flow is selected since its spectral richness is expected to represent a significant challenge for this method. This dataset allows isolating the effects of correlation between field measurements and point measurements, removing issues connected to noise contamination or to the finite spatial resolution which would inevitably affect experimental data. The experimental test case is the wake-flow behind a high-angle-of-attack airfoil with a relatively small number of samples, affected by significant noise. The quality of the dynamic estimation is found to be affected by the noise contamination of the data and by the poor convergence of the POD modes, which add on the effect of the probe location, i.e. on the correlation between probe events and flow features. The squared correlation coefficient between reconstructed data and in-sample data is proposed as an assessment of the flow fields estimation quality. The use of the squared correlation coefficient directly on in-sample data is allowed by the truncation itself.},\\n bibtype = {article},\\n author = {Discetti, Stefano and Raiola, Marco and Ianiro, Andrea},\\n doi = {10.1016/j.expthermflusci.2017.12.011},\\n journal = {Experimental Thermal and Fluid Science}\\n}\",\"author_short\":[\"Discetti,  S.\",\"Raiola,  M.\",\"Ianiro,  A.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018\",\"role\":\"author\",\"keyword\":[\"Dynamic estimation\",\"Linear stochastic estimation\",\"PIV\",\"Proper orthogonal decomposition\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport\",\"type\":\"article\",\"year\":\"2012\",\"pages\":\"n/a-n/a\",\"volume\":\"117\",\"websites\":\"http://doi.wiley.com/10.1029/2011JF002127\",\"month\":\"4\",\"id\":\"cf45c3cd-ec34-3554-a185-77fd023702b3\",\"created\":\"2021-04-09T15:23:41.333Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:41.333Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Kolmogorov�s classic theory for turbulence assumed an independence velocity increments and the value for the velocity itself., recent work has called this assumption in to question, which implications for the structure of atmospheric, oceanic and fluvial. Here we propose a conceptually simple analytical framework studying velocity-intermittency coupling that is similar in essence the popular quadrant analysis method for studying near-wall flows., we study the dominant (longitudinal) velocity component with a measure of the roughness of the signal, given mathematically its series of H�lder exponents. Thus, we permit a possible dependence velocity and intermittency. We compare boundary layer data in a wind tunnel to turbulent jets and wake flows. These classes all have distinct characteristics, which cause them be readily distinguished using our technique and the results are to changes in flow Reynolds numbers. Classification of environmental is then possible based on their similarities to the idealized classes and we demonstrate this using laboratory data for flow a parallel-channel confluence. Our results have clear implications sediment transport in a range of geophysical applications as suggest that the recently proposed impulse-based methods for bed load transport are particularly relevant in domains as gravel bed river flows where the boundary layer is disrupted wake interactions predominate.\",\"bibtype\":\"article\",\"author\":\"Keylock, C J and Nishimura, K and Peinke, J\",\"doi\":\"10.1029/2011JF002127\",\"journal\":\"Journal of Geophysical Research: Earth Surface\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport},\\n type = {article},\\n year = {2012},\\n pages = {n/a-n/a},\\n volume = {117},\\n websites = {http://doi.wiley.com/10.1029/2011JF002127},\\n month = {4},\\n id = {cf45c3cd-ec34-3554-a185-77fd023702b3},\\n created = {2021-04-09T15:23:41.333Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:41.333Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Kolmogorov�s classic theory for turbulence assumed an independence velocity increments and the value for the velocity itself., recent work has called this assumption in to question, which implications for the structure of atmospheric, oceanic and fluvial. Here we propose a conceptually simple analytical framework studying velocity-intermittency coupling that is similar in essence the popular quadrant analysis method for studying near-wall flows., we study the dominant (longitudinal) velocity component with a measure of the roughness of the signal, given mathematically its series of H�lder exponents. Thus, we permit a possible dependence velocity and intermittency. We compare boundary layer data in a wind tunnel to turbulent jets and wake flows. These classes all have distinct characteristics, which cause them be readily distinguished using our technique and the results are to changes in flow Reynolds numbers. Classification of environmental is then possible based on their similarities to the idealized classes and we demonstrate this using laboratory data for flow a parallel-channel confluence. Our results have clear implications sediment transport in a range of geophysical applications as suggest that the recently proposed impulse-based methods for bed load transport are particularly relevant in domains as gravel bed river flows where the boundary layer is disrupted wake interactions predominate.},\\n bibtype = {article},\\n author = {Keylock, C J and Nishimura, K and Peinke, J},\\n doi = {10.1029/2011JF002127},\\n journal = {Journal of Geophysical Research: Earth Surface},\\n number = {1}\\n}\",\"author_short\":[\"Keylock,  C., J.\",\"Nishimura,  K.\",\"Peinke,  J.\"],\"urls\":{\"Website\":\"http://doi.wiley.com/10.1029/2011JF002127\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"3D Fluid Flow Estimation with Integrated Particle Reconstruction\",\"type\":\"inproceedings\",\"year\":\"2018\",\"pages\":\"315-332\",\"websites\":\"http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22\",\"month\":\"4\",\"id\":\"494766c9-e3b7-399f-9215-806df54ff32a\",\"created\":\"2021-04-09T15:23:41.951Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:41.951Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps: first, a per-frame reconstruction of the particles, usually in the form of soft occupancy likelihoods in a voxel representation; followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model explicitly reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-resolution input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over a recent baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of state-of-the-art tracking-based methods that require much longer sequences.\",\"bibtype\":\"inproceedings\",\"author\":\"Lasinger, Katrin and Vogel, Christoph and Pock, Thomas and Schindler, Konrad\",\"doi\":\"10.1007/978-3-030-12939-2_22\",\"booktitle\":\"40th German Conference on Pattern Recognition, GCPR 2018\",\"bibtex\":\"@inproceedings{\\n title = {3D Fluid Flow Estimation with Integrated Particle Reconstruction},\\n type = {inproceedings},\\n year = {2018},\\n pages = {315-332},\\n websites = {http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22},\\n month = {4},\\n id = {494766c9-e3b7-399f-9215-806df54ff32a},\\n created = {2021-04-09T15:23:41.951Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:41.951Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps: first, a per-frame reconstruction of the particles, usually in the form of soft occupancy likelihoods in a voxel representation; followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model explicitly reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-resolution input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over a recent baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of state-of-the-art tracking-based methods that require much longer sequences.},\\n bibtype = {inproceedings},\\n author = {Lasinger, Katrin and Vogel, Christoph and Pock, Thomas and Schindler, Konrad},\\n doi = {10.1007/978-3-030-12939-2_22},\\n booktitle = {40th German Conference on Pattern Recognition, GCPR 2018}\\n}\",\"author_short\":[\"Lasinger,  K.\",\"Vogel,  C.\",\"Pock,  T.\",\"Schindler,  K.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"1665-1671\",\"volume\":\"382\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918\",\"month\":\"4\",\"publisher\":\"North-Holland\",\"id\":\"f51f7ca2-fc3f-3dcb-9662-759d1235c5ba\",\"created\":\"2021-04-09T15:23:42.918Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:42.918Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In order to introduce new physics to traditional two-point correlations, we define the second-order correlation of longitudinal velocity increments at three points and obtain the analytical expressions in isotropic turbulence. By introducing the Kolmogorov 4/5 law, this three-point correlation explicitly contains velocity second- and third-order moments, which correspond to energy and energy transfer respectively. The combination of them then shows additional information of non-equilibrium turbulence by comparing to two-point correlations. Moreover, this three-point correlation shows the underlying inconsistency between numerical interpolation and three-point scaling law in numerical calculations, and inspires a preliminary model to correct this problem in isotropic turbulence.\",\"bibtype\":\"article\",\"author\":\"Wu, J Z and Fang, L and Shao, L and Lu, L P\",\"doi\":\"10.1016/j.physleta.2018.04.021\",\"journal\":\"Physics Letters A\",\"number\":\"25\",\"bibtex\":\"@article{\\n title = {Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence},\\n type = {article},\\n year = {2018},\\n pages = {1665-1671},\\n volume = {382},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918},\\n month = {4},\\n publisher = {North-Holland},\\n id = {f51f7ca2-fc3f-3dcb-9662-759d1235c5ba},\\n created = {2021-04-09T15:23:42.918Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:42.918Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In order to introduce new physics to traditional two-point correlations, we define the second-order correlation of longitudinal velocity increments at three points and obtain the analytical expressions in isotropic turbulence. By introducing the Kolmogorov 4/5 law, this three-point correlation explicitly contains velocity second- and third-order moments, which correspond to energy and energy transfer respectively. The combination of them then shows additional information of non-equilibrium turbulence by comparing to two-point correlations. Moreover, this three-point correlation shows the underlying inconsistency between numerical interpolation and three-point scaling law in numerical calculations, and inspires a preliminary model to correct this problem in isotropic turbulence.},\\n bibtype = {article},\\n author = {Wu, J Z and Fang, L and Shao, L and Lu, L P},\\n doi = {10.1016/j.physleta.2018.04.021},\\n journal = {Physics Letters A},\\n number = {25}\\n}\",\"author_short\":[\"Wu,  J., Z.\",\"Fang,  L.\",\"Shao,  L.\",\"Lu,  L., P.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Isotropic turbulence,correlators,four-fifths law,incompressibility\",\"pages\":\"717-730\",\"volume\":\"19\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055\",\"month\":\"4\",\"publisher\":\"Taylor & Francis\",\"id\":\"ea64be6e-fa7d-30d9-97b6-f2a6881023cd\",\"created\":\"2021-04-09T15:23:43.536Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:43.536Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"ABSTRACTOn the grounds of Kolmogorov's 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are deriv...\",\"bibtype\":\"article\",\"author\":\"Kopyev, A V and Zybin, K P\",\"doi\":\"10.1080/14685248.2018.1511055\",\"journal\":\"Journal of Turbulence\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {Isotropic turbulence,correlators,four-fifths law,incompressibility},\\n pages = {717-730},\\n volume = {19},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055},\\n month = {4},\\n publisher = {Taylor & Francis},\\n id = {ea64be6e-fa7d-30d9-97b6-f2a6881023cd},\\n created = {2021-04-09T15:23:43.536Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:43.536Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {ABSTRACTOn the grounds of Kolmogorov's 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are deriv...},\\n bibtype = {article},\\n author = {Kopyev, A V and Zybin, K P},\\n doi = {10.1080/14685248.2018.1511055},\\n journal = {Journal of Turbulence},\\n number = {9}\\n}\",\"author_short\":[\"Kopyev,  A., V.\",\"Zybin,  K., P.\"],\"urls\":{\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018\",\"role\":\"author\",\"keyword\":[\"Isotropic turbulence\",\"correlators\",\"four-fifths law\",\"incompressibility\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Tensor geometry in the turbulent cascade\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"turbulence theory,turbulent flows\",\"pages\":\"1048-1064\",\"volume\":\"835\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"10073d10-c167-3626-bd0c-6712d69b8083\",\"created\":\"2021-04-09T15:23:44.057Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:44.057Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The defining characteristic of highly turbulent flows is the net directed transport of energy from the injection scales to the dissipation scales. This cascade is typically described in Fourier space, obscuring its connection to the mechanics of the flow. Here, we recast the energy cascade in mechanical terms, noting that for some scales to transfer energy to others, they must do mechanical work on them. This work can be expressed as the inner product of a turbulent stress and a rate of strain. But, as with all inner products, the relative alignment of these two tensors matters, and determines how strong the energy transfer will be. We show that this tensor alignment behaves very differently in two and three dimensions; in particular, the tensor eigenvalues affect the inner product in very different ways. By comparing the observed energy flux to the maximum possible if the tensors were in perfect alignment, we define an efficiency for the energy cascade. Using data from a direct numerical simulation of isotropic turbulence, we show that this efficiency is perhaps surprisingly low, with an average value of approximately 25 % in the inertial range, although it is spatially heterogeneous. Our results have implications for how the stress and strain-rate magnitudes influence the flux of energy between scales, and may help to explain why the energy cascades in two and three dimensions are different.\",\"bibtype\":\"article\",\"author\":\"Ballouz, Joseph G and Ouellette, Nicholas T\",\"doi\":\"10.1017/jfm.2017.802\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Tensor geometry in the turbulent cascade},\\n type = {article},\\n year = {2018},\\n keywords = {turbulence theory,turbulent flows},\\n pages = {1048-1064},\\n volume = {835},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {10073d10-c167-3626-bd0c-6712d69b8083},\\n created = {2021-04-09T15:23:44.057Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:44.057Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The defining characteristic of highly turbulent flows is the net directed transport of energy from the injection scales to the dissipation scales. This cascade is typically described in Fourier space, obscuring its connection to the mechanics of the flow. Here, we recast the energy cascade in mechanical terms, noting that for some scales to transfer energy to others, they must do mechanical work on them. This work can be expressed as the inner product of a turbulent stress and a rate of strain. But, as with all inner products, the relative alignment of these two tensors matters, and determines how strong the energy transfer will be. We show that this tensor alignment behaves very differently in two and three dimensions; in particular, the tensor eigenvalues affect the inner product in very different ways. By comparing the observed energy flux to the maximum possible if the tensors were in perfect alignment, we define an efficiency for the energy cascade. Using data from a direct numerical simulation of isotropic turbulence, we show that this efficiency is perhaps surprisingly low, with an average value of approximately 25 % in the inertial range, although it is spatially heterogeneous. Our results have implications for how the stress and strain-rate magnitudes influence the flux of energy between scales, and may help to explain why the energy cascades in two and three dimensions are different.},\\n bibtype = {article},\\n author = {Ballouz, Joseph G and Ouellette, Nicholas T},\\n doi = {10.1017/jfm.2017.802},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Ballouz,  J., G.\",\"Ouellette,  N., T.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ballouz-ouellette-tensorgeometryintheturbulentcascade-2018\",\"role\":\"author\",\"keyword\":[\"turbulence theory\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":9,\"html\":\"\"},{\"title\":\"Line density control in screen-space via balanced line hierarchies\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"Flow visualization,Focus + Context,Line fields,Line hierarchy,Scientific visualization\",\"pages\":\"29-39\",\"volume\":\"61\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0097849316300899\",\"month\":\"4\",\"publisher\":\"Pergamon\",\"id\":\"02127f1b-afa6-31a9-ad0b-875309b32cf3\",\"created\":\"2021-04-09T15:23:44.570Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:44.570Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"For the visualization of dense sets of 3D lines, view-dependent approaches have been proposed to avoid the occlusion of important structures. Popular concepts consider global line selection based on line importance and screen-space occupancy, and opacity optimization to resolve locally the occlusion problem. In this work, we present a novel approach to improve the spatial perception and enable the interactive visualization of large 3D line sets. Instead of making lines locally transparent, which affects a lines spatial perception and can obscure spatial relationships, we propose to adapt the line density based on line importance and screen-space occupancy. In contrast to global line selection, however, our adaptation is local and only thins out the lines where significant occlusions occur. To achieve this we present a novel approach based on minimum cost perfect matching to construct an optimal, fully balanced line hierarchy. For determining locally the desired line density, we propose a projection-based screen-space measure considering the variation in line direction, line coverage, importance, and depth. This measure can be computed in an order-independent way and evaluated efficiently on the GPU.\",\"bibtype\":\"article\",\"author\":\"Kanzler, Mathias and Ferstl, Florian and Westermann, Rüdiger\",\"doi\":\"10.1016/j.cag.2016.08.001\",\"journal\":\"Computers and Graphics\",\"bibtex\":\"@article{\\n title = {Line density control in screen-space via balanced line hierarchies},\\n type = {article},\\n year = {2016},\\n keywords = {Flow visualization,Focus + Context,Line fields,Line hierarchy,Scientific visualization},\\n pages = {29-39},\\n volume = {61},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0097849316300899},\\n month = {4},\\n publisher = {Pergamon},\\n id = {02127f1b-afa6-31a9-ad0b-875309b32cf3},\\n created = {2021-04-09T15:23:44.570Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:44.570Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {For the visualization of dense sets of 3D lines, view-dependent approaches have been proposed to avoid the occlusion of important structures. Popular concepts consider global line selection based on line importance and screen-space occupancy, and opacity optimization to resolve locally the occlusion problem. In this work, we present a novel approach to improve the spatial perception and enable the interactive visualization of large 3D line sets. Instead of making lines locally transparent, which affects a lines spatial perception and can obscure spatial relationships, we propose to adapt the line density based on line importance and screen-space occupancy. In contrast to global line selection, however, our adaptation is local and only thins out the lines where significant occlusions occur. To achieve this we present a novel approach based on minimum cost perfect matching to construct an optimal, fully balanced line hierarchy. For determining locally the desired line density, we propose a projection-based screen-space measure considering the variation in line direction, line coverage, importance, and depth. This measure can be computed in an order-independent way and evaluated efficiently on the GPU.},\\n bibtype = {article},\\n author = {Kanzler, Mathias and Ferstl, Florian and Westermann, Rüdiger},\\n doi = {10.1016/j.cag.2016.08.001},\\n journal = {Computers and Graphics}\\n}\",\"author_short\":[\"Kanzler,  M.\",\"Ferstl,  F.\",\"Westermann,  R.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0097849316300899\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016\",\"role\":\"author\",\"keyword\":[\"Flow visualization\",\"Focus + Context\",\"Line fields\",\"Line hierarchy\",\"Scientific visualization\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Stochastic flux freezing and magnetic dynamo\",\"type\":\"article\",\"year\":\"2011\",\"pages\":\"56405\",\"volume\":\"83\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.83.056405\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"86fc86ac-22a9-3fa9-917f-b58302cd9209\",\"created\":\"2021-04-09T15:23:45.122Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:45.122Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the \\\"spontaneous stochasticity\\\" of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.\",\"bibtype\":\"article\",\"author\":\"Eyink, Gregory L\",\"doi\":\"10.1103/PhysRevE.83.056405\",\"journal\":\"Physical Review E\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Stochastic flux freezing and magnetic dynamo},\\n type = {article},\\n year = {2011},\\n pages = {56405},\\n volume = {83},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.83.056405},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {86fc86ac-22a9-3fa9-917f-b58302cd9209},\\n created = {2021-04-09T15:23:45.122Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:45.122Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the \\\"spontaneous stochasticity\\\" of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.},\\n bibtype = {article},\\n author = {Eyink, Gregory L},\\n doi = {10.1103/PhysRevE.83.056405},\\n journal = {Physical Review E},\\n number = {5}\\n}\",\"author_short\":[\"Eyink,  G., L.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.83.056405\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"eyink-stochasticfluxfreezingandmagneticdynamo-2011\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Intermittency and Structure(s) of and/in Turbulence\",\"type\":\"misc\",\"year\":\"2019\",\"source\":\"The Essence of Turbulence as a Physical Phenomenon\",\"pages\":\"157-190\",\"websites\":\"http://link.springer.com/10.1007/978-3-319-99531-1_9\",\"publisher\":\"Springer International Publishing\",\"id\":\"e83f4ea7-2729-3756-b100-dc5719f9e27d\",\"created\":\"2021-04-09T15:23:46.181Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:46.181Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"book_section\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Tsinober, Arkady\",\"doi\":\"10.1007/978-3-319-99531-1_9\",\"bibtex\":\"@misc{\\n title = {Intermittency and Structure(s) of and/in Turbulence},\\n type = {misc},\\n year = {2019},\\n source = {The Essence of Turbulence as a Physical Phenomenon},\\n pages = {157-190},\\n websites = {http://link.springer.com/10.1007/978-3-319-99531-1_9},\\n publisher = {Springer International Publishing},\\n id = {e83f4ea7-2729-3756-b100-dc5719f9e27d},\\n created = {2021-04-09T15:23:46.181Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:46.181Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {book_section},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Tsinober, Arkady},\\n doi = {10.1007/978-3-319-99531-1_9}\\n}\",\"author_short\":[\"Tsinober,  A.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-319-99531-1_9\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"tsinober-intermittencyandstructuresofandinturbulence-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Using deformable particles for single particle measurements of velocity gradient tensors\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1906.03075\",\"month\":\"4\",\"id\":\"2d3fb34f-e041-36e5-9b65-9804e1cba455\",\"created\":\"2021-04-09T15:23:46.671Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:46.671Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We measure the deformation of particles made of several slender arms in a two-dimensional (2D) linear shear and a three-dimensional (3D) turbulent flow. We show how these measurements of arm deformations along with the rotation rate of the particle allow us to extract the velocity gradient tensor of the flow. The particles used in the experiments have three symmetric arms in a plane (triads) and are fabricated using 3D printing of a flexible polymeric material. Deformation measurements of a particle free to rotate about a fixed axis in a 2D simple shear flow are used to validate our model relating particle deformations to the fluid strain. We then examine deformable particles in a 3D turbulent flow created by a jet array in a vertical water tunnel. Particle orientations and deformations are measured with high precision using four high speed cameras and have an uncertainty on the order of 10^-4 radians. Measured deformations in 3D turbulence are small and only slightly larger than our orientation measurement uncertainty. Simulation results for triads in turbulence show deformations similar to the experimental observations. Deformable particles offer a promising method for measuring the full local velocity gradient tensor from measurements of a single particle where traditionally a high concentration of tracer particles would be required.\",\"bibtype\":\"article\",\"author\":\"Hejazi, Bardia and Krellenstein, Michael and Voth, Greg A\",\"bibtex\":\"@article{\\n title = {Using deformable particles for single particle measurements of velocity gradient tensors},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1906.03075},\\n month = {4},\\n id = {2d3fb34f-e041-36e5-9b65-9804e1cba455},\\n created = {2021-04-09T15:23:46.671Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:46.671Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We measure the deformation of particles made of several slender arms in a two-dimensional (2D) linear shear and a three-dimensional (3D) turbulent flow. We show how these measurements of arm deformations along with the rotation rate of the particle allow us to extract the velocity gradient tensor of the flow. The particles used in the experiments have three symmetric arms in a plane (triads) and are fabricated using 3D printing of a flexible polymeric material. Deformation measurements of a particle free to rotate about a fixed axis in a 2D simple shear flow are used to validate our model relating particle deformations to the fluid strain. We then examine deformable particles in a 3D turbulent flow created by a jet array in a vertical water tunnel. Particle orientations and deformations are measured with high precision using four high speed cameras and have an uncertainty on the order of 10^-4 radians. Measured deformations in 3D turbulence are small and only slightly larger than our orientation measurement uncertainty. Simulation results for triads in turbulence show deformations similar to the experimental observations. Deformable particles offer a promising method for measuring the full local velocity gradient tensor from measurements of a single particle where traditionally a high concentration of tracer particles would be required.},\\n bibtype = {article},\\n author = {Hejazi, Bardia and Krellenstein, Michael and Voth, Greg A}\\n}\",\"author_short\":[\"Hejazi,  B.\",\"Krellenstein,  M.\",\"Voth,  G., A.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1906.03075\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Modeling three-dimensional scalar mixing with forced one-dimensional turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"flow simulation,numerical analysis,turbulence\",\"pages\":\"125103\",\"volume\":\"30\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5055752\",\"month\":\"4\",\"publisher\":\"AIP Publishing LLC\",\"id\":\"10740e25-ecd9-3e7a-99bf-da8defaee44c\",\"created\":\"2021-04-09T15:23:47.440Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:47.440Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We study the capability of the One-Dimensional-Turbulence (ODT) model to simulate the turbulent transport and mixing of multiple passive scalars in homogeneous isotropic stationary turbulence. To t...\",\"bibtype\":\"article\",\"author\":\"Giddey, Valentin and Meyer, Daniel W and Jenny, Patrick\",\"doi\":\"10.1063/1.5055752\",\"journal\":\"Physics of Fluids\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Modeling three-dimensional scalar mixing with forced one-dimensional turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {flow simulation,numerical analysis,turbulence},\\n pages = {125103},\\n volume = {30},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5055752},\\n month = {4},\\n publisher = {AIP Publishing LLC},\\n id = {10740e25-ecd9-3e7a-99bf-da8defaee44c},\\n created = {2021-04-09T15:23:47.440Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:47.440Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We study the capability of the One-Dimensional-Turbulence (ODT) model to simulate the turbulent transport and mixing of multiple passive scalars in homogeneous isotropic stationary turbulence. To t...},\\n bibtype = {article},\\n author = {Giddey, Valentin and Meyer, Daniel W and Jenny, Patrick},\\n doi = {10.1063/1.5055752},\\n journal = {Physics of Fluids},\\n number = {12}\\n}\",\"author_short\":[\"Giddey,  V.\",\"Meyer,  D., W.\",\"Jenny,  P.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5055752\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018\",\"role\":\"author\",\"keyword\":[\"flow simulation\",\"numerical analysis\",\"turbulence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Voxel-Based Rendering Pipeline for Large 3D Line Sets\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Ray-casting,global illumination,large 3D line sets,transparency\",\"pages\":\"2378-2391\",\"volume\":\"25\",\"websites\":\"https://ieeexplore.ieee.org/document/8356687/\",\"month\":\"4\",\"id\":\"f26f0e03-62ab-3fb6-a185-654bd2768cf8\",\"created\":\"2021-04-09T15:23:47.931Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:47.931Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We present a voxel-based rendering pipeline for large 3D line sets that employs GPU ray-casting to achieve scalable rendering including transparency and global illumination effects that cannot be achieved with GPU rasterization. Even for opaque lines we demonstrate superior rendering performance compared to GPU rasterization of lines, and when transparency is used we can interactively render large amounts of lines that are infeasible to be rendered via rasterization. To achieve this, we propose a direction-preserving encoding of lines into a regular voxel grid, along with the quantization of directions using face-to-face connectivity in this grid. On the regular grid structure, parallel GPU ray-casting is used to determine visible fragments in correct visibility order. To enable interactive rendering of global illumination effects like low-frequency shadows and ambient occlusions, illumination simulation is performed during ray-casting on a level-of-detail (LoD) line representation that considers the number of lines and their lengths per voxel. In this way we can render effects which are very difficult to render via GPU rasterization. A detailed performance and quality evaluation compares our approach to rasterization-based rendering of lines.\",\"bibtype\":\"article\",\"author\":\"Kanzler, Mathias and Rautenhaus, Marc and Westermann, Rudiger\",\"doi\":\"10.1109/TVCG.2018.2834372\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"number\":\"7\",\"bibtex\":\"@article{\\n title = {A Voxel-Based Rendering Pipeline for Large 3D Line Sets},\\n type = {article},\\n year = {2019},\\n keywords = {Ray-casting,global illumination,large 3D line sets,transparency},\\n pages = {2378-2391},\\n volume = {25},\\n websites = {https://ieeexplore.ieee.org/document/8356687/},\\n month = {4},\\n id = {f26f0e03-62ab-3fb6-a185-654bd2768cf8},\\n created = {2021-04-09T15:23:47.931Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:47.931Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We present a voxel-based rendering pipeline for large 3D line sets that employs GPU ray-casting to achieve scalable rendering including transparency and global illumination effects that cannot be achieved with GPU rasterization. Even for opaque lines we demonstrate superior rendering performance compared to GPU rasterization of lines, and when transparency is used we can interactively render large amounts of lines that are infeasible to be rendered via rasterization. To achieve this, we propose a direction-preserving encoding of lines into a regular voxel grid, along with the quantization of directions using face-to-face connectivity in this grid. On the regular grid structure, parallel GPU ray-casting is used to determine visible fragments in correct visibility order. To enable interactive rendering of global illumination effects like low-frequency shadows and ambient occlusions, illumination simulation is performed during ray-casting on a level-of-detail (LoD) line representation that considers the number of lines and their lengths per voxel. In this way we can render effects which are very difficult to render via GPU rasterization. A detailed performance and quality evaluation compares our approach to rasterization-based rendering of lines.},\\n bibtype = {article},\\n author = {Kanzler, Mathias and Rautenhaus, Marc and Westermann, Rudiger},\\n doi = {10.1109/TVCG.2018.2834372},\\n journal = {IEEE Transactions on Visualization and Computer Graphics},\\n number = {7}\\n}\",\"author_short\":[\"Kanzler,  M.\",\"Rautenhaus,  M.\",\"Westermann,  R.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8356687/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019\",\"role\":\"author\",\"keyword\":[\"Ray-casting\",\"global illumination\",\"large 3D line sets\",\"transparency\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data\",\"type\":\"inproceedings\",\"year\":\"2019\",\"pages\":\"1-6\",\"websites\":\"https://ieeexplore.ieee.org/document/8817345/\",\"month\":\"4\",\"publisher\":\"IEEE\",\"id\":\"4a0ae990-a42f-3d6c-bb0e-654d5daa9608\",\"created\":\"2021-04-09T15:23:48.365Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:48.365Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Baghaie, Ahmadreza\",\"doi\":\"10.1109/LISAT.2019.8817345\",\"booktitle\":\"2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT)\",\"bibtex\":\"@inproceedings{\\n title = {Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data},\\n type = {inproceedings},\\n year = {2019},\\n pages = {1-6},\\n websites = {https://ieeexplore.ieee.org/document/8817345/},\\n month = {4},\\n publisher = {IEEE},\\n id = {4a0ae990-a42f-3d6c-bb0e-654d5daa9608},\\n created = {2021-04-09T15:23:48.365Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:48.365Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Baghaie, Ahmadreza},\\n doi = {10.1109/LISAT.2019.8817345},\\n booktitle = {2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT)}\\n}\",\"author_short\":[\"Baghaie,  A.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8817345/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Visibility graph analysis of wall turbulence time-series\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Complex networks,Direct numerical simulations,Time-series analysis,Turbulent channel flows,Visibility graph\",\"pages\":\"1-11\",\"volume\":\"382\",\"websites\":\"http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X\",\"month\":\"4\",\"publisher\":\"North-Holland\",\"id\":\"117a628a-3309-3870-811a-5f4e5b726b7e\",\"created\":\"2021-04-09T15:23:49.217Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:49.217Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.\",\"bibtype\":\"article\",\"author\":\"Iacobello, Giovanni and Scarsoglio, Stefania and Ridolfi, Luca\",\"doi\":\"10.1016/j.physleta.2017.10.027\",\"journal\":\"Physics Letters A\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Visibility graph analysis of wall turbulence time-series},\\n type = {article},\\n year = {2018},\\n keywords = {Complex networks,Direct numerical simulations,Time-series analysis,Turbulent channel flows,Visibility graph},\\n pages = {1-11},\\n volume = {382},\\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X},\\n month = {4},\\n publisher = {North-Holland},\\n id = {117a628a-3309-3870-811a-5f4e5b726b7e},\\n created = {2021-04-09T15:23:49.217Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:49.217Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.},\\n bibtype = {article},\\n author = {Iacobello, Giovanni and Scarsoglio, Stefania and Ridolfi, Luca},\\n doi = {10.1016/j.physleta.2017.10.027},\\n journal = {Physics Letters A},\\n number = {1}\\n}\",\"author_short\":[\"Iacobello,  G.\",\"Scarsoglio,  S.\",\"Ridolfi,  L.\"],\"urls\":{\"Website\":\"http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018\",\"role\":\"author\",\"keyword\":[\"Complex networks\",\"Direct numerical simulations\",\"Time-series analysis\",\"Turbulent channel flows\",\"Visibility graph\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"85110\",\"volume\":\"27\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.4928699\",\"month\":\"4\",\"id\":\"62e0a3b8-f203-3460-bb83-528b9ee3de45\",\"created\":\"2021-04-09T15:23:49.861Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:49.861Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Johnson, Perry L and Meneveau, Charles\",\"doi\":\"10.1063/1.4928699\",\"journal\":\"Physics of Fluids\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence},\\n type = {article},\\n year = {2015},\\n pages = {85110},\\n volume = {27},\\n websites = {http://aip.scitation.org/doi/10.1063/1.4928699},\\n month = {4},\\n id = {62e0a3b8-f203-3460-bb83-528b9ee3de45},\\n created = {2021-04-09T15:23:49.861Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:49.861Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Johnson, Perry L and Meneveau, Charles},\\n doi = {10.1063/1.4928699},\\n journal = {Physics of Fluids},\\n number = {8}\\n}\",\"author_short\":[\"Johnson,  P., L.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.4928699\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Tracer particle dispersion around elementary flow patterns\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"topological fluid dynamics,turbulence theory,turbulent mixing\",\"pages\":\"872-897\",\"volume\":\"843\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"20461682-0462-316b-935f-97d5994ffecc\",\"created\":\"2021-04-09T15:23:50.515Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:50.515Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The motion of tracer particles is kinematically simulated around three elementary flow patterns; a Burgers vortex, a shear-layer structure with coincident vortices and a node-saddle topology. These patterns are representative for their broader class of coherent structures in turbulence. Therefore, examining the dispersion in these elementary structures can improve the general understanding of turbulent dispersion at short time scales. The shear-layer structure and the node-saddle topology exhibit similar pair dispersion statistics compared to the actual turbulent flow for times up to 3-10[STIX]x1D70F_[STIX]x1D702 , where, [STIX]x1D70F_[STIX]x1D702 is the Kolmogorov time scale. However, oscillations are observed for the pair dispersion in the Burgers vortex. Furthermore, all three structures exhibit Batchelor’s scaling. Richardson’s scaling was observed for initial particle pair separations r_0 4[STIX]x1D702 for the shear-layer topology and the node-saddle topology and was related to the formation of the particle sheets. Moreover, the material line orientation statistics for the shear-layer and node-saddle topology are similar to the actual turbulent flow statistics, up to at least 4[STIX]x1D70F_[STIX]x1D702 . However, only the shear-layer structure can explain the non-perpendicular preferential alignment between the material lines and the direction of the most compressive strain, as observed in actual turbulence. This behaviour is due to shear-layer vorticity, which rotates the particle sheet generated by straining motions and causes the particles to spread in the direction of compressive strain also. The material line statistics in the Burgers vortex clearly differ, due to the presence of two compressive principal straining directions as opposed to two stretching directions in the shear-layer structure and the node-saddle topology. The tetrad dispersion statistics for the shear-layer structure qualitatively capture the behaviour of the shape parameters as observed in actual turbulence. In particular, it shows the initial development towards planar shapes followed by a return to more volumetric tetrads at approximately 10[STIX]x1D70F_[STIX]x1D702 , which is associated with the particles approaching the vortices inside the shear layer. However, a large deviation is observed in such behaviour in the node-saddle topology and the Burgers vortex. It is concluded that the results for the Burgers vortex deviated the most from actual turbulence and the node-saddle topology dispersion exhibits some similarities, but does not capture the geometrical features associated with material lines and tetrad dispersion. Finally, the dispersion around the shear-layer structure shows many quantitative (until 2– 4[STIX]x1D70F_[STIX]x1D702 ) and qualitative (until 20[STIX]x1D70F_[STIX]x1D702 ) similarities to the actual turbulence.\",\"bibtype\":\"article\",\"author\":\"Goudar, Manu V and Elsinga, Gerrit E\",\"doi\":\"10.1017/jfm.2018.146\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Tracer particle dispersion around elementary flow patterns},\\n type = {article},\\n year = {2018},\\n keywords = {topological fluid dynamics,turbulence theory,turbulent mixing},\\n pages = {872-897},\\n volume = {843},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {20461682-0462-316b-935f-97d5994ffecc},\\n created = {2021-04-09T15:23:50.515Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:50.515Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The motion of tracer particles is kinematically simulated around three elementary flow patterns; a Burgers vortex, a shear-layer structure with coincident vortices and a node-saddle topology. These patterns are representative for their broader class of coherent structures in turbulence. Therefore, examining the dispersion in these elementary structures can improve the general understanding of turbulent dispersion at short time scales. The shear-layer structure and the node-saddle topology exhibit similar pair dispersion statistics compared to the actual turbulent flow for times up to 3-10[STIX]x1D70F_[STIX]x1D702 , where, [STIX]x1D70F_[STIX]x1D702 is the Kolmogorov time scale. However, oscillations are observed for the pair dispersion in the Burgers vortex. Furthermore, all three structures exhibit Batchelor’s scaling. Richardson’s scaling was observed for initial particle pair separations r_0 4[STIX]x1D702 for the shear-layer topology and the node-saddle topology and was related to the formation of the particle sheets. Moreover, the material line orientation statistics for the shear-layer and node-saddle topology are similar to the actual turbulent flow statistics, up to at least 4[STIX]x1D70F_[STIX]x1D702 . However, only the shear-layer structure can explain the non-perpendicular preferential alignment between the material lines and the direction of the most compressive strain, as observed in actual turbulence. This behaviour is due to shear-layer vorticity, which rotates the particle sheet generated by straining motions and causes the particles to spread in the direction of compressive strain also. The material line statistics in the Burgers vortex clearly differ, due to the presence of two compressive principal straining directions as opposed to two stretching directions in the shear-layer structure and the node-saddle topology. The tetrad dispersion statistics for the shear-layer structure qualitatively capture the behaviour of the shape parameters as observed in actual turbulence. In particular, it shows the initial development towards planar shapes followed by a return to more volumetric tetrads at approximately 10[STIX]x1D70F_[STIX]x1D702 , which is associated with the particles approaching the vortices inside the shear layer. However, a large deviation is observed in such behaviour in the node-saddle topology and the Burgers vortex. It is concluded that the results for the Burgers vortex deviated the most from actual turbulence and the node-saddle topology dispersion exhibits some similarities, but does not capture the geometrical features associated with material lines and tetrad dispersion. Finally, the dispersion around the shear-layer structure shows many quantitative (until 2– 4[STIX]x1D70F_[STIX]x1D702 ) and qualitative (until 20[STIX]x1D70F_[STIX]x1D702 ) similarities to the actual turbulence.},\\n bibtype = {article},\\n author = {Goudar, Manu V and Elsinga, Gerrit E},\\n doi = {10.1017/jfm.2018.146},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Goudar,  M., V.\",\"Elsinga,  G., E.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018\",\"role\":\"author\",\"keyword\":[\"topological fluid dynamics\",\"turbulence theory\",\"turbulent mixing\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"CCS Concepts,Graphics systems and interfaces,• Computing methodologies → Computer graphics,• Human‐centered computing → Scientific visualizat\",\"pages\":\"53-66\",\"volume\":\"38\",\"websites\":\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671\",\"month\":\"4\",\"publisher\":\"John Wiley & Sons, Ltd (10.1111)\",\"id\":\"4b5cd8db-6947-3ac8-b9dd-7f6ed694dab5\",\"created\":\"2021-04-09T15:23:51.035Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:51.035Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Marton, Fabio and Agus, Marco and Gobbetti, Enrico\",\"doi\":\"10.1111/cgf.13671\",\"journal\":\"Computer Graphics Forum\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes},\\n type = {article},\\n year = {2019},\\n keywords = {CCS Concepts,Graphics systems and interfaces,• Computing methodologies → Computer graphics,• Human‐centered computing → Scientific visualizat},\\n pages = {53-66},\\n volume = {38},\\n websites = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671},\\n month = {4},\\n publisher = {John Wiley & Sons, Ltd (10.1111)},\\n id = {4b5cd8db-6947-3ac8-b9dd-7f6ed694dab5},\\n created = {2021-04-09T15:23:51.035Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:51.035Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Marton, Fabio and Agus, Marco and Gobbetti, Enrico},\\n doi = {10.1111/cgf.13671},\\n journal = {Computer Graphics Forum},\\n number = {3}\\n}\",\"author_short\":[\"Marton,  F.\",\"Agus,  M.\",\"Gobbetti,  E.\"],\"urls\":{\"Website\":\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019\",\"role\":\"author\",\"keyword\":[\"CCS Concepts\",\"Graphics systems and interfaces\",\"• Computing methodologies → Computer graphics\",\"• Human‐centered computing → Scientific visualizat\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":11,\"html\":\"\"},{\"title\":\"A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks\",\"type\":\"article\",\"year\":\"2018\",\"websites\":\"http://arxiv.org/abs/1804.09269\",\"month\":\"4\",\"id\":\"3506f98e-a070-3139-824c-288b57b0e8d1\",\"created\":\"2021-04-09T15:23:51.617Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:51.617Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Reduced Order Modeling (ROM) for engineering applications has been a major research focus in the past few decades due to the unprecedented physical insight into turbulence offered by high-fidelity CFD. The primary goal of a ROM is to model the key physics/features of a flow-field without computing the full Navier-Stokes (NS) equations. This is accomplished by projecting the high-dimensional dynamics to a low-dimensional subspace, typically utilizing dimensionality reduction techniques like Proper Orthogonal Decomposition (POD), coupled with Galerkin projection. In this work, we demonstrate a deep learning based approach to build a ROM using the POD basis of canonical DNS datasets, for turbulent flow control applications. We find that a type of Recurrent Neural Network, the Long Short Term Memory (LSTM) which has been primarily utilized for problems like speech modeling and language translation, shows attractive potential in modeling temporal dynamics of turbulence. Additionally, we introduce the Hurst Exponent as a tool to study LSTM behavior for non-stationary data, and uncover useful characteristics that may aid ROM development for a variety of applications.\",\"bibtype\":\"article\",\"author\":\"Mohan, Arvind T and Gaitonde, Datta V\",\"bibtex\":\"@article{\\n title = {A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks},\\n type = {article},\\n year = {2018},\\n websites = {http://arxiv.org/abs/1804.09269},\\n month = {4},\\n id = {3506f98e-a070-3139-824c-288b57b0e8d1},\\n created = {2021-04-09T15:23:51.617Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:51.617Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Reduced Order Modeling (ROM) for engineering applications has been a major research focus in the past few decades due to the unprecedented physical insight into turbulence offered by high-fidelity CFD. The primary goal of a ROM is to model the key physics/features of a flow-field without computing the full Navier-Stokes (NS) equations. This is accomplished by projecting the high-dimensional dynamics to a low-dimensional subspace, typically utilizing dimensionality reduction techniques like Proper Orthogonal Decomposition (POD), coupled with Galerkin projection. In this work, we demonstrate a deep learning based approach to build a ROM using the POD basis of canonical DNS datasets, for turbulent flow control applications. We find that a type of Recurrent Neural Network, the Long Short Term Memory (LSTM) which has been primarily utilized for problems like speech modeling and language translation, shows attractive potential in modeling temporal dynamics of turbulence. Additionally, we introduce the Hurst Exponent as a tool to study LSTM behavior for non-stationary data, and uncover useful characteristics that may aid ROM development for a variety of applications.},\\n bibtype = {article},\\n author = {Mohan, Arvind T and Gaitonde, Datta V}\\n}\",\"author_short\":[\"Mohan,  A., T.\",\"Gaitonde,  D., V.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1804.09269\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Viscous tilting and production of vorticity in homogeneous turbulence\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"flow simulation,flow visualisation,turbulence,vortices\",\"pages\":\"1-4\",\"volume\":\"22\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.3442477\",\"month\":\"4\",\"publisher\":\"American Institute of Physics\",\"id\":\"13eeab2c-f93a-38bc-8939-c93fd2904977\",\"created\":\"2021-04-09T15:23:52.216Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:52.216Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Viscous depletion of vorticity is an essential and well known property of turbulent flows, balancing, in the mean, the net vorticity production associated with the vortex stretching mechanism. In this letter we however demonstrate that viscous effects are not restricted to a mere destruction process, but play a more complex role in vorticity dynamics that is as important as vortex stretching. Based on results from particle tracking experiments (3D-PTV) and direct numerical simulation (DNS) of homogeneous and quasi isotropic turbulence, we show that the viscous term in the vorticity equation can also locally induce production of vorticity and changes of its orientation (viscous tilting).\",\"bibtype\":\"article\",\"author\":\"Holzner, M and Guala, M and Lüthi, B and Liberzon, A and Nikitin, N and Kinzelbach, W and Tsinober, A\",\"doi\":\"10.1063/1.3442477\",\"journal\":\"Physics of Fluids\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Viscous tilting and production of vorticity in homogeneous turbulence},\\n type = {article},\\n year = {2010},\\n keywords = {flow simulation,flow visualisation,turbulence,vortices},\\n pages = {1-4},\\n volume = {22},\\n websites = {http://aip.scitation.org/doi/10.1063/1.3442477},\\n month = {4},\\n publisher = {American Institute of Physics},\\n id = {13eeab2c-f93a-38bc-8939-c93fd2904977},\\n created = {2021-04-09T15:23:52.216Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:52.216Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Viscous depletion of vorticity is an essential and well known property of turbulent flows, balancing, in the mean, the net vorticity production associated with the vortex stretching mechanism. In this letter we however demonstrate that viscous effects are not restricted to a mere destruction process, but play a more complex role in vorticity dynamics that is as important as vortex stretching. Based on results from particle tracking experiments (3D-PTV) and direct numerical simulation (DNS) of homogeneous and quasi isotropic turbulence, we show that the viscous term in the vorticity equation can also locally induce production of vorticity and changes of its orientation (viscous tilting).},\\n bibtype = {article},\\n author = {Holzner, M and Guala, M and Lüthi, B and Liberzon, A and Nikitin, N and Kinzelbach, W and Tsinober, A},\\n doi = {10.1063/1.3442477},\\n journal = {Physics of Fluids},\\n number = {6}\\n}\",\"author_short\":[\"Holzner,  M.\",\"Guala,  M.\",\"Lüthi,  B.\",\"Liberzon,  A.\",\"Nikitin,  N.\",\"Kinzelbach,  W.\",\"Tsinober,  A.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.3442477\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010\",\"role\":\"author\",\"keyword\":[\"flow simulation\",\"flow visualisation\",\"turbulence\",\"vortices\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"isotropic turbulence,turbulence modelling,turbulent flows\",\"pages\":\"387-419\",\"volume\":\"804\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112016005516\",\"month\":\"4\",\"id\":\"058be0e8-0927-31b3-a73c-e061a85b4271\",\"created\":\"2021-04-09T15:23:53.201Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:53.201Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The statistics of the velocity gradient tensor in turbulent flows are of both theoretical and practical importance. The Lagrangian view provides a privileged perspective for studying the dynamics of turbulence in general, and of the velocity gradient tensor in particular. Stochastic models for the Lagrangian evolution of velocity gradients in isotropic turbulence, with closure models for the pressure Hesssian and viscous Laplacian, have been shown to reproduce important features such as non-Gaussian probability distributions, skewness and vorticity strain-rate alignments. The Recent Fluid Deformation (RFD) closure introduced the idea of mapping an isotropic Lagrangian pressure Hessian as upstream initial condition using the fluid deformation tensor. Recent work on a Gaussian fields closure, however, has shown that even Gaussian isotropic velocity fields contain significant anisotropy for the conditional pressure Hessian tensor due to the inherent velocity-pressure couplings, and that assuming an isotropic pressure Hessian as upstream condition may not be realistic. In this paper, Gaussian isotropic field statistics are used to generate more physical upstream conditions for the recent fluid deformation mapping. In this new framework, known isotropy relations can be satisfied  a priori and no DNS-tuned coefficients are necessary. A detailed comparison of results from the new model, referred to as the recent deformation of Gaussian fields (RDGF) closure, with existing models and DNS shows the improvements gained, especially in various single-time statistics of the velocity gradient tensor at moderate Reynolds numbers. Application to arbitrarily high Reynolds numbers remains an open challenge for this type of model, however.\",\"bibtype\":\"article\",\"author\":\"Johnson, Perry L and Meneveau, Charles\",\"doi\":\"10.1017/jfm.2016.551\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields},\\n type = {article},\\n year = {2016},\\n keywords = {isotropic turbulence,turbulence modelling,turbulent flows},\\n pages = {387-419},\\n volume = {804},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005516},\\n month = {4},\\n id = {058be0e8-0927-31b3-a73c-e061a85b4271},\\n created = {2021-04-09T15:23:53.201Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:53.201Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The statistics of the velocity gradient tensor in turbulent flows are of both theoretical and practical importance. The Lagrangian view provides a privileged perspective for studying the dynamics of turbulence in general, and of the velocity gradient tensor in particular. Stochastic models for the Lagrangian evolution of velocity gradients in isotropic turbulence, with closure models for the pressure Hesssian and viscous Laplacian, have been shown to reproduce important features such as non-Gaussian probability distributions, skewness and vorticity strain-rate alignments. The Recent Fluid Deformation (RFD) closure introduced the idea of mapping an isotropic Lagrangian pressure Hessian as upstream initial condition using the fluid deformation tensor. Recent work on a Gaussian fields closure, however, has shown that even Gaussian isotropic velocity fields contain significant anisotropy for the conditional pressure Hessian tensor due to the inherent velocity-pressure couplings, and that assuming an isotropic pressure Hessian as upstream condition may not be realistic. In this paper, Gaussian isotropic field statistics are used to generate more physical upstream conditions for the recent fluid deformation mapping. In this new framework, known isotropy relations can be satisfied  a priori and no DNS-tuned coefficients are necessary. A detailed comparison of results from the new model, referred to as the recent deformation of Gaussian fields (RDGF) closure, with existing models and DNS shows the improvements gained, especially in various single-time statistics of the velocity gradient tensor at moderate Reynolds numbers. Application to arbitrarily high Reynolds numbers remains an open challenge for this type of model, however.},\\n bibtype = {article},\\n author = {Johnson, Perry L and Meneveau, Charles},\\n doi = {10.1017/jfm.2016.551},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Johnson,  P., L.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112016005516\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016\",\"role\":\"author\",\"keyword\":[\"isotropic turbulence\",\"turbulence modelling\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Weighted divergence correction scheme and its fast implementation\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"44\",\"volume\":\"58\",\"websites\":\"http://link.springer.com/10.1007/s00348-017-2307-0\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"0192ceee-aab1-3e66-936d-56c4d9b81025\",\"created\":\"2021-04-09T15:23:54.184Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:54.184Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.\",\"bibtype\":\"article\",\"author\":\"Wang, Cheng Yue and Gao, Qi and Wei, Run Jie and Li, Tian and Wang, Jin Jun\",\"doi\":\"10.1007/s00348-017-2307-0\",\"journal\":\"Experiments in Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Weighted divergence correction scheme and its fast implementation},\\n type = {article},\\n year = {2017},\\n pages = {44},\\n volume = {58},\\n websites = {http://link.springer.com/10.1007/s00348-017-2307-0},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {0192ceee-aab1-3e66-936d-56c4d9b81025},\\n created = {2021-04-09T15:23:54.184Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:54.184Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.},\\n bibtype = {article},\\n author = {Wang, Cheng Yue and Gao, Qi and Wei, Run Jie and Li, Tian and Wang, Jin Jun},\\n doi = {10.1007/s00348-017-2307-0},\\n journal = {Experiments in Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Wang,  C., Y.\",\"Gao,  Q.\",\"Wei,  R., J.\",\"Li,  T.\",\"Wang,  J., J.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-017-2307-0\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Estimating large-scale structures in wall turbulence using linear models\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"turbulence control,turbulence modelling,turbulent flows\",\"pages\":\"146-162\",\"volume\":\"842\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"3e4a0e2c-0224-3e99-bc54-88aeb5f4790c\",\"created\":\"2021-04-09T15:23:54.716Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:54.716Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of Re_[STIX]x1D70F=1000 . The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon &amp; Sharma ( J. Fluid Mech. , vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.\",\"bibtype\":\"article\",\"author\":\"Illingworth, Simon J and Monty, Jason P and Marusic, Ivan\",\"doi\":\"10.1017/jfm.2018.129\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Estimating large-scale structures in wall turbulence using linear models},\\n type = {article},\\n year = {2018},\\n keywords = {turbulence control,turbulence modelling,turbulent flows},\\n pages = {146-162},\\n volume = {842},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {3e4a0e2c-0224-3e99-bc54-88aeb5f4790c},\\n created = {2021-04-09T15:23:54.716Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:54.716Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of Re_[STIX]x1D70F=1000 . The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon &amp; Sharma ( J. Fluid Mech. , vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.},\\n bibtype = {article},\\n author = {Illingworth, Simon J and Monty, Jason P and Marusic, Ivan},\\n doi = {10.1017/jfm.2018.129},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Illingworth,  S., J.\",\"Monty,  J., P.\",\"Marusic,  I.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018\",\"role\":\"author\",\"keyword\":[\"turbulence control\",\"turbulence modelling\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":4,\"html\":\"\"},{\"title\":\"On velocity gradient dynamics and turbulent structure\",\"type\":\"article\",\"year\":\"2015\",\"keywords\":\"homogeneous turbulence,turbulence modelling,turbulent flows\",\"pages\":\"60-98\",\"volume\":\"780\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112015004528\",\"month\":\"4\",\"id\":\"9b621a34-c3f3-3ac7-b9dd-a490b7dff598\",\"created\":\"2021-04-09T15:23:55.819Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:55.819Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The statistics of the velocity gradient tensor [STIX]x1D63C=u , which embody the fine scales of turbulence, are influenced by turbulent ‘structure’. Whilst velocity gradient statistics and dynamics have been well characterised, the connection between structure and dynamics has largely focused on rotation-dominated flow and relied upon data from numerical simulation alone. Using numerical and spatially resolved experimental datasets of homogeneous turbulence, the role of structure is examined for all local (incompressible) flow topologies characterisable by [STIX]x1D63C . Structures are studied through the footprints they leave in conditional averages of the Q=-Tr([STIX]x1D63C^2)/2 field, pertinent to non-local strain production, obtained using two complementary conditional averaging techniques. The first, stochastic estimation, approximates the Q field conditioned upon [STIX]x1D63C and educes quantitatively similar structure in both datasets, dissimilar to that of random Gaussian velocity fields. Moreover, it strongly resembles a promising model for velocity gradient dynamics recently proposed by Wilczek &amp; Meneveau ( J. Fluid Mech. , vol. 756, 2014, pp. 191–225), but is derived under a less restrictive premise, with explicitly determined closure coefficients. The second technique examines true conditional averages of the Q field, which is used to validate the stochastic estimation and provide insights towards the model’s refinement. Jointly, these approaches confirm that vortex tubes are the predominant feature of rotation-dominated regions and additionally show that shear layer structures are active in strain-dominated regions. In both cases, kinematic features of these structures explain alignment statistics of the pressure Hessian eigenvectors and why local and non-local strain production act in opposition to each other.\",\"bibtype\":\"article\",\"author\":\"Lawson, J M and Dawson, J R\",\"doi\":\"10.1017/jfm.2015.452\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {On velocity gradient dynamics and turbulent structure},\\n type = {article},\\n year = {2015},\\n keywords = {homogeneous turbulence,turbulence modelling,turbulent flows},\\n pages = {60-98},\\n volume = {780},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112015004528},\\n month = {4},\\n id = {9b621a34-c3f3-3ac7-b9dd-a490b7dff598},\\n created = {2021-04-09T15:23:55.819Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:55.819Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The statistics of the velocity gradient tensor [STIX]x1D63C=u , which embody the fine scales of turbulence, are influenced by turbulent ‘structure’. Whilst velocity gradient statistics and dynamics have been well characterised, the connection between structure and dynamics has largely focused on rotation-dominated flow and relied upon data from numerical simulation alone. Using numerical and spatially resolved experimental datasets of homogeneous turbulence, the role of structure is examined for all local (incompressible) flow topologies characterisable by [STIX]x1D63C . Structures are studied through the footprints they leave in conditional averages of the Q=-Tr([STIX]x1D63C^2)/2 field, pertinent to non-local strain production, obtained using two complementary conditional averaging techniques. The first, stochastic estimation, approximates the Q field conditioned upon [STIX]x1D63C and educes quantitatively similar structure in both datasets, dissimilar to that of random Gaussian velocity fields. Moreover, it strongly resembles a promising model for velocity gradient dynamics recently proposed by Wilczek &amp; Meneveau ( J. Fluid Mech. , vol. 756, 2014, pp. 191–225), but is derived under a less restrictive premise, with explicitly determined closure coefficients. The second technique examines true conditional averages of the Q field, which is used to validate the stochastic estimation and provide insights towards the model’s refinement. Jointly, these approaches confirm that vortex tubes are the predominant feature of rotation-dominated regions and additionally show that shear layer structures are active in strain-dominated regions. In both cases, kinematic features of these structures explain alignment statistics of the pressure Hessian eigenvectors and why local and non-local strain production act in opposition to each other.},\\n bibtype = {article},\\n author = {Lawson, J M and Dawson, J R},\\n doi = {10.1017/jfm.2015.452},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Lawson,  J., M.\",\"Dawson,  J., R.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112015004528\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015\",\"role\":\"author\",\"keyword\":[\"homogeneous turbulence\",\"turbulence modelling\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"doi:10.1103/PhysRevFluids.3.064301 url:https://doi\",\"pages\":\"64301\",\"volume\":\"3\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"6ee00bf4-b546-3cfe-8cb4-4d8cec83ae01\",\"created\":\"2021-04-09T15:23:57.403Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:57.403Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Fouxon, Itzhak and Schmidt, Lukas and Ditlevsen, Peter and van Reeuwijk, Maarten and Holzner, Markus\",\"doi\":\"10.1103/PhysRevFluids.3.064301\",\"journal\":\"Physical Review Fluids\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {doi:10.1103/PhysRevFluids.3.064301 url:https://doi},\\n pages = {64301},\\n volume = {3},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {6ee00bf4-b546-3cfe-8cb4-4d8cec83ae01},\\n created = {2021-04-09T15:23:57.403Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:57.403Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Fouxon, Itzhak and Schmidt, Lukas and Ditlevsen, Peter and van Reeuwijk, Maarten and Holzner, Markus},\\n doi = {10.1103/PhysRevFluids.3.064301},\\n journal = {Physical Review Fluids},\\n number = {6}\\n}\",\"author_short\":[\"Fouxon,  I.\",\"Schmidt,  L.\",\"Ditlevsen,  P.\",\"van Reeuwijk,  M.\",\"Holzner,  M.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018\",\"role\":\"author\",\"keyword\":[\"doi:10.1103/PhysRevFluids.3.064301 url:https://doi\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Main results of the 4th International PIV Challenge\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"97\",\"volume\":\"57\",\"websites\":\"http://link.springer.com/10.1007/s00348-016-2173-1\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"df1350f7-41d2-3e6d-902b-cadcc3b62429\",\"created\":\"2021-04-09T15:23:57.952Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:57.952Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In the last decade, worldwide PIV development have resulted in significant improvements in terms accuracy, resolution, dynamic range and extension to dimensions. To assess the achievements and to guide development efforts, an International PIV Challenge performed in Lisbon (Portugal) on July 5, 2014. leading participants, including the major system, i.e., Dantec (Denmark), LaVision (Germany), (China), PIVTEC (Germany), TSI (USA), have 5 cases. The cases and analysis explore challenges to 2D microscopic PIV (case A), 2D timeresolved (case B), 3D tomographic PIV (cases C and) and stereoscopic PIV (case E). During the event, 2D PIV images (case F) were provided to all 80 of the workshop in Lisbon, with the aim to assess impact of the user’s experience on the evaluation result. paper describes the cases and specific algorithms evaluation parameters applied by the participants and reviews the main results. For future analysis and comparison, full image database\",\"bibtype\":\"article\",\"author\":\"Kähler, Christian J and Astarita, Tommaso and Vlachos, Pavlos P and Sakakibara, Jun and Hain, Rainer and Discetti, Stefano and Foy, Roderick La and Cierpka, Christian\",\"doi\":\"10.1007/s00348-016-2173-1\",\"journal\":\"Experiments in Fluids\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Main results of the 4th International PIV Challenge},\\n type = {article},\\n year = {2016},\\n pages = {97},\\n volume = {57},\\n websites = {http://link.springer.com/10.1007/s00348-016-2173-1},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {df1350f7-41d2-3e6d-902b-cadcc3b62429},\\n created = {2021-04-09T15:23:57.952Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:57.952Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In the last decade, worldwide PIV development have resulted in significant improvements in terms accuracy, resolution, dynamic range and extension to dimensions. To assess the achievements and to guide development efforts, an International PIV Challenge performed in Lisbon (Portugal) on July 5, 2014. leading participants, including the major system, i.e., Dantec (Denmark), LaVision (Germany), (China), PIVTEC (Germany), TSI (USA), have 5 cases. The cases and analysis explore challenges to 2D microscopic PIV (case A), 2D timeresolved (case B), 3D tomographic PIV (cases C and) and stereoscopic PIV (case E). During the event, 2D PIV images (case F) were provided to all 80 of the workshop in Lisbon, with the aim to assess impact of the user’s experience on the evaluation result. paper describes the cases and specific algorithms evaluation parameters applied by the participants and reviews the main results. For future analysis and comparison, full image database},\\n bibtype = {article},\\n author = {Kähler, Christian J and Astarita, Tommaso and Vlachos, Pavlos P and Sakakibara, Jun and Hain, Rainer and Discetti, Stefano and Foy, Roderick La and Cierpka, Christian},\\n doi = {10.1007/s00348-016-2173-1},\\n journal = {Experiments in Fluids},\\n number = {6}\\n}\",\"author_short\":[\"Kähler,  C., J.\",\"Astarita,  T.\",\"Vlachos,  P., P.\",\"Sakakibara,  J.\",\"Hain,  R.\",\"Discetti,  S.\",\"Foy,  R., L.\",\"Cierpka,  C.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-016-2173-1\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Uncertainty quantification in LES of channel flow\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"Bayesian framework,Rosenblatt transformation,calibration,large eddy simulation,model error,polynomial chaos\",\"pages\":\"376-401\",\"volume\":\"83\",\"websites\":\"http://doi.wiley.com/10.1002/fld.4272\",\"month\":\"4\",\"id\":\"0e749df6-9a68-34cb-a517-ccc9d4a029c0\",\"created\":\"2021-04-09T15:23:58.644Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:58.644Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Dis- crepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.\",\"bibtype\":\"article\",\"author\":\"Safta, Cosmin and Blaylock, Myra and Templeton, Jeremy and Domino, Stefan and Sargsyan, Khachik and Najm, Habib\",\"doi\":\"10.1002/fld.4272\",\"journal\":\"International Journal for Numerical Methods in Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Uncertainty quantification in LES of channel flow},\\n type = {article},\\n year = {2017},\\n keywords = {Bayesian framework,Rosenblatt transformation,calibration,large eddy simulation,model error,polynomial chaos},\\n pages = {376-401},\\n volume = {83},\\n websites = {http://doi.wiley.com/10.1002/fld.4272},\\n month = {4},\\n id = {0e749df6-9a68-34cb-a517-ccc9d4a029c0},\\n created = {2021-04-09T15:23:58.644Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:58.644Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Dis- crepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.},\\n bibtype = {article},\\n author = {Safta, Cosmin and Blaylock, Myra and Templeton, Jeremy and Domino, Stefan and Sargsyan, Khachik and Najm, Habib},\\n doi = {10.1002/fld.4272},\\n journal = {International Journal for Numerical Methods in Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Safta,  C.\",\"Blaylock,  M.\",\"Templeton,  J.\",\"Domino,  S.\",\"Sargsyan,  K.\",\"Najm,  H.\"],\"urls\":{\"Website\":\"http://doi.wiley.com/10.1002/fld.4272\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017\",\"role\":\"author\",\"keyword\":[\"Bayesian framework\",\"Rosenblatt transformation\",\"calibration\",\"large eddy simulation\",\"model error\",\"polynomial chaos\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"From Deep to Physics-Informed Learning of Turbulence: Diagnostics\",\"type\":\"article\",\"year\":\"2018\",\"websites\":\"http://arxiv.org/abs/1810.07785\",\"month\":\"4\",\"id\":\"c2ce5c72-f100-31b5-9cac-81b8dc4415c7\",\"created\":\"2021-04-09T15:23:59.239Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:59.239Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of turbulence. Even the bare DL solutions, which do not take into account any physics of turbulence explicitly, are impressively good overall when it comes to qualitative description of important features of turbulence. However, the early tests have also uncovered some caveats of the DL approaches. We observe that the static DL scheme, implementing Convolutional GAN and trained on spatial snapshots of turbulence, fails to reproduce intermittency of turbulent fluctuations at small scales and details of the turbulence geometry at large scales. We show that the dynamic NN schemes, namely LAT-NET and Compressed Convolutional LSTM, trained on a temporal sequence of turbulence snapshots are capable to correct for the caveats of the static NN. We suggest a path forward towards improving reproducibility of the large-scale geometry of turbulence with NN.\",\"bibtype\":\"article\",\"author\":\"King, Ryan and Hennigh, Oliver and Mohan, Arvind and Chertkov, Michael\",\"bibtex\":\"@article{\\n title = {From Deep to Physics-Informed Learning of Turbulence: Diagnostics},\\n type = {article},\\n year = {2018},\\n websites = {http://arxiv.org/abs/1810.07785},\\n month = {4},\\n id = {c2ce5c72-f100-31b5-9cac-81b8dc4415c7},\\n created = {2021-04-09T15:23:59.239Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:59.239Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of turbulence. Even the bare DL solutions, which do not take into account any physics of turbulence explicitly, are impressively good overall when it comes to qualitative description of important features of turbulence. However, the early tests have also uncovered some caveats of the DL approaches. We observe that the static DL scheme, implementing Convolutional GAN and trained on spatial snapshots of turbulence, fails to reproduce intermittency of turbulent fluctuations at small scales and details of the turbulence geometry at large scales. We show that the dynamic NN schemes, namely LAT-NET and Compressed Convolutional LSTM, trained on a temporal sequence of turbulence snapshots are capable to correct for the caveats of the static NN. We suggest a path forward towards improving reproducibility of the large-scale geometry of turbulence with NN.},\\n bibtype = {article},\\n author = {King, Ryan and Hennigh, Oliver and Mohan, Arvind and Chertkov, Michael}\\n}\",\"author_short\":[\"King,  R.\",\"Hennigh,  O.\",\"Mohan,  A.\",\"Chertkov,  M.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1810.07785\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Active Pointillistic Pattern Search\",\"type\":\"inproceedings\",\"year\":\"2015\",\"pages\":\"672-680\",\"websites\":\"http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf\",\"month\":\"4\",\"id\":\"87abb4bb-fb22-349d-bf7c-053866f19df0\",\"created\":\"2021-04-09T15:23:59.817Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:23:59.817Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"abstract\":\"We introduce the problem of active pointillistic pattern search (APPS), which seeks to discover regions of a domain exhibiting desired behavior with limited observations. Unusually, the patterns we consider are defined by large-scale proper-ties of an underlying function that we can only observe at a limited number of points. Given a description of the desired patterns (in the form of a classifier taking functional inputs), we se-quentially decide where to query function values to identify as many regions matching the pattern as possible, with high confience. For one broad class of models the expected reward of each un-observed point can be computed analytically. We demonstrate the proposed algorithm on three dif-ficult search problems: locating polluted regions in a lake via mobile sensors, forecasting winning electoral districts with minimal polling, and iden-tifying vortices in a fluid flow simulation.\",\"bibtype\":\"inproceedings\",\"author\":\"Ma, Yifei and Sutherland, Dougal J and Garnett, Roman and Schneider, Jeff\",\"booktitle\":\"AISTATS\",\"bibtex\":\"@inproceedings{\\n title = {Active Pointillistic Pattern Search},\\n type = {inproceedings},\\n year = {2015},\\n pages = {672-680},\\n websites = {http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf},\\n month = {4},\\n id = {87abb4bb-fb22-349d-bf7c-053866f19df0},\\n created = {2021-04-09T15:23:59.817Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:23:59.817Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n abstract = {We introduce the problem of active pointillistic pattern search (APPS), which seeks to discover regions of a domain exhibiting desired behavior with limited observations. Unusually, the patterns we consider are defined by large-scale proper-ties of an underlying function that we can only observe at a limited number of points. Given a description of the desired patterns (in the form of a classifier taking functional inputs), we se-quentially decide where to query function values to identify as many regions matching the pattern as possible, with high confience. For one broad class of models the expected reward of each un-observed point can be computed analytically. We demonstrate the proposed algorithm on three dif-ficult search problems: locating polluted regions in a lake via mobile sensors, forecasting winning electoral districts with minimal polling, and iden-tifying vortices in a fluid flow simulation.},\\n bibtype = {inproceedings},\\n author = {Ma, Yifei and Sutherland, Dougal J and Garnett, Roman and Schneider, Jeff},\\n booktitle = {AISTATS}\\n}\",\"author_short\":[\"Ma,  Y.\",\"Sutherland,  D., J.\",\"Garnett,  R.\",\"Schneider,  J.\"],\"urls\":{\"Website\":\"http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"53202\",\"volume\":\"99\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.99.053202\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"f3da8baa-5c3d-344e-87ea-28d5bbeac4a0\",\"created\":\"2021-04-09T15:24:00.465Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:00.465Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Kuzzay, Denis and Alexandrova, Olga and Matteini, Lorenzo\",\"doi\":\"10.1103/PhysRevE.99.053202\",\"journal\":\"Physical Review E\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence},\\n type = {article},\\n year = {2019},\\n pages = {53202},\\n volume = {99},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.99.053202},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {f3da8baa-5c3d-344e-87ea-28d5bbeac4a0},\\n created = {2021-04-09T15:24:00.465Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:00.465Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Kuzzay, Denis and Alexandrova, Olga and Matteini, Lorenzo},\\n doi = {10.1103/PhysRevE.99.053202},\\n journal = {Physical Review E},\\n number = {5}\\n}\",\"author_short\":[\"Kuzzay,  D.\",\"Alexandrova,  O.\",\"Matteini,  L.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.99.053202\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Dual channels of helicity cascade in turbulent flows\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1907.03634\",\"month\":\"4\",\"id\":\"f1f0d347-1a37-3f18-bb4c-677bb59ee33c\",\"created\":\"2021-04-09T15:24:01.743Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:01.743Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.\",\"bibtype\":\"article\",\"author\":\"Yan, Zheng and Li, Xinliang and Yu, Changping and Chen, Shiyi\",\"bibtex\":\"@article{\\n title = {Dual channels of helicity cascade in turbulent flows},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1907.03634},\\n month = {4},\\n id = {f1f0d347-1a37-3f18-bb4c-677bb59ee33c},\\n created = {2021-04-09T15:24:01.743Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:01.743Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.},\\n bibtype = {article},\\n author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Chen, Shiyi}\\n}\",\"author_short\":[\"Yan,  Z.\",\"Li,  X.\",\"Yu,  C.\",\"Chen,  S.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1907.03634\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"64602\",\"volume\":\"4\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"021f32d8-a291-3056-a16b-dc980553a5b4\",\"created\":\"2021-04-09T15:24:02.532Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:02.532Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Sosa-Correa, W and Pereira, R M and Macêdo, A M S and Raposo, E P and Salazar, D S P and Vasconcelos, G L\",\"doi\":\"10.1103/PhysRevFluids.4.064602\",\"journal\":\"Physical Review Fluids\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence},\\n type = {article},\\n year = {2019},\\n pages = {64602},\\n volume = {4},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {021f32d8-a291-3056-a16b-dc980553a5b4},\\n created = {2021-04-09T15:24:02.532Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:02.532Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Sosa-Correa, W and Pereira, R M and Macêdo, A M S and Raposo, E P and Salazar, D S P and Vasconcelos, G L},\\n doi = {10.1103/PhysRevFluids.4.064602},\\n journal = {Physical Review Fluids},\\n number = {6}\\n}\",\"author_short\":[\"Sosa-Correa,  W.\",\"Pereira,  R., M.\",\"Macêdo,  A., M., S.\",\"Raposo,  E., P.\",\"Salazar,  D., S., P.\",\"Vasconcelos,  G., L.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Velocity and pressure visualization of three-dimensional flow in porous textiles\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"and systems engineering,flow visualization,magnetic resonance velocimetry,management of systems,materials,measurement,pressure visualization,product,product design,structure-properties\",\"pages\":\"5041-5052\",\"volume\":\"89\",\"websites\":\"http://journals.sagepub.com/doi/10.1177/0040517519846078\",\"month\":\"4\",\"publisher\":\"SAGE PublicationsSage UK: London, England\",\"id\":\"6aaefaff-4247-3be7-b4e8-2ed4fff906f5\",\"created\":\"2021-04-09T15:24:03.314Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:03.314Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Advances in flow visualization techniques based on optics, such as lasers and digital cameras, have contributed considerably to the development of various flow models. However, the uses of optical techniques for flow visualization in porous media are limited owing to the complexity or opaqueness of the medium. This study demonstrates the utilization of magnetic resonance velocimetry to visualize a flow field in a textile material. By using phase-contrast magnetic resonance imaging, a three-dimensional, three-component velocity vector field was obtained for induced flow through a cut-pile carpet owing to the suction of a vacuum cleaner nozzle. As a result, we were able to experimentally identify the flow-dominant region in the carpet. Specifically, velocity vector plots and flow streamlines facilitated the identification of the flow paths, and indicated that the flow was strongest beneath the narrow walls of the vacuum nozzle. In addition, the pressure field in the carpet was estimated by an omni-directional integral method based on the utilization of the visualized velocity field, which showed where the pressure loss was maximized.\",\"bibtype\":\"article\",\"author\":\"Lee, Jeesoo and Yang, Byungkuen and Cho, Jee-Hyun and Song, Simon\",\"doi\":\"10.1177/0040517519846078\",\"journal\":\"Textile Research Journal\",\"number\":\"23-24\",\"bibtex\":\"@article{\\n title = {Velocity and pressure visualization of three-dimensional flow in porous textiles},\\n type = {article},\\n year = {2019},\\n keywords = {and systems engineering,flow visualization,magnetic resonance velocimetry,management of systems,materials,measurement,pressure visualization,product,product design,structure-properties},\\n pages = {5041-5052},\\n volume = {89},\\n websites = {http://journals.sagepub.com/doi/10.1177/0040517519846078},\\n month = {4},\\n publisher = {SAGE PublicationsSage UK: London, England},\\n id = {6aaefaff-4247-3be7-b4e8-2ed4fff906f5},\\n created = {2021-04-09T15:24:03.314Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:03.314Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Advances in flow visualization techniques based on optics, such as lasers and digital cameras, have contributed considerably to the development of various flow models. However, the uses of optical techniques for flow visualization in porous media are limited owing to the complexity or opaqueness of the medium. This study demonstrates the utilization of magnetic resonance velocimetry to visualize a flow field in a textile material. By using phase-contrast magnetic resonance imaging, a three-dimensional, three-component velocity vector field was obtained for induced flow through a cut-pile carpet owing to the suction of a vacuum cleaner nozzle. As a result, we were able to experimentally identify the flow-dominant region in the carpet. Specifically, velocity vector plots and flow streamlines facilitated the identification of the flow paths, and indicated that the flow was strongest beneath the narrow walls of the vacuum nozzle. In addition, the pressure field in the carpet was estimated by an omni-directional integral method based on the utilization of the visualized velocity field, which showed where the pressure loss was maximized.},\\n bibtype = {article},\\n author = {Lee, Jeesoo and Yang, Byungkuen and Cho, Jee-Hyun and Song, Simon},\\n doi = {10.1177/0040517519846078},\\n journal = {Textile Research Journal},\\n number = {23-24}\\n}\",\"author_short\":[\"Lee,  J.\",\"Yang,  B.\",\"Cho,  J.\",\"Song,  S.\"],\"urls\":{\"Website\":\"http://journals.sagepub.com/doi/10.1177/0040517519846078\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019\",\"role\":\"author\",\"keyword\":[\"and systems engineering\",\"flow visualization\",\"magnetic resonance velocimetry\",\"management of systems\",\"materials\",\"measurement\",\"pressure visualization\",\"product\",\"product design\",\"structure-properties\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence\",\"type\":\"article\",\"year\":\"2011\",\"pages\":\"N45\",\"volume\":\"12\",\"websites\":\"http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047\",\"month\":\"4\",\"id\":\"d9d6d4ff-bbf2-3017-9a97-263565beec5a\",\"created\":\"2021-04-09T15:24:03.970Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:03.970Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The specification of inlet conditions for eddy-resolving simulations is an important research question in turbulence research. A large number of schemes have been proposed but comparisons to a benchmark simulation are usually undertaken in such a way that it is ambiguous as to whether the source of the improved preservation of the properties of the benchmark case is due to the physics captured in the inlet generation algorithm or to differences in the precise values or spectra generated at a particular position. This article uses gradual wavelet reconstruction to degrade a precursor simulation such that the time series input at each cell has the same histogram and Fourier spectrum as the original precursor case, thereby removing this source of variability. A parameter, ρ, is used to index the nature of the degraded inlets and as ρ increases from 0 to 1 the cross-correlative and nonlinear properties of the precursor are increasingly preserved too. We compare the results of four large-eddy simulations for the flow over a wall-mounted square rib and show that there are clear differences between these simulations for the flow before and over the rib, and in the far-field. However, in the wake, the intense shearing and mixing means that any differences are harder to attribute to the nature of the inlet. Hence, for flows that are mixed strongly, there is less of a need to preserve the cross-correlative structure of the inlet condition as long as the individual velocity components are modelled with an appropriate set of values and Fourier spectrum. By comparing particular inlet generation algorithms in terms of the value for ρ that they can attain, their suitability for modelling flows of particular configurations may be determined.\",\"bibtype\":\"article\",\"author\":\"Keylock, C J and Tokyay, T E and Constantinescu, G\",\"doi\":\"10.1080/14685248.2011.636047\",\"journal\":\"Journal of Turbulence\",\"bibtex\":\"@article{\\n title = {A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence},\\n type = {article},\\n year = {2011},\\n pages = {N45},\\n volume = {12},\\n websites = {http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047},\\n month = {4},\\n id = {d9d6d4ff-bbf2-3017-9a97-263565beec5a},\\n created = {2021-04-09T15:24:03.970Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:03.970Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The specification of inlet conditions for eddy-resolving simulations is an important research question in turbulence research. A large number of schemes have been proposed but comparisons to a benchmark simulation are usually undertaken in such a way that it is ambiguous as to whether the source of the improved preservation of the properties of the benchmark case is due to the physics captured in the inlet generation algorithm or to differences in the precise values or spectra generated at a particular position. This article uses gradual wavelet reconstruction to degrade a precursor simulation such that the time series input at each cell has the same histogram and Fourier spectrum as the original precursor case, thereby removing this source of variability. A parameter, ρ, is used to index the nature of the degraded inlets and as ρ increases from 0 to 1 the cross-correlative and nonlinear properties of the precursor are increasingly preserved too. We compare the results of four large-eddy simulations for the flow over a wall-mounted square rib and show that there are clear differences between these simulations for the flow before and over the rib, and in the far-field. However, in the wake, the intense shearing and mixing means that any differences are harder to attribute to the nature of the inlet. Hence, for flows that are mixed strongly, there is less of a need to preserve the cross-correlative structure of the inlet condition as long as the individual velocity components are modelled with an appropriate set of values and Fourier spectrum. By comparing particular inlet generation algorithms in terms of the value for ρ that they can attain, their suitability for modelling flows of particular configurations may be determined.},\\n bibtype = {article},\\n author = {Keylock, C J and Tokyay, T E and Constantinescu, G},\\n doi = {10.1080/14685248.2011.636047},\\n journal = {Journal of Turbulence}\\n}\",\"author_short\":[\"Keylock,  C., J.\",\"Tokyay,  T., E.\",\"Constantinescu,  G.\"],\"urls\":{\"Website\":\"http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Multilevel techniques for compression and reduction of scientific data—the univariate case\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"65-76\",\"volume\":\"19\",\"websites\":\"http://link.springer.com/10.1007/s00791-018-00303-9\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"b18efc62-6fe3-3e73-b604-803dc1772fcf\",\"created\":\"2021-04-09T15:24:04.997Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:04.997Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott\",\"doi\":\"10.1007/s00791-018-00303-9\",\"journal\":\"Computing and Visualization in Science\",\"number\":\"5-6\",\"bibtex\":\"@article{\\n title = {Multilevel techniques for compression and reduction of scientific data—the univariate case},\\n type = {article},\\n year = {2018},\\n pages = {65-76},\\n volume = {19},\\n websites = {http://link.springer.com/10.1007/s00791-018-00303-9},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {b18efc62-6fe3-3e73-b604-803dc1772fcf},\\n created = {2021-04-09T15:24:04.997Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:04.997Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},\\n doi = {10.1007/s00791-018-00303-9},\\n journal = {Computing and Visualization in Science},\\n number = {5-6}\\n}\",\"author_short\":[\"Ainsworth,  M.\",\"Tugluk,  O.\",\"Whitney,  B.\",\"Klasky,  S.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00791-018-00303-9\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Invariants of the reduced velocity gradient tensor in turbulent flows\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"isotropic turbulence,turbulence theory,turbulent flows\",\"pages\":\"597-615\",\"volume\":\"716\",\"websites\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5\",\"month\":\"4\",\"id\":\"c1df0993-9b68-35fd-9b00-e89c04ec2e25\",\"created\":\"2021-04-09T15:24:05.475Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:05.475Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In this paper we examine the invariants p and q of the reduced 2 × 2 velocity gradient tensor (VGT) formed from a two-dimensional (2D) slice of an incompressible three-dimensional (3D) flow. Using data from both 2D particle image velocimetry (PIV) measurements and 3D direct numerical simulations of various turbulent flows, we show that the joint probability density functions (p.d.f.s) of p and q exhibit a common characteristic asymmetric shape consistent with < 0. An explanation for this inequality is proposed. Assuming local homogeneity we derive = 0 and = 0. With the addition of local isotropy the sign of is proved to be the same as that of the skewness of ∂u 1 /∂x 1 , hence negative. This suggests that the observed asymmetry in the joint p.d.f.s of p–q stems from the universal predominance of vortex stretching at the smallest scales. Some advantages of this joint p.d.f. compared with that of Q–R obtained from the full 3 × 3 VGT are discussed. Analysing the eigenvalues of the reduced strain-rate matrix associated with the reduced VGT, we prove that in some cases the 2D data can unambiguously discriminate between the bi-axial (sheet-forming) and axial (tube-forming) strain-rate configurations of the full 3 × 3 strain-rate tensor. 1. Introduction With the arrival of data sets providing access to the full three-dimensional velocity gradient tensor (3D VGT), new ways of analysing this wealth of information have been introduced. The 3D VGT can be written as A ij = ∂u i /∂x j = S ij + W ij , where S ij is the symmetric rate-of-strain tensor and W ij is the antisymmetric rate-of-rotation tensor. One approach is to examine the eigenvalues of S ij . They indicate if the strain-rate tensor is compressing or extending along its principal axes, which in turn determines whether or not the overall strain-rate configuration at a point is sheet forming or tube forming. Another approach is to analyse the local flow topology using the invariants of A ij , as set out by the work of Chong, Perry & Cantwell (1990). In an incompressible flow the number of non-vanishing similarity invariants of the second-order tensor A ij reduces to two, namely Q and R. These two quantities can fully characterize the category to which the local flow topology belongs. The local flow topology refers to the streamline pattern of a region of the flow in the immediate vicinity of the point\",\"bibtype\":\"article\",\"author\":\"Cardesa, J A I and Mistry, D and Gan, L and Dawson, J A R\",\"doi\":\"10.1017/jfm.2012.558\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Invariants of the reduced velocity gradient tensor in turbulent flows},\\n type = {article},\\n year = {2013},\\n keywords = {isotropic turbulence,turbulence theory,turbulent flows},\\n pages = {597-615},\\n volume = {716},\\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5},\\n month = {4},\\n id = {c1df0993-9b68-35fd-9b00-e89c04ec2e25},\\n created = {2021-04-09T15:24:05.475Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:05.475Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In this paper we examine the invariants p and q of the reduced 2 × 2 velocity gradient tensor (VGT) formed from a two-dimensional (2D) slice of an incompressible three-dimensional (3D) flow. Using data from both 2D particle image velocimetry (PIV) measurements and 3D direct numerical simulations of various turbulent flows, we show that the joint probability density functions (p.d.f.s) of p and q exhibit a common characteristic asymmetric shape consistent with < 0. An explanation for this inequality is proposed. Assuming local homogeneity we derive = 0 and = 0. With the addition of local isotropy the sign of is proved to be the same as that of the skewness of ∂u 1 /∂x 1 , hence negative. This suggests that the observed asymmetry in the joint p.d.f.s of p–q stems from the universal predominance of vortex stretching at the smallest scales. Some advantages of this joint p.d.f. compared with that of Q–R obtained from the full 3 × 3 VGT are discussed. Analysing the eigenvalues of the reduced strain-rate matrix associated with the reduced VGT, we prove that in some cases the 2D data can unambiguously discriminate between the bi-axial (sheet-forming) and axial (tube-forming) strain-rate configurations of the full 3 × 3 strain-rate tensor. 1. Introduction With the arrival of data sets providing access to the full three-dimensional velocity gradient tensor (3D VGT), new ways of analysing this wealth of information have been introduced. The 3D VGT can be written as A ij = ∂u i /∂x j = S ij + W ij , where S ij is the symmetric rate-of-strain tensor and W ij is the antisymmetric rate-of-rotation tensor. One approach is to examine the eigenvalues of S ij . They indicate if the strain-rate tensor is compressing or extending along its principal axes, which in turn determines whether or not the overall strain-rate configuration at a point is sheet forming or tube forming. Another approach is to analyse the local flow topology using the invariants of A ij , as set out by the work of Chong, Perry & Cantwell (1990). In an incompressible flow the number of non-vanishing similarity invariants of the second-order tensor A ij reduces to two, namely Q and R. These two quantities can fully characterize the category to which the local flow topology belongs. The local flow topology refers to the streamline pattern of a region of the flow in the immediate vicinity of the point},\\n bibtype = {article},\\n author = {Cardesa, J A I and Mistry, D and Gan, L and Dawson, J A R},\\n doi = {10.1017/jfm.2012.558},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Cardesa,  J., A., I.\",\"Mistry,  D.\",\"Gan,  L.\",\"Dawson,  J., A., R.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013\",\"role\":\"author\",\"keyword\":[\"isotropic turbulence\",\"turbulence theory\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Spatiotemporal velocity-velocity correlation function in fully developed turbulence\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"23107\",\"volume\":\"95\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.95.023107\",\"month\":\"4\",\"id\":\"154cc137-ce6e-3f00-84dd-862eaefbfbb8\",\"created\":\"2021-04-09T15:24:06.109Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:06.109Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Turbulence is an ubiquitous phenomenon in natural and industrial flows. Since the celebrated work of Kolmogorov in 1941, understanding the statistical properties of fully developed turbulence has remained a major quest. In particular, deriving the properties of turbulent flows from a mesoscopic description, that is from Navier-Stokes equation, has eluded most theoretical attempts. Here, we provide a theoretical prediction for the  space and time dependent velocity-velocity correlation function of homogeneous and isotropic turbulence from the field theory associated to Navier-Stokes equation with stochastic forcing. This prediction is the analytical fixed-point solution of Non-Perturbative Renormalisation Group flow equations, which are exact in a certain large wave-number limit. This solution is compared to two-point two-times correlation functions computed in direct numerical simulations. We obtain a remarkable agreement both in the inertial and in the dissipative ranges.\",\"bibtype\":\"article\",\"author\":\"Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás and Balarac, Guillaume\",\"doi\":\"10.1103/PhysRevE.95.023107\",\"journal\":\"Physical Review E\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Spatiotemporal velocity-velocity correlation function in fully developed turbulence},\\n type = {article},\\n year = {2017},\\n pages = {23107},\\n volume = {95},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.95.023107},\\n month = {4},\\n id = {154cc137-ce6e-3f00-84dd-862eaefbfbb8},\\n created = {2021-04-09T15:24:06.109Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:06.109Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Turbulence is an ubiquitous phenomenon in natural and industrial flows. Since the celebrated work of Kolmogorov in 1941, understanding the statistical properties of fully developed turbulence has remained a major quest. In particular, deriving the properties of turbulent flows from a mesoscopic description, that is from Navier-Stokes equation, has eluded most theoretical attempts. Here, we provide a theoretical prediction for the  space and time dependent velocity-velocity correlation function of homogeneous and isotropic turbulence from the field theory associated to Navier-Stokes equation with stochastic forcing. This prediction is the analytical fixed-point solution of Non-Perturbative Renormalisation Group flow equations, which are exact in a certain large wave-number limit. This solution is compared to two-point two-times correlation functions computed in direct numerical simulations. We obtain a remarkable agreement both in the inertial and in the dissipative ranges.},\\n bibtype = {article},\\n author = {Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás and Balarac, Guillaume},\\n doi = {10.1103/PhysRevE.95.023107},\\n journal = {Physical Review E},\\n number = {2}\\n}\",\"author_short\":[\"Canet,  L.\",\"Rossetto,  V.\",\"Wschebor,  N.\",\"Balarac,  G.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.95.023107\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Extracting the spectrum of a flow by spatial filtering\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"124610\",\"volume\":\"3\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"6af5bb72-a429-33a8-9102-fa8f60b255d8\",\"created\":\"2021-04-09T15:24:06.594Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:06.594Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Sadek, Mahmoud and Aluie, Hussein\",\"doi\":\"10.1103/PhysRevFluids.3.124610\",\"journal\":\"Physical Review Fluids\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Extracting the spectrum of a flow by spatial filtering},\\n type = {article},\\n year = {2018},\\n pages = {124610},\\n volume = {3},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {6af5bb72-a429-33a8-9102-fa8f60b255d8},\\n created = {2021-04-09T15:24:06.594Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:06.594Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Sadek, Mahmoud and Aluie, Hussein},\\n doi = {10.1103/PhysRevFluids.3.124610},\\n journal = {Physical Review Fluids},\\n number = {12}\\n}\",\"author_short\":[\"Sadek,  M.\",\"Aluie,  H.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Dense motion estimation of particle images via a convolutional neural network\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"73\",\"volume\":\"60\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2717-2\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"e0ac0c33-5c62-3be2-976c-160d3a74533a\",\"created\":\"2021-04-09T15:24:07.101Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:07.101Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Cai, Shengze and Zhou, Shichao and Xu, Chao and Gao, Qi\",\"doi\":\"10.1007/s00348-019-2717-2\",\"journal\":\"Experiments in Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Dense motion estimation of particle images via a convolutional neural network},\\n type = {article},\\n year = {2019},\\n pages = {73},\\n volume = {60},\\n websites = {http://link.springer.com/10.1007/s00348-019-2717-2},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {e0ac0c33-5c62-3be2-976c-160d3a74533a},\\n created = {2021-04-09T15:24:07.101Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:07.101Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Cai, Shengze and Zhou, Shichao and Xu, Chao and Gao, Qi},\\n doi = {10.1007/s00348-019-2717-2},\\n journal = {Experiments in Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Cai,  S.\",\"Zhou,  S.\",\"Xu,  C.\",\"Gao,  Q.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2717-2\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"25001\",\"volume\":\"115\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevLett.115.025001\",\"month\":\"4\",\"id\":\"4a6557a7-2f59-3fed-9845-28f0b8412a15\",\"created\":\"2021-04-09T15:24:07.560Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:07.560Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In situ spacecraft data on the solar wind show events identified as magnetic reconnection with wide outflows and extended “X lines,” 103–104 times ion scales. To understand the role of turbulence at these scales, we make a case study of an inertial-range reconnection event in a magnetohydrodynamic simulation. We observe stochastic wandering of field lines in space, breakdown of standard magnetic flux freezing due to Richardson dispersion, and a broadened reconnection zone containing many current sheets. The coarse-grain magnetic geometry is like large-scale reconnection in the solar wind, however, with a hyperbolic flux tube or apparent X line extending over integral length scales.\",\"bibtype\":\"article\",\"author\":\"Lalescu, Cristian C and Shi, Yi Kang and Eyink, Gregory L and Drivas, Theodore D and Vishniac, Ethan T and Lazarian, Alexander\",\"doi\":\"10.1103/PhysRevLett.115.025001\",\"journal\":\"Physical Review Letters\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind},\\n type = {article},\\n year = {2015},\\n pages = {25001},\\n volume = {115},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.115.025001},\\n month = {4},\\n id = {4a6557a7-2f59-3fed-9845-28f0b8412a15},\\n created = {2021-04-09T15:24:07.560Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:07.560Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In situ spacecraft data on the solar wind show events identified as magnetic reconnection with wide outflows and extended “X lines,” 103–104 times ion scales. To understand the role of turbulence at these scales, we make a case study of an inertial-range reconnection event in a magnetohydrodynamic simulation. We observe stochastic wandering of field lines in space, breakdown of standard magnetic flux freezing due to Richardson dispersion, and a broadened reconnection zone containing many current sheets. The coarse-grain magnetic geometry is like large-scale reconnection in the solar wind, however, with a hyperbolic flux tube or apparent X line extending over integral length scales.},\\n bibtype = {article},\\n author = {Lalescu, Cristian C and Shi, Yi Kang and Eyink, Gregory L and Drivas, Theodore D and Vishniac, Ethan T and Lazarian, Alexander},\\n doi = {10.1103/PhysRevLett.115.025001},\\n journal = {Physical Review Letters},\\n number = {2}\\n}\",\"author_short\":[\"Lalescu,  C., C.\",\"Shi,  Y., K.\",\"Eyink,  G., L.\",\"Drivas,  T., D.\",\"Vishniac,  E., T.\",\"Lazarian,  A.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevLett.115.025001\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments\",\"type\":\"article\",\"year\":\"2011\",\"pages\":\"34106\",\"volume\":\"23\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.3555635\",\"month\":\"4\",\"id\":\"4c17b164-a584-3e14-b6d0-bb2be167808d\",\"created\":\"2021-04-09T15:24:08.268Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:08.268Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper-flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer-Meshkov instabilities in planar shock-tube laboratory experiments is reported. Our particular focus is devoted to the initial material interface characterization and modeling difficulties, and effects of initial condition specifics (resolved spectral content) on transitional and late-time turbulent mixing-which were not previously addressed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3555635]\",\"bibtype\":\"article\",\"author\":\"Grinstein, F F and Gowardhan, A A and Wachtor, A J\",\"doi\":\"10.1063/1.3555635\",\"journal\":\"Physics of Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments},\\n type = {article},\\n year = {2011},\\n pages = {34106},\\n volume = {23},\\n websites = {http://aip.scitation.org/doi/10.1063/1.3555635},\\n month = {4},\\n id = {4c17b164-a584-3e14-b6d0-bb2be167808d},\\n created = {2021-04-09T15:24:08.268Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:08.268Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper-flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer-Meshkov instabilities in planar shock-tube laboratory experiments is reported. Our particular focus is devoted to the initial material interface characterization and modeling difficulties, and effects of initial condition specifics (resolved spectral content) on transitional and late-time turbulent mixing-which were not previously addressed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3555635]},\\n bibtype = {article},\\n author = {Grinstein, F F and Gowardhan, A A and Wachtor, A J},\\n doi = {10.1063/1.3555635},\\n journal = {Physics of Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Grinstein,  F., F.\",\"Gowardhan,  A., A.\",\"Wachtor,  A., J.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.3555635\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Pulsed, high-power LED illumination for tomographic particle image velocimetry\",\"type\":\"article\",\"year\":\"2012\",\"pages\":\"1545-1560\",\"volume\":\"53\",\"websites\":\"http://link.springer.com/10.1007/s00348-012-1374-5\",\"month\":\"4\",\"publisher\":\"Springer-Verlag\",\"id\":\"20ac55ec-3931-33b8-bee4-44ff227b4ec7\",\"created\":\"2021-04-09T15:24:08.857Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:08.857Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 mu s duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of approximate to 3-4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2-0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.\",\"bibtype\":\"article\",\"author\":\"Buchmann, Nicolas A and Willert, Christian E and Soria, Julio\",\"doi\":\"10.1007/s00348-012-1374-5\",\"journal\":\"Experiments in Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Pulsed, high-power LED illumination for tomographic particle image velocimetry},\\n type = {article},\\n year = {2012},\\n pages = {1545-1560},\\n volume = {53},\\n websites = {http://link.springer.com/10.1007/s00348-012-1374-5},\\n month = {4},\\n publisher = {Springer-Verlag},\\n id = {20ac55ec-3931-33b8-bee4-44ff227b4ec7},\\n created = {2021-04-09T15:24:08.857Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:08.857Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 mu s duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of approximate to 3-4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2-0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.},\\n bibtype = {article},\\n author = {Buchmann, Nicolas A and Willert, Christian E and Soria, Julio},\\n doi = {10.1007/s00348-012-1374-5},\\n journal = {Experiments in Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Buchmann,  N., A.\",\"Willert,  C., E.\",\"Soria,  J.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-012-1374-5\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Assessment of the modulated gradient model in decaying isotropic turbulence\",\"type\":\"article\",\"year\":\"2011\",\"keywords\":\"isotropic turbulence,large-eddy simulation,subgrid-scale model\",\"pages\":\"41004\",\"volume\":\"1\",\"websites\":\"http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611\",\"id\":\"946ab0e5-f9b6-3355-95e1-780cbcb83d88\",\"created\":\"2021-04-09T15:24:09.345Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:09.345Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Lu, Hao\",\"doi\":\"10.1063/2.1104104\",\"journal\":\"Theoretical and Applied Mechanics Letters\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Assessment of the modulated gradient model in decaying isotropic turbulence},\\n type = {article},\\n year = {2011},\\n keywords = {isotropic turbulence,large-eddy simulation,subgrid-scale model},\\n pages = {41004},\\n volume = {1},\\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611},\\n id = {946ab0e5-f9b6-3355-95e1-780cbcb83d88},\\n created = {2021-04-09T15:24:09.345Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:09.345Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Lu, Hao},\\n doi = {10.1063/2.1104104},\\n journal = {Theoretical and Applied Mechanics Letters},\\n number = {4}\\n}\",\"author_short\":[\"Lu,  H.\"],\"urls\":{\"Website\":\"http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011\",\"role\":\"author\",\"keyword\":[\"isotropic turbulence\",\"large-eddy simulation\",\"subgrid-scale model\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"125102\",\"volume\":\"27\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.4936140\",\"month\":\"4\",\"id\":\"f140aa79-c55c-3afc-8d4e-6b5afcb58f77\",\"created\":\"2021-04-09T15:24:09.828Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:09.828Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© 2015 AIP Publishing LLC. We show by direct numerical simulation (DNS) that the Lagrangian cross correlation of velocity gradients in homogeneous isotropic turbulence increases at short times, whereas its auto-correlation decreases. Kinematic considerations allow to show that two invariants of the turbulent velocity field determine the short-time velocity gradient correlations. In order to get a more intuitive understanding of the dynamics for longer times, heuristic models are proposed involving the combined action of local shear and rotation. These models quantitatively reproduce the effects and disentangle the different physical mechanisms leading to the observations in the DNS.\",\"bibtype\":\"article\",\"author\":\"Fang, L and Bos, W J T and Jin, G D\",\"doi\":\"10.1063/1.4936140\",\"journal\":\"Physics of Fluids\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence},\\n type = {article},\\n year = {2015},\\n pages = {125102},\\n volume = {27},\\n websites = {http://aip.scitation.org/doi/10.1063/1.4936140},\\n month = {4},\\n id = {f140aa79-c55c-3afc-8d4e-6b5afcb58f77},\\n created = {2021-04-09T15:24:09.828Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:09.828Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© 2015 AIP Publishing LLC. We show by direct numerical simulation (DNS) that the Lagrangian cross correlation of velocity gradients in homogeneous isotropic turbulence increases at short times, whereas its auto-correlation decreases. Kinematic considerations allow to show that two invariants of the turbulent velocity field determine the short-time velocity gradient correlations. In order to get a more intuitive understanding of the dynamics for longer times, heuristic models are proposed involving the combined action of local shear and rotation. These models quantitatively reproduce the effects and disentangle the different physical mechanisms leading to the observations in the DNS.},\\n bibtype = {article},\\n author = {Fang, L and Bos, W J T and Jin, G D},\\n doi = {10.1063/1.4936140},\\n journal = {Physics of Fluids},\\n number = {12}\\n}\",\"author_short\":[\"Fang,  L.\",\"Bos,  W., J., T.\",\"Jin,  G., D.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.4936140\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Shape-dependence of particle rotation in isotropic turbulence\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"35101\",\"volume\":\"27\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.4913501\",\"month\":\"4\",\"id\":\"fcd7cc5c-da75-3d52-a57a-f3d9ead99673\",\"created\":\"2021-04-09T15:24:10.552Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:10.552Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We consider the rotation of neutrally buoyant axisymmetric particles suspended in isotropic turbulence. Using laboratory experiments as well as numerical and analytical calculations, we explore how particle rotation depends upon particle shape. We find that shape strongly affects orientational trajectories, but that it has negligible effect on the variance of the particle angular velocity. Previous work has shown that shape significantly affects the variance of the tumbling rate of axisymmetric particles. It follows that shape affects the spinning rate in a way that is, on average, complementary to the shape-dependence of the tumbling rate. We confirm this relationship using direct numerical simulations, showing how tumbling rate and spinning rate variances show complementary trends for rod-shaped and disk-shaped particles. We also consider a random but non-turbulent flow. This allows us to explore which of the features observed for rotation in turbulent flow are due to the effects of particle alignment in vortex tubes.\",\"bibtype\":\"article\",\"author\":\"Byron, M and Einarsson, J and Gustavsson, K and Voth, G and Mehlig, B and Variano, E\",\"doi\":\"10.1063/1.4913501\",\"journal\":\"Physics of Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Shape-dependence of particle rotation in isotropic turbulence},\\n type = {article},\\n year = {2015},\\n pages = {35101},\\n volume = {27},\\n websites = {http://aip.scitation.org/doi/10.1063/1.4913501},\\n month = {4},\\n id = {fcd7cc5c-da75-3d52-a57a-f3d9ead99673},\\n created = {2021-04-09T15:24:10.552Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:10.552Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We consider the rotation of neutrally buoyant axisymmetric particles suspended in isotropic turbulence. Using laboratory experiments as well as numerical and analytical calculations, we explore how particle rotation depends upon particle shape. We find that shape strongly affects orientational trajectories, but that it has negligible effect on the variance of the particle angular velocity. Previous work has shown that shape significantly affects the variance of the tumbling rate of axisymmetric particles. It follows that shape affects the spinning rate in a way that is, on average, complementary to the shape-dependence of the tumbling rate. We confirm this relationship using direct numerical simulations, showing how tumbling rate and spinning rate variances show complementary trends for rod-shaped and disk-shaped particles. We also consider a random but non-turbulent flow. This allows us to explore which of the features observed for rotation in turbulent flow are due to the effects of particle alignment in vortex tubes.},\\n bibtype = {article},\\n author = {Byron, M and Einarsson, J and Gustavsson, K and Voth, G and Mehlig, B and Variano, E},\\n doi = {10.1063/1.4913501},\\n journal = {Physics of Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Byron,  M.\",\"Einarsson,  J.\",\"Gustavsson,  K.\",\"Voth,  G.\",\"Mehlig,  B.\",\"Variano,  E.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.4913501\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Dot-Tracking Methodology for Background Oriented Schlieren (BOS)\",\"type\":\"article\",\"year\":\"2018\",\"websites\":\"http://arxiv.org/abs/1812.10870\",\"month\":\"4\",\"id\":\"55e1a8fa-d58c-383c-91dc-41eb42ac2471\",\"created\":\"2021-04-09T15:24:11.040Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:11.040Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a \\\"correlation correction\\\", whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in th exit plane of a converging-diverging nozzle.\",\"bibtype\":\"article\",\"author\":\"Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P\",\"bibtex\":\"@article{\\n title = {Dot-Tracking Methodology for Background Oriented Schlieren (BOS)},\\n type = {article},\\n year = {2018},\\n websites = {http://arxiv.org/abs/1812.10870},\\n month = {4},\\n id = {55e1a8fa-d58c-383c-91dc-41eb42ac2471},\\n created = {2021-04-09T15:24:11.040Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:11.040Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a \\\"correlation correction\\\", whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in th exit plane of a converging-diverging nozzle.},\\n bibtype = {article},\\n author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P}\\n}\",\"author_short\":[\"Rajendran,  L., K.\",\"Bane,  S., P., M.\",\"Vlachos,  P., P.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1812.10870\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":4,\"html\":\"\"},{\"title\":\"On the inherent bias of swirling strength in defining vortical structure\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"35107\",\"volume\":\"31\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5089883\",\"month\":\"4\",\"publisher\":\"AIP Publishing LLC\",\"id\":\"1bcc598a-709e-3005-a0d9-7596e55ee9b5\",\"created\":\"2021-04-09T15:24:12.031Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:12.031Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The traditional practice of using rotational motion as the principal attribute of coherent vortical structures in the buffer region of near-wall turbulent flow is shown to create a biased accountin...\",\"bibtype\":\"article\",\"author\":\"Bernard, Peter S\",\"doi\":\"10.1063/1.5089883\",\"journal\":\"Physics of Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {On the inherent bias of swirling strength in defining vortical structure},\\n type = {article},\\n year = {2019},\\n pages = {35107},\\n volume = {31},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5089883},\\n month = {4},\\n publisher = {AIP Publishing LLC},\\n id = {1bcc598a-709e-3005-a0d9-7596e55ee9b5},\\n created = {2021-04-09T15:24:12.031Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:12.031Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The traditional practice of using rotational motion as the principal attribute of coherent vortical structures in the buffer region of near-wall turbulent flow is shown to create a biased accountin...},\\n bibtype = {article},\\n author = {Bernard, Peter S},\\n doi = {10.1063/1.5089883},\\n journal = {Physics of Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Bernard,  P., S.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5089883\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Interactive visual exploration of line clusters\",\"type\":\"inproceedings\",\"year\":\"2018\",\"pages\":\"155-163\",\"websites\":\"https://dl.acm.org/citation.cfm?id=3307680\",\"publisher\":\"Eurographics Association\",\"id\":\"3af76be2-f576-3cff-afa8-adcecb7e50bb\",\"created\":\"2021-04-09T15:24:13.073Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:13.073Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Kanzler, Mathias and Westermann, Rüdiger\",\"editor\":\"Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip\",\"doi\":\"10.2312/VMV.20181265\",\"booktitle\":\"EG VMV '18 Proceedings of the Conference on Vision, Modeling, and Visualization\",\"bibtex\":\"@inproceedings{\\n title = {Interactive visual exploration of line clusters},\\n type = {inproceedings},\\n year = {2018},\\n pages = {155-163},\\n websites = {https://dl.acm.org/citation.cfm?id=3307680},\\n publisher = {Eurographics Association},\\n id = {3af76be2-f576-3cff-afa8-adcecb7e50bb},\\n created = {2021-04-09T15:24:13.073Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:13.073Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Kanzler, Mathias and Westermann, Rüdiger},\\n editor = {Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip},\\n doi = {10.2312/VMV.20181265},\\n booktitle = {EG VMV '18 Proceedings of the Conference on Vision, Modeling, and Visualization}\\n}\",\"author_short\":[\"Kanzler,  M.\",\"Westermann,  R.\"],\"editor_short\":[\"Beck,  F.\",\"Dachsbacher,  C.\",\"Sadlo,  F.\"],\"urls\":{\"Website\":\"https://dl.acm.org/citation.cfm?id=3307680\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kanzler-westermann-interactivevisualexplorationoflineclusters-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence\",\"type\":\"article\",\"year\":\"2010\",\"keywords\":\"Direct numerical simulation,Isotropic turbulence,Lagrangian statistics,Refined Kolomogorov similarity hypothesis,Turbulence database\",\"pages\":\"457-472\",\"volume\":\"85\",\"websites\":\"http://link.springer.com/10.1007/s10494-010-9256-5\",\"month\":\"4\",\"publisher\":\"Springer Netherlands\",\"id\":\"4f1f9075-6def-3580-8365-e90f69ed1485\",\"created\":\"2021-04-09T15:24:13.990Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:13.990Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We study Lagrangian statistics of the magnitudes of velocity and pressure gradients in isotropic turbulence by quantifying their correlation functions and their characteristic time scales. In a recent work (Yu and Meneveau, Phys Rev Lett 104:084502, 2010), it has been found that the Lagrangian time-correlations of the velocity and pressure gradient tensor and vector elements scale with the locally- definedKolmogorov time scale, evaluated from the locally-averaged dissipation-rate (?r) and viscosity (ν) according to τK,r = √ν/?r. In thiswork, we study theLagrangian time-correlations of the absolute values of velocity and pressure gradients. It has long been known that such correlations display longer memories into the inertial- range as well as possible intermittency effects. We explore the appropriate temporal scales with the aim to achieve collapse of the correlation functions. The data used in this study are sampled from the web-services accessible public turbulence database (http://turbulence.pha.jhu.edu). The database archives a 10244 (space+time) pseudo- spectral direct numerical simulation of forced isotropic turbulence with Taylor- scale Reynolds number Reλ = 433, and supports spatial differentiation and spa- tial/temporal interpolation inside the database. The analysis shows that the temporal auto-correlations of the absolute values extend deep into the inertial range where they are determined not by the local Kolmogorov time-scale but by the local eddy-turnover time scale defined as τe,r = r2/3?−1/3 r .However, considerable scatter remains and appears to be reduced only after a further (intermittency) correction factor of the form of (r/L)χ is introduced, where L is the turbulence integral scale. The exponent χ varies for different variables. The collapse of the correlation functions for absolute values is, however, less satisfactory than the collapse observed for the more rapidly decaying strain-rate tensor element correlation functions in the viscous range.\",\"bibtype\":\"article\",\"author\":\"Yu, Huidan and Meneveau, Charles\",\"doi\":\"10.1007/s10494-010-9256-5\",\"journal\":\"Flow, Turbulence and Combustion\",\"number\":\"3-4\",\"bibtex\":\"@article{\\n title = {Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence},\\n type = {article},\\n year = {2010},\\n keywords = {Direct numerical simulation,Isotropic turbulence,Lagrangian statistics,Refined Kolomogorov similarity hypothesis,Turbulence database},\\n pages = {457-472},\\n volume = {85},\\n websites = {http://link.springer.com/10.1007/s10494-010-9256-5},\\n month = {4},\\n publisher = {Springer Netherlands},\\n id = {4f1f9075-6def-3580-8365-e90f69ed1485},\\n created = {2021-04-09T15:24:13.990Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:13.990Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We study Lagrangian statistics of the magnitudes of velocity and pressure gradients in isotropic turbulence by quantifying their correlation functions and their characteristic time scales. In a recent work (Yu and Meneveau, Phys Rev Lett 104:084502, 2010), it has been found that the Lagrangian time-correlations of the velocity and pressure gradient tensor and vector elements scale with the locally- definedKolmogorov time scale, evaluated from the locally-averaged dissipation-rate (?r) and viscosity (ν) according to τK,r = √ν/?r. In thiswork, we study theLagrangian time-correlations of the absolute values of velocity and pressure gradients. It has long been known that such correlations display longer memories into the inertial- range as well as possible intermittency effects. We explore the appropriate temporal scales with the aim to achieve collapse of the correlation functions. The data used in this study are sampled from the web-services accessible public turbulence database (http://turbulence.pha.jhu.edu). The database archives a 10244 (space+time) pseudo- spectral direct numerical simulation of forced isotropic turbulence with Taylor- scale Reynolds number Reλ = 433, and supports spatial differentiation and spa- tial/temporal interpolation inside the database. The analysis shows that the temporal auto-correlations of the absolute values extend deep into the inertial range where they are determined not by the local Kolmogorov time-scale but by the local eddy-turnover time scale defined as τe,r = r2/3?−1/3 r .However, considerable scatter remains and appears to be reduced only after a further (intermittency) correction factor of the form of (r/L)χ is introduced, where L is the turbulence integral scale. The exponent χ varies for different variables. The collapse of the correlation functions for absolute values is, however, less satisfactory than the collapse observed for the more rapidly decaying strain-rate tensor element correlation functions in the viscous range.},\\n bibtype = {article},\\n author = {Yu, Huidan and Meneveau, Charles},\\n doi = {10.1007/s10494-010-9256-5},\\n journal = {Flow, Turbulence and Combustion},\\n number = {3-4}\\n}\",\"author_short\":[\"Yu,  H.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s10494-010-9256-5\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010\",\"role\":\"author\",\"keyword\":[\"Direct numerical simulation\",\"Isotropic turbulence\",\"Lagrangian statistics\",\"Refined Kolomogorov similarity hypothesis\",\"Turbulence database\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Turbulence visualization at the terascale on desktop PCs\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Visualization system and toolkit design,data compression,data streaming,vector fields,volume rendering\",\"pages\":\"2169-2177\",\"volume\":\"18\",\"websites\":\"http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124\",\"month\":\"4\",\"id\":\"40c4dabb-3c4d-39df-998a-492543c75ed1\",\"created\":\"2021-04-09T15:24:14.491Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:14.491Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small-and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. © 1995-2012 IEEE.\",\"bibtype\":\"article\",\"author\":\"Treib, Marc and Burger, Kai and Reichl, Florian and Meneveau, Charles and Szalay, Alex and Westermann, Rudiger\",\"doi\":\"10.1109/TVCG.2012.274\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Turbulence visualization at the terascale on desktop PCs},\\n type = {article},\\n year = {2012},\\n keywords = {Visualization system and toolkit design,data compression,data streaming,vector fields,volume rendering},\\n pages = {2169-2177},\\n volume = {18},\\n websites = {http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124},\\n month = {4},\\n id = {40c4dabb-3c4d-39df-998a-492543c75ed1},\\n created = {2021-04-09T15:24:14.491Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:14.491Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small-and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. © 1995-2012 IEEE.},\\n bibtype = {article},\\n author = {Treib, Marc and Burger, Kai and Reichl, Florian and Meneveau, Charles and Szalay, Alex and Westermann, Rudiger},\\n doi = {10.1109/TVCG.2012.274},\\n journal = {IEEE Transactions on Visualization and Computer Graphics},\\n number = {12}\\n}\",\"author_short\":[\"Treib,  M.\",\"Burger,  K.\",\"Reichl,  F.\",\"Meneveau,  C.\",\"Szalay,  A.\",\"Westermann,  R.\"],\"urls\":{\"Website\":\"http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012\",\"role\":\"author\",\"keyword\":[\"Visualization system and toolkit design\",\"data compression\",\"data streaming\",\"vector fields\",\"volume rendering\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Algorithms,Computer software,Graphics processing units,Particulate matter\",\"volume\":\"141\",\"websites\":\"https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource\",\"month\":\"4\",\"publisher\":\"American Society of Mechanical Engineers Digital Collection\",\"id\":\"cc217224-e312-3428-96b2-ee61491e548c\",\"created\":\"2021-04-09T15:24:14.978Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:14.978Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Particle image velocimetry (PIV) data processing time can constrain data set size and limit the types of statistical analyses performed. General purpose graphics processing unit (GPGPU) computing can accelerate PIV data processing allowing for larger datasets and accompanying higher order statistical analyses. However, this has not been widespread likely due to limited accessibility to the GPU-PIV hardware and software. Most GPU-PIV software is platform dependent and proprietary, which restricts the computing systems that can be used and makes the details of the algorithm unknown. This work highlights the development of an open-source, cross-platform, GPU-accelerated, PIV algorithm. Validation of the algorithm is done using both synthetic and experimental images. The algorithm was found to accurately resolve the time-averaged flow, instantaneous velocity fluctuations, and vortices. All data processing was done on a GPU supercomputing cluster and notably outperformed the central processing unit version of the software by a factor of 175. The algorithm is freely available and included in the OpenPIV distribution.\",\"bibtype\":\"article\",\"author\":\"Dallas, Cameron and Wu, Maria and Chou, Vincent and Liberzon, Alex and Sullivan, Pierre E\",\"doi\":\"10.1115/1.4043422\",\"journal\":\"Journal of Fluids Engineering\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems},\\n type = {article},\\n year = {2019},\\n keywords = {Algorithms,Computer software,Graphics processing units,Particulate matter},\\n volume = {141},\\n websites = {https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource},\\n month = {4},\\n publisher = {American Society of Mechanical Engineers Digital Collection},\\n id = {cc217224-e312-3428-96b2-ee61491e548c},\\n created = {2021-04-09T15:24:14.978Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:14.978Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Particle image velocimetry (PIV) data processing time can constrain data set size and limit the types of statistical analyses performed. General purpose graphics processing unit (GPGPU) computing can accelerate PIV data processing allowing for larger datasets and accompanying higher order statistical analyses. However, this has not been widespread likely due to limited accessibility to the GPU-PIV hardware and software. Most GPU-PIV software is platform dependent and proprietary, which restricts the computing systems that can be used and makes the details of the algorithm unknown. This work highlights the development of an open-source, cross-platform, GPU-accelerated, PIV algorithm. Validation of the algorithm is done using both synthetic and experimental images. The algorithm was found to accurately resolve the time-averaged flow, instantaneous velocity fluctuations, and vortices. All data processing was done on a GPU supercomputing cluster and notably outperformed the central processing unit version of the software by a factor of 175. The algorithm is freely available and included in the OpenPIV distribution.},\\n bibtype = {article},\\n author = {Dallas, Cameron and Wu, Maria and Chou, Vincent and Liberzon, Alex and Sullivan, Pierre E},\\n doi = {10.1115/1.4043422},\\n journal = {Journal of Fluids Engineering},\\n number = {11}\\n}\",\"author_short\":[\"Dallas,  C.\",\"Wu,  M.\",\"Chou,  V.\",\"Liberzon,  A.\",\"Sullivan,  P., E.\"],\"urls\":{\"Website\":\"https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019\",\"role\":\"author\",\"keyword\":[\"Algorithms\",\"Computer software\",\"Graphics processing units\",\"Particulate matter\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Isotropic turbulence,chaos and fractals,direct numerical simulation\",\"pages\":\"297-321\",\"volume\":\"19\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995\",\"month\":\"4\",\"publisher\":\"Taylor & Francis\",\"id\":\"32a620b0-6e74-3b93-806b-efbd3195b9c1\",\"created\":\"2021-04-09T15:24:15.454Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:15.454Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Motivated by interest in the geometry of high intensity events of turbulent flows, we examine spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analyzed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation, and velocity gradient invariants Q and R and their joint spatial distibutions, using data from a direct numerical simulation of isotropic turbulence at  Re_λ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus a geometric characterization in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behavior. Nevertheless the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on the multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow. We show that sets defined by joint conditions on strain and enstrophy, and on Q and R, also display power law scaling of correlation functions, providing further characterization of the complex spatial structure of these intersection sets.\",\"bibtype\":\"article\",\"author\":\"Elsas, José Hugo and Szalay, Alexander S and Meneveau, Charles\",\"doi\":\"10.1080/14685248.2018.1424995\",\"journal\":\"Journal of Turbulence\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {Isotropic turbulence,chaos and fractals,direct numerical simulation},\\n pages = {297-321},\\n volume = {19},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995},\\n month = {4},\\n publisher = {Taylor & Francis},\\n id = {32a620b0-6e74-3b93-806b-efbd3195b9c1},\\n created = {2021-04-09T15:24:15.454Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:15.454Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Motivated by interest in the geometry of high intensity events of turbulent flows, we examine spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analyzed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation, and velocity gradient invariants Q and R and their joint spatial distibutions, using data from a direct numerical simulation of isotropic turbulence at  Re_λ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus a geometric characterization in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behavior. Nevertheless the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on the multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow. We show that sets defined by joint conditions on strain and enstrophy, and on Q and R, also display power law scaling of correlation functions, providing further characterization of the complex spatial structure of these intersection sets.},\\n bibtype = {article},\\n author = {Elsas, José Hugo and Szalay, Alexander S and Meneveau, Charles},\\n doi = {10.1080/14685248.2018.1424995},\\n journal = {Journal of Turbulence},\\n number = {4}\\n}\",\"author_short\":[\"Elsas,  J., H.\",\"Szalay,  A., S.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018\",\"role\":\"author\",\"keyword\":[\"Isotropic turbulence\",\"chaos and fractals\",\"direct numerical simulation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"b6773a3d-bb0f-3392-b88a-44c5aaaa5583\",\"created\":\"2021-04-09T15:24:15.979Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:15.979Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The subgrid-scale effects on particle motion were investigated in forced isotropic turbulence by DNS and prior-LES methods. In the DNS field, the importance of Kolmogorov scaling to preferential accumulation was validated by comparing the radial distribution functions under various particle Stokes numbers. The prior-LES fields were generated by filtering the DNS data. The subgrid-scale Stokes number (StSGS) is a useful tool for determining the effects of subgrid-scale eddies on particle motion. The subgrid-scale eddies tend to accumulate particles with StSGS < 1 and disperse particles with 1 < StSGS < 10. For particles with StSGS ≫ 1, the effects of subgrid-scale eddies on particle motion can be neglected. In order to restore the subgrid-scale effects, the Langevin-type stochastic model with optimized parameters was adopted in this study. This model is effective for the particles with StSGS > 1 while has an adverse impact on the particles with StSGS < 1. The results show that the Langevin-type stochastic model tends to smooth the particle distribution in the isotropic turbulence.\",\"bibtype\":\"article\",\"author\":\"Shen, Haoshu and Wu, Yuxin and Zhou, Minmin and Zhang, Hai and Yue, Guangxi\",\"doi\":\"10.1016/j.cjche.2019.05.007\",\"journal\":\"Chinese Journal of Chemical Engineering\",\"bibtex\":\"@article{\\n title = {Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence},\\n type = {article},\\n year = {2019},\\n websites = {https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X},\\n month = {4},\\n publisher = {Elsevier},\\n id = {b6773a3d-bb0f-3392-b88a-44c5aaaa5583},\\n created = {2021-04-09T15:24:15.979Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:15.979Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The subgrid-scale effects on particle motion were investigated in forced isotropic turbulence by DNS and prior-LES methods. In the DNS field, the importance of Kolmogorov scaling to preferential accumulation was validated by comparing the radial distribution functions under various particle Stokes numbers. The prior-LES fields were generated by filtering the DNS data. The subgrid-scale Stokes number (StSGS) is a useful tool for determining the effects of subgrid-scale eddies on particle motion. The subgrid-scale eddies tend to accumulate particles with StSGS < 1 and disperse particles with 1 < StSGS < 10. For particles with StSGS ≫ 1, the effects of subgrid-scale eddies on particle motion can be neglected. In order to restore the subgrid-scale effects, the Langevin-type stochastic model with optimized parameters was adopted in this study. This model is effective for the particles with StSGS > 1 while has an adverse impact on the particles with StSGS < 1. The results show that the Langevin-type stochastic model tends to smooth the particle distribution in the isotropic turbulence.},\\n bibtype = {article},\\n author = {Shen, Haoshu and Wu, Yuxin and Zhou, Minmin and Zhang, Hai and Yue, Guangxi},\\n doi = {10.1016/j.cjche.2019.05.007},\\n journal = {Chinese Journal of Chemical Engineering}\\n}\",\"author_short\":[\"Shen,  H.\",\"Wu,  Y.\",\"Zhou,  M.\",\"Zhang,  H.\",\"Yue,  G.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"85302\",\"volume\":\"30\",\"websites\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8\",\"month\":\"4\",\"publisher\":\"IOP Publishing\",\"id\":\"694f4e21-cf49-34b6-a913-a707e0253073\",\"created\":\"2021-04-09T15:24:16.417Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:16.417Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P\",\"doi\":\"10.1088/1361-6501/ab1ca8\",\"journal\":\"Measurement Science and Technology\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design},\\n type = {article},\\n year = {2019},\\n pages = {85302},\\n volume = {30},\\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8},\\n month = {4},\\n publisher = {IOP Publishing},\\n id = {694f4e21-cf49-34b6-a913-a707e0253073},\\n created = {2021-04-09T15:24:16.417Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:16.417Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P},\\n doi = {10.1088/1361-6501/ab1ca8},\\n journal = {Measurement Science and Technology},\\n number = {8}\\n}\",\"author_short\":[\"Rajendran,  L., K.\",\"Bane,  S., P., M.\",\"Vlachos,  P., P.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Accurate and Efficient Autonomic Closure for Turbulent Flows\",\"type\":\"misc\",\"year\":\"2019\",\"websites\":\"https://search.proquest.com/docview/2226592272?pq-origsite=gscholar\",\"institution\":\"ARIZONA STATE UNIVERSITY\",\"id\":\"30a18ab6-0157-38f8-9532-b74068f5a841\",\"created\":\"2021-04-09T15:24:17.608Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:17.608Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"thesis\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Kshitij, Abhinav\",\"bibtex\":\"@misc{\\n title = {Accurate and Efficient Autonomic Closure for Turbulent Flows},\\n type = {misc},\\n year = {2019},\\n websites = {https://search.proquest.com/docview/2226592272?pq-origsite=gscholar},\\n institution = {ARIZONA STATE UNIVERSITY},\\n id = {30a18ab6-0157-38f8-9532-b74068f5a841},\\n created = {2021-04-09T15:24:17.608Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:17.608Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {thesis},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Kshitij, Abhinav}\\n}\",\"author_short\":[\"Kshitij,  A.\"],\"urls\":{\"Website\":\"https://search.proquest.com/docview/2226592272?pq-origsite=gscholar\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kshitij-accurateandefficientautonomicclosureforturbulentflows-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Singular value decomposition of noisy data: noise filtering\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"126\",\"volume\":\"60\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2768-4\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"4b1ae409-ef40-393c-94fd-d0ed9c3d2f1d\",\"created\":\"2021-04-09T15:24:18.163Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:18.163Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Epps, Brenden P and Krivitzky, Eric M\",\"doi\":\"10.1007/s00348-019-2768-4\",\"journal\":\"Experiments in Fluids\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Singular value decomposition of noisy data: noise filtering},\\n type = {article},\\n year = {2019},\\n pages = {126},\\n volume = {60},\\n websites = {http://link.springer.com/10.1007/s00348-019-2768-4},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {4b1ae409-ef40-393c-94fd-d0ed9c3d2f1d},\\n created = {2021-04-09T15:24:18.163Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:18.163Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Epps, Brenden P and Krivitzky, Eric M},\\n doi = {10.1007/s00348-019-2768-4},\\n journal = {Experiments in Fluids},\\n number = {8}\\n}\",\"author_short\":[\"Epps,  B., P.\",\"Krivitzky,  E., M.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2768-4\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"1-21\",\"volume\":\"57\",\"websites\":\"http://link.springer.com/10.1007/s00348-015-2110-8\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"f3a9a6ab-3a9a-3167-8cfb-b879798e7980\",\"created\":\"2021-04-09T15:24:18.620Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:18.620Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© 2016, The Author(s). The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096–1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.\",\"bibtype\":\"article\",\"author\":\"Masullo, Alessandro and Theunissen, Raf\",\"doi\":\"10.1007/s00348-015-2110-8\",\"journal\":\"Experiments in Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters},\\n type = {article},\\n year = {2016},\\n pages = {1-21},\\n volume = {57},\\n websites = {http://link.springer.com/10.1007/s00348-015-2110-8},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {f3a9a6ab-3a9a-3167-8cfb-b879798e7980},\\n created = {2021-04-09T15:24:18.620Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:18.620Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© 2016, The Author(s). The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096–1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.},\\n bibtype = {article},\\n author = {Masullo, Alessandro and Theunissen, Raf},\\n doi = {10.1007/s00348-015-2110-8},\\n journal = {Experiments in Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Masullo,  A.\",\"Theunissen,  R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-015-2110-8\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Scale and rotation invariant detection of singular patterns in vector flow fields\",\"type\":\"misc\",\"year\":\"2010\",\"source\":\"Structural, Syntactic, and Statistical Pattern Recognition\",\"pages\":\"522-531\",\"volume\":\"6218\",\"websites\":\"http://link.springer.com/10.1007/978-3-642-14980-1_51\",\"publisher\":\"Springer, Berlin, Heidelberg\",\"id\":\"87624f2f-71c5-35a8-8049-4b22ce15c2a2\",\"created\":\"2021-04-09T15:24:19.096Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:19.096Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"book_section\",\"private_publication\":false,\"abstract\":\"We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based inner-product. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.\",\"bibtype\":\"misc\",\"author\":\"Liu, Wei and Ribeiro, Eraldo\",\"doi\":\"10.1007/978-3-642-14980-1_51\",\"bibtex\":\"@misc{\\n title = {Scale and rotation invariant detection of singular patterns in vector flow fields},\\n type = {misc},\\n year = {2010},\\n source = {Structural, Syntactic, and Statistical Pattern Recognition},\\n pages = {522-531},\\n volume = {6218},\\n websites = {http://link.springer.com/10.1007/978-3-642-14980-1_51},\\n publisher = {Springer, Berlin, Heidelberg},\\n id = {87624f2f-71c5-35a8-8049-4b22ce15c2a2},\\n created = {2021-04-09T15:24:19.096Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:19.096Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {book_section},\\n private_publication = {false},\\n abstract = {We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based inner-product. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.},\\n bibtype = {misc},\\n author = {Liu, Wei and Ribeiro, Eraldo},\\n doi = {10.1007/978-3-642-14980-1_51}\\n}\",\"author_short\":[\"Liu,  W.\",\"Ribeiro,  E.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-642-14980-1_51\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Regularized inverse holographic volume reconstruction for 3D particle tracking\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Compressive holography,High speed photography,Image metrics,Image processing,Image quality,Phase retrieval\",\"pages\":\"18069\",\"volume\":\"27\",\"websites\":\"https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069\",\"month\":\"4\",\"publisher\":\"Optical Society of America\",\"id\":\"77ebf8f3-d916-351b-8ed0-2df7438d554d\",\"created\":\"2021-04-09T15:24:19.672Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:19.672Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.\",\"bibtype\":\"article\",\"author\":\"Mallery, Kevin and Hong, Jiarong\",\"doi\":\"10.1364/OE.27.018069\",\"journal\":\"Optics Express\",\"number\":\"13\",\"bibtex\":\"@article{\\n title = {Regularized inverse holographic volume reconstruction for 3D particle tracking},\\n type = {article},\\n year = {2019},\\n keywords = {Compressive holography,High speed photography,Image metrics,Image processing,Image quality,Phase retrieval},\\n pages = {18069},\\n volume = {27},\\n websites = {https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069},\\n month = {4},\\n publisher = {Optical Society of America},\\n id = {77ebf8f3-d916-351b-8ed0-2df7438d554d},\\n created = {2021-04-09T15:24:19.672Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:19.672Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.},\\n bibtype = {article},\\n author = {Mallery, Kevin and Hong, Jiarong},\\n doi = {10.1364/OE.27.018069},\\n journal = {Optics Express},\\n number = {13}\\n}\",\"author_short\":[\"Mallery,  K.\",\"Hong,  J.\"],\"urls\":{\"Website\":\"https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019\",\"role\":\"author\",\"keyword\":[\"Compressive holography\",\"High speed photography\",\"Image metrics\",\"Image processing\",\"Image quality\",\"Phase retrieval\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Declarative Grammar of Flexible Volume Visualization Pipelines\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"1050-1059\",\"volume\":\"25\",\"websites\":\"https://ieeexplore.ieee.org/document/8440063/\",\"month\":\"4\",\"id\":\"d2fa3e23-d58f-3188-801f-b9802e93fb62\",\"created\":\"2021-04-09T15:24:20.241Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:20.241Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Shih, Min and Rozhon, Charles and Ma, Kwan-Liu\",\"doi\":\"10.1109/TVCG.2018.2864841\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A Declarative Grammar of Flexible Volume Visualization Pipelines},\\n type = {article},\\n year = {2019},\\n pages = {1050-1059},\\n volume = {25},\\n websites = {https://ieeexplore.ieee.org/document/8440063/},\\n month = {4},\\n id = {d2fa3e23-d58f-3188-801f-b9802e93fb62},\\n created = {2021-04-09T15:24:20.241Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:20.241Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Shih, Min and Rozhon, Charles and Ma, Kwan-Liu},\\n doi = {10.1109/TVCG.2018.2864841},\\n journal = {IEEE Transactions on Visualization and Computer Graphics},\\n number = {1}\\n}\",\"author_short\":[\"Shih,  M.\",\"Rozhon,  C.\",\"Ma,  K.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/8440063/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Structure of the velocity gradient tensor in turbulent shear flows\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"74602\",\"volume\":\"2\",\"websites\":\"http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"03d44fe9-4542-3cf6-90b0-3277cd950651\",\"created\":\"2021-04-09T15:24:20.716Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:20.716Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The expected universality of small-scale properties of turbulent flows implies isotropic properties of the velocity gradient tensor in the very large Reynolds number limit. Using direct numerical simulations, we determine the tensors formed by n = 2 and 3 velocity gradients at a single point in turbulent homogeneous shear flows, and in the log-layer of a turbulent channel flow, and we characterize the departure of these tensors from the corresponding isotropic prediction. Specifically, we separate the even components of the tensors, invariant under reflexion with respect to all axes, from the odd ones, which identically vanish in the absence of shear. Our results indicate that the largest deviation from isotropy comes from the odd component of the third velocity gradient correlation function, especially from the third moment of the derivative along the normal direction of the streamwise velocity component. At the Reynolds numbers considered (R_lambda ~ 140), we observe that these second and third order correlation functions are significantly larger in turbulent channel flows than in homogeneous shear flow. Overall, our work demonstrates that a mean shear leads to relatively simple structure of the velocity gradient tensor. How isotropy is restored in the very large Reynolds limit remains to be understood.\",\"bibtype\":\"article\",\"author\":\"Pumir, Alain\",\"doi\":\"10.1103/PhysRevFluids.2.074602\",\"journal\":\"Physical Review Fluids\",\"number\":\"7\",\"bibtex\":\"@article{\\n title = {Structure of the velocity gradient tensor in turbulent shear flows},\\n type = {article},\\n year = {2017},\\n pages = {74602},\\n volume = {2},\\n websites = {http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {03d44fe9-4542-3cf6-90b0-3277cd950651},\\n created = {2021-04-09T15:24:20.716Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:20.716Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The expected universality of small-scale properties of turbulent flows implies isotropic properties of the velocity gradient tensor in the very large Reynolds number limit. Using direct numerical simulations, we determine the tensors formed by n = 2 and 3 velocity gradients at a single point in turbulent homogeneous shear flows, and in the log-layer of a turbulent channel flow, and we characterize the departure of these tensors from the corresponding isotropic prediction. Specifically, we separate the even components of the tensors, invariant under reflexion with respect to all axes, from the odd ones, which identically vanish in the absence of shear. Our results indicate that the largest deviation from isotropy comes from the odd component of the third velocity gradient correlation function, especially from the third moment of the derivative along the normal direction of the streamwise velocity component. At the Reynolds numbers considered (R_lambda ~ 140), we observe that these second and third order correlation functions are significantly larger in turbulent channel flows than in homogeneous shear flow. Overall, our work demonstrates that a mean shear leads to relatively simple structure of the velocity gradient tensor. How isotropy is restored in the very large Reynolds limit remains to be understood.},\\n bibtype = {article},\\n author = {Pumir, Alain},\\n doi = {10.1103/PhysRevFluids.2.074602},\\n journal = {Physical Review Fluids},\\n number = {7}\\n}\",\"author_short\":[\"Pumir,  A.\"],\"urls\":{\"Website\":\"http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Small-scale anisotropy in turbulent boundary layers\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"turbulence theory,turbulent boundary layers,turbulent flows\",\"pages\":\"5-23\",\"volume\":\"804\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112016005292\",\"month\":\"4\",\"id\":\"d2a55492-2a18-3e31-81e7-c7585aa3805c\",\"created\":\"2021-04-09T15:24:21.280Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:21.280Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ( Re_[STIX]x1D70F 1000 ), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is R_[STIX]x1D706 150 . This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of R_[STIX]x1D706 . In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.\",\"bibtype\":\"article\",\"author\":\"Pumir, Alain and Xu, Haitao and Siggia, Eric D\",\"doi\":\"10.1017/jfm.2016.529\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Small-scale anisotropy in turbulent boundary layers},\\n type = {article},\\n year = {2016},\\n keywords = {turbulence theory,turbulent boundary layers,turbulent flows},\\n pages = {5-23},\\n volume = {804},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005292},\\n month = {4},\\n id = {d2a55492-2a18-3e31-81e7-c7585aa3805c},\\n created = {2021-04-09T15:24:21.280Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:21.280Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ( Re_[STIX]x1D70F 1000 ), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is R_[STIX]x1D706 150 . This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of R_[STIX]x1D706 . In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.},\\n bibtype = {article},\\n author = {Pumir, Alain and Xu, Haitao and Siggia, Eric D},\\n doi = {10.1017/jfm.2016.529},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Pumir,  A.\",\"Xu,  H.\",\"Siggia,  E., D.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112016005292\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016\",\"role\":\"author\",\"keyword\":[\"turbulence theory\",\"turbulent boundary layers\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"On the Reynolds number dependence of velocity-gradient structure and dynamics\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"intermittency,isotropic turbulence,turbulent flows\",\"pages\":\"163-179\",\"volume\":\"861\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"ae410480-9dcc-3981-b2c4-c727efa02cc1\",\"created\":\"2021-04-09T15:24:21.799Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:21.799Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We seek to examine the changes in velocity-gradient structure (local streamline topology) and related dynamics as a function of Reynolds number ( Re_[STIX]x1D706 ). The analysis factorizes the velocity gradient ( [STIX]x1D608_ij ) into the magnitude ( A^2 ) and normalized-gradient tensor ( [STIX]x1D623_ij [STIX]x1D608_ij/A^2 ). The focus is on bounded [STIX]x1D623_ij as (i) it describes small-scale structure and local streamline topology, and (ii) its dynamics is shown to determine magnitude evolution. Using direct numerical simulation (DNS) data, the moments and probability distributions of [STIX]x1D623_ij and its scalar invariants are shown to attain Re_[STIX]x1D706 independence. The critical values beyond which each feature attains Re_[STIX]x1D706 independence are established. We proceed to characterize the Re_[STIX]x1D706 dependence of [STIX]x1D623_ij -conditioned statistics of key non-local pressure and viscous processes. Overall, the analysis provides further insight into velocity-gradient dynamics and offers an alternative framework for investigating intermittency, multifractal behaviour and for developing closure models.\",\"bibtype\":\"article\",\"author\":\"Das, Rishita and Girimaji, Sharath S\",\"doi\":\"10.1017/jfm.2018.924\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {On the Reynolds number dependence of velocity-gradient structure and dynamics},\\n type = {article},\\n year = {2019},\\n keywords = {intermittency,isotropic turbulence,turbulent flows},\\n pages = {163-179},\\n volume = {861},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {ae410480-9dcc-3981-b2c4-c727efa02cc1},\\n created = {2021-04-09T15:24:21.799Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:21.799Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We seek to examine the changes in velocity-gradient structure (local streamline topology) and related dynamics as a function of Reynolds number ( Re_[STIX]x1D706 ). The analysis factorizes the velocity gradient ( [STIX]x1D608_ij ) into the magnitude ( A^2 ) and normalized-gradient tensor ( [STIX]x1D623_ij [STIX]x1D608_ij/A^2 ). The focus is on bounded [STIX]x1D623_ij as (i) it describes small-scale structure and local streamline topology, and (ii) its dynamics is shown to determine magnitude evolution. Using direct numerical simulation (DNS) data, the moments and probability distributions of [STIX]x1D623_ij and its scalar invariants are shown to attain Re_[STIX]x1D706 independence. The critical values beyond which each feature attains Re_[STIX]x1D706 independence are established. We proceed to characterize the Re_[STIX]x1D706 dependence of [STIX]x1D623_ij -conditioned statistics of key non-local pressure and viscous processes. Overall, the analysis provides further insight into velocity-gradient dynamics and offers an alternative framework for investigating intermittency, multifractal behaviour and for developing closure models.},\\n bibtype = {article},\\n author = {Das, Rishita and Girimaji, Sharath S},\\n doi = {10.1017/jfm.2018.924},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Das,  R.\",\"Girimaji,  S., S.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019\",\"role\":\"author\",\"keyword\":[\"intermittency\",\"isotropic turbulence\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1905.02657\",\"month\":\"4\",\"id\":\"280c93e9-f450-3915-b1f9-260517c43d49\",\"created\":\"2021-04-09T15:24:22.355Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:22.355Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Homogeneous and isotropic turbulent fields obtained from two DNS databases (with Re_λ equal to 150 and 418) were seeded with point particles that moved with the local fluid velocity to obtain Lagrangian pressure histories. Motivated by cavitation inception modeling, the statistics of events in which such particles undergo low-pressure fluctuations were computed, parameterized by the amplitude of the fluctuations and by their duration. The main results are the average frequencies of these events and the probabilistic distribution of their duration, which are of predictive value. A connection is also established between these average frequencies and the pressure probability density function, thus justifying experimental methods proposed in the literature. Further analyses of the data show that the occurrence of very-low-pressure events is highly intermittent and is associated with worm-like vortical structures of length comparable to the integral scale of the flow.\",\"bibtype\":\"article\",\"author\":\"Bappy, Mehedi and Carrica, Pablo M and Buscaglia, Gustavo C\",\"bibtex\":\"@article{\\n title = {Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1905.02657},\\n month = {4},\\n id = {280c93e9-f450-3915-b1f9-260517c43d49},\\n created = {2021-04-09T15:24:22.355Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:22.355Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Homogeneous and isotropic turbulent fields obtained from two DNS databases (with Re_λ equal to 150 and 418) were seeded with point particles that moved with the local fluid velocity to obtain Lagrangian pressure histories. Motivated by cavitation inception modeling, the statistics of events in which such particles undergo low-pressure fluctuations were computed, parameterized by the amplitude of the fluctuations and by their duration. The main results are the average frequencies of these events and the probabilistic distribution of their duration, which are of predictive value. A connection is also established between these average frequencies and the pressure probability density function, thus justifying experimental methods proposed in the literature. Further analyses of the data show that the occurrence of very-low-pressure events is highly intermittent and is associated with worm-like vortical structures of length comparable to the integral scale of the flow.},\\n bibtype = {article},\\n author = {Bappy, Mehedi and Carrica, Pablo M and Buscaglia, Gustavo C}\\n}\",\"author_short\":[\"Bappy,  M.\",\"Carrica,  P., M.\",\"Buscaglia,  G., C.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1905.02657\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Identifying the Wall Signature of Large-Scale Motions with Extended POD\",\"type\":\"inproceedings\",\"year\":\"2019\",\"pages\":\"75-80\",\"websites\":\"http://link.springer.com/10.1007/978-3-030-22196-6_12\",\"month\":\"4\",\"publisher\":\"Springer, Cham\",\"id\":\"d61dbfb7-bdc7-3a6d-be6f-dd3b8a1f6f86\",\"created\":\"2021-04-09T15:24:22.820Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:22.820Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Güemes, A and Vaquero, A and Flores, O and Discetti, S and Ianiro, A\",\"editor\":\"Örlü, R and Talamelli, A and Peinke, J and Oberlack, M\",\"doi\":\"10.1007/978-3-030-22196-6_12\",\"booktitle\":\"8th iTi Conference on Turbulence\",\"bibtex\":\"@inproceedings{\\n title = {Identifying the Wall Signature of Large-Scale Motions with Extended POD},\\n type = {inproceedings},\\n year = {2019},\\n pages = {75-80},\\n websites = {http://link.springer.com/10.1007/978-3-030-22196-6_12},\\n month = {4},\\n publisher = {Springer, Cham},\\n id = {d61dbfb7-bdc7-3a6d-be6f-dd3b8a1f6f86},\\n created = {2021-04-09T15:24:22.820Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:22.820Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Güemes, A and Vaquero, A and Flores, O and Discetti, S and Ianiro, A},\\n editor = {Örlü, R and Talamelli, A and Peinke, J and Oberlack, M},\\n doi = {10.1007/978-3-030-22196-6_12},\\n booktitle = {8th iTi Conference on Turbulence}\\n}\",\"author_short\":[\"Güemes,  A.\",\"Vaquero,  A.\",\"Flores,  O.\",\"Discetti,  S.\",\"Ianiro,  A.\"],\"editor_short\":[\"Örlü,  R.\",\"Talamelli,  A.\",\"Peinke,  J.\",\"Oberlack,  M.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/978-3-030-22196-6_12\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":7,\"html\":\"\"},{\"title\":\"Robust Principal Component Analysis for Particle Image Velocimetry\",\"type\":\"article\",\"year\":\"2019\",\"websites\":\"http://arxiv.org/abs/1905.07062\",\"month\":\"4\",\"id\":\"b2b8c1c5-c3df-3831-acee-24a087c7762f\",\"created\":\"2021-04-09T15:24:23.533Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:23.533Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Particle image velocimetry (PIV) is an experimental technique used to measure fluid flow fields. However, PIV fields often have spurious and missing velocity vectors that degrade subsequent analyses. Standard post-processing involves the identification and replacement of outliers based on local information. We present a method to identify and fill in erroneous or missing PIV vectors using global information via robust principal component analysis (RPCA), a statistical technique developed for outlier rejection. RPCA decomposes a data matrix into a low-rank matrix containing coherent structures and a sparse matrix of outliers. We explore RPCA on a range of fluid simulations and experiments of varying complexity. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificially added outliers, alongside similar PIV measurements at Reynolds number 413. Next, we apply RPCA to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are maintained and the turbulent kinetic energy spectrum remains largely intact. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA extracts dominant fluid coherent structures and identifies and fills in corruption and outliers, with minimal degradation of small scale structures.\",\"bibtype\":\"article\",\"author\":\"Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L\",\"bibtex\":\"@article{\\n title = {Robust Principal Component Analysis for Particle Image Velocimetry},\\n type = {article},\\n year = {2019},\\n websites = {http://arxiv.org/abs/1905.07062},\\n month = {4},\\n id = {b2b8c1c5-c3df-3831-acee-24a087c7762f},\\n created = {2021-04-09T15:24:23.533Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:23.533Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Particle image velocimetry (PIV) is an experimental technique used to measure fluid flow fields. However, PIV fields often have spurious and missing velocity vectors that degrade subsequent analyses. Standard post-processing involves the identification and replacement of outliers based on local information. We present a method to identify and fill in erroneous or missing PIV vectors using global information via robust principal component analysis (RPCA), a statistical technique developed for outlier rejection. RPCA decomposes a data matrix into a low-rank matrix containing coherent structures and a sparse matrix of outliers. We explore RPCA on a range of fluid simulations and experiments of varying complexity. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificially added outliers, alongside similar PIV measurements at Reynolds number 413. Next, we apply RPCA to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are maintained and the turbulent kinetic energy spectrum remains largely intact. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA extracts dominant fluid coherent structures and identifies and fills in corruption and outliers, with minimal degradation of small scale structures.},\\n bibtype = {article},\\n author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L}\\n}\",\"author_short\":[\"Scherl,  I.\",\"Strom,  B.\",\"Shang,  J., K.\",\"Williams,  O.\",\"Polagye,  B., L.\",\"Brunton,  S., L.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1905.07062\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Flow structure interactions,Shear layer turbulence,Vortex dynamics\",\"pages\":\"417-457\",\"volume\":\"728\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112013002759\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"f07ba240-7dc8-3d45-90d2-e2f8bd3cee75\",\"created\":\"2021-04-09T15:24:24.005Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:24.005Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The flow structure and turbulence in an open cavity shear layer has been investigated experimentally at a Reynolds number of 4.0 × 104, with an emphasis on interactions of the unsteady pressure field with the cavity corners. A large database of time-resolved two-dimensional PIV measurements has been used to obtain the velocity distributions and calculate the pressure by spatially integrating the material acceleration at a series of sample areas covering the entire shear layer and the flow surrounding the corners. Conditional sampling, low-pass filtering and time correlations among variables enable us to elucidate several processes, which have distinctly different frequency ranges, that dominate the shear layer interactions with the corners. Kelvin-Helmholtz shear layer eddies have the expected Strouhal number range of 0.5-3.2. Their interactions with the trailing corner introduce two sources of vorticity fluctuations above the corner. The first is caused by the expected advection of remnants of the shear layer eddies. The second source involves fluctuations in local viscous vorticity flux away from the wall caused by periodic variations in the streamwise pressure gradients. This local production peaks when the shear layer vortices are located away from the corner, creating a lingering region with peak vorticity just above the corner. The associated periodic pressure minima there are lower than any other point in the entire flow field, making the region above the corner most prone to cavitation inception. Flapping of the shear layer and boundary layer upstream of the leading corner occurs at very low Strouhal numbers of ~0.05, affecting all the flow and turbulence quantities around both corners. Time-dependent correlations of the shear layer elevation show that the flapping starts in the boundary layer upstream of the leading corner and propagates downstream at the free stream speed. Near the trailing corner, when the shear layer elevation is low, the stagnation pressure in front of the wall, the downward jetting flow along this wall, the fraction of shear layer vorticity entrained back into the cavity, and the magnitude of the pressure minimum above the corner are higher than those measured when the shear layer is high. However, the variations in downward jetting decay rapidly with increasing distance from the trailing corner, indicating that it does not play a direct role in a feedback mechanism that sustains the flapping. There is also low correlation between the boundary/shear layer elevation and the returning flow along the upstream vertical wall, providing little evidence that this returning flow affects the flapping directly. However, the characteristic period of flapping, ~0.6 s, is consistent with recirculation time of the fluid within the cavity away from boundaries. The high negative correlations of shear/boundary layer elevation with the streamwise pressure gradient above the leading corner introduce a plausible mechanism that sustains the flapping: when the shear layer is low, the boundary layer is subjected to high adverse streamwise pressure gradients that force it to widen, and when the shear layer is high, the pressure gradients decrease, allowing the boundary layer to thin down. Flow mechanisms that would cause the flapping-induced pressure changes, and their relations to the flow within the cavity are discussed. © 2013 Cambridge University Press.\",\"bibtype\":\"article\",\"author\":\"Liu, Xiaofeng and Katz, Joseph\",\"doi\":\"10.1017/jfm.2013.275\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field},\\n type = {article},\\n year = {2013},\\n keywords = {Flow structure interactions,Shear layer turbulence,Vortex dynamics},\\n pages = {417-457},\\n volume = {728},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112013002759},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {f07ba240-7dc8-3d45-90d2-e2f8bd3cee75},\\n created = {2021-04-09T15:24:24.005Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:24.005Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The flow structure and turbulence in an open cavity shear layer has been investigated experimentally at a Reynolds number of 4.0 × 104, with an emphasis on interactions of the unsteady pressure field with the cavity corners. A large database of time-resolved two-dimensional PIV measurements has been used to obtain the velocity distributions and calculate the pressure by spatially integrating the material acceleration at a series of sample areas covering the entire shear layer and the flow surrounding the corners. Conditional sampling, low-pass filtering and time correlations among variables enable us to elucidate several processes, which have distinctly different frequency ranges, that dominate the shear layer interactions with the corners. Kelvin-Helmholtz shear layer eddies have the expected Strouhal number range of 0.5-3.2. Their interactions with the trailing corner introduce two sources of vorticity fluctuations above the corner. The first is caused by the expected advection of remnants of the shear layer eddies. The second source involves fluctuations in local viscous vorticity flux away from the wall caused by periodic variations in the streamwise pressure gradients. This local production peaks when the shear layer vortices are located away from the corner, creating a lingering region with peak vorticity just above the corner. The associated periodic pressure minima there are lower than any other point in the entire flow field, making the region above the corner most prone to cavitation inception. Flapping of the shear layer and boundary layer upstream of the leading corner occurs at very low Strouhal numbers of ~0.05, affecting all the flow and turbulence quantities around both corners. Time-dependent correlations of the shear layer elevation show that the flapping starts in the boundary layer upstream of the leading corner and propagates downstream at the free stream speed. Near the trailing corner, when the shear layer elevation is low, the stagnation pressure in front of the wall, the downward jetting flow along this wall, the fraction of shear layer vorticity entrained back into the cavity, and the magnitude of the pressure minimum above the corner are higher than those measured when the shear layer is high. However, the variations in downward jetting decay rapidly with increasing distance from the trailing corner, indicating that it does not play a direct role in a feedback mechanism that sustains the flapping. There is also low correlation between the boundary/shear layer elevation and the returning flow along the upstream vertical wall, providing little evidence that this returning flow affects the flapping directly. However, the characteristic period of flapping, ~0.6 s, is consistent with recirculation time of the fluid within the cavity away from boundaries. The high negative correlations of shear/boundary layer elevation with the streamwise pressure gradient above the leading corner introduce a plausible mechanism that sustains the flapping: when the shear layer is low, the boundary layer is subjected to high adverse streamwise pressure gradients that force it to widen, and when the shear layer is high, the pressure gradients decrease, allowing the boundary layer to thin down. Flow mechanisms that would cause the flapping-induced pressure changes, and their relations to the flow within the cavity are discussed. © 2013 Cambridge University Press.},\\n bibtype = {article},\\n author = {Liu, Xiaofeng and Katz, Joseph},\\n doi = {10.1017/jfm.2013.275},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Liu,  X.\",\"Katz,  J.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112013002759\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013\",\"role\":\"author\",\"keyword\":[\"Flow structure interactions\",\"Shear layer turbulence\",\"Vortex dynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"84607\",\"volume\":\"2\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607\",\"month\":\"4\",\"id\":\"07452386-7dbf-3811-a8de-be917350f3f1\",\"created\":\"2021-04-09T15:24:24.548Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:24.548Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Keylock, Christopher J\",\"doi\":\"10.1103/PhysRevFluids.2.084607\",\"journal\":\"Physical Review Fluids\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence},\\n type = {article},\\n year = {2017},\\n pages = {84607},\\n volume = {2},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607},\\n month = {4},\\n id = {07452386-7dbf-3811-a8de-be917350f3f1},\\n created = {2021-04-09T15:24:24.548Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:24.548Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Keylock, Christopher J},\\n doi = {10.1103/PhysRevFluids.2.084607},\\n journal = {Physical Review Fluids},\\n number = {8}\\n}\",\"author_short\":[\"Keylock,  C., J.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Inhomogeneous preferential concentration of inertial particles in turbulent channel flow\",\"type\":\"article\",\"year\":\"2017\",\"websites\":\"http://arxiv.org/abs/1702.01438\",\"month\":\"4\",\"id\":\"969b0689-e176-3ccf-97c1-524f2b1d503b\",\"created\":\"2021-04-09T15:24:25.148Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:25.148Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Turbophoresis leading to preferential concentration of inertial particles in regions of low turbulent diffusivity is a unique feature of inhomogeneous turbulent flows, such as free shear flows or wall-bounded flows. In this work, the theory for clustering of weakly inertial particles in homogeneous turbulence is extended to the inhomogeneous case of a turbulent channel flow. The inhomogeneity contributes to the cluster formation in addition to clustering in homogeneous turbulence. A space-dependent rate for the creation of inhomogeneous particle concentration is derived in terms of local statistics of turbulence. We provide the formula for the pair-correlation function of concentration that factorizes in product of time and space-dependent average concentrations and time-independent factor of clustering that obeys a power-law in the distance between the points. This power-law characterizes inhomogeneous multifractality of the particle distribution. A unique demonstration and quantification of the combined effects of turbophoresis and fractal clustering in a direct numerical simulation of particle motion in a turbulent channel flow is performed according to the presented theory. The strongest contribution to clustering coming from the inhomogeneity of the flow occurs in the transitional region between viscous sublayer and the buffer layer. Further the ratio of homogeneous and inhomogeneous term depends on the wall distance. The inhomogeneous terms may significantly increase the preferential concentration of inertial particles, thus the overall degree of clustering in inhomogeneous turbulence is potentially stronger compared to particles with the same inertia in purely homogeneous turbulence.\",\"bibtype\":\"article\",\"author\":\"Schmidt, Lukas and Fouxon, Itzhak and Ditlevsen, Peter and Holzner, Markus\",\"bibtex\":\"@article{\\n title = {Inhomogeneous preferential concentration of inertial particles in turbulent channel flow},\\n type = {article},\\n year = {2017},\\n websites = {http://arxiv.org/abs/1702.01438},\\n month = {4},\\n id = {969b0689-e176-3ccf-97c1-524f2b1d503b},\\n created = {2021-04-09T15:24:25.148Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:25.148Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Turbophoresis leading to preferential concentration of inertial particles in regions of low turbulent diffusivity is a unique feature of inhomogeneous turbulent flows, such as free shear flows or wall-bounded flows. In this work, the theory for clustering of weakly inertial particles in homogeneous turbulence is extended to the inhomogeneous case of a turbulent channel flow. The inhomogeneity contributes to the cluster formation in addition to clustering in homogeneous turbulence. A space-dependent rate for the creation of inhomogeneous particle concentration is derived in terms of local statistics of turbulence. We provide the formula for the pair-correlation function of concentration that factorizes in product of time and space-dependent average concentrations and time-independent factor of clustering that obeys a power-law in the distance between the points. This power-law characterizes inhomogeneous multifractality of the particle distribution. A unique demonstration and quantification of the combined effects of turbophoresis and fractal clustering in a direct numerical simulation of particle motion in a turbulent channel flow is performed according to the presented theory. The strongest contribution to clustering coming from the inhomogeneity of the flow occurs in the transitional region between viscous sublayer and the buffer layer. Further the ratio of homogeneous and inhomogeneous term depends on the wall distance. The inhomogeneous terms may significantly increase the preferential concentration of inertial particles, thus the overall degree of clustering in inhomogeneous turbulence is potentially stronger compared to particles with the same inertia in purely homogeneous turbulence.},\\n bibtype = {article},\\n author = {Schmidt, Lukas and Fouxon, Itzhak and Ditlevsen, Peter and Holzner, Markus}\\n}\",\"author_short\":[\"Schmidt,  L.\",\"Fouxon,  I.\",\"Ditlevsen,  P.\",\"Holzner,  M.\"],\"urls\":{\"Website\":\"http://arxiv.org/abs/1702.01438\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"turbulence modelling,turbulence simulation,turbulent flows\",\"pages\":\"80-114\",\"volume\":\"837\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"7ec7ca23-80fc-34ff-a1d2-9fbfa4fdf7c8\",\"created\":\"2021-04-09T15:24:25.619Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:25.619Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The detailed dynamics of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modelling challenge, because many micro-physical processes such as deformation of aggregates, drops, bubbles and polymers dynamics depend strongly on the velocity gradient tensor, which is dominated by the turbulence structure in the viscous range. In this paper, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with coarse-grained fluid simulations to recover small-scale physics without resorting to direct numerical simulations (DNS). The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modelling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out and results are again compared to DNS results. Results illustrate the ability of the proposed model to predict the influence of small-scale turbulence on droplet micro-physics in the context of LES.\",\"bibtype\":\"article\",\"author\":\"Johnson, Perry L and Meneveau, Charles\",\"doi\":\"10.1017/jfm.2017.838\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence},\\n type = {article},\\n year = {2018},\\n keywords = {turbulence modelling,turbulence simulation,turbulent flows},\\n pages = {80-114},\\n volume = {837},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {7ec7ca23-80fc-34ff-a1d2-9fbfa4fdf7c8},\\n created = {2021-04-09T15:24:25.619Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:25.619Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The detailed dynamics of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modelling challenge, because many micro-physical processes such as deformation of aggregates, drops, bubbles and polymers dynamics depend strongly on the velocity gradient tensor, which is dominated by the turbulence structure in the viscous range. In this paper, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with coarse-grained fluid simulations to recover small-scale physics without resorting to direct numerical simulations (DNS). The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modelling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out and results are again compared to DNS results. Results illustrate the ability of the proposed model to predict the influence of small-scale turbulence on droplet micro-physics in the context of LES.},\\n bibtype = {article},\\n author = {Johnson, Perry L and Meneveau, Charles},\\n doi = {10.1017/jfm.2017.838},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Johnson,  P., L.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018\",\"role\":\"author\",\"keyword\":[\"turbulence modelling\",\"turbulence simulation\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Channel,Mixing Length,Pipe,Turbulent Flow\",\"pages\":\"677-692\",\"volume\":\"06\",\"websites\":\"http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061\",\"month\":\"4\",\"publisher\":\"Scientific Research Publishing\",\"id\":\"15314fa1-afcd-3437-82f0-3af0189ff9a2\",\"created\":\"2021-04-09T15:24:26.097Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:26.097Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This research used the common decomposition of the velocity and pressure in an average part and a fluctuating part, for high Reynolds number, of the Navier-Stokes equation, which leads to the classic problem of turbulent closure. The Prandtl’s mixing length model, based on the Boussinesq hypothesis and traditionally used for free shear flows, was chosen and adapted for internal flows to solve the closure problem. For channel flows, Johann Nikuradse proposed a model for the Prandtl mixing length. In the present paper, which has an academic character, the authors made a return to the model of the mixing length of Prandtl and the model of Nikuradse, to solve turbulent flows inside a plane channel. It was possible to develop an ordinary differential model for the velocity in the direction of the flow whose solution occurs computationally in a simple but extremely accurate way when compared with Direct Numerical Simulation databases. For the viscous stress on the wall, it was possible to determine the exact mathematical solution of the ordinary differential equation. It is a model of great academic value and even to be used as reference for verification of computational codes destined to the solution of complete numerical and computational models.\",\"bibtype\":\"article\",\"author\":\"Antonialli, Luigi A and Silveira-Neto, Aristeu and Mecânica, Faculdade De Engenharia and Uberlândia, Universidade Federal De and Gerais, Minas\",\"doi\":\"10.4236/jamp.2018.64061\",\"journal\":\"Journal of Applied Mathematics and Physics\",\"number\":\"04\",\"bibtex\":\"@article{\\n title = {Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model},\\n type = {article},\\n year = {2018},\\n keywords = {Channel,Mixing Length,Pipe,Turbulent Flow},\\n pages = {677-692},\\n volume = {06},\\n websites = {http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061},\\n month = {4},\\n publisher = {Scientific Research Publishing},\\n id = {15314fa1-afcd-3437-82f0-3af0189ff9a2},\\n created = {2021-04-09T15:24:26.097Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:26.097Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This research used the common decomposition of the velocity and pressure in an average part and a fluctuating part, for high Reynolds number, of the Navier-Stokes equation, which leads to the classic problem of turbulent closure. The Prandtl’s mixing length model, based on the Boussinesq hypothesis and traditionally used for free shear flows, was chosen and adapted for internal flows to solve the closure problem. For channel flows, Johann Nikuradse proposed a model for the Prandtl mixing length. In the present paper, which has an academic character, the authors made a return to the model of the mixing length of Prandtl and the model of Nikuradse, to solve turbulent flows inside a plane channel. It was possible to develop an ordinary differential model for the velocity in the direction of the flow whose solution occurs computationally in a simple but extremely accurate way when compared with Direct Numerical Simulation databases. For the viscous stress on the wall, it was possible to determine the exact mathematical solution of the ordinary differential equation. It is a model of great academic value and even to be used as reference for verification of computational codes destined to the solution of complete numerical and computational models.},\\n bibtype = {article},\\n author = {Antonialli, Luigi A and Silveira-Neto, Aristeu and Mecânica, Faculdade De Engenharia and Uberlândia, Universidade Federal De and Gerais, Minas},\\n doi = {10.4236/jamp.2018.64061},\\n journal = {Journal of Applied Mathematics and Physics},\\n number = {04}\\n}\",\"author_short\":[\"Antonialli,  L., A.\",\"Silveira-Neto,  A.\",\"Mecânica,  F., D., E.\",\"Uberlândia,  U., F., D.\",\"Gerais,  M.\"],\"urls\":{\"Website\":\"http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018\",\"role\":\"author\",\"keyword\":[\"Channel\",\"Mixing Length\",\"Pipe\",\"Turbulent Flow\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A new two-scale model for large eddy simulation of wall-bounded flows\",\"type\":\"misc\",\"year\":\"2010\",\"source\":\"Progress in Aerospace Sciences\",\"keywords\":\"Large eddy simulation,Near-wall modeling,Two-scale model,Wall-bounded flows\",\"pages\":\"28-45\",\"volume\":\"46\",\"issue\":\"1\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0376042109000335\",\"month\":\"4\",\"publisher\":\"Pergamon\",\"id\":\"4ccb1c94-15b2-3ba4-bb44-eb3f823029b8\",\"created\":\"2021-04-09T15:24:26.762Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:26.762Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"generic\",\"private_publication\":false,\"abstract\":\"A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS-LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS-LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS-LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS-LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number. © 2009 Elsevier Ltd. All rights reserved.\",\"bibtype\":\"misc\",\"author\":\"Gungor, Ayse Gul and Menon, Suresh\",\"doi\":\"10.1016/j.paerosci.2009.10.001\",\"bibtex\":\"@misc{\\n title = {A new two-scale model for large eddy simulation of wall-bounded flows},\\n type = {misc},\\n year = {2010},\\n source = {Progress in Aerospace Sciences},\\n keywords = {Large eddy simulation,Near-wall modeling,Two-scale model,Wall-bounded flows},\\n pages = {28-45},\\n volume = {46},\\n issue = {1},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0376042109000335},\\n month = {4},\\n publisher = {Pergamon},\\n id = {4ccb1c94-15b2-3ba4-bb44-eb3f823029b8},\\n created = {2021-04-09T15:24:26.762Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:26.762Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {generic},\\n private_publication = {false},\\n abstract = {A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS-LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS-LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS-LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS-LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number. © 2009 Elsevier Ltd. All rights reserved.},\\n bibtype = {misc},\\n author = {Gungor, Ayse Gul and Menon, Suresh},\\n doi = {10.1016/j.paerosci.2009.10.001}\\n}\",\"author_short\":[\"Gungor,  A., G.\",\"Menon,  S.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0376042109000335\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010\",\"role\":\"author\",\"keyword\":[\"Large eddy simulation\",\"Near-wall modeling\",\"Two-scale model\",\"Wall-bounded flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":1,\"html\":\"\"},{\"title\":\"Fluid particle dynamics and the non-local origin of the Reynolds shear stress\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"turbulence modelling,turbulence theory,turbulent flows\",\"pages\":\"520-551\",\"volume\":\"847\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"42c6b162-4fe6-3fc0-897e-a0b8228970c7\",\"created\":\"2021-04-09T15:24:27.317Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:27.317Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The causative factors leading to the Reynolds shear stress distribution in turbulent channel flow are analysed via a backward particle path analysis. It is found that the classical displacement transport mechanism, by which changes in the mean velocity field over a mixing time correlate with the wall-normal velocity, is the dominant source of Reynolds shear stress. Approximately 20 % of channel flow at any given time contains fluid motions that contribute to displacement transport. Much rarer events provide a small but non-negligible contribution to the Reynolds shear stress due to fluid particle accelerations and long-lived correlations deriving from structural features of the near-wall flow. The Reynolds shear stress in channel flow is shown to be a non-local phenomenon that is not conducive to description via a local model and particularly one depending directly on the local mean velocity gradient.\",\"bibtype\":\"article\",\"author\":\"Bernard, Peter S and Erinin, Martin A\",\"doi\":\"10.1017/jfm.2018.333\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Fluid particle dynamics and the non-local origin of the Reynolds shear stress},\\n type = {article},\\n year = {2018},\\n keywords = {turbulence modelling,turbulence theory,turbulent flows},\\n pages = {520-551},\\n volume = {847},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {42c6b162-4fe6-3fc0-897e-a0b8228970c7},\\n created = {2021-04-09T15:24:27.317Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:27.317Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The causative factors leading to the Reynolds shear stress distribution in turbulent channel flow are analysed via a backward particle path analysis. It is found that the classical displacement transport mechanism, by which changes in the mean velocity field over a mixing time correlate with the wall-normal velocity, is the dominant source of Reynolds shear stress. Approximately 20 % of channel flow at any given time contains fluid motions that contribute to displacement transport. Much rarer events provide a small but non-negligible contribution to the Reynolds shear stress due to fluid particle accelerations and long-lived correlations deriving from structural features of the near-wall flow. The Reynolds shear stress in channel flow is shown to be a non-local phenomenon that is not conducive to description via a local model and particularly one depending directly on the local mean velocity gradient.},\\n bibtype = {article},\\n author = {Bernard, Peter S and Erinin, Martin A},\\n doi = {10.1017/jfm.2018.333},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Bernard,  P., S.\",\"Erinin,  M., A.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018\",\"role\":\"author\",\"keyword\":[\"turbulence modelling\",\"turbulence theory\",\"turbulent flows\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"POD-based background removal for particle image velocimetry\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"PIV image pre-processing,POD decomposition of video sequences,Reduced Order Modeling (ROM)\",\"pages\":\"181-192\",\"volume\":\"80\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0894177716302266\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"ae00564d-5c14-3b61-bdab-99f9cbbc9812\",\"created\":\"2021-04-09T15:24:27.798Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:27.798Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.\",\"bibtype\":\"article\",\"author\":\"Mendez, M A and Raiola, M and Masullo, A and Discetti, S and Ianiro, A and Theunissen, R and Buchlin, J M\",\"doi\":\"10.1016/j.expthermflusci.2016.08.021\",\"journal\":\"Experimental Thermal and Fluid Science\",\"bibtex\":\"@article{\\n title = {POD-based background removal for particle image velocimetry},\\n type = {article},\\n year = {2017},\\n keywords = {PIV image pre-processing,POD decomposition of video sequences,Reduced Order Modeling (ROM)},\\n pages = {181-192},\\n volume = {80},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177716302266},\\n month = {4},\\n publisher = {Elsevier},\\n id = {ae00564d-5c14-3b61-bdab-99f9cbbc9812},\\n created = {2021-04-09T15:24:27.798Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:27.798Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.},\\n bibtype = {article},\\n author = {Mendez, M A and Raiola, M and Masullo, A and Discetti, S and Ianiro, A and Theunissen, R and Buchlin, J M},\\n doi = {10.1016/j.expthermflusci.2016.08.021},\\n journal = {Experimental Thermal and Fluid Science}\\n}\",\"author_short\":[\"Mendez,  M., A.\",\"Raiola,  M.\",\"Masullo,  A.\",\"Discetti,  S.\",\"Ianiro,  A.\",\"Theunissen,  R.\",\"Buchlin,  J., M.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0894177716302266\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017\",\"role\":\"author\",\"keyword\":[\"PIV image pre-processing\",\"POD decomposition of video sequences\",\"Reduced Order Modeling (ROM)\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":4,\"html\":\"\"},{\"title\":\"Long-range μPIV to resolve the small scales in a jet at high Reynolds number\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"High Reynolds number,Long-range μPIV,Small scales\",\"pages\":\"1-15\",\"volume\":\"55\",\"websites\":\"http://link.springer.com/10.1007/s00348-014-1812-7\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"7ec67954-6936-3b40-80b4-1bcddac0c0ad\",\"created\":\"2021-04-09T15:24:28.325Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:28.325Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a self- similar round jet at high Reynolds numbers (Rek ? 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and kci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vor- ticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissi- pation tend to organize in the form of sheets with a char- acteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of long- range lPIV for characterizing turbulent flow structures at high Reynolds number. D.\",\"bibtype\":\"article\",\"author\":\"Fiscaletti, D and Westerweel, J and Elsinga, G E\",\"doi\":\"10.1007/s00348-014-1812-7\",\"journal\":\"Experiments in Fluids\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Long-range μPIV to resolve the small scales in a jet at high Reynolds number},\\n type = {article},\\n year = {2014},\\n keywords = {High Reynolds number,Long-range μPIV,Small scales},\\n pages = {1-15},\\n volume = {55},\\n websites = {http://link.springer.com/10.1007/s00348-014-1812-7},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {7ec67954-6936-3b40-80b4-1bcddac0c0ad},\\n created = {2021-04-09T15:24:28.325Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:28.325Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a self- similar round jet at high Reynolds numbers (Rek ? 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and kci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vor- ticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissi- pation tend to organize in the form of sheets with a char- acteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of long- range lPIV for characterizing turbulent flow structures at high Reynolds number. D.},\\n bibtype = {article},\\n author = {Fiscaletti, D and Westerweel, J and Elsinga, G E},\\n doi = {10.1007/s00348-014-1812-7},\\n journal = {Experiments in Fluids},\\n number = {9}\\n}\",\"author_short\":[\"Fiscaletti,  D.\",\"Westerweel,  J.\",\"Elsinga,  G., E.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-014-1812-7\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014\",\"role\":\"author\",\"keyword\":[\"High Reynolds number\",\"Long-range μPIV\",\"Small scales\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"68P30,94A24,big data,data compression,data reduction\",\"pages\":\"A2146-A2171\",\"volume\":\"41\",\"websites\":\"https://epubs.siam.org/doi/10.1137/18M1208885\",\"month\":\"4\",\"publisher\":\"Society for Industrial and Applied Mathematics\",\"id\":\"c4627576-776b-3e42-afb9-47c6f4432697\",\"created\":\"2021-04-09T15:24:28.816Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:28.816Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may ...\",\"bibtype\":\"article\",\"author\":\"Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott\",\"doi\":\"10.1137/18M1208885\",\"journal\":\"SIAM Journal on Scientific Computing\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities},\\n type = {article},\\n year = {2019},\\n keywords = {68P30,94A24,big data,data compression,data reduction},\\n pages = {A2146-A2171},\\n volume = {41},\\n websites = {https://epubs.siam.org/doi/10.1137/18M1208885},\\n month = {4},\\n publisher = {Society for Industrial and Applied Mathematics},\\n id = {c4627576-776b-3e42-afb9-47c6f4432697},\\n created = {2021-04-09T15:24:28.816Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:28.816Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may ...},\\n bibtype = {article},\\n author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},\\n doi = {10.1137/18M1208885},\\n journal = {SIAM Journal on Scientific Computing},\\n number = {4}\\n}\",\"author_short\":[\"Ainsworth,  M.\",\"Tugluk,  O.\",\"Whitney,  B.\",\"Klasky,  S.\"],\"urls\":{\"Website\":\"https://epubs.siam.org/doi/10.1137/18M1208885\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019\",\"role\":\"author\",\"keyword\":[\"68P30\",\"94A24\",\"big data\",\"data compression\",\"data reduction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"High Spatial Resolution 3D Fluid Velocimetry by Tomographic Particle Flow 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{https://arc.aiaa.org/doi/10.2514/6.2019-0269},\\n month = {4},\\n publisher = {American Institute of Aeronautics and Astronautics},\\n id = {7092cfa0-40fc-3f5a-9dc4-623b16b65db8},\\n created = {2021-04-09T15:24:29.312Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:29.312Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Kumashiro, Keishi and Steinberg, Adam M and Yano, Masayuki},\\n doi = {10.2514/6.2019-0269},\\n booktitle = {AIAA Scitech 2019 Forum}\\n}\",\"author_short\":[\"Kumashiro,  K.\",\"Steinberg,  A., M.\",\"Yano,  M.\"],\"urls\":{\"Website\":\"https://arc.aiaa.org/doi/10.2514/6.2019-0269\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Hypothesis Testing For Nonlinear Phenomena In The Geosciences Using Synthetic, Surrogate Data\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Fourier transform,chaos,gradual reconstruction,nonlinearity,surrogate data,wavelets\",\"pages\":\"2018EA000435\",\"volume\":\"6\",\"websites\":\"https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435\",\"month\":\"4\",\"publisher\":\"John Wiley & Sons, 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& Sons, Ltd},\\n id = {e44a6f1f-eb36-366b-aae3-126fdaaf70f8},\\n created = {2021-04-09T15:24:29.792Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:29.792Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Keylock, C J},\\n doi = {10.1029/2018EA000435},\\n journal = {Earth and Space Science},\\n number = {1}\\n}\",\"author_short\":[\"Keylock,  C., J.\"],\"urls\":{\"Website\":\"https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018\",\"role\":\"author\",\"keyword\":[\"Fourier transform\",\"chaos\",\"gradual reconstruction\",\"nonlinearity\",\"surrogate data\",\"wavelets\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Expanding the Q-R space to three dimensions\",\"type\":\"article\",\"year\":\"2009\",\"keywords\":\"Dynamics,Isotropic,Theory\",\"pages\":\"497-507\",\"volume\":\"641\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112009991947\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"55fd8e33-1071-34c1-9965-1831405aefe6\",\"created\":\"2021-04-09T15:24:30.382Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:30.382Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The two-dimensional space spanned by the velocity gradient invariants Q and R is expanded to three dimensions by the decomposition of R into its strain production −1/3sijsjkski and enstrophy production 1/4ωiωjsij terms. The Q; R space is a planar projection of the new three-dimensional representation. In the Q; −sss; ωωs space the Lagrangian evolution of the velocity gradient tensor Aij is studied via conditional mean trajectories (CMTs) as introduced by Martín et al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence of Reλ ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to the Q–R plane. The relatively weak cyclic evolution in the Q–R space is thus only a projection of a much stronger cycle in the Q; −sss; ωωs space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian of Aij, on the other hand, seems the main responsible for intermittently alternating between low and high intensity Aij states.\",\"bibtype\":\"article\",\"author\":\"Lthi, Beat and Holzner, Markus and Tsinober, Arkady\",\"doi\":\"10.1017/S0022112009991947\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Expanding the Q-R space to three dimensions},\\n type = {article},\\n year = {2009},\\n keywords = {Dynamics,Isotropic,Theory},\\n pages = {497-507},\\n volume = {641},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112009991947},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {55fd8e33-1071-34c1-9965-1831405aefe6},\\n created = {2021-04-09T15:24:30.382Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:30.382Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The two-dimensional space spanned by the velocity gradient invariants Q and R is expanded to three dimensions by the decomposition of R into its strain production −1/3sijsjkski and enstrophy production 1/4ωiωjsij terms. The Q; R space is a planar projection of the new three-dimensional representation. In the Q; −sss; ωωs space the Lagrangian evolution of the velocity gradient tensor Aij is studied via conditional mean trajectories (CMTs) as introduced by Martín et al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence of Reλ ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to the Q–R plane. The relatively weak cyclic evolution in the Q–R space is thus only a projection of a much stronger cycle in the Q; −sss; ωωs space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian of Aij, on the other hand, seems the main responsible for intermittently alternating between low and high intensity Aij states.},\\n bibtype = {article},\\n author = {Lthi, Beat and Holzner, Markus and Tsinober, Arkady},\\n doi = {10.1017/S0022112009991947},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Lthi,  B.\",\"Holzner,  M.\",\"Tsinober,  A.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112009991947\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009\",\"role\":\"author\",\"keyword\":[\"Dynamics\",\"Isotropic\",\"Theory\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Asymptotic results for backwards two-particle dispersion in a turbulent flow\",\"type\":\"article\",\"year\":\"2014\",\"pages\":\"41003\",\"volume\":\"89\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.89.041003\",\"month\":\"4\",\"id\":\"c0be1397-382a-3ab4-a087-8d8134ed9ee6\",\"created\":\"2021-04-09T15:24:30.893Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:30.893Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We derive an exact equation governing two-particle backwards mean-squared dispersion for both deterministic and stochastic tracer particles in turbulent flows. For the deterministic trajectories, we probe the consequences of our formula for short times and arrive at approximate expressions for the mean-squared dispersion which involve second order structure functions of the velocity and acceleration fields. For the stochastic trajectories, we analytically compute an exact t^3 contribution to the squared separation of stochastic paths. We argue that this contribution appears also for deterministic paths at long times and present direct numerical simulation results for incompressible Navier-Stokes flows to support this claim. We also numerically compute the probability distribution of particle separations for the deterministic paths and the stochastic paths and show their strong self-similar nature.\",\"bibtype\":\"article\",\"author\":\"Benveniste, Damien and Drivas, Theodore D\",\"doi\":\"10.1103/PhysRevE.89.041003\",\"journal\":\"Physical Review E\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Asymptotic results for backwards two-particle dispersion in a turbulent flow},\\n type = {article},\\n year = {2014},\\n pages = {41003},\\n volume = {89},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.89.041003},\\n month = {4},\\n id = {c0be1397-382a-3ab4-a087-8d8134ed9ee6},\\n created = {2021-04-09T15:24:30.893Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:30.893Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We derive an exact equation governing two-particle backwards mean-squared dispersion for both deterministic and stochastic tracer particles in turbulent flows. For the deterministic trajectories, we probe the consequences of our formula for short times and arrive at approximate expressions for the mean-squared dispersion which involve second order structure functions of the velocity and acceleration fields. For the stochastic trajectories, we analytically compute an exact t^3 contribution to the squared separation of stochastic paths. We argue that this contribution appears also for deterministic paths at long times and present direct numerical simulation results for incompressible Navier-Stokes flows to support this claim. We also numerically compute the probability distribution of particle separations for the deterministic paths and the stochastic paths and show their strong self-similar nature.},\\n bibtype = {article},\\n author = {Benveniste, Damien and Drivas, Theodore D},\\n doi = {10.1103/PhysRevE.89.041003},\\n journal = {Physical Review E},\\n number = {4}\\n}\",\"author_short\":[\"Benveniste,  D.\",\"Drivas,  T., D.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.89.041003\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database\",\"type\":\"article\",\"year\":\"2015\",\"pages\":\"1-11\",\"websites\":\"http://arc.aiaa.org/doi/10.2514/6.2016-3403\",\"month\":\"4\",\"publisher\":\"American Institute of Aeronautics and Astronautics\",\"id\":\"719dacb2-6fd9-3d09-a4d7-a80d14f4bac6\",\"created\":\"2021-04-09T15:24:31.394Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:31.394Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Liu, Xiaofeng and Siddle-mitchel, Seth and Rybarczyk, Rachel and Katz, Joseph\",\"doi\":\"10.2514/6.2016-3403\",\"journal\":\"32nd AIAA Aerodynamic Measurement Technology and Ground Testing Conference\",\"bibtex\":\"@article{\\n title = {Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database},\\n type = {article},\\n year = {2015},\\n pages = {1-11},\\n websites = {http://arc.aiaa.org/doi/10.2514/6.2016-3403},\\n month = {4},\\n publisher = {American Institute of Aeronautics and Astronautics},\\n id = {719dacb2-6fd9-3d09-a4d7-a80d14f4bac6},\\n created = {2021-04-09T15:24:31.394Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:31.394Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Liu, Xiaofeng and Siddle-mitchel, Seth and Rybarczyk, Rachel and Katz, Joseph},\\n doi = {10.2514/6.2016-3403},\\n journal = {32nd AIAA Aerodynamic Measurement Technology and Ground Testing Conference}\\n}\",\"author_short\":[\"Liu,  X.\",\"Siddle-mitchel,  S.\",\"Rybarczyk,  R.\",\"Katz,  J.\"],\"urls\":{\"Website\":\"http://arc.aiaa.org/doi/10.2514/6.2016-3403\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"High-End Volume Visualization\",\"type\":\"misc\",\"year\":\"2018\",\"pages\":\"135\",\"websites\":\"https://search.proquest.com/docview/2133012476\",\"institution\":\"University of California, Davis\",\"id\":\"e72c3b4c-0dd6-3e15-87f9-c049e8ff0df1\",\"created\":\"2021-04-09T15:24:31.948Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:31.948Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"thesis\",\"private_publication\":false,\"bibtype\":\"misc\",\"author\":\"Shih, Min\",\"bibtex\":\"@misc{\\n title = {High-End Volume Visualization},\\n type = {misc},\\n year = {2018},\\n pages = {135},\\n websites = {https://search.proquest.com/docview/2133012476},\\n institution = {University of California, Davis},\\n id = {e72c3b4c-0dd6-3e15-87f9-c049e8ff0df1},\\n created = {2021-04-09T15:24:31.948Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:31.948Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {thesis},\\n private_publication = {false},\\n bibtype = {misc},\\n author = {Shih, Min}\\n}\",\"author_short\":[\"Shih,  M.\"],\"urls\":{\"Website\":\"https://search.proquest.com/docview/2133012476\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"shih-highendvolumevisualization-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"132138\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573\",\"month\":\"4\",\"publisher\":\"North-Holland\",\"id\":\"b9e7ee8b-2fc2-36aa-9dba-abcc4c501d46\",\"created\":\"2021-04-09T15:24:32.670Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:32.670Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We are concerned with the inviscid limit of the Navier–Stokes equations to the Euler equations for compressible fluids in R3. Motivated by the Kolmogorov hypothesis (1941) for incompressible flow, we introduce a Kolmogorov-type hypothesis for barotropic flows, in which the density and the sonic speed normally vary significantly. We then observe that the compressible Kolmogorov-type hypothesis implies the uniform boundedness of some fractional derivatives of the weighted velocity and sonic speed in the space variables in L2, which is independent of the viscosity coefficient μ>0. It is shown that this key observation yields the equicontinuity in both space and time of the density in Lγ and the momentum in L2, as well as the uniform bound of the density in Lq1 and the velocity in Lq2 for some fixed q1>γ and q2>2, independent of μ>0, where γ>1 is the adiabatic exponent. These results lead to the strong convergence of solutions of the Navier–Stokes equations to a solution of the Euler equations for barotropic fluids in R3. Not only do we offer a framework for mathematical existence theories, but also we offer a framework for the interpretation of numerical solutions through the identification of a function space in which convergence should take place, with the bounds that are independent of μ>0, that is in the high Reynolds number limit.\",\"bibtype\":\"article\",\"author\":\"Chen, Gui-Qiang G and Glimm, James\",\"doi\":\"10.1016/j.physd.2019.06.004\",\"journal\":\"Physica D: Nonlinear Phenomena\",\"bibtex\":\"@article{\\n title = {Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3},\\n type = {article},\\n year = {2019},\\n pages = {132138},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573},\\n month = {4},\\n publisher = {North-Holland},\\n id = {b9e7ee8b-2fc2-36aa-9dba-abcc4c501d46},\\n created = {2021-04-09T15:24:32.670Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:32.670Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We are concerned with the inviscid limit of the Navier–Stokes equations to the Euler equations for compressible fluids in R3. Motivated by the Kolmogorov hypothesis (1941) for incompressible flow, we introduce a Kolmogorov-type hypothesis for barotropic flows, in which the density and the sonic speed normally vary significantly. We then observe that the compressible Kolmogorov-type hypothesis implies the uniform boundedness of some fractional derivatives of the weighted velocity and sonic speed in the space variables in L2, which is independent of the viscosity coefficient μ>0. It is shown that this key observation yields the equicontinuity in both space and time of the density in Lγ and the momentum in L2, as well as the uniform bound of the density in Lq1 and the velocity in Lq2 for some fixed q1>γ and q2>2, independent of μ>0, where γ>1 is the adiabatic exponent. These results lead to the strong convergence of solutions of the Navier–Stokes equations to a solution of the Euler equations for barotropic fluids in R3. Not only do we offer a framework for mathematical existence theories, but also we offer a framework for the interpretation of numerical solutions through the identification of a function space in which convergence should take place, with the bounds that are independent of μ>0, that is in the high Reynolds number limit.},\\n bibtype = {article},\\n author = {Chen, Gui-Qiang G and Glimm, James},\\n doi = {10.1016/j.physd.2019.06.004},\\n journal = {Physica D: Nonlinear Phenomena}\\n}\",\"author_short\":[\"Chen,  G., G.\",\"Glimm,  J.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"33301\",\"volume\":\"10\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5004710\",\"month\":\"4\",\"publisher\":\"AIP Publishing LLC\",\"id\":\"6cce001b-5f00-397b-b895-e112dad1bbb1\",\"created\":\"2021-04-09T15:24:33.156Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:33.156Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Large-eddy simulation (LES) of a wind turbine under uniform inflow is performed using an actuator line model (ALM). Predictions from four LES research codes from the wind energy community are compa...\",\"bibtype\":\"article\",\"author\":\"Martínez-Tossas, Luis A and Churchfield, Matthew J and Yilmaz, Ali Emre and Sarlak, Hamid and Johnson, Perry L and Sørensen, Jens N and Meyers, Johan and Meneveau, Charles\",\"doi\":\"10.1063/1.5004710\",\"journal\":\"Journal of Renewable and Sustainable Energy\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling},\\n type = {article},\\n year = {2018},\\n pages = {33301},\\n volume = {10},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5004710},\\n month = {4},\\n publisher = {AIP Publishing LLC},\\n id = {6cce001b-5f00-397b-b895-e112dad1bbb1},\\n created = {2021-04-09T15:24:33.156Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:33.156Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Large-eddy simulation (LES) of a wind turbine under uniform inflow is performed using an actuator line model (ALM). Predictions from four LES research codes from the wind energy community are compa...},\\n bibtype = {article},\\n author = {Martínez-Tossas, Luis A and Churchfield, Matthew J and Yilmaz, Ali Emre and Sarlak, Hamid and Johnson, Perry L and Sørensen, Jens N and Meyers, Johan and Meneveau, Charles},\\n doi = {10.1063/1.5004710},\\n journal = {Journal of Renewable and Sustainable Energy},\\n number = {3}\\n}\",\"author_short\":[\"Martínez-Tossas,  L., A.\",\"Churchfield,  M., J.\",\"Yilmaz,  A., E.\",\"Sarlak,  H.\",\"Johnson,  P., L.\",\"Sørensen,  J., N.\",\"Meyers,  J.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5004710\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Accurate estimate of turbulent dissipation rate using PIV data\",\"type\":\"article\",\"year\":\"2013\",\"keywords\":\"Energy spectra,PIV,Structure function,Turbulent dissipation rate\",\"pages\":\"662-672\",\"volume\":\"44\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"eb9c0ce8-55c3-3c88-a7b6-067038618599\",\"created\":\"2021-04-09T15:24:33.718Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:33.718Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the -5/3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes. © 2012 Elsevier Inc.\",\"bibtype\":\"article\",\"author\":\"Xu, Duo and Chen, Jun\",\"doi\":\"10.1016/j.expthermflusci.2012.09.006\",\"journal\":\"Experimental Thermal and Fluid Science\",\"bibtex\":\"@article{\\n title = {Accurate estimate of turbulent dissipation rate using PIV data},\\n type = {article},\\n year = {2013},\\n keywords = {Energy spectra,PIV,Structure function,Turbulent dissipation rate},\\n pages = {662-672},\\n volume = {44},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464},\\n month = {4},\\n publisher = {Elsevier},\\n id = {eb9c0ce8-55c3-3c88-a7b6-067038618599},\\n created = {2021-04-09T15:24:33.718Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:33.718Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the -5/3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes. © 2012 Elsevier Inc.},\\n bibtype = {article},\\n author = {Xu, Duo and Chen, Jun},\\n doi = {10.1016/j.expthermflusci.2012.09.006},\\n journal = {Experimental Thermal and Fluid Science}\\n}\",\"author_short\":[\"Xu,  D.\",\"Chen,  J.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013\",\"role\":\"author\",\"keyword\":[\"Energy spectra\",\"PIV\",\"Structure function\",\"Turbulent dissipation rate\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Angular dynamics of a small particle in turbulence\",\"type\":\"article\",\"year\":\"2016\",\"pages\":\"204501\",\"volume\":\"117\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevLett.117.204501\",\"month\":\"4\",\"id\":\"9868f702-ead3-3e01-8357-e5578df0b81f\",\"created\":\"2021-04-09T15:24:34.259Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:34.259Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We compute the angular dynamics of a neutrally buoyant nearly spherical particle immersed in an unsteady fluid. We assume that the particle is small, that its translational slip velocity is negligible, and that unsteady and convective inertia are small perturbations. We derive an approximation for the torque on the particle that determines the first inertial corrections to Jeffery's equation. These corrections arise as a consequence of local vortex stretching, and can be substantial in turbulence where local vortex stretching is strong and closely linked to the irreversibility of turbulence.\",\"bibtype\":\"article\",\"author\":\"Candelier, F and Einarsson, J and Mehlig, B\",\"doi\":\"10.1103/PhysRevLett.117.204501\",\"journal\":\"Physical Review Letters\",\"number\":\"20\",\"bibtex\":\"@article{\\n title = {Angular dynamics of a small particle in turbulence},\\n type = {article},\\n year = {2016},\\n pages = {204501},\\n volume = {117},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.117.204501},\\n month = {4},\\n id = {9868f702-ead3-3e01-8357-e5578df0b81f},\\n created = {2021-04-09T15:24:34.259Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:34.259Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We compute the angular dynamics of a neutrally buoyant nearly spherical particle immersed in an unsteady fluid. We assume that the particle is small, that its translational slip velocity is negligible, and that unsteady and convective inertia are small perturbations. We derive an approximation for the torque on the particle that determines the first inertial corrections to Jeffery's equation. These corrections arise as a consequence of local vortex stretching, and can be substantial in turbulence where local vortex stretching is strong and closely linked to the irreversibility of turbulence.},\\n bibtype = {article},\\n author = {Candelier, F and Einarsson, J and Mehlig, B},\\n doi = {10.1103/PhysRevLett.117.204501},\\n journal = {Physical Review Letters},\\n number = {20}\\n}\",\"author_short\":[\"Candelier,  F.\",\"Einarsson,  J.\",\"Mehlig,  B.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevLett.117.204501\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry\",\"type\":\"article\",\"year\":\"2017\",\"pages\":\"118\",\"volume\":\"58\",\"websites\":\"http://link.springer.com/10.1007/s00348-017-2395-x\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"fb414d52-e7c1-3c6d-96c0-a6059b9dcc40\",\"created\":\"2021-04-09T15:24:34.718Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:34.718Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© 2017, The Author(s). The experimental evaluation of the topological characteristics of the turbulent flow in a ‘box’ of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.\",\"bibtype\":\"article\",\"author\":\"Lian, Huan and Soulopoulos, Nikolaos and Hardalupas, Yannis\",\"doi\":\"10.1007/s00348-017-2395-x\",\"journal\":\"Experiments in Fluids\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry},\\n type = {article},\\n year = {2017},\\n pages = {118},\\n volume = {58},\\n websites = {http://link.springer.com/10.1007/s00348-017-2395-x},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {fb414d52-e7c1-3c6d-96c0-a6059b9dcc40},\\n created = {2021-04-09T15:24:34.718Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:34.718Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© 2017, The Author(s). The experimental evaluation of the topological characteristics of the turbulent flow in a ‘box’ of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.},\\n bibtype = {article},\\n author = {Lian, Huan and Soulopoulos, Nikolaos and Hardalupas, Yannis},\\n doi = {10.1007/s00348-017-2395-x},\\n journal = {Experiments in Fluids},\\n number = {9}\\n}\",\"author_short\":[\"Lian,  H.\",\"Soulopoulos,  N.\",\"Hardalupas,  Y.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-017-2395-x\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"Adaptive mesh refinement,Atmospheric boundary layer,Direct numerical simulations,Large-eddy simulations,Turbulence\",\"pages\":\"421-443\",\"volume\":\"167\",\"websites\":\"http://link.springer.com/10.1007/s10546-018-0335-9\",\"month\":\"4\",\"publisher\":\"Springer Netherlands\",\"id\":\"4bc7706d-0fde-3429-a0b5-d729ea5cdb3f\",\"created\":\"2021-04-09T15:24:35.225Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:35.225Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"© 2018 The Author(s) We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.\",\"bibtype\":\"article\",\"author\":\"van Hooft, J Antoon and Popinet, Stéphane and van Heerwaarden, Chiel C and van der Linden, Steven J A A and de Roode, Stephan R and van de Wiel, Bas J H H\",\"doi\":\"10.1007/s10546-018-0335-9\",\"journal\":\"Boundary-Layer Meteorology\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations},\\n type = {article},\\n year = {2018},\\n keywords = {Adaptive mesh refinement,Atmospheric boundary layer,Direct numerical simulations,Large-eddy simulations,Turbulence},\\n pages = {421-443},\\n volume = {167},\\n websites = {http://link.springer.com/10.1007/s10546-018-0335-9},\\n month = {4},\\n publisher = {Springer Netherlands},\\n id = {4bc7706d-0fde-3429-a0b5-d729ea5cdb3f},\\n created = {2021-04-09T15:24:35.225Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:35.225Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {© 2018 The Author(s) We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.},\\n bibtype = {article},\\n author = {van Hooft, J Antoon and Popinet, Stéphane and van Heerwaarden, Chiel C and van der Linden, Steven J A A and de Roode, Stephan R and van de Wiel, Bas J H H},\\n doi = {10.1007/s10546-018-0335-9},\\n journal = {Boundary-Layer Meteorology},\\n number = {3}\\n}\",\"author_short\":[\"van Hooft,  J., A.\",\"Popinet,  S.\",\"van Heerwaarden,  C., C.\",\"van der Linden,  S., J., A., A.\",\"de Roode,  S., R.\",\"van de Wiel,  B., J., H., H.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s10546-018-0335-9\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018\",\"role\":\"author\",\"keyword\":[\"Adaptive mesh refinement\",\"Atmospheric boundary layer\",\"Direct numerical simulations\",\"Large-eddy simulations\",\"Turbulence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Redistribution of kinetic energy in turbulent flows\",\"type\":\"article\",\"year\":\"2014\",\"keywords\":\"Fluid dynamics,Nonlinear dynamics,Statistical physics\",\"pages\":\"41006\",\"volume\":\"4\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevX.4.041006\",\"month\":\"4\",\"id\":\"078fb0f4-b620-36e6-ab06-b4a0bbf5dce8\",\"created\":\"2021-04-09T15:24:35.860Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:35.860Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In statistically homogeneous turbulent flows, pressure forces provide the main mechanism to redistribute kinetic energy among fluid elements, without net contribution to the overall energy budget. This holds true in both two-dimensional (2D) and three-dimensional (3D) flows, which show fundamentally different physics. As we demonstrate here, pressure forces act on fluid elements very differently in these two cases. We find in numerical simulations that in 3D pressure forces strongly accelerate the fastest fluid elements, and that in 2D this effect is absent. In 3D turbulence, our findings put forward a mechanism for a possibly singular buildup of energy, and thus may shed new light on the smoothness problem of the solution of the Navier-Stokes equation in 3D.\",\"bibtype\":\"article\",\"author\":\"Pumir, Alain and Xu, Haitao and Boffetta, Guido and Falkovich, Gregory and Bodenschatz, Eberhard\",\"doi\":\"10.1103/PhysRevX.4.041006\",\"journal\":\"Physical Review X\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Redistribution of kinetic energy in turbulent flows},\\n type = {article},\\n year = {2014},\\n keywords = {Fluid dynamics,Nonlinear dynamics,Statistical physics},\\n pages = {41006},\\n volume = {4},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevX.4.041006},\\n month = {4},\\n id = {078fb0f4-b620-36e6-ab06-b4a0bbf5dce8},\\n created = {2021-04-09T15:24:35.860Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:35.860Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In statistically homogeneous turbulent flows, pressure forces provide the main mechanism to redistribute kinetic energy among fluid elements, without net contribution to the overall energy budget. This holds true in both two-dimensional (2D) and three-dimensional (3D) flows, which show fundamentally different physics. As we demonstrate here, pressure forces act on fluid elements very differently in these two cases. We find in numerical simulations that in 3D pressure forces strongly accelerate the fastest fluid elements, and that in 2D this effect is absent. In 3D turbulence, our findings put forward a mechanism for a possibly singular buildup of energy, and thus may shed new light on the smoothness problem of the solution of the Navier-Stokes equation in 3D.},\\n bibtype = {article},\\n author = {Pumir, Alain and Xu, Haitao and Boffetta, Guido and Falkovich, Gregory and Bodenschatz, Eberhard},\\n doi = {10.1103/PhysRevX.4.041006},\\n journal = {Physical Review X},\\n number = {4}\\n}\",\"author_short\":[\"Pumir,  A.\",\"Xu,  H.\",\"Boffetta,  G.\",\"Falkovich,  G.\",\"Bodenschatz,  E.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevX.4.041006\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014\",\"role\":\"author\",\"keyword\":[\"Fluid dynamics\",\"Nonlinear dynamics\",\"Statistical physics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"137\",\"volume\":\"60\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2777-3\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"1c8096ee-c7d7-33c2-a56c-6a2f7ef84968\",\"created\":\"2021-04-09T15:24:36.419Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:36.419Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Kozul, Melissa and Koothur, Vipin and Worth, Nicholas A and Dawson, James R\",\"doi\":\"10.1007/s00348-019-2777-3\",\"journal\":\"Experiments in Fluids\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows},\\n type = {article},\\n year = {2019},\\n pages = {137},\\n volume = {60},\\n websites = {http://link.springer.com/10.1007/s00348-019-2777-3},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {1c8096ee-c7d7-33c2-a56c-6a2f7ef84968},\\n created = {2021-04-09T15:24:36.419Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:36.419Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Kozul, Melissa and Koothur, Vipin and Worth, Nicholas A and Dawson, James R},\\n doi = {10.1007/s00348-019-2777-3},\\n journal = {Experiments in Fluids},\\n number = {8}\\n}\",\"author_short\":[\"Kozul,  M.\",\"Koothur,  V.\",\"Worth,  N., A.\",\"Dawson,  J., R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2777-3\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Pressure from 2D snapshot PIV\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"32\",\"volume\":\"60\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2678-5\",\"month\":\"4\",\"publisher\":\"Springer Berlin Heidelberg\",\"id\":\"ba00cf84-a72d-3998-a269-642fe5c25cf6\",\"created\":\"2021-04-09T15:24:36.935Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:36.935Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"der Kindere, J W Van and Laskari, A and Ganapathisubramani, B and de Kat, R\",\"doi\":\"10.1007/s00348-019-2678-5\",\"journal\":\"Experiments in Fluids\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Pressure from 2D snapshot PIV},\\n type = {article},\\n year = {2019},\\n pages = {32},\\n volume = {60},\\n websites = {http://link.springer.com/10.1007/s00348-019-2678-5},\\n month = {4},\\n publisher = {Springer Berlin Heidelberg},\\n id = {ba00cf84-a72d-3998-a269-642fe5c25cf6},\\n created = {2021-04-09T15:24:36.935Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:36.935Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {der Kindere, J W Van and Laskari, A and Ganapathisubramani, B and de Kat, R},\\n doi = {10.1007/s00348-019-2678-5},\\n journal = {Experiments in Fluids},\\n number = {2}\\n}\",\"author_short\":[\"der Kindere,  J., W., V.\",\"Laskari,  A.\",\"Ganapathisubramani,  B.\",\"de Kat,  R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2678-5\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Vorticity statistics and the time scales of turbulent strain\",\"type\":\"article\",\"year\":\"2013\",\"pages\":\"13005\",\"volume\":\"88\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.88.013005\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"9326f9aa-e723-3f33-8803-969549fd326b\",\"created\":\"2021-04-09T15:24:37.611Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:37.611Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of Lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual “1/s” strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.\",\"bibtype\":\"article\",\"author\":\"Moriconi, L and Pereira, R M\",\"doi\":\"10.1103/PhysRevE.88.013005\",\"journal\":\"Physical Review E\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Vorticity statistics and the time scales of turbulent strain},\\n type = {article},\\n year = {2013},\\n pages = {13005},\\n volume = {88},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.88.013005},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {9326f9aa-e723-3f33-8803-969549fd326b},\\n created = {2021-04-09T15:24:37.611Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:37.611Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of Lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual “1/s” strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.},\\n bibtype = {article},\\n author = {Moriconi, L and Pereira, R M},\\n doi = {10.1103/PhysRevE.88.013005},\\n journal = {Physical Review E},\\n number = {1}\\n}\",\"author_short\":[\"Moriconi,  L.\",\"Pereira,  R., M.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.88.013005\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Spurious noise in direct noise computation with a finite volume method for automotive applications\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"243-256\",\"volume\":\"72\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"e3f14195-dd58-3ff8-9dcc-5636fa237eeb\",\"created\":\"2021-04-09T15:24:38.065Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:38.065Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The present paper represents a study on spurious noise generated in direct noise computation using finite volume methods. Different sources of spurious noise are examined as well as the mechanism of their generation. This investigation involves two test cases. The first one consists of a turbulence box convected by a uniform flow field. This case serves to identify spurious noise sources and qualitatively evaluate their relevance. The second test case involves a single side mirror mounted on a flat plate, which serves to quantify the level of spurious noise produced and its relevance compared to physical sound generated by the flow past the mirror. Both test cases are calculated using a compressible flow solver for low Mach-number flows utilised with an IDDES approach for turbulence modelling. A new acoustic damping model which damps out acoustic waves without affecting hydrodynamic turbulent fluctuations has been implemented. Furthermore, special emphasis on refinement interfaces is given. Since no measurements are available, the results of the direct noise computation are compared to the results of a method based on Kirchhoff integral.\",\"bibtype\":\"article\",\"author\":\"Dawi, Ali H and Akkermans, Rinie A D\",\"doi\":\"10.1016/j.ijheatfluidflow.2018.06.008\",\"journal\":\"International Journal of Heat and Fluid Flow\",\"bibtex\":\"@article{\\n title = {Spurious noise in direct noise computation with a finite volume method for automotive applications},\\n type = {article},\\n year = {2018},\\n pages = {243-256},\\n volume = {72},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923},\\n month = {4},\\n publisher = {Elsevier},\\n id = {e3f14195-dd58-3ff8-9dcc-5636fa237eeb},\\n created = {2021-04-09T15:24:38.065Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:38.065Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The present paper represents a study on spurious noise generated in direct noise computation using finite volume methods. Different sources of spurious noise are examined as well as the mechanism of their generation. This investigation involves two test cases. The first one consists of a turbulence box convected by a uniform flow field. This case serves to identify spurious noise sources and qualitatively evaluate their relevance. The second test case involves a single side mirror mounted on a flat plate, which serves to quantify the level of spurious noise produced and its relevance compared to physical sound generated by the flow past the mirror. Both test cases are calculated using a compressible flow solver for low Mach-number flows utilised with an IDDES approach for turbulence modelling. A new acoustic damping model which damps out acoustic waves without affecting hydrodynamic turbulent fluctuations has been implemented. Furthermore, special emphasis on refinement interfaces is given. Since no measurements are available, the results of the direct noise computation are compared to the results of a method based on Kirchhoff integral.},\\n bibtype = {article},\\n author = {Dawi, Ali H and Akkermans, Rinie A D},\\n doi = {10.1016/j.ijheatfluidflow.2018.06.008},\\n journal = {International Journal of Heat and Fluid Flow}\\n}\",\"author_short\":[\"Dawi,  A., H.\",\"Akkermans,  R., A., D.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Detecting singular patterns in 2D vector fields using weighted Laurent polynomial\",\"type\":\"article\",\"year\":\"2012\",\"keywords\":\"Complex-valued function,Laurent polynomials,Scale- and rotation-invariance,Singular-pattern detection,Vector fields\",\"pages\":\"3912-3925\",\"volume\":\"45\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0031320312002051\",\"month\":\"4\",\"publisher\":\"Pergamon\",\"id\":\"cbfa91e7-6cad-35ed-9166-39b6d4808341\",\"created\":\"2021-04-09T15:24:38.546Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:38.546Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. © 2012 Elsevier Ltd. All rights reserved.\",\"bibtype\":\"article\",\"author\":\"Liu, Wei and Ribeiro, Eraldo\",\"doi\":\"10.1016/j.patcog.2012.04.025\",\"journal\":\"Pattern Recognition\",\"number\":\"11\",\"bibtex\":\"@article{\\n title = {Detecting singular patterns in 2D vector fields using weighted Laurent polynomial},\\n type = {article},\\n year = {2012},\\n keywords = {Complex-valued function,Laurent polynomials,Scale- and rotation-invariance,Singular-pattern detection,Vector fields},\\n pages = {3912-3925},\\n volume = {45},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0031320312002051},\\n month = {4},\\n publisher = {Pergamon},\\n id = {cbfa91e7-6cad-35ed-9166-39b6d4808341},\\n created = {2021-04-09T15:24:38.546Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:38.546Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. © 2012 Elsevier Ltd. All rights reserved.},\\n bibtype = {article},\\n author = {Liu, Wei and Ribeiro, Eraldo},\\n doi = {10.1016/j.patcog.2012.04.025},\\n journal = {Pattern Recognition},\\n number = {11}\\n}\",\"author_short\":[\"Liu,  W.\",\"Ribeiro,  E.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0031320312002051\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012\",\"role\":\"author\",\"keyword\":[\"Complex-valued function\",\"Laurent polynomials\",\"Scale- and rotation-invariance\",\"Singular-pattern detection\",\"Vector fields\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Matrix exponential-based closures for the turbulent subgrid-scale stress tensor\",\"type\":\"article\",\"year\":\"2009\",\"pages\":\"16305\",\"volume\":\"79\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevE.79.016305\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"10a7b192-a61d-398c-87e8-0b2c2e32adc1\",\"created\":\"2021-04-09T15:24:39.135Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:39.135Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Two approaches for closing the turbulence subgrid-scale stress tensor in terms of matrix exponentials are introduced and compared. The first approach is based on a formal solution of the stress transport equation in which the production terms can be integrated exactly in terms of matrix exponentials. This formal solution of the subgrid-scale stress transport equation is shown to be useful to explore special cases, such as the response to constant velocity gradient, but neglecting pressure-strain correlations and diffusion effects. The second approach is based on an Eulerian-Lagrangian change of variables, combined with the assumption of isotropy for the conditionally averaged Lagrangian velocity gradient tensor and with the recent fluid deformation approximation. It is shown that both approaches lead to the same basic closure in which the stress tensor is expressed as the matrix exponential of the resolved velocity gradient tensor multiplied by its transpose. Short-time expansions of the matrix exponentials are shown to provide an eddy-viscosity term and particular quadratic terms, and thus allow a reinterpretation of traditional eddy-viscosity and nonlinear stress closures. The basic feasibility of the matrix-exponential closure is illustrated by implementing it successfully in large eddy simulation of forced isotropic turbulence. The matrix-exponential closure employs the drastic approximation of entirely omitting the pressure-strain correlation and other nonlinear scrambling terms. But unlike eddy-viscosity closures, the matrix exponential approach provides a simple and local closure that can be derived directly from the stress transport equation with the production term, and using physically motivated assumptions about Lagrangian decorrelation and upstream isotropy.\",\"bibtype\":\"article\",\"author\":\"Li, Yi and Chevillard, Laurent and Eyink, Gregory and Meneveau, Charles\",\"doi\":\"10.1103/PhysRevE.79.016305\",\"journal\":\"Physical Review E\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Matrix exponential-based closures for the turbulent subgrid-scale stress tensor},\\n type = {article},\\n year = {2009},\\n pages = {16305},\\n volume = {79},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.79.016305},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {10a7b192-a61d-398c-87e8-0b2c2e32adc1},\\n created = {2021-04-09T15:24:39.135Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:39.135Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Two approaches for closing the turbulence subgrid-scale stress tensor in terms of matrix exponentials are introduced and compared. The first approach is based on a formal solution of the stress transport equation in which the production terms can be integrated exactly in terms of matrix exponentials. This formal solution of the subgrid-scale stress transport equation is shown to be useful to explore special cases, such as the response to constant velocity gradient, but neglecting pressure-strain correlations and diffusion effects. The second approach is based on an Eulerian-Lagrangian change of variables, combined with the assumption of isotropy for the conditionally averaged Lagrangian velocity gradient tensor and with the recent fluid deformation approximation. It is shown that both approaches lead to the same basic closure in which the stress tensor is expressed as the matrix exponential of the resolved velocity gradient tensor multiplied by its transpose. Short-time expansions of the matrix exponentials are shown to provide an eddy-viscosity term and particular quadratic terms, and thus allow a reinterpretation of traditional eddy-viscosity and nonlinear stress closures. The basic feasibility of the matrix-exponential closure is illustrated by implementing it successfully in large eddy simulation of forced isotropic turbulence. The matrix-exponential closure employs the drastic approximation of entirely omitting the pressure-strain correlation and other nonlinear scrambling terms. But unlike eddy-viscosity closures, the matrix exponential approach provides a simple and local closure that can be derived directly from the stress transport equation with the production term, and using physically motivated assumptions about Lagrangian decorrelation and upstream isotropy.},\\n bibtype = {article},\\n author = {Li, Yi and Chevillard, Laurent and Eyink, Gregory and Meneveau, Charles},\\n doi = {10.1103/PhysRevE.79.016305},\\n journal = {Physical Review E},\\n number = {1}\\n}\",\"author_short\":[\"Li,  Y.\",\"Chevillard,  L.\",\"Eyink,  G.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.79.016305\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence\",\"type\":\"article\",\"year\":\"2016\",\"keywords\":\"High-order methods,Large-Eddy simulation,Spectral Difference method\",\"pages\":\"261-280\",\"volume\":\"139\",\"websites\":\"http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512\",\"month\":\"4\",\"id\":\"eb50f798-2dbb-3002-b3d1-ac088b613ddd\",\"created\":\"2021-04-09T15:24:39.658Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:39.658Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper aims at understanding the numerical dissipation mechanisms related to the Spectral Difference (SD) method in the context of three-dimensional (3D) turbulence. The numerical dissipation stemming from the discretization of the convective terms is studied by performing inviscid computations of the transitional Taylor–Green vortex and isotropic turbulence configurations. The Taylor–Green vortex computations show that the increase in the order of accuracy restricts the numerical dissipation to smaller scales which, in turn, leads to a better representation of transitional mechanisms. However, isotropic turbulence computations using a fifth-order accuracy or above show obvious manifestations of under-resolution (such as the onset of oscillations and numerical noise), which suggests that the high-order numerical dissipation alone is unable to mimic the dissipation originating from sub-grid scales in the case freely decaying turbulence. Computations of the channel flow configuration at Reτ=1000 at typical large-eddy simulation resolutions show that under-resolved SD discretizations using a high order of accuracy (fifth and sixth) lead to an excellent prediction of the wall-friction, the velocity profiles, the turbulent structures near the wall and the energy spectra, while lower order discretizations lead to an underestimation of the wall-friction and globally a poor representation of wall-bounded turbulence. The present study emphasizes the benefit of using high-order SD discretizations for an accurate representation of turbulent phenomena (namely, transitional and wall-bounded turbulence) but also the necessity of combining this approach with dynamic large-eddy simulation models or appropriate regularization techniques which would activate only where needed to recover physically consistent results, e.g., in regions where fully developed turbulence is present.\",\"bibtype\":\"article\",\"author\":\"Chapelier, J B and Lodato, G and Jameson, A\",\"doi\":\"10.1016/j.compfluid.2016.03.006\",\"journal\":\"Computers and Fluids\",\"bibtex\":\"@article{\\n title = {A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence},\\n type = {article},\\n year = {2016},\\n keywords = {High-order methods,Large-Eddy simulation,Spectral Difference method},\\n pages = {261-280},\\n volume = {139},\\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512},\\n month = {4},\\n id = {eb50f798-2dbb-3002-b3d1-ac088b613ddd},\\n created = {2021-04-09T15:24:39.658Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:39.658Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper aims at understanding the numerical dissipation mechanisms related to the Spectral Difference (SD) method in the context of three-dimensional (3D) turbulence. The numerical dissipation stemming from the discretization of the convective terms is studied by performing inviscid computations of the transitional Taylor–Green vortex and isotropic turbulence configurations. The Taylor–Green vortex computations show that the increase in the order of accuracy restricts the numerical dissipation to smaller scales which, in turn, leads to a better representation of transitional mechanisms. However, isotropic turbulence computations using a fifth-order accuracy or above show obvious manifestations of under-resolution (such as the onset of oscillations and numerical noise), which suggests that the high-order numerical dissipation alone is unable to mimic the dissipation originating from sub-grid scales in the case freely decaying turbulence. Computations of the channel flow configuration at Reτ=1000 at typical large-eddy simulation resolutions show that under-resolved SD discretizations using a high order of accuracy (fifth and sixth) lead to an excellent prediction of the wall-friction, the velocity profiles, the turbulent structures near the wall and the energy spectra, while lower order discretizations lead to an underestimation of the wall-friction and globally a poor representation of wall-bounded turbulence. The present study emphasizes the benefit of using high-order SD discretizations for an accurate representation of turbulent phenomena (namely, transitional and wall-bounded turbulence) but also the necessity of combining this approach with dynamic large-eddy simulation models or appropriate regularization techniques which would activate only where needed to recover physically consistent results, e.g., in regions where fully developed turbulence is present.},\\n bibtype = {article},\\n author = {Chapelier, J B and Lodato, G and Jameson, A},\\n doi = {10.1016/j.compfluid.2016.03.006},\\n journal = {Computers and Fluids}\\n}\",\"author_short\":[\"Chapelier,  J., B.\",\"Lodato,  G.\",\"Jameson,  A.\"],\"urls\":{\"Website\":\"http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016\",\"role\":\"author\",\"keyword\":[\"High-order methods\",\"Large-Eddy simulation\",\"Spectral Difference method\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"44604\",\"volume\":\"3\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"ebeac5a4-3763-3b93-bf27-ee587aebb8e5\",\"created\":\"2021-04-09T15:24:40.168Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:40.168Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Danish, Mohammad and Meneveau, Charles\",\"doi\":\"10.1103/PhysRevFluids.3.044604\",\"journal\":\"Physical Review Fluids\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence},\\n type = {article},\\n year = {2018},\\n pages = {44604},\\n volume = {3},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {ebeac5a4-3763-3b93-bf27-ee587aebb8e5},\\n created = {2021-04-09T15:24:40.168Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:40.168Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Danish, Mohammad and Meneveau, Charles},\\n doi = {10.1103/PhysRevFluids.3.044604},\\n journal = {Physical Review Fluids},\\n number = {4}\\n}\",\"author_short\":[\"Danish,  M.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Nonlinear effects in buoyancy-driven variable-density turbulence\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"Navier–Stokes equations,buoyancy-driven instability,mathematical foundations\",\"pages\":\"362-377\",\"volume\":\"810\",\"websites\":\"http://www.journals.cambridge.org/abstract_S0022112016007199\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"d4f5f478-aada-3f5f-87d3-74e0200b074e\",\"created\":\"2021-04-09T15:24:40.792Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:40.792Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We consider the time dependence of a hierarchy of scaled L^2m -norms D_m,[STIX]x1D714 and D_m,[STIX]x1D703 of the vorticity [STIX]x1D74E=[STIX]x1D735 u and the density gradient [STIX]x1D735[STIX]x1D703 , where [STIX]x1D703= ([STIX]x1D70C^ /[STIX]x1D70C_0^ ) , in a buoyancy-driven turbulent flow as simulated by Livescu &amp; Ristorcelli ( J. Fluid Mech. , vol. 591, 2007, pp. 43–71). Here, [STIX]x1D70C^ (x,t) is the composition density of a mixture of two incompressible miscible fluids with fluid densities [STIX]x1D70C_2^ >[STIX]x1D70C_1^  , and [STIX]x1D70C_0^  is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the L^2 -spatial average of the density gradient [STIX]x1D735[STIX]x1D703 can reach extremely large values at intermediate times, even in flows with low Atwood number At=([STIX]x1D70C_2^ -[STIX]x1D70C_1^ )/([STIX]x1D70C_2^ +[STIX]x1D70C_1^ )=0.05 , implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient [STIX]x1D735[STIX]x1D703 might blow up in a finite time.\",\"bibtype\":\"article\",\"author\":\"Rao, P and Caulfield, C P and Gibbon, J D\",\"doi\":\"10.1017/jfm.2016.719\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Nonlinear effects in buoyancy-driven variable-density turbulence},\\n type = {article},\\n year = {2017},\\n keywords = {Navier–Stokes equations,buoyancy-driven instability,mathematical foundations},\\n pages = {362-377},\\n volume = {810},\\n websites = {http://www.journals.cambridge.org/abstract_S0022112016007199},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {d4f5f478-aada-3f5f-87d3-74e0200b074e},\\n created = {2021-04-09T15:24:40.792Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:40.792Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We consider the time dependence of a hierarchy of scaled L^2m -norms D_m,[STIX]x1D714 and D_m,[STIX]x1D703 of the vorticity [STIX]x1D74E=[STIX]x1D735 u and the density gradient [STIX]x1D735[STIX]x1D703 , where [STIX]x1D703= ([STIX]x1D70C^ /[STIX]x1D70C_0^ ) , in a buoyancy-driven turbulent flow as simulated by Livescu &amp; Ristorcelli ( J. Fluid Mech. , vol. 591, 2007, pp. 43–71). Here, [STIX]x1D70C^ (x,t) is the composition density of a mixture of two incompressible miscible fluids with fluid densities [STIX]x1D70C_2^ >[STIX]x1D70C_1^  , and [STIX]x1D70C_0^  is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the L^2 -spatial average of the density gradient [STIX]x1D735[STIX]x1D703 can reach extremely large values at intermediate times, even in flows with low Atwood number At=([STIX]x1D70C_2^ -[STIX]x1D70C_1^ )/([STIX]x1D70C_2^ +[STIX]x1D70C_1^ )=0.05 , implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient [STIX]x1D735[STIX]x1D703 might blow up in a finite time.},\\n bibtype = {article},\\n author = {Rao, P and Caulfield, C P and Gibbon, J D},\\n doi = {10.1017/jfm.2016.719},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Rao,  P.\",\"Caulfield,  C., P.\",\"Gibbon,  J., D.\"],\"urls\":{\"Website\":\"http://www.journals.cambridge.org/abstract_S0022112016007199\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017\",\"role\":\"author\",\"keyword\":[\"Navier–Stokes equations\",\"buoyancy-driven instability\",\"mathematical foundations\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows\",\"type\":\"article\",\"year\":\"2017\",\"keywords\":\"mathematical foundations,turbulence theory,turbulent mixing\",\"pages\":\"236-279\",\"volume\":\"829\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"ab7a41aa-5bfe-3e00-be27-392ff5926cb1\",\"created\":\"2021-04-09T15:24:41.296Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:41.296Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We derive here Lagrangian fluctuation–dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values, boundary values and internal sources, as those are sampled backward in time by stochastic Lagrangian trajectories. New probabilistic concepts are required to represent scalar boundary conditions at the walls: the boundary local-time density at points on the wall where scalar fluxes are imposed and the boundary first hitting time at points where scalar values are imposed. These concepts are illustrated both by analytical results for the problem of pure heat conduction and by numerical results from a database of channel-flow turbulence, which also demonstrate the scalar mixing properties of near-wall turbulence. As an application of the fluctuation–dissipation relation, we examine for wall-bounded flows the relation between anomalous scalar dissipation and Lagrangian spontaneous stochasticity, i.e. the persistent non-determinism of Lagrangian particle trajectories in the limit of vanishing viscosity and diffusivity. In Part I of this series, we showed that spontaneous stochasticity is the only possible mechanism for anomalous dissipation of passive or active scalars, away from walls. Here it is shown that this remains true when there are no scalar fluxes through walls. Simple examples show, on the other hand, that a distinct mechanism of non-vanishing scalar dissipation can be thin scalar boundary layers near the walls. Nevertheless, we prove for general wall-bounded flows that spontaneous stochasticity is another possible mechanism of anomalous scalar dissipation.\",\"bibtype\":\"article\",\"author\":\"Drivas, Theodore D and Eyink, Gregory L\",\"doi\":\"10.1017/jfm.2017.571\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows},\\n type = {article},\\n year = {2017},\\n keywords = {mathematical foundations,turbulence theory,turbulent mixing},\\n pages = {236-279},\\n volume = {829},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {ab7a41aa-5bfe-3e00-be27-392ff5926cb1},\\n created = {2021-04-09T15:24:41.296Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:41.296Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We derive here Lagrangian fluctuation–dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values, boundary values and internal sources, as those are sampled backward in time by stochastic Lagrangian trajectories. New probabilistic concepts are required to represent scalar boundary conditions at the walls: the boundary local-time density at points on the wall where scalar fluxes are imposed and the boundary first hitting time at points where scalar values are imposed. These concepts are illustrated both by analytical results for the problem of pure heat conduction and by numerical results from a database of channel-flow turbulence, which also demonstrate the scalar mixing properties of near-wall turbulence. As an application of the fluctuation–dissipation relation, we examine for wall-bounded flows the relation between anomalous scalar dissipation and Lagrangian spontaneous stochasticity, i.e. the persistent non-determinism of Lagrangian particle trajectories in the limit of vanishing viscosity and diffusivity. In Part I of this series, we showed that spontaneous stochasticity is the only possible mechanism for anomalous dissipation of passive or active scalars, away from walls. Here it is shown that this remains true when there are no scalar fluxes through walls. Simple examples show, on the other hand, that a distinct mechanism of non-vanishing scalar dissipation can be thin scalar boundary layers near the walls. Nevertheless, we prove for general wall-bounded flows that spontaneous stochasticity is another possible mechanism of anomalous scalar dissipation.},\\n bibtype = {article},\\n author = {Drivas, Theodore D and Eyink, Gregory L},\\n doi = {10.1017/jfm.2017.571},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Drivas,  T., D.\",\"Eyink,  G., L.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017\",\"role\":\"author\",\"keyword\":[\"mathematical foundations\",\"turbulence theory\",\"turbulent mixing\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":2,\"html\":\"\"},{\"title\":\"Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic 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{Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic Web},\\n type = {article},\\n year = {2015},\\n keywords = {Fractals,ROMA,cosmic gas,fluid turbulence,magnetospheric cusp},\\n pages = {2025-2043},\\n volume = {172},\\n websites = {http://link.springer.com/10.1007/s00024-014-0874-z},\\n month = {4},\\n publisher = {Springer Basel},\\n id = {b553ef8e-fc2f-38f3-a3c1-dacf3828984f},\\n created = {2021-04-09T15:24:41.947Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:41.947Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Chang, Tom and chin Wu, Cheng and Echim, Marius and Lamy, Hervé and Vogelsberger, Mark and Hernquist, Lars and Sijacki, Debora},\\n doi = {10.1007/s00024-014-0874-z},\\n journal = {Pure and Applied Geophysics},\\n number = {7}\\n}\",\"author_short\":[\"Chang,  T.\",\"chin Wu,  C.\",\"Echim,  M.\",\"Lamy,  H.\",\"Vogelsberger,  M.\",\"Hernquist,  L.\",\"Sijacki,  D.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00024-014-0874-z\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015\",\"role\":\"author\",\"keyword\":[\"Fractals\",\"ROMA\",\"cosmic gas\",\"fluid turbulence\",\"magnetospheric cusp\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Building a scientific workflow framework to enable real-time machine learning and visualization\",\"type\":\"article\",\"year\":\"2018\",\"keywords\":\"DataSpaces,computational fluid dynamics,high performance 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Visualizing Continuous Turbulence Scales\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Human‐centered computing∼Scientific visualization,flow visualization,scientific visualization,visualization,volume visualization\",\"pages\":\"300-315\",\"volume\":\"38\",\"websites\":\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532\",\"month\":\"4\",\"publisher\":\"John Wiley & Sons, Ltd (10.1111)\",\"id\":\"e60aa66b-61a5-3dc9-a8a9-4d541b501276\",\"created\":\"2021-04-09T15:24:43.766Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:43.766Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Liu, Xiaopei and Mishra, Maneesh and Skote, Martin and Fu, Chi‐Wing\",\"doi\":\"10.1111/cgf.13532\",\"journal\":\"Computer Graphics 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E.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevE.98.033116\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"24602\",\"volume\":\"3\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602\",\"month\":\"4\",\"publisher\":\"American Physical 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This spectrum, obtained from direct measurements in space, exhibits nearly two decades of Kolmogorov k −5/3 decay in the inertial range of scales. Beyond this regime, in the dissipative range of scales, a crossover to a stretched exponential decay on scale k 2/3 is observed, in full agreement with a recent theoretical prediction based on nonperturbative renormalization group theory.\",\"bibtype\":\"article\",\"author\":\"Debue, Paul and Kuzzay, Denis and Saw, Ewe-Wei and Daviaud, François and Dubrulle, Bérengère and Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás\",\"doi\":\"10.1103/PhysRevFluids.3.024602\",\"journal\":\"Physical Review Fluids\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow},\\n type = {article},\\n year = {2018},\\n pages = {24602},\\n volume = {3},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {4d7dc155-2758-3e9a-b31c-49fcd1d57167},\\n created = {2021-04-09T15:24:45.029Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:45.029Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The kinetic energy spectrum of high-Reynolds turbulent swirling flows is experimentally studied. This spectrum, obtained from direct measurements in space, exhibits nearly two decades of Kolmogorov k −5/3 decay in the inertial range of scales. Beyond this regime, in the dissipative range of scales, a crossover to a stretched exponential decay on scale k 2/3 is observed, in full agreement with a recent theoretical prediction based on nonperturbative renormalization group theory.},\\n bibtype = {article},\\n author = {Debue, Paul and Kuzzay, Denis and Saw, Ewe-Wei and Daviaud, François and Dubrulle, Bérengère and Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás},\\n doi = {10.1103/PhysRevFluids.3.024602},\\n journal = {Physical Review Fluids},\\n number = {2}\\n}\",\"author_short\":[\"Debue,  P.\",\"Kuzzay,  D.\",\"Saw,  E.\",\"Daviaud,  F.\",\"Dubrulle,  B.\",\"Canet,  L.\",\"Rossetto,  V.\",\"Wschebor,  N.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":3,\"html\":\"\"},{\"title\":\"Remote visual analysis of large turbulence databases at multiple scales\",\"type\":\"article\",\"year\":\"2018\",\"pages\":\"115-126\",\"volume\":\"120\",\"websites\":\"https://www.sciencedirect.com/science/article/pii/S0743731518303927\",\"month\":\"4\",\"publisher\":\"Academic Press\",\"id\":\"35837047-3f06-3d53-b882-ecb1c35bd473\",\"created\":\"2021-04-09T15:24:46.266Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:46.266Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. We present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. The database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.\",\"bibtype\":\"article\",\"author\":\"Pulido, Jesus and Livescu, Daniel and Kanov, Kalin and Burns, Randal and Canada, Curtis and Ahrens, James and Hamann, Bernd\",\"doi\":\"10.1016/J.JPDC.2018.05.011\",\"journal\":\"Journal of Parallel and Distributed Computing\",\"bibtex\":\"@article{\\n title = {Remote visual analysis of large turbulence databases at multiple scales},\\n type = {article},\\n year = {2018},\\n pages = {115-126},\\n volume = {120},\\n websites = {https://www.sciencedirect.com/science/article/pii/S0743731518303927},\\n month = {4},\\n publisher = {Academic Press},\\n id = {35837047-3f06-3d53-b882-ecb1c35bd473},\\n created = {2021-04-09T15:24:46.266Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:46.266Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. We present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. The database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.},\\n bibtype = {article},\\n author = {Pulido, Jesus and Livescu, Daniel and Kanov, Kalin and Burns, Randal and Canada, Curtis and Ahrens, James and Hamann, Bernd},\\n doi = {10.1016/J.JPDC.2018.05.011},\\n journal = {Journal of Parallel and Distributed Computing}\\n}\",\"author_short\":[\"Pulido,  J.\",\"Livescu,  D.\",\"Kanov,  K.\",\"Burns,  R.\",\"Canada,  C.\",\"Ahrens,  J.\",\"Hamann,  B.\"],\"urls\":{\"Website\":\"https://www.sciencedirect.com/science/article/pii/S0743731518303927\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":9,\"html\":\"\"},{\"title\":\"Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"54604\",\"volume\":\"5\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"f211ca87-c1f5-30ae-b860-b03aca46a225\",\"created\":\"2021-04-09T15:24:46.917Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:46.917Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Krishna, C Vamsi and Wang, Mengying and Hemati, Maziar S and Luhar, Mitul\",\"doi\":\"10.1103/PhysRevFluids.5.054604\",\"journal\":\"Physical Review Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements},\\n type = {article},\\n year = {2020},\\n pages = {54604},\\n volume = {5},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {f211ca87-c1f5-30ae-b860-b03aca46a225},\\n created = {2021-04-09T15:24:46.917Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:46.917Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Krishna, C Vamsi and Wang, Mengying and Hemati, Maziar S and Luhar, Mitul},\\n doi = {10.1103/PhysRevFluids.5.054604},\\n journal = {Physical Review Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Krishna,  C., V.\",\"Wang,  M.\",\"Hemati,  M., S.\",\"Luhar,  M.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"High-Reynolds-number fractal signature of nascent turbulence during transition\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Fractal dimension,Transitional boundary layer,Turbulent spots\",\"pages\":\"3461-3468\",\"volume\":\"117\",\"websites\":\"http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117\",\"month\":\"4\",\"publisher\":\"National Academy of Sciences\",\"id\":\"961c0616-69f2-3de4-b644-445021490b1f\",\"created\":\"2021-04-09T15:24:47.453Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:47.453Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension D ≈ 7 / 3 , where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume–area fractal scaling exponent. Measurements show a dimension of D = 2.36 ± 0.03 over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.\",\"bibtype\":\"article\",\"author\":\"Wu, Zhao and Zaki, Tamer A and Meneveau, Charles\",\"doi\":\"10.1073/pnas.1916636117\",\"journal\":\"Proceedings of the National Academy of Sciences\",\"number\":\"7\",\"bibtex\":\"@article{\\n title = {High-Reynolds-number fractal signature of nascent turbulence during transition},\\n type = {article},\\n year = {2020},\\n keywords = {Fractal dimension,Transitional boundary layer,Turbulent spots},\\n pages = {3461-3468},\\n volume = {117},\\n websites = {http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117},\\n month = {4},\\n publisher = {National Academy of Sciences},\\n id = {961c0616-69f2-3de4-b644-445021490b1f},\\n created = {2021-04-09T15:24:47.453Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:47.453Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension D ≈ 7 / 3 , where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume–area fractal scaling exponent. Measurements show a dimension of D = 2.36 ± 0.03 over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.},\\n bibtype = {article},\\n author = {Wu, Zhao and Zaki, Tamer A and Meneveau, Charles},\\n doi = {10.1073/pnas.1916636117},\\n journal = {Proceedings of the National Academy of Sciences},\\n number = {7}\\n}\",\"author_short\":[\"Wu,  Z.\",\"Zaki,  T., A.\",\"Meneveau,  C.\"],\"urls\":{\"Website\":\"http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020\",\"role\":\"author\",\"keyword\":[\"Fractal dimension\",\"Transitional boundary layer\",\"Turbulent spots\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Geometric constraints on energy transfer in the turbulent cascade\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"34603\",\"volume\":\"5\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"a82e659f-7268-3e32-b8f7-441f609d4224\",\"created\":\"2021-04-09T15:24:48.171Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:48.171Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The energy cascade is the most significant feature that separates turbulence from other unsteady flows, and results from the behavior of the nonlinear term in the Navier-Stokes equations. The mathematical form of this term, however, places constraints on exactly how it can act. Here we consider the action of the nonlinear term in physical space rather than in Fourier space, where the energy transfer between scales can be interpreted as a mechanical process where some scales do work on others. This formulation reveals the fundamental role played by geometry, as work can only be done when the eigenframes of the turbulent stress and strain rate are appropriately aligned. By comparing a direct numerical simulation of the Navier-Stokes equations, an ensemble of random solenoidal vector fields, and a random sampling of uniform eigenframe alignments, we show that this geometric alignment plays a much stronger role in determining the flux between scales than do the magnitudes of the stress and strain rate. We also show that when the alignment is effectively two dimensional, even when embedded in a three-dimensional flow, the energy flux is typically inverse, suggesting that the inverse cascade in two-dimensional turbulence may have a kinematic origin. Our results point to some potentially fruitful directions for turbulence modeling.\",\"bibtype\":\"article\",\"author\":\"Ballouz, Joseph G and Ouellette, Nicholas T\",\"doi\":\"10.1103/PhysRevFluids.5.034603\",\"journal\":\"Physical Review Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Geometric constraints on energy transfer in the turbulent cascade},\\n type = {article},\\n year = {2020},\\n pages = {34603},\\n volume = {5},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {a82e659f-7268-3e32-b8f7-441f609d4224},\\n created = {2021-04-09T15:24:48.171Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:48.171Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The energy cascade is the most significant feature that separates turbulence from other unsteady flows, and results from the behavior of the nonlinear term in the Navier-Stokes equations. The mathematical form of this term, however, places constraints on exactly how it can act. Here we consider the action of the nonlinear term in physical space rather than in Fourier space, where the energy transfer between scales can be interpreted as a mechanical process where some scales do work on others. This formulation reveals the fundamental role played by geometry, as work can only be done when the eigenframes of the turbulent stress and strain rate are appropriately aligned. By comparing a direct numerical simulation of the Navier-Stokes equations, an ensemble of random solenoidal vector fields, and a random sampling of uniform eigenframe alignments, we show that this geometric alignment plays a much stronger role in determining the flux between scales than do the magnitudes of the stress and strain rate. We also show that when the alignment is effectively two dimensional, even when embedded in a three-dimensional flow, the energy flux is typically inverse, suggesting that the inverse cascade in two-dimensional turbulence may have a kinematic origin. Our results point to some potentially fruitful directions for turbulence modeling.},\\n bibtype = {article},\\n author = {Ballouz, Joseph G and Ouellette, Nicholas T},\\n doi = {10.1103/PhysRevFluids.5.034603},\\n journal = {Physical Review Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Ballouz,  J., G.\",\"Ouellette,  N., T.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"23902\",\"volume\":\"4\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"ec287cd3-c0fe-353a-a570-e6ae60c03bac\",\"created\":\"2021-04-09T15:24:48.752Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:48.752Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Existing methods to identify the interfaces separating different regions in turbulent flows, such as turbulent/nonturbulent interfaces, typically rely on subjectively chosen thresholds, often including visual verification that the resulting surface meaningfully separates the different regions. Since machine learning tools are known to help automate such classification tasks, we here propose to use an unsupervised self-organizing map (SOM) machine learning algorithm as an automatic classifier. We use it to separate a boundary layer undergoing bypass transition into two distinct spatial regions, the turbulent boundary layer (TBL) and non-TBL regions, the latter including the laminar portion prior to transition and the outer flow which possibly contains weak free-stream turbulence. Both regions are separated by the turbulent boundary layer interface (TBLI). The data used in this study are from a direct numerical simulation and are available on an open database system. In our analysis of one snapshot in time, every spatial point is characterized by a 16-dimensional vector containing the magnitudes of the components of total and fluctuating velocity, magnitudes of the velocity gradient tensor elements, and the streamwise and wall-normal coordinates, all normalized by their global standard deviation. In an unsupervised fashion, the SOM classifier separates the points into TBL and non-TBL regions, thus identifying the TBLI without the need for user-specified thresholds. Remarkably, it avoids including vortical streaky structures that exist in the laminar portion prior to transition as well as the weak free-stream turbulence in the turbulent boundary layer region. The approach is compared quantitatively with existing methods to determine the TBLI (vorticity magnitude, cross-stream velocity fluctuation). Also, the SOM classifier is cast as a linear hyperplane that separates the two clusters of data points, and the method is tested by finding the TBLI of other snapshots in the transitional boundary layer data set, as well as in a fully turbulent boundary layer with similar levels of free-stream turbulence. Variants in which the approach failed are also summarized.\",\"bibtype\":\"article\",\"author\":\"Wu, Zhao and Lee, Jin and Meneveau, Charles and Zaki, Tamer\",\"doi\":\"10.1103/PhysRevFluids.4.023902\",\"journal\":\"Physical Review Fluids\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow},\\n type = {article},\\n year = {2019},\\n pages = {23902},\\n volume = {4},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {ec287cd3-c0fe-353a-a570-e6ae60c03bac},\\n created = {2021-04-09T15:24:48.752Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:48.752Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Existing methods to identify the interfaces separating different regions in turbulent flows, such as turbulent/nonturbulent interfaces, typically rely on subjectively chosen thresholds, often including visual verification that the resulting surface meaningfully separates the different regions. Since machine learning tools are known to help automate such classification tasks, we here propose to use an unsupervised self-organizing map (SOM) machine learning algorithm as an automatic classifier. We use it to separate a boundary layer undergoing bypass transition into two distinct spatial regions, the turbulent boundary layer (TBL) and non-TBL regions, the latter including the laminar portion prior to transition and the outer flow which possibly contains weak free-stream turbulence. Both regions are separated by the turbulent boundary layer interface (TBLI). The data used in this study are from a direct numerical simulation and are available on an open database system. In our analysis of one snapshot in time, every spatial point is characterized by a 16-dimensional vector containing the magnitudes of the components of total and fluctuating velocity, magnitudes of the velocity gradient tensor elements, and the streamwise and wall-normal coordinates, all normalized by their global standard deviation. In an unsupervised fashion, the SOM classifier separates the points into TBL and non-TBL regions, thus identifying the TBLI without the need for user-specified thresholds. Remarkably, it avoids including vortical streaky structures that exist in the laminar portion prior to transition as well as the weak free-stream turbulence in the turbulent boundary layer region. The approach is compared quantitatively with existing methods to determine the TBLI (vorticity magnitude, cross-stream velocity fluctuation). Also, the SOM classifier is cast as a linear hyperplane that separates the two clusters of data points, and the method is tested by finding the TBLI of other snapshots in the transitional boundary layer data set, as well as in a fully turbulent boundary layer with similar levels of free-stream turbulence. Variants in which the approach failed are also summarized.},\\n bibtype = {article},\\n author = {Wu, Zhao and Lee, Jin and Meneveau, Charles and Zaki, Tamer},\\n doi = {10.1103/PhysRevFluids.4.023902},\\n journal = {Physical Review Fluids},\\n number = {2}\\n}\",\"author_short\":[\"Wu,  Z.\",\"Lee,  J.\",\"Meneveau,  C.\",\"Zaki,  T.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"Turbulent channel flow,quiescent core,spheroidal inertialess particles\",\"pages\":\"424-438\",\"volume\":\"20\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747\",\"month\":\"4\",\"publisher\":\"Taylor and Francis Ltd.\",\"id\":\"bde9b67c-cc56-3e5a-ba15-32edb1794316\",\"created\":\"2021-04-09T15:24:49.272Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:49.272Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Numerical studies into the dynamics of non-spherical particles in turbulent channel flow have, until now, been mostly confined to low Reynolds numbers. In this paper, we investigate the dynamics of tracer non-spherical particles in a channel flow at (Formula presented.) for the first time. Tracer spheroidal particles suspended in a turbulent channel flow are computed by means of direct numerical simulation coupled with a Lagrangian point-particle approach. We examine the rotational dynamics and alignment of tracer spheroids of different aspect ratio in both the near-wall region and, in particular, the quiescent core which is not observed at lower Reynolds numbers. In the near-wall region, the effect of Reynolds number on preferential alignment is negligible with particle rotation exhibiting a weak dependence for all aspect ratios investigated. However, the particle rotation is strongly damped in the quiescent core demonstrating that the motion of tracer spheroids becomes quiescent. The striking difference in spheroids' rotational dynamics observed inside and outside of the quiescent core is correlated with the local Kolmogorov time scale in the core and outside of it.\",\"bibtype\":\"article\",\"author\":\"Jie, Yucheng and Xu, Chunxiao and Dawson, James R and Andersson, Helge I and Zhao, Lihao\",\"doi\":\"10.1080/14685248.2019.1664747\",\"journal\":\"Journal of Turbulence\",\"number\":\"7\",\"bibtex\":\"@article{\\n title = {Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow},\\n type = {article},\\n year = {2019},\\n keywords = {Turbulent channel flow,quiescent core,spheroidal inertialess particles},\\n pages = {424-438},\\n volume = {20},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747},\\n month = {4},\\n publisher = {Taylor and Francis Ltd.},\\n id = {bde9b67c-cc56-3e5a-ba15-32edb1794316},\\n created = {2021-04-09T15:24:49.272Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:49.272Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Numerical studies into the dynamics of non-spherical particles in turbulent channel flow have, until now, been mostly confined to low Reynolds numbers. In this paper, we investigate the dynamics of tracer non-spherical particles in a channel flow at (Formula presented.) for the first time. Tracer spheroidal particles suspended in a turbulent channel flow are computed by means of direct numerical simulation coupled with a Lagrangian point-particle approach. We examine the rotational dynamics and alignment of tracer spheroids of different aspect ratio in both the near-wall region and, in particular, the quiescent core which is not observed at lower Reynolds numbers. In the near-wall region, the effect of Reynolds number on preferential alignment is negligible with particle rotation exhibiting a weak dependence for all aspect ratios investigated. However, the particle rotation is strongly damped in the quiescent core demonstrating that the motion of tracer spheroids becomes quiescent. The striking difference in spheroids' rotational dynamics observed inside and outside of the quiescent core is correlated with the local Kolmogorov time scale in the core and outside of it.},\\n bibtype = {article},\\n author = {Jie, Yucheng and Xu, Chunxiao and Dawson, James R and Andersson, Helge I and Zhao, Lihao},\\n doi = {10.1080/14685248.2019.1664747},\\n journal = {Journal of Turbulence},\\n number = {7}\\n}\",\"author_short\":[\"Jie,  Y.\",\"Xu,  C.\",\"Dawson,  J., R.\",\"Andersson,  H., I.\",\"Zhao,  L.\"],\"urls\":{\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019\",\"role\":\"author\",\"keyword\":[\"Turbulent channel flow\",\"quiescent core\",\"spheroidal inertialess particles\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Sensing the turbulent large-scale motions with their wall signature\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"125112\",\"volume\":\"31\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5128053\",\"month\":\"4\",\"publisher\":\"American Institute of Physics Inc.\",\"id\":\"34785306-ab75-301c-9fe7-4a8b56499b9d\",\"created\":\"2021-04-09T15:24:50.032Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:50.032Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.\",\"bibtype\":\"article\",\"author\":\"Güemes, A and Discetti, S and Ianiro, A\",\"doi\":\"10.1063/1.5128053\",\"journal\":\"Physics of Fluids\",\"number\":\"12\",\"bibtex\":\"@article{\\n title = {Sensing the turbulent large-scale motions with their wall signature},\\n type = {article},\\n year = {2019},\\n pages = {125112},\\n volume = {31},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5128053},\\n month = {4},\\n publisher = {American Institute of Physics Inc.},\\n id = {34785306-ab75-301c-9fe7-4a8b56499b9d},\\n created = {2021-04-09T15:24:50.032Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:50.032Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.},\\n bibtype = {article},\\n author = {Güemes, A and Discetti, S and Ianiro, A},\\n doi = {10.1063/1.5128053},\\n journal = {Physics of Fluids},\\n number = {12}\\n}\",\"author_short\":[\"Güemes,  A.\",\"Discetti,  S.\",\"Ianiro,  A.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5128053\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Mean dynamics and transition to turbulence in oscillatory channel flow\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"boundary layer structure,transition to turbulence,turbulent boundary layers\",\"pages\":\"864-889\",\"volume\":\"880\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"2b9bc248-7bec-3add-aaf3-c815e69e4177\",\"created\":\"2021-04-09T15:24:50.517Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:50.517Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The mean dynamics in oscillatory channel flow is examined to investigate the dynamical mechanisms underlying the transition to turbulence in oscillatory wall-bounded flow. The analyses employ direct numerical simulation data acquired at three Stokes Reynolds numbers: Re_s=648 , 801 and 1009, where the lower Re_s flow is transitional over the entire cycle and the two higher Re_s flows exhibit flow characteristics similar to steady turbulent wall-bounded flow during part of the cycle. The flow evolution over a half-period of oscillation for all three Re_s is as follows: near-wall streamwise velocity streaks develop during the early accelerating portion of the cycle; then at some later point in the cycle that depends on Re_s , the near-wall streaks breakdown (demarking the onset of the nonlinear development stage), and the near-wall Reynolds stress grows explosively; the Reynolds stress remains elevated for part of the cycle before diminishing (yet remaining finite) during the late decelerating portion of the cycle. This process is then repeated indefinitely. The present findings demonstrate that transition to turbulence occurs when the nonlinear development stage begins during the accelerating portion of the cycle. This crucially leads to the diminishing importance of the centreline momentum source, the emergence of a locally accelerating/decelerating internal layer centred about the edge of the Stokes layer and the wall-normal rearrangement of the mean forces prior to the start of the decelerating portion of the cycle. The rearrangement of mean forces culminates in a four layer structure in the mean balance of forces. This is significant on a number of accounts since empirical and theoretical evidence suggests that the formation of a four layer structure is an important characteristic of a self-similar hierarchal structure that underlies logarithmic dependence of the mean velocity profile in steady turbulent wall-bounded flows (Klewicki et al. , J. Fluid Mech. , vol. 638, 2009, pp. 73–93). When the nonlinear development stage begins during the decelerating portion of the cycle (i.e. at Re_s=648 ), a four layer structure is not observed in the mean balance of forces and the flow remains weakly transitional over the entire cycle.\",\"bibtype\":\"article\",\"author\":\"Ebadi, Alireza and White, Christopher M and Pond, Ian and Dubief, Yves\",\"doi\":\"10.1017/jfm.2019.706\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Mean dynamics and transition to turbulence in oscillatory channel flow},\\n type = {article},\\n year = {2019},\\n keywords = {boundary layer structure,transition to turbulence,turbulent boundary layers},\\n pages = {864-889},\\n volume = {880},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {2b9bc248-7bec-3add-aaf3-c815e69e4177},\\n created = {2021-04-09T15:24:50.517Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:50.517Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The mean dynamics in oscillatory channel flow is examined to investigate the dynamical mechanisms underlying the transition to turbulence in oscillatory wall-bounded flow. The analyses employ direct numerical simulation data acquired at three Stokes Reynolds numbers: Re_s=648 , 801 and 1009, where the lower Re_s flow is transitional over the entire cycle and the two higher Re_s flows exhibit flow characteristics similar to steady turbulent wall-bounded flow during part of the cycle. The flow evolution over a half-period of oscillation for all three Re_s is as follows: near-wall streamwise velocity streaks develop during the early accelerating portion of the cycle; then at some later point in the cycle that depends on Re_s , the near-wall streaks breakdown (demarking the onset of the nonlinear development stage), and the near-wall Reynolds stress grows explosively; the Reynolds stress remains elevated for part of the cycle before diminishing (yet remaining finite) during the late decelerating portion of the cycle. This process is then repeated indefinitely. The present findings demonstrate that transition to turbulence occurs when the nonlinear development stage begins during the accelerating portion of the cycle. This crucially leads to the diminishing importance of the centreline momentum source, the emergence of a locally accelerating/decelerating internal layer centred about the edge of the Stokes layer and the wall-normal rearrangement of the mean forces prior to the start of the decelerating portion of the cycle. The rearrangement of mean forces culminates in a four layer structure in the mean balance of forces. This is significant on a number of accounts since empirical and theoretical evidence suggests that the formation of a four layer structure is an important characteristic of a self-similar hierarchal structure that underlies logarithmic dependence of the mean velocity profile in steady turbulent wall-bounded flows (Klewicki et al. , J. Fluid Mech. , vol. 638, 2009, pp. 73–93). When the nonlinear development stage begins during the decelerating portion of the cycle (i.e. at Re_s=648 ), a four layer structure is not observed in the mean balance of forces and the flow remains weakly transitional over the entire cycle.},\\n bibtype = {article},\\n author = {Ebadi, Alireza and White, Christopher M and Pond, Ian and Dubief, Yves},\\n doi = {10.1017/jfm.2019.706},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Ebadi,  A.\",\"White,  C., M.\",\"Pond,  I.\",\"Dubief,  Y.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019\",\"role\":\"author\",\"keyword\":[\"boundary layer structure\",\"transition to turbulence\",\"turbulent boundary layers\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate\",\"type\":\"article\",\"year\":\"2019\",\"keywords\":\"isotropic turbulence,turbulence theory,vortex dynamics\",\"pages\":\"283-312\",\"volume\":\"881\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"0acc8cd3-af07-36ae-9efd-4e068111d3af\",\"created\":\"2021-04-09T15:24:50.978Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:50.978Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper uses a tight mathematical bound on the degree of the non-normality of the turbulent velocity gradient tensor to classify flow behaviour within vortical regions (where the eigenvalues of the tensor contain a conjugate pair). Structures attaining this bound are preferentially generated where enstrophy exceeds total strain and there is a positive balance between strain production and enstrophy production. Lagrangian analysis of homogeneous, isotropic turbulence shows that attainment of this bound is associated with relatively short durations and an upper limit to the spatial extent of the flow structures that is similar to the Taylor scale. An analysis of the dynamically relevant terms using a recently developed formulation (Keylock, J. Fluid Mech. , vol. 848, 2018, pp. 876–904), highlights the controls on this dynamics. In particular, in high enstrophy regions it is shown that the bound is attained when normal strain decreases rather than when non-normality increases. The near absence of normal total strain results in a source of intermittency in the dynamics of dissipation that is hidden in standard analyses. It is shown that of the two terms that contribute to the non-normal production dynamics, it is the one that is typically smallest in magnitude that is of greatest importance within these  =1 filaments. The typical distance between filament centroids is just less than a Taylor scale, implying a connection to the manner in which flow topology at the Taylor scale explains dissipation at smaller scales.\",\"bibtype\":\"article\",\"author\":\"Keylock, Christopher J\",\"doi\":\"10.1017/jfm.2019.779\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate},\\n type = {article},\\n year = {2019},\\n keywords = {isotropic turbulence,turbulence theory,vortex dynamics},\\n pages = {283-312},\\n volume = {881},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {0acc8cd3-af07-36ae-9efd-4e068111d3af},\\n created = {2021-04-09T15:24:50.978Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:50.978Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper uses a tight mathematical bound on the degree of the non-normality of the turbulent velocity gradient tensor to classify flow behaviour within vortical regions (where the eigenvalues of the tensor contain a conjugate pair). Structures attaining this bound are preferentially generated where enstrophy exceeds total strain and there is a positive balance between strain production and enstrophy production. Lagrangian analysis of homogeneous, isotropic turbulence shows that attainment of this bound is associated with relatively short durations and an upper limit to the spatial extent of the flow structures that is similar to the Taylor scale. An analysis of the dynamically relevant terms using a recently developed formulation (Keylock, J. Fluid Mech. , vol. 848, 2018, pp. 876–904), highlights the controls on this dynamics. In particular, in high enstrophy regions it is shown that the bound is attained when normal strain decreases rather than when non-normality increases. The near absence of normal total strain results in a source of intermittency in the dynamics of dissipation that is hidden in standard analyses. It is shown that of the two terms that contribute to the non-normal production dynamics, it is the one that is typically smallest in magnitude that is of greatest importance within these  =1 filaments. The typical distance between filament centroids is just less than a Taylor scale, implying a connection to the manner in which flow topology at the Taylor scale explains dissipation at smaller scales.},\\n bibtype = {article},\\n author = {Keylock, Christopher J},\\n doi = {10.1017/jfm.2019.779},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Keylock,  C., J.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019\",\"role\":\"author\",\"keyword\":[\"isotropic turbulence\",\"turbulence theory\",\"vortex dynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Predictive large-eddy-simulation wall modeling via physics-informed neural networks\",\"type\":\"article\",\"year\":\"2019\",\"pages\":\"34602\",\"volume\":\"4\",\"websites\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"3981fbac-dbaf-3646-acef-d3d887d228e4\",\"created\":\"2021-04-09T15:24:52.317Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:52.317Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"While data-based approaches were found to be useful for subgrid scale (SGS) modeling in Reynolds-averaged Navier-Stokes (RANS) simulations, there have not been many attempts at using machine learning techniques for wall modeling in large-eddy simulations (LESs). Large-eddy simulation differs from RANS simulation in many aspects. For one thing, LES is scale resolving. For another, LES is in and of itself a high-fidelity tool. Because data sets of higher fidelity are in general not frequently accessible or available, this poses additional challenges to data-based modeling in LES. Further, SGS modeling usually needs flow information at only large scales, in contrast with wall modeling, which needs to account for both near-wall small scales and large scales above the wall. In this work we discuss how the above-noted challenges may be addressed when taking a data-based approach for wall modeling. We also show the necessity of incorporating physical insights in model inputs, i.e., using inputs that are inspired by the vertically integrated thin-boundary-layer equations and the eddy population density scalings. We show that the inclusion of the above physics-based considerations would enhance extrapolation capabilities of a neural network to flow conditions that are not within the train data. Being cheap to evaluate and using only channel flow data at Reτ=1000, the trained networks are found to capture the law of the wall at arbitrary Reynolds numbers and outperform the conventional equilibrium model in a nonequilibrium flow.\",\"bibtype\":\"article\",\"author\":\"Yang, X I A and Zafar, S and Wang, J.-X. and Xiao, H\",\"doi\":\"10.1103/PhysRevFluids.4.034602\",\"journal\":\"Physical Review Fluids\",\"number\":\"3\",\"bibtex\":\"@article{\\n title = {Predictive large-eddy-simulation wall modeling via physics-informed neural networks},\\n type = {article},\\n year = {2019},\\n pages = {34602},\\n volume = {4},\\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {3981fbac-dbaf-3646-acef-d3d887d228e4},\\n created = {2021-04-09T15:24:52.317Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:52.317Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {While data-based approaches were found to be useful for subgrid scale (SGS) modeling in Reynolds-averaged Navier-Stokes (RANS) simulations, there have not been many attempts at using machine learning techniques for wall modeling in large-eddy simulations (LESs). Large-eddy simulation differs from RANS simulation in many aspects. For one thing, LES is scale resolving. For another, LES is in and of itself a high-fidelity tool. Because data sets of higher fidelity are in general not frequently accessible or available, this poses additional challenges to data-based modeling in LES. Further, SGS modeling usually needs flow information at only large scales, in contrast with wall modeling, which needs to account for both near-wall small scales and large scales above the wall. In this work we discuss how the above-noted challenges may be addressed when taking a data-based approach for wall modeling. We also show the necessity of incorporating physical insights in model inputs, i.e., using inputs that are inspired by the vertically integrated thin-boundary-layer equations and the eddy population density scalings. We show that the inclusion of the above physics-based considerations would enhance extrapolation capabilities of a neural network to flow conditions that are not within the train data. Being cheap to evaluate and using only channel flow data at Reτ=1000, the trained networks are found to capture the law of the wall at arbitrary Reynolds numbers and outperform the conventional equilibrium model in a nonequilibrium flow.},\\n bibtype = {article},\\n author = {Yang, X I A and Zafar, S and Wang, J.-X. and Xiao, H},\\n doi = {10.1103/PhysRevFluids.4.034602},\\n journal = {Physical Review Fluids},\\n number = {3}\\n}\",\"author_short\":[\"Yang,  X., I., A.\",\"Zafar,  S.\",\"Wang,  J.\",\"Xiao,  H.\"],\"urls\":{\"Website\":\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Double-frame tomographic PTV at high seeding densities\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics\",\"pages\":\"23\",\"volume\":\"61\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2859-2\",\"month\":\"4\",\"publisher\":\"Springer\",\"id\":\"f97dbeff-e7dd-31f8-8835-6edc9b4add50\",\"created\":\"2021-04-09T15:24:52.904Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:52.904Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"A novel method performing 3D PTV from double-frame multi-camera images is introduced. Particle velocities are estimated by following three steps: First, separate particle reconstructions with a sparsity based algorithm are performed on a fine grid. Second, they are expanded on a coarser grid on which 3D correlation is performed, yielding a predictor displacement field that allows to efficiently match particles at the two time instants. As these particles are still located on a voxel grid, the third, final step achieves particle position refinement to their actual subvoxel position by a global optimization process, also accounting for their intensities. As it strongly leverages on principles from tomographic reconstruction, the technique is termed Double-Frame Tomo-PTV (DF-TPTV). Standard synthetic tests on a complex turbulent flow show that the method achieves high particle and vector detection efficiency, up to seeding densities of around 0.08 particles per pixel (ppp). On these tests, it also shows a higher robustness to noise and lower root-mean-square errors on velocity estimation than similar state-of-the-art methods. Results from an experimental campaign on a transitional round air jet at Reynolds number 4600 are also presented. Average seeding density varies in time from 0.06 to 0.03 ppp during the considered run, with different densities and signal-to-noise ratios being observed with time in the jet and ambient air regions, supplied by two different seeding systems. The strong polydisperse nature of the seeding, as well as the coexistence of two spatial zones of significantly different particle densities and signal-to-noise ratios, are observed to be the most influential sources of limitation for DF-TPTV performance. However, the method still successfully reconstructs a large amount of particles, and, associated with an outlier rejection scheme based on temporal statistics, truthfully reconstructs the instantaneous jet dynamics. Further quantitative performance assessment is then provided by introducing statistics performed by bin averaging, upon assuming statistical axisymmetry of the jet. Mean and fluctuating axial velocity components in the jet near-field are compared with reference results obtained from planar PIV at higher seeding density, with an interrogation window of size comparable to that of the bins. Results are found to be in excellent agreement with one another, confirming the high performance of DF-TPTV to yield reliable volumetric vector fields at seeding densities usually considered for tomographic PIV processing.\",\"bibtype\":\"article\",\"author\":\"Cornic, Philippe and Leclaire, Benjamin and Champagnat, Frédéric and Besnerais, Guy Le and Cheminet, Adam and Illoul, Cédric and Losfeld, Gilles\",\"doi\":\"10.1007/s00348-019-2859-2\",\"journal\":\"Experiments in Fluids\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Double-frame tomographic PTV at high seeding densities},\\n type = {article},\\n year = {2020},\\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\\n pages = {23},\\n volume = {61},\\n websites = {http://link.springer.com/10.1007/s00348-019-2859-2},\\n month = {4},\\n publisher = {Springer},\\n id = {f97dbeff-e7dd-31f8-8835-6edc9b4add50},\\n created = {2021-04-09T15:24:52.904Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:52.904Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {A novel method performing 3D PTV from double-frame multi-camera images is introduced. Particle velocities are estimated by following three steps: First, separate particle reconstructions with a sparsity based algorithm are performed on a fine grid. Second, they are expanded on a coarser grid on which 3D correlation is performed, yielding a predictor displacement field that allows to efficiently match particles at the two time instants. As these particles are still located on a voxel grid, the third, final step achieves particle position refinement to their actual subvoxel position by a global optimization process, also accounting for their intensities. As it strongly leverages on principles from tomographic reconstruction, the technique is termed Double-Frame Tomo-PTV (DF-TPTV). Standard synthetic tests on a complex turbulent flow show that the method achieves high particle and vector detection efficiency, up to seeding densities of around 0.08 particles per pixel (ppp). On these tests, it also shows a higher robustness to noise and lower root-mean-square errors on velocity estimation than similar state-of-the-art methods. Results from an experimental campaign on a transitional round air jet at Reynolds number 4600 are also presented. Average seeding density varies in time from 0.06 to 0.03 ppp during the considered run, with different densities and signal-to-noise ratios being observed with time in the jet and ambient air regions, supplied by two different seeding systems. The strong polydisperse nature of the seeding, as well as the coexistence of two spatial zones of significantly different particle densities and signal-to-noise ratios, are observed to be the most influential sources of limitation for DF-TPTV performance. However, the method still successfully reconstructs a large amount of particles, and, associated with an outlier rejection scheme based on temporal statistics, truthfully reconstructs the instantaneous jet dynamics. Further quantitative performance assessment is then provided by introducing statistics performed by bin averaging, upon assuming statistical axisymmetry of the jet. Mean and fluctuating axial velocity components in the jet near-field are compared with reference results obtained from planar PIV at higher seeding density, with an interrogation window of size comparable to that of the bins. Results are found to be in excellent agreement with one another, confirming the high performance of DF-TPTV to yield reliable volumetric vector fields at seeding densities usually considered for tomographic PIV processing.},\\n bibtype = {article},\\n author = {Cornic, Philippe and Leclaire, Benjamin and Champagnat, Frédéric and Besnerais, Guy Le and Cheminet, Adam and Illoul, Cédric and Losfeld, Gilles},\\n doi = {10.1007/s00348-019-2859-2},\\n journal = {Experiments in Fluids},\\n number = {2}\\n}\",\"author_short\":[\"Cornic,  P.\",\"Leclaire,  B.\",\"Champagnat,  F.\",\"Besnerais,  G., L.\",\"Cheminet,  A.\",\"Illoul,  C.\",\"Losfeld,  G.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2859-2\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020\",\"role\":\"author\",\"keyword\":[\"Engineering Fluid Dynamics\",\"Engineering Thermodynamics\",\"Fluid\",\"Heat and Mass Transfer\",\"and Aerodynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"buoyancy-driven instability,homogeneous turbulence,turbulent mixing\",\"pages\":\"A12\",\"volume\":\"895\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"e07b1214-d2e2-3f30-b087-fa980a509277\",\"created\":\"2021-04-09T15:24:53.393Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:53.393Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Aslangil, Denis and Livescu, Daniel and Banerjee, Arindam\",\"doi\":\"10.1017/jfm.2020.268\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence},\\n type = {article},\\n year = {2020},\\n keywords = {buoyancy-driven instability,homogeneous turbulence,turbulent mixing},\\n pages = {A12},\\n volume = {895},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {e07b1214-d2e2-3f30-b087-fa980a509277},\\n created = {2021-04-09T15:24:53.393Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:53.393Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Aslangil, Denis and Livescu, Daniel and Banerjee, Arindam},\\n doi = {10.1017/jfm.2020.268},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Aslangil,  D.\",\"Livescu,  D.\",\"Banerjee,  A.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020\",\"role\":\"author\",\"keyword\":[\"buoyancy-driven instability\",\"homogeneous turbulence\",\"turbulent mixing\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Developing particle image velocimetry software based on a deep neural network\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"deep neural networks,fluid motion estimation,particle image velocimetry\",\"pages\":\"359-376\",\"volume\":\"27\",\"websites\":\"http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\",\"publisher\":\"Begell House\",\"id\":\"06f51761-ca9e-36a5-9636-b609c6c8f2c7\",\"created\":\"2021-04-09T15:24:54.071Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:54.071Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Majewski, Wojciech and Wei, Runjie and Kumar, Vivek\",\"doi\":\"10.1615/JFlowVisImageProc.2020033180\",\"journal\":\"Journal of Flow Visualization and Image Processing\",\"number\":\"4\",\"bibtex\":\"@article{\\n title = {Developing particle image velocimetry software based on a deep neural network},\\n type = {article},\\n year = {2020},\\n keywords = {deep neural networks,fluid motion estimation,particle image velocimetry},\\n pages = {359-376},\\n volume = {27},\\n websites = {http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},\\n publisher = {Begell House},\\n id = {06f51761-ca9e-36a5-9636-b609c6c8f2c7},\\n created = {2021-04-09T15:24:54.071Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:54.071Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},\\n doi = {10.1615/JFlowVisImageProc.2020033180},\\n journal = {Journal of Flow Visualization and Image Processing},\\n number = {4}\\n}\",\"author_short\":[\"Majewski,  W.\",\"Wei,  R.\",\"Kumar,  V.\"],\"urls\":{\"Website\":\"http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\",\"role\":\"author\",\"keyword\":[\"deep neural networks\",\"fluid motion estimation\",\"particle image velocimetry\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":12,\"html\":\"\"},{\"title\":\"Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data\",\"pages\":\"45-56\",\"volume\":\"88\",\"websites\":\"https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285\",\"month\":\"4\",\"publisher\":\"Elsevier Ltd\",\"id\":\"363377e2-48c9-3547-a8c4-1cf8706456c9\",\"created\":\"2021-04-09T15:24:54.552Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:54.552Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.\",\"bibtype\":\"article\",\"author\":\"Díaz, Jose and Marton, Fabio and Gobbetti, Enrico\",\"doi\":\"10.1016/j.cag.2020.03.002\",\"journal\":\"Computers & Graphics\",\"bibtex\":\"@article{\\n title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},\\n type = {article},\\n year = {2020},\\n keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},\\n pages = {45-56},\\n volume = {88},\\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285},\\n month = {4},\\n publisher = {Elsevier Ltd},\\n id = {363377e2-48c9-3547-a8c4-1cf8706456c9},\\n created = {2021-04-09T15:24:54.552Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:54.552Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},\\n bibtype = {article},\\n author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},\\n doi = {10.1016/j.cag.2020.03.002},\\n journal = {Computers & Graphics}\\n}\",\"author_short\":[\"Díaz,  J.\",\"Marton,  F.\",\"Gobbetti,  E.\"],\"urls\":{\"Website\":\"https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\",\"role\":\"author\",\"keyword\":[\"Compression\",\"Direct volume rendering\",\"Learned dictionary\",\"Sparse coding\",\"Time-varying data\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":7,\"html\":\"\"},{\"title\":\"A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"55102\",\"volume\":\"32\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5128379\",\"month\":\"4\",\"publisher\":\"AIP Publishing LLCAIP Publishing\",\"id\":\"8c44d1e5-9a8d-3934-8a8e-5c4f91bf7721\",\"created\":\"2021-04-09T15:24:55.310Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:55.310Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian ...\",\"bibtype\":\"article\",\"author\":\"Samiee, Mehdi and Akhavan-Safaei, Ali and Zayernouri, Mohsen\",\"doi\":\"10.1063/1.5128379\",\"journal\":\"Physics of Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study},\\n type = {article},\\n year = {2020},\\n pages = {55102},\\n volume = {32},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5128379},\\n month = {4},\\n publisher = {AIP Publishing LLCAIP Publishing},\\n id = {8c44d1e5-9a8d-3934-8a8e-5c4f91bf7721},\\n created = {2021-04-09T15:24:55.310Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:55.310Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian ...},\\n bibtype = {article},\\n author = {Samiee, Mehdi and Akhavan-Safaei, Ali and Zayernouri, Mohsen},\\n doi = {10.1063/1.5128379},\\n journal = {Physics of Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Samiee,  M.\",\"Akhavan-Safaei,  A.\",\"Zayernouri,  M.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5128379\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":10,\"html\":\"\"},{\"title\":\"Wall-attached and wall-detached eddies in wall-bounded turbulent flows\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"boundary layer structure,turbulence theory,turbulent boundary layers\",\"pages\":\"A30\",\"volume\":\"885\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University Press\",\"id\":\"3bd35814-20d4-35a0-a335-1615f7927ae3\",\"created\":\"2021-04-09T15:24:55.789Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:55.789Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Hu, Ruifeng and Yang, Xiang I A and Zheng, Xiaojing\",\"doi\":\"10.1017/jfm.2019.980\",\"journal\":\"Journal of Fluid Mechanics\",\"bibtex\":\"@article{\\n title = {Wall-attached and wall-detached eddies in wall-bounded turbulent flows},\\n type = {article},\\n year = {2020},\\n keywords = {boundary layer structure,turbulence theory,turbulent boundary layers},\\n pages = {A30},\\n volume = {885},\\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {3bd35814-20d4-35a0-a335-1615f7927ae3},\\n created = {2021-04-09T15:24:55.789Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:55.789Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Hu, Ruifeng and Yang, Xiang I A and Zheng, Xiaojing},\\n doi = {10.1017/jfm.2019.980},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Hu,  R.\",\"Yang,  X., I., A.\",\"Zheng,  X.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020\",\"role\":\"author\",\"keyword\":[\"boundary layer structure\",\"turbulence theory\",\"turbulent boundary layers\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics\",\"pages\":\"47\",\"volume\":\"61\",\"websites\":\"http://link.springer.com/10.1007/s00348-019-2875-2\",\"month\":\"4\",\"publisher\":\"Springer\",\"id\":\"a329aa66-d78d-3813-af6b-87dfe61107eb\",\"created\":\"2021-04-09T15:24:56.527Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:56.527Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"We developed an open-source Lagrangian particle tracking (OpenLPT) based on the Shake-the-Box (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) method. The source code of OpenLPT is available on GitHub repository (@JHU-NI-LAB). The code features a new method that removes the majority of ghost particles at a high particle image density. The resulting percentage of ghost particles drops from 110% to 26% for image density at 0.125 ppp—nearly 84% of ghost particles are removed. Extensive tests of OpenLPT using synthetic data sets show that the code produces tracks with accuracy and processing time similar to the previously-reported values. In addition, OpenLPT has been parallelized to run on high-performance computing clusters to drastically increase its processing speed. To examine the code’s capability of tracking shadows of small tracers for backlit experiments, the blurred-particle effect was also included on synthetic images and OpenLPT was tested to process these noisy images. The results show that OpenLPT can also track shadows of a high-concentration of particles reliably in 3D. Based on the test, the optimal depth of field (DoF) and particle concentration for future experiments using Lagrangian shadow tracking are provided. For example, DoF controlled by the aperture should be set at around half of the size of the view area. At this DoF, most particles in the interrogation volume can be tracked, whereas particles outside the interrogation volume become too dim to affect results. 40 experimental data sets for a wide range of particle concentrations were also used for evaluating the code, and the results show a nice agreement with the synthetic tests.\",\"bibtype\":\"article\",\"author\":\"Tan, Shiyong and Salibindla, Ashwanth and Masuk, Ashik Ullah Mohammad and Ni, Rui\",\"doi\":\"10.1007/s00348-019-2875-2\",\"journal\":\"Experiments in Fluids\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking},\\n type = {article},\\n year = {2020},\\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\\n pages = {47},\\n volume = {61},\\n websites = {http://link.springer.com/10.1007/s00348-019-2875-2},\\n month = {4},\\n publisher = {Springer},\\n id = {a329aa66-d78d-3813-af6b-87dfe61107eb},\\n created = {2021-04-09T15:24:56.527Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:56.527Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {We developed an open-source Lagrangian particle tracking (OpenLPT) based on the Shake-the-Box (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) method. The source code of OpenLPT is available on GitHub repository (@JHU-NI-LAB). The code features a new method that removes the majority of ghost particles at a high particle image density. The resulting percentage of ghost particles drops from 110% to 26% for image density at 0.125 ppp—nearly 84% of ghost particles are removed. Extensive tests of OpenLPT using synthetic data sets show that the code produces tracks with accuracy and processing time similar to the previously-reported values. In addition, OpenLPT has been parallelized to run on high-performance computing clusters to drastically increase its processing speed. To examine the code’s capability of tracking shadows of small tracers for backlit experiments, the blurred-particle effect was also included on synthetic images and OpenLPT was tested to process these noisy images. The results show that OpenLPT can also track shadows of a high-concentration of particles reliably in 3D. Based on the test, the optimal depth of field (DoF) and particle concentration for future experiments using Lagrangian shadow tracking are provided. For example, DoF controlled by the aperture should be set at around half of the size of the view area. At this DoF, most particles in the interrogation volume can be tracked, whereas particles outside the interrogation volume become too dim to affect results. 40 experimental data sets for a wide range of particle concentrations were also used for evaluating the code, and the results show a nice agreement with the synthetic tests.},\\n bibtype = {article},\\n author = {Tan, Shiyong and Salibindla, Ashwanth and Masuk, Ashik Ullah Mohammad and Ni, Rui},\\n doi = {10.1007/s00348-019-2875-2},\\n journal = {Experiments in Fluids},\\n number = {2}\\n}\",\"author_short\":[\"Tan,  S.\",\"Salibindla,  A.\",\"Masuk,  A., U., M.\",\"Ni,  R.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-019-2875-2\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020\",\"role\":\"author\",\"keyword\":[\"Engineering Fluid Dynamics\",\"Engineering Thermodynamics\",\"Fluid\",\"Heat and Mass Transfer\",\"and Aerodynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"13302\",\"volume\":\"32\",\"websites\":\"http://aip.scitation.org/doi/10.1063/1.5139028\",\"month\":\"4\",\"publisher\":\"American Institute of Physics Inc.\",\"id\":\"39347325-914b-3dc5-abf4-3bffa7a604d6\",\"created\":\"2021-04-09T15:24:57.014Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:57.014Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Particle stress is known to play a vital role in turbulence modulation. However, the earlier studies on particle stress were mostly confined to the cases of spherical and elongated particles. In the present study, we investigated the stress generated in dilute suspensions of inertialess spheroids with various shapes in wall-bounded turbulence. We performed direct numerical simulations of turbulent particle-laden channel flows utilizing a one-way coupled Eulerian-Lagrangian approach. The stress in the suspension of oblate spheroids was examined in detail and compared with prolate spheroid cases for the first time. The results show that particle stress is strongly dependent on particle shape and the stress of the oblate spheroid is qualitatively different from the case of prolate particles. However, we found that the fluctuating spanwise shear stress of flat oblate spheroids, which makes a significant contribution to turbulence dissipation, is in the same order of magnitude of the term generated by elongated prolate spheroids at a constant volume fraction. We also examined the effect of the Reynolds number on the particle stress in channel flows at Reτ = 180 and 1000. The results reveal a negligible influence on the mean stresses, but the fluctuating stresses are significantly Reynolds number dependent. In the buffer layer, we observed the correlations between the particle stress of spheroids and the fluctuating velocity of the fluid in the streamwise direction, which could be attributed to the different orientation of spheroids and fluid strain rate in low- and high-speed streaks of near-wall turbulence.\",\"bibtype\":\"article\",\"author\":\"Wang, Ze and Zhao, Lihao\",\"doi\":\"10.1063/1.5139028\",\"journal\":\"Physics of Fluids\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow},\\n type = {article},\\n year = {2020},\\n pages = {13302},\\n volume = {32},\\n websites = {http://aip.scitation.org/doi/10.1063/1.5139028},\\n month = {4},\\n publisher = {American Institute of Physics Inc.},\\n id = {39347325-914b-3dc5-abf4-3bffa7a604d6},\\n created = {2021-04-09T15:24:57.014Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:57.014Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Particle stress is known to play a vital role in turbulence modulation. However, the earlier studies on particle stress were mostly confined to the cases of spherical and elongated particles. In the present study, we investigated the stress generated in dilute suspensions of inertialess spheroids with various shapes in wall-bounded turbulence. We performed direct numerical simulations of turbulent particle-laden channel flows utilizing a one-way coupled Eulerian-Lagrangian approach. The stress in the suspension of oblate spheroids was examined in detail and compared with prolate spheroid cases for the first time. The results show that particle stress is strongly dependent on particle shape and the stress of the oblate spheroid is qualitatively different from the case of prolate particles. However, we found that the fluctuating spanwise shear stress of flat oblate spheroids, which makes a significant contribution to turbulence dissipation, is in the same order of magnitude of the term generated by elongated prolate spheroids at a constant volume fraction. We also examined the effect of the Reynolds number on the particle stress in channel flows at Reτ = 180 and 1000. The results reveal a negligible influence on the mean stresses, but the fluctuating stresses are significantly Reynolds number dependent. In the buffer layer, we observed the correlations between the particle stress of spheroids and the fluctuating velocity of the fluid in the streamwise direction, which could be attributed to the different orientation of spheroids and fluid strain rate in low- and high-speed streaks of near-wall turbulence.},\\n bibtype = {article},\\n author = {Wang, Ze and Zhao, Lihao},\\n doi = {10.1063/1.5139028},\\n journal = {Physics of Fluids},\\n number = {1}\\n}\",\"author_short\":[\"Wang,  Z.\",\"Zhao,  L.\"],\"urls\":{\"Website\":\"http://aip.scitation.org/doi/10.1063/1.5139028\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Pressure power spectrum in high-Reynolds number wall-bounded flows\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"108620\",\"volume\":\"84\",\"websites\":\"https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916\",\"month\":\"4\",\"publisher\":\"Elsevier\",\"id\":\"b85f5b6f-a0aa-376a-ad98-fc145ff5b768\",\"created\":\"2021-04-09T15:24:57.575Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:57.575Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Xu, Haosen H A and Towne, Aaron and Yang, Xiang I A and Marusic, Ivan\",\"doi\":\"10.1016/j.ijheatfluidflow.2020.108620\",\"journal\":\"International Journal of Heat and Fluid Flow\",\"bibtex\":\"@article{\\n title = {Pressure power spectrum in high-Reynolds number wall-bounded flows},\\n type = {article},\\n year = {2020},\\n pages = {108620},\\n volume = {84},\\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916},\\n month = {4},\\n publisher = {Elsevier},\\n id = {b85f5b6f-a0aa-376a-ad98-fc145ff5b768},\\n created = {2021-04-09T15:24:57.575Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:57.575Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Xu, Haosen H A and Towne, Aaron and Yang, Xiang I A and Marusic, Ivan},\\n doi = {10.1016/j.ijheatfluidflow.2020.108620},\\n journal = {International Journal of Heat and Fluid Flow}\\n}\",\"author_short\":[\"Xu,  H., H., A.\",\"Towne,  A.\",\"Yang,  X., I., A.\",\"Marusic,  I.\"],\"urls\":{\"Website\":\"https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Comparison of Rendering Techniques for 3D Line Sets with Transparency\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"1\",\"websites\":\"https://ieeexplore.ieee.org/document/9007507/\",\"month\":\"4\",\"publisher\":\"Institute of Electrical and Electronics Engineers (IEEE)\",\"id\":\"77692821-f40f-3cb9-9904-265929f62c49\",\"created\":\"2021-04-09T15:24:58.040Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:58.040Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visualizing trajectories of tracer particles in flow fields. Transparency is then used to fade out lines deemed unimportant, based on, for instance, geometric properties or attributes defined along them. Since accurate blending of transparent lines requires rendering the lines in back-to-front or front-to-back order, enforcing this order for 3D line sets with tens or even hundreds of thousands of elements becomes challenging. In this paper, we study CPU and GPU rendering techniques for large transparent 3D line sets. We compare accurate and approximate techniques using optimized implementations and a number of benchmark data sets. We discuss the effects of data size and transparency on quality, performance and memory consumption. Based on our study, we propose two improvements to per-pixel fragment lists and multi-layer alpha blending. The first improves the rendering speed via an improved GPU sorting operation, and the second improves rendering quality via a transparency-based bucketing.\",\"bibtype\":\"article\",\"author\":\"Kern, Michael and Neuhauser, Christoph and Maack, Torben and Han, Mengjiao and Usher, Will and Westermann, Ruediger\",\"doi\":\"10.1109/TVCG.2020.2975795\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"bibtex\":\"@article{\\n title = {A Comparison of Rendering Techniques for 3D Line Sets with Transparency},\\n type = {article},\\n year = {2020},\\n pages = {1},\\n websites = {https://ieeexplore.ieee.org/document/9007507/},\\n month = {4},\\n publisher = {Institute of Electrical and Electronics Engineers (IEEE)},\\n id = {77692821-f40f-3cb9-9904-265929f62c49},\\n created = {2021-04-09T15:24:58.040Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:58.040Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visualizing trajectories of tracer particles in flow fields. Transparency is then used to fade out lines deemed unimportant, based on, for instance, geometric properties or attributes defined along them. Since accurate blending of transparent lines requires rendering the lines in back-to-front or front-to-back order, enforcing this order for 3D line sets with tens or even hundreds of thousands of elements becomes challenging. In this paper, we study CPU and GPU rendering techniques for large transparent 3D line sets. We compare accurate and approximate techniques using optimized implementations and a number of benchmark data sets. We discuss the effects of data size and transparency on quality, performance and memory consumption. Based on our study, we propose two improvements to per-pixel fragment lists and multi-layer alpha blending. The first improves the rendering speed via an improved GPU sorting operation, and the second improves rendering quality via a transparency-based bucketing.},\\n bibtype = {article},\\n author = {Kern, Michael and Neuhauser, Christoph and Maack, Torben and Han, Mengjiao and Usher, Will and Westermann, Ruediger},\\n doi = {10.1109/TVCG.2020.2975795},\\n journal = {IEEE Transactions on Visualization and Computer Graphics}\\n}\",\"author_short\":[\"Kern,  M.\",\"Neuhauser,  C.\",\"Maack,  T.\",\"Han,  M.\",\"Usher,  W.\",\"Westermann,  R.\"],\"urls\":{\"Website\":\"https://ieeexplore.ieee.org/document/9007507/\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra\",\"pages\":\"1-15\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\",\"month\":\"4\",\"publisher\":\"Taylor and Francis Ltd.\",\"id\":\"5fb83e3f-627a-3eb4-98b2-e71bbadefb97\",\"created\":\"2021-04-09T15:24:58.541Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:58.541Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.\",\"bibtype\":\"article\",\"author\":\"Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran\",\"doi\":\"10.1080/00221686.2020.1729265\",\"journal\":\"Journal of Hydraulic Research\",\"bibtex\":\"@article{\\n title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020},\\n type = {article},\\n year = {2020},\\n keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},\\n pages = {1-15},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},\\n month = {4},\\n publisher = {Taylor and Francis Ltd.},\\n id = {5fb83e3f-627a-3eb4-98b2-e71bbadefb97},\\n created = {2021-04-09T15:24:58.541Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:58.541Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},\\n bibtype = {article},\\n author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},\\n doi = {10.1080/00221686.2020.1729265},\\n journal = {Journal of Hydraulic Research}\\n}\",\"author_short\":[\"Ahmed,  U.\",\"Apsley,  D.\",\"Stallard,  T.\",\"Stansby,  P.\",\"Afgan,  I.\"],\"urls\":{\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020\",\"role\":\"author\",\"keyword\":[\"Anisotropy\",\"budgets\",\"open-channel flow\",\"tidal stream turbines\",\"turbulence length scales\",\"turbulence spectra\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"94013\",\"volume\":\"31\",\"websites\":\"https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d\",\"month\":\"4\",\"publisher\":\"Institute of Physics Publishing\",\"id\":\"48519ba0-b237-3437-bb93-5ee1105659c9\",\"created\":\"2021-04-09T15:24:59.283Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:59.283Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.\",\"bibtype\":\"article\",\"author\":\"Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian\",\"doi\":\"10.1088/1361-6501/ab848d\",\"journal\":\"Measurement Science and Technology\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},\\n type = {article},\\n year = {2020},\\n pages = {94013},\\n volume = {31},\\n websites = {https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d},\\n month = {4},\\n publisher = {Institute of Physics Publishing},\\n id = {48519ba0-b237-3437-bb93-5ee1105659c9},\\n created = {2021-04-09T15:24:59.283Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:59.283Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},\\n bibtype = {article},\\n author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},\\n doi = {10.1088/1361-6501/ab848d},\\n journal = {Measurement Science and Technology},\\n number = {9}\\n}\",\"author_short\":[\"Ehlers,  F.\",\"Schröder,  A.\",\"Gesemann,  S.\"],\"urls\":{\"Website\":\"https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":14,\"html\":\"\"},{\"title\":\"Adaptive ensemble PTV\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"PIV,PTV,spatial resolution,turbulent flow statistics\",\"pages\":\"85301\",\"volume\":\"31\",\"websites\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta\",\"month\":\"4\",\"publisher\":\"Institute of Physics Publishing\",\"id\":\"40b7bc2d-a36e-33e4-8f93-3ef9a1935879\",\"created\":\"2021-04-09T15:24:59.778Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:24:59.778Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out.\",\"bibtype\":\"article\",\"author\":\"Raiola, Marco and Lopez-Nuñez, Elena and Cafiero, Gioacchino and Discetti, Stefano\",\"doi\":\"10.1088/1361-6501/ab82bf\",\"journal\":\"Measurement Science and Technology\",\"number\":\"8\",\"bibtex\":\"@article{\\n title = {Adaptive ensemble PTV},\\n type = {article},\\n year = {2020},\\n keywords = {PIV,PTV,spatial resolution,turbulent flow statistics},\\n pages = {85301},\\n volume = {31},\\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta},\\n month = {4},\\n publisher = {Institute of Physics Publishing},\\n id = {40b7bc2d-a36e-33e4-8f93-3ef9a1935879},\\n created = {2021-04-09T15:24:59.778Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:24:59.778Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out.},\\n bibtype = {article},\\n author = {Raiola, Marco and Lopez-Nuñez, Elena and Cafiero, Gioacchino and Discetti, Stefano},\\n doi = {10.1088/1361-6501/ab82bf},\\n journal = {Measurement Science and Technology},\\n number = {8}\\n}\",\"author_short\":[\"Raiola,  M.\",\"Lopez-Nuñez,  E.\",\"Cafiero,  G.\",\"Discetti,  S.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020\",\"role\":\"author\",\"keyword\":[\"PIV\",\"PTV\",\"spatial resolution\",\"turbulent flow statistics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Priori Sub-grid Modelling Using Artificial Neural Networks\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"ANN,LES,turbulence\",\"pages\":\"397-417\",\"volume\":\"34\",\"websites\":\"https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116\",\"month\":\"4\",\"publisher\":\"Taylor and Francis Ltd.\",\"id\":\"d7410cf0-8ad5-3cc3-afea-2ec408731071\",\"created\":\"2021-04-09T15:25:00.319Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:00.319Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation of Homogeneous Isotropic Turbulence at different Reynolds numbers. The results show that the correlation coefficients are superior to other sub-grid models, using a similar set of input variables. As the ANN model extrapolates to larger Reynolds, the correlation coefficient decreases. However, it remains higher than other sub-grid approaches, and suggest that the combined LES-ANN methodology can potentially be used as a sub-grid model at realistic Reynolds numbers. Models derived from Homogeneous Isotropic Turbulence can also be used in different simple flows and provide relatively good agreement.\",\"bibtype\":\"article\",\"author\":\"Prat, Alvaro and Sautory, Theophile and Navarro-Martinez, S\",\"doi\":\"10.1080/10618562.2020.1789116\",\"journal\":\"International Journal of Computational Fluid Dynamics\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {A Priori Sub-grid Modelling Using Artificial Neural Networks},\\n type = {article},\\n year = {2020},\\n keywords = {ANN,LES,turbulence},\\n pages = {397-417},\\n volume = {34},\\n websites = {https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116},\\n month = {4},\\n publisher = {Taylor and Francis Ltd.},\\n id = {d7410cf0-8ad5-3cc3-afea-2ec408731071},\\n created = {2021-04-09T15:25:00.319Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:00.319Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation of Homogeneous Isotropic Turbulence at different Reynolds numbers. The results show that the correlation coefficients are superior to other sub-grid models, using a similar set of input variables. As the ANN model extrapolates to larger Reynolds, the correlation coefficient decreases. However, it remains higher than other sub-grid approaches, and suggest that the combined LES-ANN methodology can potentially be used as a sub-grid model at realistic Reynolds numbers. Models derived from Homogeneous Isotropic Turbulence can also be used in different simple flows and provide relatively good agreement.},\\n bibtype = {article},\\n author = {Prat, Alvaro and Sautory, Theophile and Navarro-Martinez, S},\\n doi = {10.1080/10618562.2020.1789116},\\n journal = {International Journal of Computational Fluid Dynamics},\\n number = {6}\\n}\",\"author_short\":[\"Prat,  A.\",\"Sautory,  T.\",\"Navarro-Martinez,  S.\"],\"urls\":{\"Website\":\"https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020\",\"role\":\"author\",\"keyword\":[\"ANN\",\"LES\",\"turbulence\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Robust principal component analysis for modal decomposition of corrupt fluid flows\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"doi:10.1103/PhysRevFluids.5.054401 url:https://doi\",\"pages\":\"54401\",\"volume\":\"5\",\"websites\":\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401\",\"month\":\"4\",\"publisher\":\"American Physical Society\",\"id\":\"0d4e9077-a45a-3e73-b1bf-865c5c74c7c8\",\"created\":\"2021-04-09T15:25:00.870Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:00.870Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Modal analysis techniques are used to identify patterns and develop reduced-order models in a variety of fluid applications. However, experimentally acquired flow fields may be corrupted with incorrect and missing entries, which may degrade modal decomposition. Here we use robust principal component analysis (RPCA) to improve the quality of flow-field data by leveraging global coherent structures to identify and replace spurious data points. RPCA is a robust variant of principal component analysis, also known as proper orthogonal decomposition in fluids, that decomposes a data matrix into the sum of a low-rank matrix containing coherent structures and a sparse matrix of outliers and corrupt entries. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. The performance is particularly striking when flow fields are analyzed using dynamic mode decomposition, which is sensitive to noise and outliers.\",\"bibtype\":\"article\",\"author\":\"Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L\",\"doi\":\"10.1103/PhysRevFluids.5.054401\",\"journal\":\"Physical Review Fluids\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Robust principal component analysis for modal decomposition of corrupt fluid flows},\\n type = {article},\\n year = {2020},\\n keywords = {doi:10.1103/PhysRevFluids.5.054401 url:https://doi},\\n pages = {54401},\\n volume = {5},\\n websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401},\\n month = {4},\\n publisher = {American Physical Society},\\n id = {0d4e9077-a45a-3e73-b1bf-865c5c74c7c8},\\n created = {2021-04-09T15:25:00.870Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:00.870Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Modal analysis techniques are used to identify patterns and develop reduced-order models in a variety of fluid applications. However, experimentally acquired flow fields may be corrupted with incorrect and missing entries, which may degrade modal decomposition. Here we use robust principal component analysis (RPCA) to improve the quality of flow-field data by leveraging global coherent structures to identify and replace spurious data points. RPCA is a robust variant of principal component analysis, also known as proper orthogonal decomposition in fluids, that decomposes a data matrix into the sum of a low-rank matrix containing coherent structures and a sparse matrix of outliers and corrupt entries. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. The performance is particularly striking when flow fields are analyzed using dynamic mode decomposition, which is sensitive to noise and outliers.},\\n bibtype = {article},\\n author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L},\\n doi = {10.1103/PhysRevFluids.5.054401},\\n journal = {Physical Review Fluids},\\n number = {5}\\n}\",\"author_short\":[\"Scherl,  I.\",\"Strom,  B.\",\"Shang,  J., K.\",\"Williams,  O.\",\"Polagye,  B., L.\",\"Brunton,  S., L.\"],\"urls\":{\"Website\":\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020\",\"role\":\"author\",\"keyword\":[\"doi:10.1103/PhysRevFluids.5.054401 url:https://doi\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Nanoflare Theory and Stochastic Reconnection\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"89\",\"volume\":\"4\",\"websites\":\"https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta\",\"month\":\"4\",\"publisher\":\"American Astronomical Society\",\"id\":\"e476ace8-2be9-37fa-8534-8643d2ebfb1b\",\"created\":\"2021-04-09T15:25:01.361Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:01.361Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Jafari, Amir and Vishniac, Ethan T and Xu, Siyao\",\"doi\":\"10.3847/2515-5172/ab9e02\",\"journal\":\"Research Notes of the AAS\",\"number\":\"6\",\"bibtex\":\"@article{\\n title = {Nanoflare Theory and Stochastic Reconnection},\\n type = {article},\\n year = {2020},\\n pages = {89},\\n volume = {4},\\n websites = {https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta},\\n month = {4},\\n publisher = {American Astronomical Society},\\n id = {e476ace8-2be9-37fa-8534-8643d2ebfb1b},\\n created = {2021-04-09T15:25:01.361Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:01.361Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Jafari, Amir and Vishniac, Ethan T and Xu, Siyao},\\n doi = {10.3847/2515-5172/ab9e02},\\n journal = {Research Notes of the AAS},\\n number = {6}\\n}\",\"author_short\":[\"Jafari,  A.\",\"Vishniac,  E., T.\",\"Xu,  S.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity\",\"type\":\"inproceedings\",\"year\":\"2020\",\"websites\":\"https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060\",\"month\":\"4\",\"publisher\":\"American Institute of Aeronautics and Astronautics\",\"id\":\"2178269a-95b7-37d7-9746-7dadf37353f3\",\"created\":\"2021-04-09T15:25:02.054Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:02.054Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Myhre, Nicodemus and Prazenica, Richard J and Balas, Mark and Gnanamanickam, Ebenezer P\",\"doi\":\"10.2514/6.2020-3060\",\"booktitle\":\"AIAA AVIATION 2020 FORUM\",\"bibtex\":\"@inproceedings{\\n title = {A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity},\\n type = {inproceedings},\\n year = {2020},\\n websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060},\\n month = {4},\\n publisher = {American Institute of Aeronautics and Astronautics},\\n id = {2178269a-95b7-37d7-9746-7dadf37353f3},\\n created = {2021-04-09T15:25:02.054Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:02.054Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {inproceedings},\\n private_publication = {false},\\n bibtype = {inproceedings},\\n author = {Myhre, Nicodemus and Prazenica, Richard J and Balas, Mark and Gnanamanickam, Ebenezer P},\\n doi = {10.2514/6.2020-3060},\\n booktitle = {AIAA AVIATION 2020 FORUM}\\n}\",\"author_short\":[\"Myhre,  N.\",\"Prazenica,  R., J.\",\"Balas,  M.\",\"Gnanamanickam,  E., P.\"],\"urls\":{\"Website\":\"https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":8,\"html\":\"\"},{\"title\":\"Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"homogeneous turbulence,isotropic turbulence,turbulence theory\",\"pages\":\"A27\",\"volume\":\"900\",\"websites\":\"https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article\",\"month\":\"4\",\"publisher\":\"Cambridge University 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{https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article},\\n month = {4},\\n publisher = {Cambridge University Press},\\n id = {a9e970dd-84ff-353a-9f37-6fb053ef372c},\\n created = {2021-04-09T15:25:02.534Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:02.534Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},\\n doi = {10.1017/jfm.2020.495},\\n journal = {Journal of Fluid Mechanics}\\n}\",\"author_short\":[\"Viggiano,  B.\",\"Friedrich,  J.\",\"Volk,  R.\",\"Bourgoin,  M.\",\"Cal,  R., B.\",\"Chevillard,  L.\"],\"urls\":{\"Website\":\"https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\",\"role\":\"author\",\"keyword\":[\"homogeneous turbulence\",\"isotropic turbulence\",\"turbulence theory\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":11,\"html\":\"\"},{\"title\":\"Vision-based correspondence using relaxation algorithms for particle tracking velocimetry\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"25303\",\"volume\":\"32\",\"websites\":\"https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta\",\"month\":\"4\",\"publisher\":\"IOP Publishing\",\"id\":\"750f71b5-9fd8-3a2b-96db-645511a456fb\",\"created\":\"2021-04-09T15:25:03.224Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:03.224Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Benkovic, Théo and Krawczynski, Jean-François and Druault, Philippe\",\"doi\":\"10.1088/1361-6501/abb437\",\"journal\":\"Measurement Science and Technology\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Vision-based correspondence using relaxation algorithms for particle tracking velocimetry},\\n type = {article},\\n year = {2021},\\n pages = {25303},\\n volume = {32},\\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta},\\n month = {4},\\n publisher = {IOP Publishing},\\n id = {750f71b5-9fd8-3a2b-96db-645511a456fb},\\n created = {2021-04-09T15:25:03.224Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:03.224Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Benkovic, Théo and Krawczynski, Jean-François and Druault, Philippe},\\n doi = {10.1088/1361-6501/abb437},\\n journal = {Measurement Science and Technology},\\n number = {2}\\n}\",\"author_short\":[\"Benkovic,  T.\",\"Krawczynski,  J.\",\"Druault,  P.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Dense particle tracking using a learned predictive model\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics\",\"pages\":\"223\",\"volume\":\"61\",\"websites\":\"http://link.springer.com/10.1007/s00348-020-03061-y\",\"month\":\"4\",\"publisher\":\"Springer\",\"id\":\"fa0bf048-fc79-3234-9569-946909b0b385\",\"created\":\"2021-04-09T15:25:03.814Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:03.814Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle's velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases-turbulent channel flow, flow through a T-junction, and swimming microorganisms-demonstrate the broad applicability of the proposed method to different fields with unique challenges. Graphic abstract 1 Introduction\",\"bibtype\":\"article\",\"author\":\"Mallery, Kevin and Shao, Siyao and Hong, Jiarong\",\"doi\":\"10.1007/s00348-020-03061-y\",\"journal\":\"Experiments in Fluids\",\"number\":\"10\",\"bibtex\":\"@article{\\n title = {Dense particle tracking using a learned predictive model},\\n type = {article},\\n year = {2020},\\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\\n pages = {223},\\n volume = {61},\\n websites = {http://link.springer.com/10.1007/s00348-020-03061-y},\\n month = {4},\\n publisher = {Springer},\\n id = {fa0bf048-fc79-3234-9569-946909b0b385},\\n created = {2021-04-09T15:25:03.814Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:03.814Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle's velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases-turbulent channel flow, flow through a T-junction, and swimming microorganisms-demonstrate the broad applicability of the proposed method to different fields with unique challenges. Graphic abstract 1 Introduction},\\n bibtype = {article},\\n author = {Mallery, Kevin and Shao, Siyao and Hong, Jiarong},\\n doi = {10.1007/s00348-020-03061-y},\\n journal = {Experiments in Fluids},\\n number = {10}\\n}\",\"author_short\":[\"Mallery,  K.\",\"Shao,  S.\",\"Hong,  J.\"],\"urls\":{\"Website\":\"http://link.springer.com/10.1007/s00348-020-03061-y\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020\",\"role\":\"author\",\"keyword\":[\"Engineering Fluid Dynamics\",\"Engineering Thermodynamics\",\"Fluid\",\"Heat and Mass Transfer\",\"and Aerodynamics\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Spectral energy analysis of bulk three-dimensional active nematic turbulence\",\"type\":\"article\",\"year\":\"2020\",\"pages\":\"9059-9068\",\"volume\":\"16\",\"websites\":\"http://xlink.rsc.org/?DOI=C9SM02492A\",\"publisher\":\"Royal Society of Chemistry (RSC)\",\"id\":\"2dcd947a-1b83-353a-a5c2-c938a56fe531\",\"created\":\"2021-04-09T15:25:04.756Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:04.756Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"Energy spectrum analysis of 3D active nematic turbulence is perfomed and combined with geometrical analysis of ordering and flow fields.\",\"bibtype\":\"article\",\"author\":\"Krajnik, Žiga and Kos, Žiga and Ravnik, Miha\",\"doi\":\"10.1039/C9SM02492A\",\"journal\":\"Soft Matter\",\"number\":\"39\",\"bibtex\":\"@article{\\n title = {Spectral energy analysis of bulk three-dimensional active nematic turbulence},\\n type = {article},\\n year = {2020},\\n pages = {9059-9068},\\n volume = {16},\\n websites = {http://xlink.rsc.org/?DOI=C9SM02492A},\\n publisher = {Royal Society of Chemistry (RSC)},\\n id = {2dcd947a-1b83-353a-a5c2-c938a56fe531},\\n created = {2021-04-09T15:25:04.756Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:04.756Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {Energy spectrum analysis of 3D active nematic turbulence is perfomed and combined with geometrical analysis of ordering and flow fields.},\\n bibtype = {article},\\n author = {Krajnik, Žiga and Kos, Žiga and Ravnik, Miha},\\n doi = {10.1039/C9SM02492A},\\n journal = {Soft Matter},\\n number = {39}\\n}\",\"author_short\":[\"Krajnik,  Ž.\",\"Kos,  Ž.\",\"Ravnik,  M.\"],\"urls\":{\"Website\":\"http://xlink.rsc.org/?DOI=C9SM02492A\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"Shallow neural networks for fluid flow reconstruction with limited sensors\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"flow field estimation,fluid dynamics,machine learning,neural networks,sensors\",\"pages\":\"20200097\",\"volume\":\"476\",\"websites\":\"https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097\",\"month\":\"4\",\"publisher\":\"The Royal Society\",\"id\":\"0bae8a3f-c6d6-3a4c-a627-b21c29e1dee7\",\"created\":\"2021-04-09T15:25:05.426Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:05.426Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"<p>In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.</p>\",\"bibtype\":\"article\",\"author\":\"Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan\",\"doi\":\"10.1098/rspa.2020.0097\",\"journal\":\"Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences\",\"number\":\"2238\",\"bibtex\":\"@article{\\n title = {Shallow neural networks for fluid flow reconstruction with limited sensors},\\n type = {article},\\n year = {2020},\\n keywords = {flow field estimation,fluid dynamics,machine learning,neural networks,sensors},\\n pages = {20200097},\\n volume = {476},\\n websites = {https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097},\\n month = {4},\\n publisher = {The Royal Society},\\n id = {0bae8a3f-c6d6-3a4c-a627-b21c29e1dee7},\\n created = {2021-04-09T15:25:05.426Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:05.426Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {<p>In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.</p>},\\n bibtype = {article},\\n author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan},\\n doi = {10.1098/rspa.2020.0097},\\n journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences},\\n number = {2238}\\n}\",\"author_short\":[\"Erichson,  N., B.\",\"Mathelin,  L.\",\"Yao,  Z.\",\"Brunton,  S., L.\",\"Mahoney,  M., W.\",\"Kutz,  J., N.\"],\"urls\":{\"Website\":\"https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020\",\"role\":\"author\",\"keyword\":[\"flow field estimation\",\"fluid dynamics\",\"machine learning\",\"neural networks\",\"sensors\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":6,\"html\":\"\"},{\"title\":\"Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method\",\"type\":\"article\",\"year\":\"2020\",\"keywords\":\"Poisson equation,boundary condition,error-embedded data,pressure,pressure gradient,pressure reconstruction\",\"pages\":\"55301\",\"volume\":\"31\",\"websites\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta\",\"month\":\"4\",\"publisher\":\"Institute of Physics Publishing\",\"id\":\"7dfa7c22-5ab5-345b-bbd0-3f7dd6656c75\",\"created\":\"2021-04-09T15:25:06.098Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-09T15:25:06.098Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"abstract\":\"This paper reports a theoretical analysis and the corresponding numerical and experimental validation results of the error propagation characteristics of the omnidirectional integration method used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omnidirectional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise embedded in the measured pressure gradient. Accurate determination of the boundary pressure values is the first step in ensuring the accuracy of the reconstructed pressure. The boundary pressure error consists of two parts, with one part decreasing exponentially in magnitude and eventually vanishing, and the other remaining as a constant with small magnitude through iteration. These results are verified by using a direct numerical simulation database of isotropic turbulence flow superimposed with noise at various noise levels and spatial distribution schemes to simulate noise embedded data. The nondimensionalized average error of the reconstructed pressure based on 1000 statistically independent pressure gradient field realizations with a 40% added noise level is 0.854 ± 0.406 for the pressure Poisson equation with Neumann boundary condition, 0.154 ± 0.015 for the circular virtual boundary omnidirectional integration and 0.149 ± 0.015 for the rotating parallel ray omnidirectional integration. If the converged boundary pressure values obtained by the rotating parallel ray are used as Dirichlet boundary conditions, the average pressure error by Poisson is reduced to 0.151 ± 0.015. Of the different variations of the omnidirectional methods, the parallel ray method shows the best performance and therefore is the method of choice. Comparisons of the performance of these pressure reconstruction methods using an experimentally obtained turbulent shear layer flow over an open cavity are in agreement with the conclusions obtained with the DNS simulation data. With the noise added DNS data, limitations regarding the pressure reconstruction methods in determining pressure fluctuation statistics are also identified and quantified.\",\"bibtype\":\"article\",\"author\":\"Liu, Xiaofeng and Moreto, Jose Roberto\",\"doi\":\"10.1088/1361-6501/ab6c28\",\"journal\":\"Measurement Science and Technology\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method},\\n type = {article},\\n year = {2020},\\n keywords = {Poisson equation,boundary condition,error-embedded data,pressure,pressure gradient,pressure reconstruction},\\n pages = {55301},\\n volume = {31},\\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta},\\n month = {4},\\n publisher = {Institute of Physics Publishing},\\n id = {7dfa7c22-5ab5-345b-bbd0-3f7dd6656c75},\\n created = {2021-04-09T15:25:06.098Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-09T15:25:06.098Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n abstract = {This paper reports a theoretical analysis and the corresponding numerical and experimental validation results of the error propagation characteristics of the omnidirectional integration method used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omnidirectional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise embedded in the measured pressure gradient. Accurate determination of the boundary pressure values is the first step in ensuring the accuracy of the reconstructed pressure. The boundary pressure error consists of two parts, with one part decreasing exponentially in magnitude and eventually vanishing, and the other remaining as a constant with small magnitude through iteration. These results are verified by using a direct numerical simulation database of isotropic turbulence flow superimposed with noise at various noise levels and spatial distribution schemes to simulate noise embedded data. The nondimensionalized average error of the reconstructed pressure based on 1000 statistically independent pressure gradient field realizations with a 40% added noise level is 0.854 ± 0.406 for the pressure Poisson equation with Neumann boundary condition, 0.154 ± 0.015 for the circular virtual boundary omnidirectional integration and 0.149 ± 0.015 for the rotating parallel ray omnidirectional integration. If the converged boundary pressure values obtained by the rotating parallel ray are used as Dirichlet boundary conditions, the average pressure error by Poisson is reduced to 0.151 ± 0.015. Of the different variations of the omnidirectional methods, the parallel ray method shows the best performance and therefore is the method of choice. Comparisons of the performance of these pressure reconstruction methods using an experimentally obtained turbulent shear layer flow over an open cavity are in agreement with the conclusions obtained with the DNS simulation data. With the noise added DNS data, limitations regarding the pressure reconstruction methods in determining pressure fluctuation statistics are also identified and quantified.},\\n bibtype = {article},\\n author = {Liu, Xiaofeng and Moreto, Jose Roberto},\\n doi = {10.1088/1361-6501/ab6c28},\\n journal = {Measurement Science and Technology},\\n number = {5}\\n}\",\"author_short\":[\"Liu,  X.\",\"Moreto,  J., R.\"],\"urls\":{\"Website\":\"https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020\",\"role\":\"author\",\"keyword\":[\"Poisson equation\",\"boundary condition\",\"error-embedded data\",\"pressure\",\"pressure gradient\",\"pressure reconstruction\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":5,\"html\":\"\"},{\"title\":\"A perspective on machine learning methods in turbulence modeling\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"LES,RANS,closure models,machine learning,turbulence simulation\",\"pages\":\"e202100002\",\"volume\":\"44\",\"websites\":\"https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002\",\"month\":\"3\",\"publisher\":\"John Wiley and Sons Inc\",\"day\":\"4\",\"id\":\"6e94090b-dae2-3ea5-ac66-dbb72308e871\",\"created\":\"2021-04-13T18:26:48.366Z\",\"accessed\":\"2021-04-13\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-13T18:26:49.437Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues but also on the advantages and promises of machine learning (ML) methods applied to parameter estimation, model identification, closure term reconstruction, and beyond, mostly from the perspective of large Eddy simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics, and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. In this study, we present a survey of the current data-driven model concepts and methods, highlight important developments, and put them into the context of the discussed challenges.\",\"bibtype\":\"article\",\"author\":\"Beck, Andrea and Kurz, Marius\",\"doi\":\"10.1002/gamm.202100002\",\"journal\":\"GAMM-Mitteilungen\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {A perspective on machine learning methods in turbulence modeling},\\n type = {article},\\n year = {2021},\\n keywords = {LES,RANS,closure models,machine learning,turbulence simulation},\\n pages = {e202100002},\\n volume = {44},\\n websites = {https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002},\\n month = {3},\\n publisher = {John Wiley and Sons Inc},\\n day = {4},\\n id = {6e94090b-dae2-3ea5-ac66-dbb72308e871},\\n created = {2021-04-13T18:26:48.366Z},\\n accessed = {2021-04-13},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-13T18:26:49.437Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues but also on the advantages and promises of machine learning (ML) methods applied to parameter estimation, model identification, closure term reconstruction, and beyond, mostly from the perspective of large Eddy simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics, and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. In this study, we present a survey of the current data-driven model concepts and methods, highlight important developments, and put them into the context of the discussed challenges.},\\n bibtype = {article},\\n author = {Beck, Andrea and Kurz, Marius},\\n doi = {10.1002/gamm.202100002},\\n journal = {GAMM-Mitteilungen},\\n number = {1}\\n}\",\"author_short\":[\"Beck,  A.\",\"Kurz,  M.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/112ac63e-5f1c-1b03-61f7-534e4ae5b885/full_text.pdf.pdf\",\"Website\":\"https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021\",\"role\":\"author\",\"keyword\":[\"LES\",\"RANS\",\"closure models\",\"machine learning\",\"turbulence simulation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Learning Similarity Metrics for Numerical Simulations\",\"type\":\"techreport\",\"year\":\"2020\",\"keywords\":\"CNNs,PDEs,metric learning,numerical simulation,perceptual evaluation,physics simulation\",\"pages\":\"5349-5360\",\"websites\":\"https://github.com/tum-pbs/LSIM.\",\"month\":\"11\",\"publisher\":\"PMLR\",\"day\":\"21\",\"id\":\"5b1c7a6a-a307-3046-be8c-474af85470ca\",\"created\":\"2021-04-13T18:41:19.893Z\",\"accessed\":\"2021-04-13\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-13T18:41:20.784Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of nu­ merical simulation sources. We focus on scalar time-dependent 2D data that commonly arises from motion and transport-based partial differen­ tial equations (PDEs). Our method employs a Siamese network architecture that is motivated by the mathematical properties of a metric. We leverage a controllable data generation setup with PDE solvers to create increasingly different out­ puts from a reference simulation in a controlled environment. A central component of our learned metric is a specialized loss function that intro­ duces knowledge about the correlation between single data samples into the training process. To demonstrate that the proposed approach outper­ forms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the dif­ ferent methods on a large range of test data. Addi­ tionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.\",\"bibtype\":\"techreport\",\"author\":\"Kohl, Georg and Um, Kiwon and Thuerey, Nils\",\"bibtex\":\"@techreport{\\n title = {Learning Similarity Metrics for Numerical Simulations},\\n type = {techreport},\\n year = {2020},\\n keywords = {CNNs,PDEs,metric learning,numerical simulation,perceptual evaluation,physics simulation},\\n pages = {5349-5360},\\n websites = {https://github.com/tum-pbs/LSIM.},\\n month = {11},\\n publisher = {PMLR},\\n day = {21},\\n id = {5b1c7a6a-a307-3046-be8c-474af85470ca},\\n created = {2021-04-13T18:41:19.893Z},\\n accessed = {2021-04-13},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-13T18:41:20.784Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of nu­ merical simulation sources. We focus on scalar time-dependent 2D data that commonly arises from motion and transport-based partial differen­ tial equations (PDEs). Our method employs a Siamese network architecture that is motivated by the mathematical properties of a metric. We leverage a controllable data generation setup with PDE solvers to create increasingly different out­ puts from a reference simulation in a controlled environment. A central component of our learned metric is a specialized loss function that intro­ duces knowledge about the correlation between single data samples into the training process. To demonstrate that the proposed approach outper­ forms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the dif­ ferent methods on a large range of test data. Addi­ tionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.},\\n bibtype = {techreport},\\n author = {Kohl, Georg and Um, Kiwon and Thuerey, Nils}\\n}\",\"author_short\":[\"Kohl,  G.\",\"Um,  K.\",\"Thuerey,  N.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/2a19625b-99c7-da31-5c26-8287f273bf25/full_text.pdf.pdf\",\"Website\":\"https://github.com/tum-pbs/LSIM.\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020\",\"role\":\"author\",\"keyword\":[\"CNNs\",\"PDEs\",\"metric learning\",\"numerical simulation\",\"perceptual evaluation\",\"physics simulation\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Drilling dataset exploration, processing and interpretation using volve field data\",\"type\":\"inproceedings\",\"year\":\"2020\",\"keywords\":\"Catalysts,Drilling,Gages\",\"volume\":\"11\",\"month\":\"12\",\"publisher\":\"American Society of Mechanical Engineers (ASME)\",\"day\":\"18\",\"id\":\"d0725421-9955-38ea-af18-eb63688a8a6f\",\"created\":\"2021-04-13T18:50:47.936Z\",\"accessed\":\"2021-04-13\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-13T18:50:47.936Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"In 2018 Equinor made an unprecedented step for an energy company and made a multi-terabyte dataset from Volve field open. However, there is a long way from downloading data to executing meaningful analysis. With no way of quickly evaluating the data due to its size and unfamiliar file formats the use of Volve data was so far limited. This paper presents our exploratory work related to the real-time drilling part of the dataset. We provide description of common obstacles and approaches for overcoming them. We also describe specific contents of the dataset for others to gauge the potential for case studies. We hope that this will lower the bar for Volve field data accessibility, promote research, and become a catalyst for other data science projects.\",\"bibtype\":\"inproceedings\",\"author\":\"Tunkiel, Andrzej T. and Wiktorski, Tomasz and Sui, Dan\",\"doi\":\"10.1115/OMAE2020-18151\",\"booktitle\":\"Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE\",\"bibtex\":\"@inproceedings{\\n title = {Drilling dataset exploration, processing and interpretation using volve field data},\\n type = {inproceedings},\\n year = {2020},\\n keywords = {Catalysts,Drilling,Gages},\\n volume = {11},\\n month = {12},\\n publisher = {American Society of Mechanical Engineers (ASME)},\\n day = {18},\\n id = {d0725421-9955-38ea-af18-eb63688a8a6f},\\n created = {2021-04-13T18:50:47.936Z},\\n accessed = {2021-04-13},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-13T18:50:47.936Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In 2018 Equinor made an unprecedented step for an energy company and made a multi-terabyte dataset from Volve field open. However, there is a long way from downloading data to executing meaningful analysis. With no way of quickly evaluating the data due to its size and unfamiliar file formats the use of Volve data was so far limited. This paper presents our exploratory work related to the real-time drilling part of the dataset. We provide description of common obstacles and approaches for overcoming them. We also describe specific contents of the dataset for others to gauge the potential for case studies. We hope that this will lower the bar for Volve field data accessibility, promote research, and become a catalyst for other data science projects.},\\n bibtype = {inproceedings},\\n author = {Tunkiel, Andrzej T. and Wiktorski, Tomasz and Sui, Dan},\\n doi = {10.1115/OMAE2020-18151},\\n booktitle = {Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE}\\n}\",\"author_short\":[\"Tunkiel,  A., T.\",\"Wiktorski,  T.\",\"Sui,  D.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"tunkiel-wiktorski-sui-drillingdatasetexplorationprocessingandinterpretationusingvolvefielddata-2020\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Catalysts\",\"Drilling\",\"Gages\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Advanced Rendering of Line Data with Ambient Occlusion and Transparency\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Scientific visualization,line rendering,ray-casting,transparency\",\"pages\":\"614-624\",\"volume\":\"27\",\"month\":\"2\",\"publisher\":\"IEEE Computer Society\",\"day\":\"1\",\"id\":\"5529d502-fd6d-310f-afa4-2deafd97a98c\",\"created\":\"2021-04-13T18:57:54.824Z\",\"accessed\":\"2021-04-13\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2021-04-13T18:57:54.824Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.\",\"bibtype\":\"article\",\"author\":\"Gross, David and Gumhold, Stefan\",\"doi\":\"10.1109/TVCG.2020.3028954\",\"journal\":\"IEEE Transactions on Visualization and Computer Graphics\",\"number\":\"2\",\"bibtex\":\"@article{\\n title = {Advanced Rendering of Line Data with Ambient Occlusion and Transparency},\\n type = {article},\\n year = {2021},\\n keywords = {Scientific visualization,line rendering,ray-casting,transparency},\\n pages = {614-624},\\n volume = {27},\\n month = {2},\\n publisher = {IEEE Computer Society},\\n day = {1},\\n id = {5529d502-fd6d-310f-afa4-2deafd97a98c},\\n created = {2021-04-13T18:57:54.824Z},\\n accessed = {2021-04-13},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2021-04-13T18:57:54.824Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.},\\n bibtype = {article},\\n author = {Gross, David and Gumhold, Stefan},\\n doi = {10.1109/TVCG.2020.3028954},\\n journal = {IEEE Transactions on Visualization and Computer Graphics},\\n number = {2}\\n}\",\"author_short\":[\"Gross,  D.\",\"Gumhold,  S.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gross-gumhold-advancedrenderingoflinedatawithambientocclusionandtransparency-2021\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Scientific visualization\",\"line rendering\",\"ray-casting\",\"transparency\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Model-based multi-sensor fusion for reconstructing wall-bounded turbulence\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"683-707\",\"volume\":\"35\",\"month\":\"10\",\"day\":\"22\",\"id\":\"349c86f2-eb91-3217-a7db-d8f1c622711a\",\"created\":\"2022-02-20T21:37:29.373Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-20T21:37:29.373Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Wang, Mengying and Krishna, C. Vamsi and Luhar, Mitul and Hemati, Maziar S.\",\"doi\":\"10.1007/s00162-021-00586-8\",\"journal\":\"Theoretical and Computational Fluid Dynamics\",\"number\":\"5\",\"bibtex\":\"@article{\\n title = {Model-based multi-sensor fusion for reconstructing wall-bounded turbulence},\\n type = {article},\\n year = {2021},\\n pages = {683-707},\\n volume = {35},\\n month = {10},\\n day = {22},\\n id = {349c86f2-eb91-3217-a7db-d8f1c622711a},\\n created = {2022-02-20T21:37:29.373Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-20T21:37:29.373Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Wang, Mengying and Krishna, C. Vamsi and Luhar, Mitul and Hemati, Maziar S.},\\n doi = {10.1007/s00162-021-00586-8},\\n journal = {Theoretical and Computational Fluid Dynamics},\\n number = {5}\\n}\",\"author_short\":[\"Wang,  M.\",\"Krishna,  C., V.\",\"Luhar,  M.\",\"Hemati,  M., S.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-krishna-luhar-hemati-modelbasedmultisensorfusionforreconstructingwallboundedturbulence-2021\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Law of bounded dissipation and its consequences in turbulent wall flows\",\"type\":\"article\",\"year\":\"2022\",\"keywords\":\"pipe flow boundary layer,turbulence theory,turbulent boundary layers\",\"pages\":\"20\",\"volume\":\"933\",\"websites\":\"https://doi.org/10.1017/jfm.2021.1052\",\"id\":\"cf4fc9f3-21d2-35ea-8c00-b82c5a72d9d3\",\"created\":\"2022-02-20T23:23:59.301Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-20T23:24:00.230Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"The dominant paradigm in turbulent wall flows is that the mean velocity near the wall, when scaled on wall variables, is independent of the friction Reynolds number Re τ. This paradigm faces challenges when applied to fluctuations but has received serious attention only recently. Here, by extending our earlier work (Chen & Sreenivasan, J. Fluid Mech., vol. 908, 2021, p. R3) we present a promising perspective, and support it with data, that fluctuations displaying non-zero wall values, or near-wall peaks, are bounded for large values of Re τ , owing to the natural constraint that the dissipation rate is bounded. Specifically, Φ ∞ − Φ = C Φ Re −1/4 τ , where Φ represents the maximum value of any of the following quantities: energy dissipation rate, turbulent diffusion, fluctuations of pressure, streamwise and spanwise velocities, squares of vorticity components, and the wall values of pressure and shear stresses; the subscript ∞ denotes the bounded asymptotic value of Φ, and the coefficient C Φ depends on Φ but not on Re τ. Moreover, there exists a scaling law for the maximum value in the wall-normal direction of high-order moments, of the form ϕ 2q 1/q max = α q − β q Re −1/4 τ , where ϕ represents the streamwise or spanwise velocity fluctuation, and α q and β q are independent of Re τ. Excellent agreement with available data is observed. A stochastic process for which the random variable has the form just mentioned, referred to here as the 'linear q-norm Gaussian', is proposed to explain the observed linear dependence of α q on q.\",\"bibtype\":\"article\",\"author\":\"Chen, Xi and Sreenivasan, Katepalli R\",\"doi\":\"10.1017/jfm.2021.1052\",\"journal\":\"J. Fluid Mech\",\"bibtex\":\"@article{\\n title = {Law of bounded dissipation and its consequences in turbulent wall flows},\\n type = {article},\\n year = {2022},\\n keywords = {pipe flow boundary layer,turbulence theory,turbulent boundary layers},\\n pages = {20},\\n volume = {933},\\n websites = {https://doi.org/10.1017/jfm.2021.1052},\\n id = {cf4fc9f3-21d2-35ea-8c00-b82c5a72d9d3},\\n created = {2022-02-20T23:23:59.301Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-20T23:24:00.230Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {The dominant paradigm in turbulent wall flows is that the mean velocity near the wall, when scaled on wall variables, is independent of the friction Reynolds number Re τ. This paradigm faces challenges when applied to fluctuations but has received serious attention only recently. Here, by extending our earlier work (Chen & Sreenivasan, J. Fluid Mech., vol. 908, 2021, p. R3) we present a promising perspective, and support it with data, that fluctuations displaying non-zero wall values, or near-wall peaks, are bounded for large values of Re τ , owing to the natural constraint that the dissipation rate is bounded. Specifically, Φ ∞ − Φ = C Φ Re −1/4 τ , where Φ represents the maximum value of any of the following quantities: energy dissipation rate, turbulent diffusion, fluctuations of pressure, streamwise and spanwise velocities, squares of vorticity components, and the wall values of pressure and shear stresses; the subscript ∞ denotes the bounded asymptotic value of Φ, and the coefficient C Φ depends on Φ but not on Re τ. Moreover, there exists a scaling law for the maximum value in the wall-normal direction of high-order moments, of the form ϕ 2q 1/q max = α q − β q Re −1/4 τ , where ϕ represents the streamwise or spanwise velocity fluctuation, and α q and β q are independent of Re τ. Excellent agreement with available data is observed. A stochastic process for which the random variable has the form just mentioned, referred to here as the 'linear q-norm Gaussian', is proposed to explain the observed linear dependence of α q on q.},\\n bibtype = {article},\\n author = {Chen, Xi and Sreenivasan, Katepalli R},\\n doi = {10.1017/jfm.2021.1052},\\n journal = {J. Fluid Mech}\\n}\",\"author_short\":[\"Chen,  X.\",\"Sreenivasan,  K., R.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3d9a7c68-32bd-0e95-2339-f9246e7a2185/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1017/jfm.2021.1052\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022\",\"role\":\"author\",\"keyword\":[\"pipe flow boundary layer\",\"turbulence theory\",\"turbulent boundary layers\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Multiresolution classification of turbulence features in image data through machine learning\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Image processing,Machine learning,Turbulence,Vortex detection\",\"pages\":\"104770\",\"volume\":\"214\",\"month\":\"1\",\"publisher\":\"Pergamon\",\"day\":\"15\",\"id\":\"052413a3-fcdc-3dff-ab3b-f7d91f97b7aa\",\"created\":\"2022-02-20T23:29:14.961Z\",\"accessed\":\"2022-02-20\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-20T23:29:14.961Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. We present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.\",\"bibtype\":\"article\",\"author\":\"Pulido, Jesus and da Silva, Ricardo Dutra and Livescu, Daniel and Hamann, Bernd\",\"doi\":\"10.1016/J.COMPFLUID.2020.104770\",\"journal\":\"Computers & Fluids\",\"bibtex\":\"@article{\\n title = {Multiresolution classification of turbulence features in image data through machine learning},\\n type = {article},\\n year = {2021},\\n keywords = {Image processing,Machine learning,Turbulence,Vortex detection},\\n pages = {104770},\\n volume = {214},\\n month = {1},\\n publisher = {Pergamon},\\n day = {15},\\n id = {052413a3-fcdc-3dff-ab3b-f7d91f97b7aa},\\n created = {2022-02-20T23:29:14.961Z},\\n accessed = {2022-02-20},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-20T23:29:14.961Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. We present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.},\\n bibtype = {article},\\n author = {Pulido, Jesus and da Silva, Ricardo Dutra and Livescu, Daniel and Hamann, Bernd},\\n doi = {10.1016/J.COMPFLUID.2020.104770},\\n journal = {Computers & Fluids}\\n}\",\"author_short\":[\"Pulido,  J.\",\"da Silva,  R., D.\",\"Livescu,  D.\",\"Hamann,  B.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"pulido-dasilva-livescu-hamann-multiresolutionclassificationofturbulencefeaturesinimagedatathroughmachinelearning-2021\",\"role\":\"author\",\"urls\":{},\"keyword\":[\"Image processing\",\"Machine learning\",\"Turbulence\",\"Vortex detection\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"101703\",\"volume\":\"33\",\"websites\":\"https://doi.org/10.1063/5.0066332\",\"id\":\"d887d298-1140-3521-b80b-f8178cac337a\",\"created\":\"2022-02-20T23:33:36.678Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-20T23:33:37.243Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Liu, Xiaofeng and Moreto, Jose Roberto\",\"doi\":\"10.1063/5.0066332\",\"journal\":\"Phys. Fluids\",\"bibtex\":\"@article{\\n title = {Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes},\\n type = {article},\\n year = {2021},\\n pages = {101703},\\n volume = {33},\\n websites = {https://doi.org/10.1063/5.0066332},\\n id = {d887d298-1140-3521-b80b-f8178cac337a},\\n created = {2022-02-20T23:33:36.678Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-20T23:33:37.243Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Liu, Xiaofeng and Moreto, Jose Roberto},\\n doi = {10.1063/5.0066332},\\n journal = {Phys. Fluids}\\n}\",\"author_short\":[\"Liu,  X.\",\"Moreto,  J., R.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1a0cafe7-d99c-4711-40ba-d076bbebebb9/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1063/5.0066332\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"turbulence modelling,turbulence theory †\",\"pages\":\"6\",\"volume\":\"914\",\"websites\":\"https://doi.org/10.1017/jfm.2020.977\",\"id\":\"d17dc74f-091c-3ad3-9876-dbe551c5865f\",\"created\":\"2022-02-20T23:35:02.757Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-20T23:35:03.347Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"By analysing the Karman-Howarth equation for filtered-velocity fields in turbulent flows, we show that the two-point correlation between the filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlation-based statistical a priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence, we show that local eddy-viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain-rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 (where α is the fractional gradient order) rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional-gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows. Hence, non-local operators thus exhibit interesting modelling capabilities and potential for large-eddy simulations although more developments are required, both on the theoretical and computational implementation fronts.\",\"bibtype\":\"article\",\"author\":\"Clark, Patricio and Leoni, Di and Zaki, Tamer A and Karniadakis, George and Meneveau, Charles and Clark, P and Zaki, T A and Karniadakis, G and Meneveau, C\",\"doi\":\"10.1017/jfm.2020.977\",\"journal\":\"J. Fluid Mech\",\"bibtex\":\"@article{\\n title = {Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows},\\n type = {article},\\n year = {2021},\\n keywords = {turbulence modelling,turbulence theory †},\\n pages = {6},\\n volume = {914},\\n websites = {https://doi.org/10.1017/jfm.2020.977},\\n id = {d17dc74f-091c-3ad3-9876-dbe551c5865f},\\n created = {2022-02-20T23:35:02.757Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-20T23:35:03.347Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {By analysing the Karman-Howarth equation for filtered-velocity fields in turbulent flows, we show that the two-point correlation between the filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlation-based statistical a priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence, we show that local eddy-viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain-rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 (where α is the fractional gradient order) rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional-gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows. Hence, non-local operators thus exhibit interesting modelling capabilities and potential for large-eddy simulations although more developments are required, both on the theoretical and computational implementation fronts.},\\n bibtype = {article},\\n author = {Clark, Patricio and Leoni, Di and Zaki, Tamer A and Karniadakis, George and Meneveau, Charles and Clark, P and Zaki, T A and Karniadakis, G and Meneveau, C},\\n doi = {10.1017/jfm.2020.977},\\n journal = {J. Fluid Mech}\\n}\",\"author_short\":[\"Clark,  P.\",\"Leoni,  D.\",\"Zaki,  T., A.\",\"Karniadakis,  G.\",\"Meneveau,  C.\",\"Clark,  P.\",\"Zaki,  T., A.\",\"Karniadakis,  G.\",\"Meneveau,  C.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/7011c56a-830c-5e45-46ca-fda21cdc358d/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1017/jfm.2020.977\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021\",\"role\":\"author\",\"keyword\":[\"turbulence modelling\",\"turbulence theory †\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Lossy compression,PCA,information retrieval\",\"id\":\"a1abcec3-2790-3c53-a0ab-83f79ddd347a\",\"created\":\"2022-02-21T19:17:28.173Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:17:28.724Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and ZFP, show promising rate-distortion efficiency. However, as the data storage burden and need for feature-preserving compression continue to grow, relying on unitary or single-stage compression is becoming insufficient for obtaining desirable data reductions and feature preservation. This paper aims to improve the compression ratio by taking advantage of information retrieval (IR), a well-established topic but under-explored in lossy compression for scientific data. We propose our lossy compression technique, called DPZ, based on multi-stage feature extractions, a commonly employed step in IR. Unlike the prior works where the compression is either done by predicting or bit-plane encoding, this work focuses on preserving the key data content from each stage to the maximum extent, ultimately elevates the compression ratio. With the application of discrete cosine transform, principal component analysis, and quantization, DPZ obtains the dominant features with the least amount of bits possible. Specifically, a knee-point detection and an explained variance variation method are designed for finding optimal tradeoffs. DPZ also employs a sampling strategy to reduce computational overhead and estimate compressibility and parameters before compression. We evaluate the performance of DPZ using real-world scientific datasets. Experiments demonstrate that DPZ achieves superior compression ratios through multi-stage retrievals and outperforms SZ and ZFP at medium to high accuracy on most of the evaluated datasets.\",\"bibtype\":\"article\",\"author\":\"Zhang, Jialing and Chen, Jiaxi and Zhuo, Xiaoyan and Moon, Aekyeung and Woo Son, Seung\",\"doi\":\"10.1109/Cluster48925.2021.00056\",\"journal\":\"2021 IEEE International Conference on Cluster Computing (CLUSTER)\",\"bibtex\":\"@article{\\n title = {DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data},\\n type = {article},\\n year = {2021},\\n keywords = {Lossy compression,PCA,information retrieval},\\n id = {a1abcec3-2790-3c53-a0ab-83f79ddd347a},\\n created = {2022-02-21T19:17:28.173Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:17:28.724Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and ZFP, show promising rate-distortion efficiency. However, as the data storage burden and need for feature-preserving compression continue to grow, relying on unitary or single-stage compression is becoming insufficient for obtaining desirable data reductions and feature preservation. This paper aims to improve the compression ratio by taking advantage of information retrieval (IR), a well-established topic but under-explored in lossy compression for scientific data. We propose our lossy compression technique, called DPZ, based on multi-stage feature extractions, a commonly employed step in IR. Unlike the prior works where the compression is either done by predicting or bit-plane encoding, this work focuses on preserving the key data content from each stage to the maximum extent, ultimately elevates the compression ratio. With the application of discrete cosine transform, principal component analysis, and quantization, DPZ obtains the dominant features with the least amount of bits possible. Specifically, a knee-point detection and an explained variance variation method are designed for finding optimal tradeoffs. DPZ also employs a sampling strategy to reduce computational overhead and estimate compressibility and parameters before compression. We evaluate the performance of DPZ using real-world scientific datasets. Experiments demonstrate that DPZ achieves superior compression ratios through multi-stage retrievals and outperforms SZ and ZFP at medium to high accuracy on most of the evaluated datasets.},\\n bibtype = {article},\\n author = {Zhang, Jialing and Chen, Jiaxi and Zhuo, Xiaoyan and Moon, Aekyeung and Woo Son, Seung},\\n doi = {10.1109/Cluster48925.2021.00056},\\n journal = {2021 IEEE International Conference on Cluster Computing (CLUSTER)}\\n}\",\"author_short\":[\"Zhang,  J.\",\"Chen,  J.\",\"Zhuo,  X.\",\"Moon,  A.\",\"Woo Son,  S.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/214133d9-0f22-d399-0c4b-c05e371716f1/full_text.pdf.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021\",\"role\":\"author\",\"keyword\":[\"Lossy compression\",\"PCA\",\"information retrieval\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"2021\",\"volume\":\"70\",\"websites\":\"https://www.ieee.org/publications/rights/index.html\",\"id\":\"a770ec53-7b70-3157-8e6a-cd62f806e33f\",\"created\":\"2022-02-21T19:20:57.099Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:20:58.051Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en. Index Terms-Deep learning (DL), fluid motion estimation, lightweight, optical flow, particle image velocimetry (PIV).\",\"bibtype\":\"article\",\"author\":\"Yu, Changdong and Bi, Xiaojun and Fan, Yiwei and Han, Yang and Kuai, Yunfei\",\"doi\":\"10.1109/TIM.2021.3082313\",\"journal\":\"IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT\",\"bibtex\":\"@article{\\n title = {LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry},\\n type = {article},\\n year = {2021},\\n pages = {2021},\\n volume = {70},\\n websites = {https://www.ieee.org/publications/rights/index.html},\\n id = {a770ec53-7b70-3157-8e6a-cd62f806e33f},\\n created = {2022-02-21T19:20:57.099Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:20:58.051Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en. Index Terms-Deep learning (DL), fluid motion estimation, lightweight, optical flow, particle image velocimetry (PIV).},\\n bibtype = {article},\\n author = {Yu, Changdong and Bi, Xiaojun and Fan, Yiwei and Han, Yang and Kuai, Yunfei},\\n doi = {10.1109/TIM.2021.3082313},\\n journal = {IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT}\\n}\",\"author_short\":[\"Yu,  C.\",\"Bi,  X.\",\"Fan,  Y.\",\"Han,  Y.\",\"Kuai,  Y.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/644cdd8a-80b3-8aa5-7d1f-3e8ebe07d145/full_text.pdf.pdf\",\"Website\":\"https://www.ieee.org/publications/rights/index.html\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression\",\"type\":\"article\",\"year\":\"2021\",\"id\":\"89d9254b-bf2f-354a-8f06-5ec1df0284b5\",\"created\":\"2022-02-21T19:20:57.493Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:20:58.433Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Continual advances in high-performance computing have enabled the development of higher resolution and more realistic simulations of a wide variety of scientific phenomena. As a result, many computational science communities are increasingly constrained by the massive volumes of data produced,for example, strict storage constraints often force reductions in the number of output variables, data output frequency, or simulation length. Accordingly, modelers across many scientific domains are beginning to adopt purpose-built scientific data compression techniques as an effective mitigation for these challenges. The origins of scientific data compression tools every so often lie in image and video compression. Recently, compression researchers have achieved state-of-the-art performance using neural networks for natural image compression, but this achievement has yet to be adapted to scientific data. This paper assesses the performance of an existing autoencoder neural network compression algorithm on two sets of two-dimensional floating-point scientific data. Compared to state-of-the-art scientific data compression algorithms SZ and ZFP, this out-of-the-box neural network achieves higher peak signal-to-noise ratios at low bit rates, and remains competitive in controlling maximum point-wise error. This preliminary assessment paves the way for future research into neural network compression on floating-point scientific data.\",\"bibtype\":\"article\",\"author\":\"Hayne, Lucas and Clyne, John and Li, Shaomeng\",\"doi\":\"10.1109/BigData52589.2021.9671627\",\"bibtex\":\"@article{\\n title = {Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression},\\n type = {article},\\n year = {2021},\\n id = {89d9254b-bf2f-354a-8f06-5ec1df0284b5},\\n created = {2022-02-21T19:20:57.493Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:20:58.433Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Continual advances in high-performance computing have enabled the development of higher resolution and more realistic simulations of a wide variety of scientific phenomena. As a result, many computational science communities are increasingly constrained by the massive volumes of data produced,for example, strict storage constraints often force reductions in the number of output variables, data output frequency, or simulation length. Accordingly, modelers across many scientific domains are beginning to adopt purpose-built scientific data compression techniques as an effective mitigation for these challenges. The origins of scientific data compression tools every so often lie in image and video compression. Recently, compression researchers have achieved state-of-the-art performance using neural networks for natural image compression, but this achievement has yet to be adapted to scientific data. This paper assesses the performance of an existing autoencoder neural network compression algorithm on two sets of two-dimensional floating-point scientific data. Compared to state-of-the-art scientific data compression algorithms SZ and ZFP, this out-of-the-box neural network achieves higher peak signal-to-noise ratios at low bit rates, and remains competitive in controlling maximum point-wise error. This preliminary assessment paves the way for future research into neural network compression on floating-point scientific data.},\\n bibtype = {article},\\n author = {Hayne, Lucas and Clyne, John and Li, Shaomeng},\\n doi = {10.1109/BigData52589.2021.9671627}\\n}\",\"author_short\":[\"Hayne,  L.\",\"Clyne,  J.\",\"Li,  S.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/78517cbb-77d3-9fbd-68e6-9cbc2117d271/full_text.pdf.pdf\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Unsupervised deep learning for super-resolution reconstruction of turbulence\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"turbulence simulation\",\"pages\":\"29\",\"volume\":\"910\",\"websites\":\"https://doi.org/10.1017/jfm.2020.1028\",\"id\":\"4720e5ff-e367-373c-8a45-62e9091085f7\",\"created\":\"2022-02-21T19:25:34.158Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:25:34.724Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.\",\"bibtype\":\"article\",\"author\":\"Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon\",\"doi\":\"10.1017/jfm.2020.1028\",\"journal\":\"J. Fluid Mech\",\"bibtex\":\"@article{\\n title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},\\n type = {article},\\n year = {2021},\\n keywords = {turbulence simulation},\\n pages = {29},\\n volume = {910},\\n websites = {https://doi.org/10.1017/jfm.2020.1028},\\n id = {4720e5ff-e367-373c-8a45-62e9091085f7},\\n created = {2022-02-21T19:25:34.158Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:25:34.724Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},\\n bibtype = {article},\\n author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},\\n doi = {10.1017/jfm.2020.1028},\\n journal = {J. 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Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks\",\"type\":\"inproceedings\",\"year\":\"2021\",\"pages\":\"V010T10A062\",\"volume\":\"85666\",\"id\":\"96b2cc13-c310-36a9-8034-bb0f3480edba\",\"created\":\"2022-02-21T19:26:56.874Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:26:56.874Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Nandal, Tanishk and Tyagi, Prince and Singh, Raj Kumar\",\"booktitle\":\"ASME International Mechanical Engineering Congress and Exposition\",\"bibtex\":\"@inproceedings{\\n title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},\\n type = {inproceedings},\\n year = {2021},\\n pages 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K.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"nandal-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R e τ= 150, 400 and 1020\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"36-50\",\"volume\":\"59\",\"publisher\":\"Taylor & 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I.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2021\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A robust single-pixel particle image velocimetry based on fully convolutional networks with cross-correlation embedded\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"127125\",\"volume\":\"33\",\"publisher\":\"AIP Publishing 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{false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:28:32.885Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Gao, Qi and Lin, Hongtao and Tu, Han and Zhu, Haoran and Wei, Runjie and Zhang, Guoping and Shao, Xueming},\\n journal = {Physics of Fluids},\\n number = {12}\\n}\",\"author_short\":[\"Gao,  Q.\",\"Lin,  H.\",\"Tu,  H.\",\"Zhu,  H.\",\"Wei,  R.\",\"Zhang,  G.\",\"Shao,  X.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"gao-lin-tu-zhu-wei-zhang-shao-arobustsinglepixelparticleimagevelocimetrybasedonfullyconvolutionalnetworkswithcrosscorrelationembedded-2021\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget\",\"type\":\"article\",\"year\":\"2022\",\"keywords\":\"homogeneous turbulence,isotropic turbulence,pipe flow\",\"pages\":\"87-109\",\"volume\":\"931\",\"websites\":\"https://doi.org/10.1017/jfm.2021.986\",\"id\":\"9e83d349-397e-3751-a3d9-b216cbfbaefc\",\"created\":\"2022-02-21T19:34:17.825Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:34:20.081Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"In this study, we propose a scale-by-scale (SBS) energy budget equation for flows with homogeneity in at least one direction. This SBS budget represents a modified form of the equation first proposed by Danaila et al. (J. for the channel centreline-the primary difference is that, here, we consider the role of pressure along with the errors associated with the isotropic approximations of the interscale divergence and Laplacian of the squared velocity increment. The term encompassing the effects of mean shear is also characterised such that the present analysis can be extended straightforwardly to locations away from the centreline. We show, based on a detailed analysis of previously published channel flow direct numerical simulations and pipe flow experiments near the centreline, how several terms in the present SBS budget equation (including the third-order velocity structure function) behave with increasing Reynolds number. The behaviour of these terms is shown to imply a rate of emergence and subsequent growth of the 4/3 law scale subrange at the channel centreline and pipe axis. The analysis also suggests that the peak magnitude of the third-order velocity structure function occurs at a scale that is fixed in proportion to the Taylor microscale at sufficiently high Reynolds number.\",\"bibtype\":\"article\",\"author\":\"Zimmerman, Spencer J and Antonia, R A and Djenidi, L and Philip, J and Klewicki, J C\",\"doi\":\"10.1017/jfm.2021.986\",\"journal\":\"A28, Fluid Mech\",\"bibtex\":\"@article{\\n title = {Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget},\\n type = {article},\\n year = {2022},\\n keywords = {homogeneous turbulence,isotropic turbulence,pipe flow},\\n pages = {87-109},\\n volume = {931},\\n websites = {https://doi.org/10.1017/jfm.2021.986},\\n id = {9e83d349-397e-3751-a3d9-b216cbfbaefc},\\n created = {2022-02-21T19:34:17.825Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:34:20.081Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {In this study, we propose a scale-by-scale (SBS) energy budget equation for flows with homogeneity in at least one direction. This SBS budget represents a modified form of the equation first proposed by Danaila et al. (J. for the channel centreline-the primary difference is that, here, we consider the role of pressure along with the errors associated with the isotropic approximations of the interscale divergence and Laplacian of the squared velocity increment. The term encompassing the effects of mean shear is also characterised such that the present analysis can be extended straightforwardly to locations away from the centreline. We show, based on a detailed analysis of previously published channel flow direct numerical simulations and pipe flow experiments near the centreline, how several terms in the present SBS budget equation (including the third-order velocity structure function) behave with increasing Reynolds number. The behaviour of these terms is shown to imply a rate of emergence and subsequent growth of the 4/3 law scale subrange at the channel centreline and pipe axis. The analysis also suggests that the peak magnitude of the third-order velocity structure function occurs at a scale that is fixed in proportion to the Taylor microscale at sufficiently high Reynolds number.},\\n bibtype = {article},\\n author = {Zimmerman, Spencer J and Antonia, R A and Djenidi, L and Philip, J and Klewicki, J C},\\n doi = {10.1017/jfm.2021.986},\\n journal = {A28, Fluid Mech}\\n}\",\"author_short\":[\"Zimmerman,  S., J.\",\"Antonia,  R., A.\",\"Djenidi,  L.\",\"Philip,  J.\",\"Klewicki,  J., C.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/17798f52-75f5-dc15-28f4-6b63dfdc2001/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1017/jfm.2021.986\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022\",\"role\":\"author\",\"keyword\":[\"homogeneous turbulence\",\"isotropic turbulence\",\"pipe flow\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"45120\",\"volume\":\"33\",\"websites\":\"https://doi.org/10.1063/5.0046502\",\"id\":\"e964db44-a8b8-3b7c-8083-764c8ca4795b\",\"created\":\"2022-02-21T19:34:18.460Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:34:20.372Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502\",\"bibtype\":\"article\",\"author\":\"Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing\",\"doi\":\"10.1063/5.0046502\",\"journal\":\"Phys. Fluids\",\"bibtex\":\"@article{\\n title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},\\n type = {article},\\n year = {2021},\\n pages = {45120},\\n volume = {33},\\n websites = {https://doi.org/10.1063/5.0046502},\\n id = {e964db44-a8b8-3b7c-8083-764c8ca4795b},\\n created = {2022-02-21T19:34:18.460Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:34:20.372Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},\\n bibtype = {article},\\n author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},\\n doi = {10.1063/5.0046502},\\n journal = {Phys. Fluids}\\n}\",\"author_short\":[\"Wang,  L.\",\"Hu,  R.\",\"Zheng,  X.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-0083-27bea5fc2259/full_text.pdf.pdf\",\"Website\":\"https://doi.org/10.1063/5.0046502\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021\",\"role\":\"author\",\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"Time-resolved particle image velocimetry algorithm based on deep learning\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow\",\"websites\":\"http://www.ieee.org/publications_standards/publications/rights/index.html\",\"id\":\"f2410f9e-f814-3ae7-86c6-4d2a103081f3\",\"created\":\"2022-02-21T19:34:18.855Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:34:20.654Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.\",\"bibtype\":\"article\",\"author\":\"Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun\",\"doi\":\"10.1109/TIM.2022.3141750\",\"bibtex\":\"@article{\\n title = {Time-resolved particle image velocimetry algorithm based on deep learning},\\n type = {article},\\n year = {2021},\\n keywords = {Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow},\\n websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},\\n id = {f2410f9e-f814-3ae7-86c6-4d2a103081f3},\\n created = {2022-02-21T19:34:18.855Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:34:20.654Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.},\\n bibtype = {article},\\n author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},\\n doi = {10.1109/TIM.2022.3141750}\\n}\",\"author_short\":[\"Guo,  C.\",\"Fan,  Y.\",\"Yu,  C.\",\"Han,  Y.\",\"Bi,  X.\"],\"urls\":{\"Paper\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-6c4a-85ec090c2385/full_text.pdf.pdf\",\"Website\":\"http://www.ieee.org/publications_standards/publications/rights/index.html\"},\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021\",\"role\":\"author\",\"keyword\":[\"Deep learning\",\"Fluid motion estimation\",\"Index Terms-Time-resolved PIV\",\"Multi-frame velocity field\",\"Optical Flow\"],\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks\",\"type\":\"article\",\"year\":\"2021\",\"keywords\":\"Particle tracking velocimetry,deep learning,deep neural networks,fluid motion estimation,point clouds\",\"volume\":\"PP\",\"websites\":\"http://www.ieee.org/publications_standards/publications/rights/index.html\",\"id\":\"62e473c0-ea0f-3ba2-bcd2-3c3aea1e9c09\",\"created\":\"2022-02-21T19:34:19.232Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:34:20.931Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Particle tracking velocimetry (PTV) is a powerful technique for global and non-intrusive flow field measurement , which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called DeepPTV, for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles are aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multi-scale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely from large scale motion to small scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.\",\"bibtype\":\"article\",\"author\":\"Liang, Jiaming and Cai, Shengze and Xu, Chao and Chen, Tehuan and Chu, Jian\",\"doi\":\"10.1109/TIM.2021.3120127\",\"journal\":\"IEEE Transactions on Instrumentation and Measurement\",\"bibtex\":\"@article{\\n title = {DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks},\\n type = {article},\\n year = {2021},\\n keywords = {Particle tracking velocimetry,deep learning,deep neural networks,fluid motion estimation,point clouds},\\n volume = {PP},\\n websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},\\n id = {62e473c0-ea0f-3ba2-bcd2-3c3aea1e9c09},\\n created = {2022-02-21T19:34:19.232Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:34:20.931Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Particle tracking velocimetry (PTV) is a powerful technique for global and non-intrusive flow field measurement , which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called DeepPTV, for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles are aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multi-scale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely from large scale motion to small scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.},\\n bibtype = {article},\\n author = {Liang, Jiaming and Cai, Shengze and Xu, Chao and Chen, Tehuan and Chu, Jian},\\n doi = {10.1109/TIM.2021.3120127},\\n journal = {IEEE Transactions on Instrumentation and Measurement}\\n}\",\"author_short\":[\"Liang,  J.\",\"Cai,  S.\",\"Xu,  C.\",\"Chen,  T.\",\"Chu,  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Networks\",\"type\":\"inproceedings\",\"year\":\"2021\",\"id\":\"9a25fc39-6427-38ee-a5c8-9504e01a0b0c\",\"created\":\"2022-02-21T19:54:37.633Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:54:37.633Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"inproceedings\",\"private_publication\":false,\"bibtype\":\"inproceedings\",\"author\":\"Kanishk, Tanishk Nandal and Tyagi, Prince and Singh, Raj Kumar\",\"booktitle\":\"ASME 2021 International Mechanical Engineering Congress and Exposition\",\"bibtex\":\"@inproceedings{\\n title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},\\n type = {inproceedings},\\n year = {2021},\\n id = {9a25fc39-6427-38ee-a5c8-9504e01a0b0c},\\n created = {2022-02-21T19:54:37.633Z},\\n file_attached = 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models—A spectrum of first-principle to machine-learned avenues\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"91301\",\"volume\":\"33\",\"publisher\":\"AIP Publishing LLC\",\"id\":\"ce06d381-1a1c-374f-b451-90ac4b12aaf3\",\"created\":\"2022-02-21T19:54:38.009Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:54:38.009Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Ahmed, Shady E and Pawar, Suraj and San, Omer and Rasheed, Adil and Iliescu, Traian and Noack, Bernd R\",\"journal\":\"Physics of Fluids\",\"number\":\"9\",\"bibtex\":\"@article{\\n title = {On closures for reduced order models—A spectrum of first-principle to machine-learned avenues},\\n type = {article},\\n year = {2021},\\n pages = {91301},\\n volume = {33},\\n publisher = {AIP Publishing LLC},\\n id = {ce06d381-1a1c-374f-b451-90ac4b12aaf3},\\n created = {2022-02-21T19:54:38.009Z},\\n file_attached = {false},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:54:38.009Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n source_type = {article},\\n private_publication = {false},\\n bibtype = {article},\\n author = {Ahmed, Shady E and Pawar, Suraj and San, Omer and Rasheed, Adil and Iliescu, Traian and Noack, Bernd R},\\n journal = {Physics of Fluids},\\n number = {9}\\n}\",\"author_short\":[\"Ahmed,  S., E.\",\"Pawar,  S.\",\"San,  O.\",\"Rasheed,  A.\",\"Iliescu,  T.\",\"Noack,  B., R.\"],\"biburl\":\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0\",\"bibbaseid\":\"ahmed-pawar-san-rasheed-iliescu-noack-onclosuresforreducedordermodelsaspectrumoffirstprincipletomachinelearnedavenues-2021\",\"role\":\"author\",\"urls\":{},\"metadata\":{\"authorlinks\":{}},\"downloads\":0,\"html\":\"\"},{\"title\":\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions\",\"type\":\"article\",\"year\":\"2021\",\"pages\":\"45120\",\"volume\":\"33\",\"websites\":\"https://doi.org/10.1063/5.0046502\",\"id\":\"4ff7eba0-ee54-370d-96b4-cfda2bbe256d\",\"created\":\"2022-02-21T19:54:57.325Z\",\"file_attached\":\"true\",\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2022-02-21T19:54:58.549Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"private_publication\":false,\"abstract\":\"Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502\",\"bibtype\":\"article\",\"author\":\"Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing\",\"doi\":\"10.1063/5.0046502\",\"journal\":\"Phys. Fluids\",\"bibtex\":\"@article{\\n title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},\\n type = {article},\\n year = {2021},\\n pages = {45120},\\n volume = {33},\\n websites = {https://doi.org/10.1063/5.0046502},\\n id = {4ff7eba0-ee54-370d-96b4-cfda2bbe256d},\\n created = {2022-02-21T19:54:57.325Z},\\n file_attached = {true},\\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\\n last_modified = {2022-02-21T19:54:58.549Z},\\n read = {false},\\n starred = {false},\\n authored = {false},\\n confirmed = {false},\\n hidden = {false},\\n private_publication = {false},\\n abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},\\n bibtype = {article},\\n author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},\\n doi = {10.1063/5.0046502},\\n journal = {Phys. 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Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. 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Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. 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London\",\"id\":\"1fc88bee-0abf-3ae6-934e-efcaeb39d4f0\",\"created\":\"2024-02-20T06:34:23.385Z\",\"file_attached\":false,\"profile_id\":\"75799766-8e2d-3c98-81f9-e3efa41233d0\",\"group_id\":\"c9329632-2a50-3043-b803-cadc8dbdfc3f\",\"last_modified\":\"2024-02-20T06:34:23.385Z\",\"read\":false,\"starred\":false,\"authored\":false,\"confirmed\":false,\"hidden\":false,\"source_type\":\"article\",\"private_publication\":false,\"bibtype\":\"article\",\"author\":\"Shnapp, Ron and Brizzolara, Stefano and Neamtu-Halic, Marius M and Gambino, Alessandro and Holzner, Markus\",\"journal\":\"Nature Communications\",\"number\":\"1\",\"bibtex\":\"@article{\\n title = {Universal alignment in turbulent pair dispersion},\\n type = {article},\\n year = {2023},\\n pages = {4195},\\n volume = {14},\\n publisher = {Nature Publishing Group UK London},\\n id = {1fc88bee-0abf-3ae6-934e-efcaeb39d4f0},\\n created = {2024-02-20T06:34:23.385Z},\\n file_attached = {false},\\n profile_id = 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 title = {Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes},
 type = {article},
 year = {2020},
 keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},
 volume = {900},
 websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F},
 publisher = {Cambridge University Press},
 id = {8cc0f47e-27fc-38bb-a4af-8911bc26fe10},
 created = {2021-04-09T15:22:51.557Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:22:51.557Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic differential equation. In comparison with previously proposed stochastic models, the obtained process is infinitely differentiable at a given finite Reynolds number, and its second-order statistical properties converge to those of an Ornstein-Uhlenbeck process in the infinite Reynolds number limit. In this limit, it exhibits furthermore intermittent scaling properties, as they can be quantified using higher-order statistics. To achieve this, we begin with generalizing the two-layered embedded stochastic process of Sawford (Phys. Fluids A, vol. 3 (6), 1991, pp. 1577-1586) by considering an infinite number of layers. We then study, both theoretically and numerically, the convergence towards a smooth (i.e. infinitely differentiable) Gaussian process. To include intermittent corrections, we follow similar considerations as for the multifractal random walk of Bacry et al. (Phys. Rev. E, vol. 64, 2001, 026103). We derive in an exact manner the statistical properties of this process, and compare them with those estimated from Lagrangian trajectories extracted from numerically simulated turbulent flows. Key predictions of the multifractal formalism regarding the acceleration correlation function and high-order structure functions are also derived. Through these predictions, we understand phenomenologically peculiar behaviours of the fluctuations in the dissipative range, that are not reproduced by our stochastic process. The proposed theoretical method regarding the modelling of infinitely differentiability opens the route to the full stochastic modelling of velocity, including the peculiar action of viscosity on the very fine scales.},
 bibtype = {article},
 author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},
 doi = {10.1017/jfm.2020.495},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},
 type = {article},
 year = {2020},
 keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},
 pages = {45-56},
 volume = {88},
 month = {5},
 publisher = {Elsevier Ltd},
 day = {1},
 id = {2163eeea-5277-3538-b932-9bca1745b1b6},
 created = {2021-04-09T15:22:57.667Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:22:57.667Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},
 bibtype = {article},
 author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},
 doi = {10.1016/j.cag.2020.03.002},
 journal = {Computers and Graphics (Pergamon)}
}

@techreport{
 title = {ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER},
 type = {techreport},
 year = {2020},
 month = {2},
 day = {26},
 id = {11ddc1a2-9ba3-3585-8fff-4772389fff79},
 created = {2021-04-09T15:22:58.110Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:07.834Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions. Many systems in the physical sciences are governed by Partial Differential Equations (PDEs). Enforcing these as hard constraints, we show, are inefficient in conventional frameworks due to the high dimensionality of the generated fields. To this end, we propose the use of a novel differentiable spectral projection layer for neural networks that efficiently enforces spatial PDE constraints using spectral methods, yet is fully differentiable, allowing for its use as a layer within Convolutional Neural Networks (CNNs) during end-to-end training. We show that its computational cost is cheaper than a single convolution layer. We apply it to an important class of physical systems-incompressible turbulent flows, where the divergence-free PDE constraint is required. We train a 3D Conditional Generative Adversarial Network (CGAN) for turbulent flow superresolution efficiently, while guaranteeing the spatial PDE constraint of zero divergence. Furthermore, our empirical results show that the model produces realistic flow statistics when trained with hard constraints imposed via the proposed novel differentiable spectral projection layer, as compared to soft constrained and unconstrained counterparts.},
 bibtype = {techreport},
 author = {Kashinath, Karthik and Marcus, Philip}
}

@article{
 title = {Speed-direction description of turbulent flows},
 type = {article},
 year = {2020},
 pages = {115128},
 volume = {32},
 websites = {http://aip.scitation.org/doi/10.1063/5.0031218},
 month = {11},
 publisher = {American Institute of Physics Inc.},
 day = {1},
 id = {61e5a178-e0bc-3b06-82b2-2ec7fe5c9107},
 created = {2021-04-09T15:22:58.545Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:08.486Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {In this note, we introduce speed and direction variables to describe the motion of incompressible viscous fluid. Fluid velocity u is decomposed into u = ur, with u = |u| and r = u/|u|. We consider a directional split of the Navier-Stokes equations into a coupled system of equations for u and for r. The equation for u is particularly simple but solely maintains the energy balance of the system. Under the assumption of a weak correlation between fluctuations in speed and direction in a developed turbulent flow, we further illustrate the application of u-r variables to describe mean statistics of a shear turbulence. The standard (full) Reynolds stress tensor does not appear in a resulting equation for the mean flow profile.},
 bibtype = {article},
 author = {Olshanskii, Maxim A.},
 doi = {10.1063/5.0031218},
 journal = {Physics of Fluids},
 number = {11}
}

@inproceedings{
 title = {A take on wake modeling of turbines based on deep learning},
 type = {inproceedings},
 year = {2020},
 keywords = {CNN,Computational fluid dynamics,GAN,Offshore renewable energy systems,Reduced-order modeling,Turbulent flow field,Unsupervised learning},
 volume = {2020-August},
 month = {10},
 publisher = {American Society of Mechanical Engineers (ASME)},
 day = {13},
 id = {7aafb4af-eba4-32ce-a7dc-e2914e92ed36},
 created = {2021-04-09T15:22:59.016Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:22:59.016Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Analyzing real-world engineering problems such as wake modeling of wind/ocean current turbines are known to be complex and challenging. The multivariable nature of these problems requires either the implementation of computational analyses under certain simplifying assumptions or conducting experiments for a limited number of scenarios. Hence, there is always several fundamental features missed in understanding the key players in determining the complex turbulent velocity fields within the wake of turbines. It becomes more critical when studying the optimization of wind/ocean renewable farms with more than one turbine to determine the true power density or cost of energy. Machine learning (ML) algorithms suggest promising complementary solutions to the existing physics-based (e.g. wind farm wake modeling) techniques. Implementation of conventional ML algorithms that require long-term historical data is either not feasible in many real-case applications or very expensive and time-consuming. Moreover, there are often infinite features in dataset with complex relation between them. It makes the tasks of feature selection and model tuning more challenging. In this work, a cross-domain study of physics and ML models is performed to show the need of integration of these domains. The key achievement of this work is two-fold: first, suggesting a group of emerging generative models (e.g. Generative Adversarial Networks) in the wake modeling domain; second, reducing the computational cost by demanding either smaller or no simulation dataset.},
 bibtype = {inproceedings},
 author = {Ziaei, Dorsa and Goudarzi, Navid},
 doi = {10.1115/POWER2020-16950},
 booktitle = {American Society of Mechanical Engineers, Power Division (Publication) POWER}
}

@article{
 title = {Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations},
 type = {article},
 year = {2020},
 keywords = {Physics-informed machine learning,Separated flows,Turbulence modeling},
 pages = {104431},
 volume = {200},
 month = {3},
 publisher = {Elsevier Ltd},
 day = {30},
 id = {d382f22a-060d-3a0c-948f-2de090393e2d},
 created = {2021-04-09T15:22:59.647Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:22:59.647Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Computational fluid dynamics models based on Reynolds-averaged Navier–Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant for decades. With recent advances in machine learning, data-driven turbulence models have become attractive alternatives worth further explorations. However, a major obstacle in the development of data-driven turbulence models is the lack of training data. In this work, we survey currently available public turbulent flow databases and conclude that they are inadequate for developing and validating data-driven models. Rather, we need more benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space for this purpose. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations. We further demonstrate the use of such a dataset by training a machine learning model that predicts Reynolds stress anisotropy based on a set of mean flow features. We expect the generated dataset, along with its design methodology and the example application presented herein, will facilitate development and comparison of future data-driven turbulence models.},
 bibtype = {article},
 author = {Xiao, Heng and Wu, Jin Long and Laizet, Sylvain and Duan, Lian},
 doi = {10.1016/j.compfluid.2020.104431},
 journal = {Computers and Fluids}
}

@article{
 title = {Developing particle image velocimetry software based on a deep neural network},
 type = {article},
 year = {2020},
 keywords = {Deep neural networks,Estimation of fluid motion,Particle image velocimetry},
 pages = {359-376},
 volume = {27},
 websites = {http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},
 publisher = {Begell House Inc.},
 id = {855967e5-91dd-34db-92b6-6aa75f42ee99},
 created = {2021-04-09T15:23:00.253Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:00.253Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {As an experimental technique for fluid mechanics, particle image velocimetry (PIV) can extract global and quantitative velocity field from images. With the development of artificial intelligence, designing PIV method based on deep learning is quite promising and worth exploring. First, in this paper, the authors introduce the optical flow neural network based on one proposed in the computer vision community. Second, a data set including particle images and the ground truth fluid motion is generated to train the parameters of the networks. This leads to a deep neural network for PIV which can provide estimation of dense motion (down to maximum one vector for one pixel) with the high degree of efficiency. The featuring of particle image extracted by the neural network is also investigated in this paper. It is found that feature matching improves the accuracy of esti-mation. The proposed network model is firstly evaluated by a synthetic image sequence of turbulent flow. An experiment measuring the flow over an aerofoil is used to validate the practicability. The experimental results indicate that compared with the traditional cross correlation method, the proposed deep neural network has advantages in accuracy, spatial resolution, and efficiency.},
 bibtype = {article},
 author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},
 doi = {10.1615/JFlowVisImageProc.2020033180},
 journal = {Journal of Flow Visualization and Image Processing},
 number = {4}
}

@article{
 title = {Dual channels of helicity cascade in turbulent flows},
 type = {article},
 year = {2020},
 keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},
 volume = {894},
 websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF},
 publisher = {Cambridge University Press},
 id = {08eeb047-4cd5-346d-9698-456857823601},
 created = {2021-04-09T15:23:00.826Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:00.826Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulent flows. Through theoretical analyses, we find that there are two channels in the helicity cascade process, which differs dramatically from the traditional viewpoint. In this paper, we have conducted important research on the newly proposed dual-channel helicity cascade theory, including vortex dynamic processes, intermittent discrepancies, tensor geometries, etc. The first channel mainly originates from the vortex twisting process, and the second channel mainly originates from the vortex stretching process. Antisymmetric tensors are introduced to the derivations of dual-channel helicity cascade theory, and a complex rotation frame leads to a higher helicity transfer efficiency. By analysing data from direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other types of turbulent flows. The intermittency of the second channel is stronger than that of the first channel. In addition, we find a novel mechanism of hindered or even inverse energy cascades, which could be attributed to the second-channel helicity flux.},
 bibtype = {article},
 author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Wang, Jianchun and Chen, Shiyi},
 doi = {10.1017/jfm.2020.289},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Data compression for turbulence databases using spatiotemporal subsampling and local resimulation},
 type = {article},
 year = {2020},
 pages = {064607},
 volume = {5},
 websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607},
 month = {6},
 publisher = {American Physical Society},
 day = {1},
 id = {6ce865be-a713-3e73-83dc-be3fbb8bd04b},
 created = {2021-04-09T15:23:01.423Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:01.423Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.},
 bibtype = {article},
 author = {Wu, Zhao and Zaki, Tamer A. and Meneveau, Charles},
 doi = {10.1103/PhysRevFluids.5.064607},
 journal = {Physical Review Fluids},
 number = {6}
}

@article{
 title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},
 type = {article},
 year = {2020},
 pages = {16},
 volume = {31},
 websites = {https://doi.org/10.1088/1361-6501/ab848d},
 month = {9},
 publisher = {Institute of Physics Publishing},
 day = {1},
 id = {65d799a3-d02e-31c4-bf57-e23d965b9285},
 created = {2021-04-09T15:23:01.980Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:10.041Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},
 bibtype = {article},
 author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},
 doi = {10.1088/1361-6501/ab848d},
 journal = {Measurement Science and Technology},
 number = {9}
}

@article{
 title = {Learning dominant physical processes with data-driven balance models},
 type = {article},
 year = {2021},
 keywords = {Applied mathematics,Computational science,Physics},
 pages = {1-10},
 volume = {12},
 websites = {https://doi.org/10.1038/s41467-021-21331-z},
 month = {12},
 publisher = {Nature Research},
 day = {1},
 id = {65773184-a381-3802-8cef-979c7b013b38},
 created = {2021-04-09T15:23:02.935Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:10.405Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only applies in asymptotic regimes where there is a strict separation of scales in the physics. Here, we automate and generalize this approach to non-asymptotic regimes by introducing the idea of an equation space, in which different local balances appear as distinct subspace clusters. Unsupervised learning can then automatically identify regions where groups of terms may be neglected. We show that our data-driven balance models successfully delineate dominant balance physics in a much richer class of systems. In particular, this approach uncovers key mechanistic models in turbulence, combustion, nonlinear optics, geophysical fluids, and neuroscience.},
 bibtype = {article},
 author = {Callaham, Jared L. and Koch, James V. and Brunton, Bingni W. and Kutz, J. Nathan and Brunton, Steven L.},
 doi = {10.1038/s41467-021-21331-z},
 journal = {Nature Communications},
 number = {1}
}

@article{
 title = {NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations},
 type = {article},
 year = {2021},
 keywords = {Ill-posed problems,PINNs,Transfer learning,Turbulence,Velocity-pressure formulation,Vorticity-velocity formulation},
 pages = {109951},
 volume = {426},
 month = {2},
 publisher = {Academic Press Inc.},
 day = {1},
 id = {e3efa042-5d37-39e7-bce7-85eb007e210c},
 created = {2021-04-09T15:23:03.649Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:03.649Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at Reτ∼1,000, but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. We also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.},
 bibtype = {article},
 author = {Jin, Xiaowei and Cai, Shengze and Li, Hui and Karniadakis, George Em},
 doi = {10.1016/j.jcp.2020.109951},
 journal = {Journal of Computational Physics}
}

@misc{
 title = {As a matter of tension - kinetic energy spectra in MHD turbulence},
 type = {misc},
 year = {2020},
 source = {arXiv},
 keywords = {MHD,Methods: numerical,Turbulence},
 pages = {148},
 volume = {909},
 issue = {2},
 websites = {https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta},
 month = {9},
 publisher = {arXiv},
 day = {7},
 id = {46aa6f81-0116-3381-9a45-cb8ae1a65f65},
 created = {2021-04-09T15:23:04.161Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:04.161Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Magnetized turbulence is ubiquitous in many astrophysical and terrestrial systems but no complete, uncontested theory even in the simplest form, magnetohydrodynamics (MHD), exists. Many theories and phenomenologies focus on the joint (kinetic and magnetic) energy fluxes and spectra. We highlight the importance of treating kinetic and magnetic energies separately to shed light on MHD turbulence dynamics. We conduct an implicit large eddy simulation of subsonic, super-Alfvénic MHD turbulence and analyze the scale-wise energy transfer over time. Our key finding is that the kinetic energy spectrum develops a scaling of approximately k−4/3 in the stationary regime as the kinetic energy cascade is suppressed by magnetic tension. This motivates a reevaluation of existing MHD turbulence theories with respect to a more differentiated modeling of the energy fluxes.},
 bibtype = {misc},
 author = {Grete, Philipp and O’Shea, Brian W. and Beckwith, Kris},
 doi = {10.3847/1538-4357/abdd22}
}

@article{
 title = {Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles},
 type = {article},
 year = {2021},
 pages = {103627},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756},
 month = {3},
 publisher = {Pergamon},
 day = {13},
 id = {f2cc069f-bc29-3f68-8cc6-734cd5d5244a},
 created = {2021-04-09T15:23:04.654Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:04.654Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Jie, Yucheng and Andersson, Helge I. and Zhao, Lihao},
 doi = {10.1016/j.ijmultiphaseflow.2021.103627},
 journal = {International Journal of Multiphase Flow}
}

@inproceedings{
 title = {Optimal clipping of the gradient model for subgrid stress closure},
 type = {inproceedings},
 year = {2021},
 pages = {1-16},
 websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665},
 publisher = {American Institute of Aeronautics and Astronautics Inc, AIAA},
 id = {2a8d900a-b84e-3601-9ead-56f37770b12a},
 created = {2021-04-09T15:23:05.122Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:05.122Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Large Eddy Simulation (LES) involves modeling of the Subgrid Stress (SGS) tensor to close the set of filtered Navier-Stokes equations. The gradient model is a well-known candidate for SGS closure. Stresses obtained using the gradient model have high structural accuracy, that is, these stresses are in high correlation with those from the filtered DNS data in a priori studies. However, a posteriori simulations at a high Reynolds number are subject to energy pileup at small resolved scales due in part to model backscatter that often cascades to numerical instabilities. The modeled stresses are often clipped to eliminate model backscatter and, thereby, improve the dissipative performance and stability of these simulations. However, this comes at the cost of reduced structural accuracy. In this paper, we propose an optimal clipping procedure that recasts the operation as a minimization problem. The proposed clipping ensures that the impact of clipping on the structural accuracy is minimal and, at the same time, there is no model backscatter. We demonstrate the resulting model form is similar to that of mixed models. We conduct a series of a priori and a posteriori tests to investigate the impact of the traditional and optimal clipping procedures. We observe that optimal clipping leads to a significant improvement in model predictions as compared to the traditional clipping procedure for select forced homogeneous isotropic turbulence, Taylor-Green vortex, and channel flow cases.},
 bibtype = {inproceedings},
 author = {Prakash, Aviral and Jansen, Kenneth E. and Evans, John A.},
 doi = {10.2514/6.2021-1665},
 booktitle = {AIAA Scitech 2021 Forum}
}

@article{
 title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},
 type = {article},
 year = {2020},
 keywords = {turbulence simulation},
 volume = {910},
 websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6},
 publisher = {Cambridge University Press},
 id = {27c4e2e7-9c31-38fb-a542-9c5db2bdcdeb},
 created = {2021-04-09T15:23:05.570Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:05.570Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},
 bibtype = {article},
 author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},
 doi = {10.1017/jfm.2020.1028},
 journal = {Journal of Fluid Mechanics}
}

@misc{
 title = {Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows},
 type = {misc},
 year = {2020},
 source = {arXiv},
 keywords = {turbulence modelling,turbulence theory †},
 pages = {6},
 volume = {914},
 websites = {https://doi.org/10.1017/jfm.2020.977},
 month = {6},
 publisher = {arXiv},
 day = {3},
 id = {70465517-279e-3fdb-9989-01d5df030e63},
 created = {2021-04-09T15:23:06.069Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:11.909Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {By analyzing the Karman-Howarth equation for filtered velocity fields in turbulent flows, we show that the two-point correlation between filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlations-based statistical priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence we show that local eddy viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows.},
 bibtype = {misc},
 author = {Clark Di Leoni, Patricio and Zaki, Tamer A. and Karniadakis, George and Meneveau, Charles},
 doi = {10.1017/jfm.2020.977}
}

@article{
 title = {A study of inner-outer interactions in turbulent channel flows by interactive POD},
 type = {article},
 year = {2021},
 pages = {100222},
 month = {2},
 publisher = {Elsevier BV},
 day = {17},
 id = {277fb85f-9a1c-3648-bf9c-83b446322b79},
 created = {2021-04-09T15:23:06.538Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:12.377Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Hongping and Gao, Qi},
 doi = {10.1016/j.taml.2021.100222},
 journal = {Theoretical and Applied Mechanics Letters}
}

@article{
 title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R <sub>eτ</sub> = 150, 400 and 1020},
 type = {article},
 year = {2021},
 keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},
 pages = {36-50},
 volume = {59},
 websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},
 month = {1},
 publisher = {Taylor and Francis Ltd.},
 day = {2},
 id = {bff8a865-3735-375b-b7b6-a81a95dfcd66},
 created = {2021-04-09T15:23:07.047Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:12.855Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},
 bibtype = {article},
 author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},
 doi = {10.1080/00221686.2020.1729265},
 journal = {Journal of Hydraulic Research},
 number = {1}
}

@article{
 title = {Construction of urban turbulent flow database with wavelet-based compression: A study with large-eddy simulation of flow and dispersion in block-arrayed building group model},
 type = {article},
 year = {2021},
 keywords = {Computational fluid dynamics,Data compression,Dispersion simulation,Large-eddy simulation,Urban flow database,Wavelet transform},
 pages = {104433},
 volume = {208},
 month = {1},
 publisher = {Elsevier B.V.},
 day = {1},
 id = {e2b98148-30c1-35b0-a10e-b9b35cd10e46},
 created = {2021-04-09T15:23:07.512Z},
 accessed = {2021-04-08},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:07.512Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Urban Turbulent flow database, which includes accurately simulated velocity field with full spatial distribution and time-dependent dynamics, is beneficial for fast analysis of pollutant dispersion and comprehensive validation. However, the enormous data volume makes storage and sharing difficult. This research investigated the feasibility of constructing a small-sized database by compression. A wavelet-based compression method was selected because of its light calculation burden and independence of time series data. The database of the flow field in urban-like arrayed blocks was obtained by large-eddy simulation, and then the velocity and diffusion coefficient fields were compressed with different error controls to construct databases. The compression ability of the wavelet-based method was evaluated, and it was found that the maximum compression ratio is reached when most information in the wavelet coefficients is discarded. The effects of compression error on both the single snapshot and the time-series results were studied. The applicability of the compressed database was verified by the resimulation of passive scalar dispersion in the flow. According to results, the database with approximately 100-times compression is suitable for such applications as the visualization and dispersion simulation of passive scalars with sufficient accuracy.},
 bibtype = {article},
 author = {Jia, Hongyuan and Kikumoto, Hideki},
 doi = {10.1016/j.jweia.2020.104433},
 journal = {Journal of Wind Engineering and Industrial Aerodynamics}
}

@article{
 title = {Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows},
 type = {article},
 year = {2021},
 keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},
 pages = {84},
 volume = {62},
 websites = {http://link.springer.com/10.1007/s00348-021-03156-0},
 month = {4},
 publisher = {Springer},
 day = {31},
 id = {96e37199-25a7-3e0b-849d-8fbb8637bf75},
 created = {2021-04-09T15:23:08.214Z},
 accessed = {2021-04-08},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:13.472Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor's hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian-Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor's hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier-Stokes equations compared to the mean flow convective method.},
 bibtype = {article},
 author = {Fratantonio, Dominique and Lai, Chris C. K. and Charonko, John and Prestridge, Kathy},
 doi = {10.1007/s00348-021-03156-0},
 journal = {Experiments in Fluids},
 number = {4}
}

@article{
 title = {Stochastic Lagrangian dynamics of vorticity. Part 1. General theory for viscous, incompressible fluids},
 type = {article},
 year = {2020},
 volume = {901},
 month = {10},
 day = {25},
 id = {31cff53d-f2e9-385b-bee6-263cf1d5df55},
 created = {2021-04-09T15:23:08.688Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:08.688Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Prior mathematical work of Constantin & Iyer (Commun. Pure Appl. Maths, vol. 61, 2008, pp. 330–345; Ann. Appl. Probab., vol. 21, 2011, pp. 1466–1492) has shown that incompressible Navier–Stokes solutions possess infinitely many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the invariants of Cauchy (Sciences mathématiques et physique, vol. I, 1815, pp. 33–73) for smooth Euler solutions. We reformulate this theory for the case of wall-bounded flows by appealing to the Kuz'min (Phys. Lett. A, vol. 96, 1983, pp. 88–90)–Oseledets (Russ. Math. Surv., vol. 44, 1989, p. 210) representation of Navier–Stokes dynamics, in terms of the vortex-momentum density associated to a continuous distribution of infinitesimal vortex rings. The Constantin–Iyer theory provides an exact representation for vorticity at any interior point as an average over stochastic vorticity contributions transported from the wall. We point out relations of this Lagrangian formulation with the Eulerian theory of Lighthill (Boundary layer theory. In Laminar Boundary Layers (ed. L. Rosenhead), 1963, pp. 46–113)–Morton (Geophys. Astrophys. Fluid Dyn., vol. 28, 1984, pp. 277–308) for vorticity generation at solid walls, and also with a statistical result of Taylor (Proc. R. Soc. Lond. A, vol. 135, 1932, pp. 685–702)–Huggins (J. Low Temp. Phys., vol. 96, 1994, pp. 317–346), which connects dissipative drag with organized cross-stream motion of vorticity and which is closely analogous to the ‘Josephson–Anderson relation’ for quantum superfluids. We elaborate a Monte Carlo numerical Lagrangian scheme to calculate the stochastic Cauchy invariants and their statistics, given the Eulerian space–time velocity field. The method is validated using an online database of a turbulent channel-flow simulation (Graham et al., J. Turbul., vol. 17, 2016, pp. 181–215), where conservation of the mean Cauchy invariant is verified for two selected buffer-layer events corresponding to an ‘ejection’ and a ‘sweep’. The variances of the stochastic Cauchy invariants grow exponentially backward in time, however, revealing Lagrangian chaos of the stochastic trajectories undergoing both fluid advection and viscous diffusion.},
 bibtype = {article},
 author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},
 doi = {10.1017/jfm.2020.491},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Stochastic Lagrangian dynamics of vorticity. Part 2. Application to near-wall channel-flow turbulence},
 type = {article},
 year = {2020},
 volume = {901},
 month = {10},
 day = {25},
 id = {f4a750c4-3dce-3e29-b0ae-ae027506a6da},
 created = {2021-04-09T15:23:09.180Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:09.180Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We use an online database of a turbulent channel-flow simulation at 𝑅𝑒𝜏=1000 (Graham et al. J. Turbul., vol. 17, issue 2, 2016, pp. 181–215) to determine the origin of vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (J. Fluid Mech., vol. 633, 2009, pp.17–60), we identify typical ‘ejection’ and ‘sweep’ events in the buffer layer by local minima/maxima of the wall stress. In contrast to their conjecture, however, we find that vortex lifting from the wall is not a discrete event requiring ∼ 1 viscous time and ∼ 10 wall units, but is instead a distributed process over a space–time region at least 1∼2 orders of magnitude larger in extent. To reach this conclusion, we exploit a rigorous mathematical theory of vorticity dynamics for Navier–Stokes solutions, in terms of stochastic Lagrangian flows and stochastic Cauchy invariants, conserved on average backward in time. This theory yields exact expressions for vorticity inside the flow domain in terms of vorticity at the wall, as transported by viscous diffusion and by nonlinear advection, stretching and rotation. We show that Lagrangian chaos observed in the buffer layer can be reconciled with saturated vorticity magnitude by ‘virtual reconnection’: although the Eulerian vorticity field in the viscous sublayer has a single sign of spanwise component, opposite signs of Lagrangian vorticity evolve by rotation and cancel by viscous destruction. Our analysis reveals many unifying features of classical fluids and quantum superfluids. We argue that ‘bundles’ of quantized vortices in superfluid turbulence will also exhibit stochastic Lagrangian dynamics and satisfy stochastic conservation laws resulting from particle relabelling symmetry.},
 bibtype = {article},
 author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},
 doi = {10.1017/jfm.2020.492},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations},
 type = {article},
 year = {2018},
 websites = {http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262},
 month = {4},
 id = {b3715914-ba21-3486-84e7-5f2b72759a86},
 created = {2021-04-09T15:23:09.679Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:09.679Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynolds number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a sixty-seven percent accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.},
 bibtype = {article},
 author = {McCracken, Megan},
 doi = {10.1145/3219104.3229262}
}

@article{
 title = {Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1902.09929},
 month = {4},
 id = {281385a6-8a49-3483-95e5-d151e1a57bd5},
 created = {2021-04-09T15:23:10.129Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:10.129Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We perform direct numerical simulations (DNSs) of emulsions in homogeneous, isotropic turbulence using a pseudopotential lattice-Boltzmann (PP-LB) method. Improving on previous literature by minimizing droplet dissolution and spurious currents, we show that the PP-LB technique is capable of long, stable simulations in certain parameter regions. Varying the dispersed phase volume fraction φ, we demonstrate that droplet breakup extracts kinetic energy from the larger scales while injecting energy into the smaller scales, increasingly with higher φ, with the Hinze scale dividing the two effects. Droplet size (d) distribution was found to follow the d^-10/3 scaling (Deane & Stokes 2002). We show the need to maintain a separation of the turbulence forcing scale and domain size to prevent the formation of large connected regions of the dispersed phase. For the first time, we show that turbulent emulsions evolve into a quasi-equilibrium cycle of alternating coalescence and breakup dominated processes. Studying the system in its state-space comprising kinetic energy E_k, enstrophy ω^2 and the droplet number density N_d, we find that their dynamics resemble limit-cycles with a time delay. Extreme values in the evolution of E_k manifest in the evolution of ω^2 and N_d with a delay of ~0.3T and ~0.9T respectively (with T the large eddy timescale). Lastly, we also show that flow topology of turbulence in an emulsion is significantly more different than single-phase turbulence than previously thought. In particular, vortex compression and axial straining mechanisms become dominant in the droplet phase, a consequence of the elastic behaviour of droplet interfaces.},
 bibtype = {article},
 author = {Mukherjee, Siddhartha and Safdari, Arman and Shardt, Orest and Kenjeres, Sasa and den Akker, Harry E A Van}
}

@misc{
 title = {Techniques for 3D-PIV},
 type = {misc},
 year = {2018},
 source = {Particle Image Velocimetry},
 pages = {309-365},
 websites = {http://link.springer.com/10.1007/978-3-319-68852-7_9},
 publisher = {Springer International Publishing},
 id = {8ee722fd-7e42-38e2-a51f-5d6d07406d7e},
 created = {2021-04-09T15:23:10.924Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:10.924Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {book_section},
 private_publication = {false},
 bibtype = {misc},
 author = {Raffel, Markus and Willert, Christian E and Scarano, Fulvio and Kähler, Christian J and Wereley, Steven T and Kompenhans, Jürgen},
 doi = {10.1007/978-3-319-68852-7_9}
}

@article{
 title = {Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers},
 type = {article},
 year = {2019},
 pages = {34101},
 volume = {4},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101},
 month = {4},
 publisher = {American Physical Society},
 id = {cdf950fb-cf1c-354d-b297-b77c65b772e1},
 created = {2021-04-09T15:23:11.553Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:11.553Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Ge, M.-W. and Yang, Xiang I A and Marusic, Ivan},
 doi = {10.1103/PhysRevFluids.4.034101},
 journal = {Physical Review Fluids},
 number = {3}
}

@inproceedings{
 title = {Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations},
 type = {inproceedings},
 year = {2017},
 pages = {2584-2592},
 websites = {http://ieeexplore.ieee.org/document/8237542/},
 month = {4},
 publisher = {IEEE},
 id = {3f68124b-812f-3e04-a39c-7163dc10e60e},
 created = {2021-04-09T15:23:12.026Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:12.026Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {In experimental fluid dynamics, the flow in a volume of fluid is observed by injecting high-contrast tracer particles and tracking them in multi-view video. Fluid dynamics re-searchers have developed variants of space-carving to re-construct the 3D particle distribution at a given time-step, and then use relatively simple local matching to recover the motion over time. On the contrary, estimating the opti-cal flow between two consecutive images is a long-standing standard problem in computer vision, but only little work exists about volumetric 3D flow. Here, we propose a varia-tional method for 3D fluid flow estimation from multi-view data. We start from a 3D version of the standard varia-tional flow model, and investigate different regularization schemes that ensure divergence-free flow fields, to account for the physics of incompressible fluids. Moreover, we pro-pose a semi-dense formulation, to cope with the computa-tional demands of large volumetric datasets. Flow is esti-mated and regularized at a lower spatial resolution, while the data term is evaluated at full resolution to preserve the discriminative power and geometric precision of the local particle distribution. Extensive experiments reveal that a simple sum of squared differences (SSD) is the most suit-able data term for our application. For regularization, an energy whose Euler-Lagrange equations correspond to the stationary Stokes equations leads to the best results. This strictly enforces a divergence-free flow and additionally pe-nalizes the squared gradient of the flow.},
 bibtype = {inproceedings},
 author = {Lasinger, Katrin and Vogel, Christoph and Schindler, Konrad},
 doi = {10.1109/ICCV.2017.280},
 booktitle = {2017 IEEE International Conference on Computer Vision (ICCV)}
}

@article{
 title = {Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency},
 type = {article},
 year = {2017},
 keywords = {Hybrid LES/RANS,OpenFOAM,Turbulence modelling,Wall-bounded flows},
 pages = {73-83},
 volume = {157},
 websites = {https://www.sciencedirect.com/science/article/pii/S0045793017302852},
 month = {4},
 publisher = {Pergamon},
 id = {8dde42f9-59e0-384e-8274-2b5e9502d15e},
 created = {2021-04-09T15:23:12.565Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:12.565Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper presents a combined RANS and LES methodology, which automates the dual-mesh hybrid LES/RANS approach and circumvents the need for wall-functions. Unlike RANS, wall-resolved LES is still unaffordable for studying high Reynolds number complex flows in industry and requires much user expertise when turbulence features are unknown a priori. The present approach avoids these issues by concurrently solving the LES and unsteady RANS equations on separate meshes, which are adapted to each model and are overlapping over the entire domain. The RANS solution guides the LES where its mesh is too coarse, and vice-versa where the LES is well-resolved. The driver- and driven-simulation locally swap roles automatically, depending on which one is deemed more reliable by a blending function. Consistency between the RANS solution and a temporal average of the LES solution is enforced by drift terms, whose strength depend on relaxation times-scales that are provided by the RANS model. Predictions for fully-developed channel flows and the flow through periodic hills are shown to be in excellent agreement with reference data. The LES grids are deliberately too coarse for wall-resolved LES, while the independent RANS mesh uses high aspect-ratio cells to economically resolve the near-wall layer.},
 bibtype = {article},
 author = {Tunstall, R and Laurence, D and Prosser, R and Skillen, A},
 doi = {10.1016/j.compfluid.2017.08.002},
 journal = {Computers and Fluids}
}

@article{
 title = {Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932},
 type = {article},
 year = {2016},
 keywords = {turbulence simulation,turbulent boundary layers,turbulent flows},
 pages = {356-394},
 volume = {803},
 websites = {http://www.journals.cambridge.org/abstract_S0022112016005048},
 month = {4},
 id = {7e9d65e4-b575-3200-b915-dd2f7127ea25},
 created = {2021-04-09T15:23:13.084Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:13.084Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The invariants of the velocity gradient tensor, R and Q, and their enstrophy and strain components are studied in the logarithmic layer of an incompressible turbulent channel flow. The velocities are filtered in the three spatial directions and the results analyzed at different scales. We show that the R–Q plane does not capture the changes undergone by the flow as the filter width increases, and that the enstrophy/enstrophy-production and strain/strain-production planes represent better choices. We also show that the conditional mean trajectories may differ significantly from the instantaneous behavior of the flow since they are the result of an averaging process where the mean is 3-5 times smaller than the corresponding standard deviation. The orbital periods in the R–Q plane are shown to be independent of the intensity of the events, and of the same order of magnitude than those in the enstrophy/enstrophy-production and strain/strain-production planes. Our final goal is to test whether the dynamics of the flow are self-similar in the inertial range, and the answer turns out to be no. The mean shear is found to be responsible for the absence of self-similarity and progressively controls the dynamics of the eddies observed as the filter width increases. However, a self-similar behavior emerges when the calculations are repeated for the fluctuating velocity gradient tensor. Finally, the turbulent cascade in terms of vortex stretching is considered by computing the alignment of the vorticity at a given scale with the strain at a different one. These results generally support a non-negligible role of the phenomenological energy-cascade model formulated in terms of vortex stretching.},
 bibtype = {article},
 author = {Lozano-Durán, A and Holzner, M and Jiménez, J},
 doi = {10.1017/jfm.2016.504},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {The anisotropic structure of turbulence and its energy spectrum},
 type = {article},
 year = {2016},
 pages = {11701},
 volume = {28},
 websites = {http://aip.scitation.org/doi/10.1063/1.4939471},
 month = {4},
 id = {15cb2dab-6eab-3807-90eb-f579a18bc5c5},
 created = {2021-04-09T15:23:13.967Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:13.967Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The spectral energy distribution in turbulent flows is observed to follow a k−5/3 power scaling, as originally predicted by Kolmogorov’s theory. However, the underlying assumptions in Kolmogorov’s theory appear not to hold with most experimental and numerical data showing evidence of small-scale anisotropy and significant direct energy transfer between the large- and the small-scales. Here, we present a flow structure that reconciles the k−5/3 spectrum with small-scale universality, small-scale anisotropy, and direct scale interactions. The flow structure is a shear layer, which contains the small-scales of motion and is bounded by the large-scales. The anisotropic shear layer reveals the expected scaling of the energy spectrum in nearly all directions.},
 bibtype = {article},
 author = {Elsinga, G E and Marusic, I},
 doi = {10.1063/1.4939471},
 journal = {Physics of Fluids},
 number = {1}
}

@misc{
 title = {Hierarchical models for financial markets and turbulence},
 type = {misc},
 year = {2018},
 websites = {https://repositorio.ufpe.br/handle/123456789/31035},
 month = {4},
 publisher = {Universidade Federal de Pernambuco},
 id = {8417a4a2-5d9f-349f-ad47-0263483f4ee4},
 created = {2021-04-09T15:23:14.900Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:14.900Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {thesis},
 private_publication = {false},
 abstract = {CAPES},
 bibtype = {misc},
 author = {Correa, William Oswaldo Sosa}
}

@article{
 title = {Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence},
 type = {article},
 year = {2013},
 keywords = {Applied mathematics,Astronomy and astrophysics,Astrophysical plasmas,Information technology},
 pages = {466-469},
 volume = {497},
 websites = {http://www.nature.com/articles/nature12128},
 month = {4},
 publisher = {Nature Publishing Group},
 id = {6a88f6fa-126a-376e-be84-8a2f914b8b62},
 created = {2021-04-09T15:23:16.064Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:16.064Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The idea of 'frozen-in' magnetic field lines for ideal plasmas is useful to explain diverse astrophysical phenomena, for example the shedding of excess angular momentum from protostars by twisting of field lines frozen into the interstellar medium. Frozen-in field lines, however, preclude the rapid changes in magnetic topology observed at high conductivities, as in solar flares. Microphysical plasma processes are a proposed explanation of the observed high rates, but it is an open question whether such processes can rapidly reconnect astrophysical flux structures much greater in extent than several thousand ion gyroradii. An alternative explanation is that turbulent Richardson advection brings field lines implosively together from distances far apart to separations of the order of gyroradii. Here we report an analysis of a simulation of magnetohydrodynamic turbulence at high conductivity that exhibits Richardson dispersion. This effect of advection in rough velocity fields, which appear non-differentiable in space, leads to line motions that are completely indeterministic or 'spontaneously stochastic', as predicted in analytical studies. The turbulent breakdown of standard flux freezing at scales greater than the ion gyroradius can explain fast reconnection of very large-scale flux structures, both observed (solar flares and coronal mass ejections) and predicted (the inner heliosheath, accretion disks, γ-ray bursts and so on). For laminar plasma flows with smooth velocity fields or for low turbulence intensity, stochastic flux freezing reduces to the usual frozen-in condition.},
 bibtype = {article},
 author = {Eyink, Gregory and Vishniac, Ethan and Lalescu, Cristian and Aluie, Hussein and Kanov, Kalin and Bürger, Kai and Burns, Randal and Meneveau, Charles and Szalay, Alexander},
 doi = {10.1038/nature12128},
 journal = {Nature},
 number = {7450}
}

@inproceedings{
 title = {Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking},
 type = {inproceedings},
 year = {2018},
 websites = {https://www.research-collection.ethz.ch/handle/20.500.11850/279200},
 month = {4},
 publisher = {ETH Zurich},
 id = {a51771b0-62fb-346c-bdc2-bb3045c1a60b},
 created = {2021-04-09T15:23:17.163Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:17.163Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Huhn, F and Schröder, Andreas and Schanz, D and Gesemann, S and Manovski, P},
 editor = {Rösgen, Thomas},
 doi = {10.3929/ETHZ-B-000279200},
 booktitle = {18th International Symposium on Flow Visualization (ISFV18)}
}

@inproceedings{
 title = {In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis},
 type = {inproceedings},
 year = {2017},
 keywords = {Floating-point compression,GPU video encoding,Volume compression},
 pages = {64-73},
 volume = {2017-Decem},
 websites = {http://ieeexplore.ieee.org/document/8231852/},
 month = {4},
 publisher = {IEEE},
 id = {ae2fd0e8-eb3b-34bb-ae02-c84319d53fb9},
 created = {2021-04-09T15:23:18.258Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:18.258Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.},
 bibtype = {inproceedings},
 author = {Leaf, Nick and Miller, Bob and Ma, Kwan Liu},
 doi = {10.1109/LDAV.2017.8231852},
 booktitle = {2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017}
}

@article{
 title = {A uniform momentum zone–vortical fissure model of the turbulent boundary layer},
 type = {article},
 year = {2019},
 keywords = {boundary layer structure,turbulence modelling,turbulent boundary layers},
 pages = {609-633},
 volume = {858},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {ee6df86a-88f6-3f40-8c15-a9446fb35c8a},
 created = {2021-04-09T15:23:19.246Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:19.246Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Recent studies reveal that at large friction Reynolds number [STIX]x1D6FF^+ the inertially dominated region of the turbulent boundary layer is composed of large-scale zones of nearly uniform momentum segregated by narrow fissures of concentrated vorticity. Experiments show that, when scaled by the boundary-layer thickness, the fissure thickness is O(1/[STIX]x1D6FF^+) , while the dimensional jump in streamwise velocity across each fissure scales in proportion to the friction velocity u_[STIX]x1D70F . A simple model that exploits these essential elements of the turbulent boundary-layer structure at large [STIX]x1D6FF^+ is developed. First, a master wall-normal profile of streamwise velocity is constructed by placing a discrete number of fissures across the boundary layer. The number of fissures and their wall-normal locations follow scalings informed by analysis of the mean momentum equation. The fissures are then randomly displaced in the wall-normal direction, exchanging momentum as they move, to create an instantaneous velocity profile. This process is repeated to generate ensembles of streamwise velocity profiles from which statistical moments are computed. The modelled statistical profiles are shown to agree remarkably well with those acquired from direct numerical simulations of turbulent channel flow at large [STIX]x1D6FF^+ . In particular, the model robustly reproduces the empirically observed sub-Gaussian behaviour for the skewness and kurtosis profiles over a large range of input parameters.},
 bibtype = {article},
 author = {Bautista, Juan Carlos Cuevas and Ebadi, Alireza and White, Christopher M and Chini, Gregory P and Klewicki, Joseph C},
 doi = {10.1017/jfm.2018.769},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Fluctuation dynamos and their Faraday rotation signatures},
 type = {article},
 year = {2013},
 pages = {2469-2481},
 volume = {429},
 websites = {http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation},
 month = {4},
 publisher = {Oxford University Press},
 id = {411f3d9f-938e-3b01-9d5d-a75cabb68633},
 created = {2021-04-09T15:23:19.834Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:19.834Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Bhat, Pallavi and Subramanian, Kandaswamy},
 doi = {10.1093/mnras/sts516},
 journal = {Monthly Notices of the Royal Astronomical Society},
 number = {3}
}

@article{
 title = {On PIV random error minimization with optimal POD-based low-order reconstruction},
 type = {article},
 year = {2015},
 pages = {75},
 volume = {56},
 websites = {http://link.springer.com/10.1007/s00348-015-1940-8},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {e02969e8-fdd8-3b3d-8ee5-c7c59492f1d8},
 created = {2021-04-09T15:23:20.692Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:20.692Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© 2015, Springer-Verlag Berlin Heidelberg. Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows.},
 bibtype = {article},
 author = {Raiola, Marco and Discetti, Stefano and Ianiro, Andrea},
 doi = {10.1007/s00348-015-1940-8},
 journal = {Experiments in Fluids},
 number = {4}
}

@misc{
 title = {Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows},
 type = {misc},
 year = {2015},
 websites = {http://www.osti.gov/servlets/purl/1221181/},
 month = {4},
 institution = {Sandia National Laboratories (SNL)},
 id = {92304c26-4a57-3361-b9af-462cc2475259},
 created = {2021-04-09T15:23:21.473Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:21.473Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {report},
 private_publication = {false},
 bibtype = {misc},
 author = {Templeton, Jeremy Alan and Blaylock, Myra L and Domino, Stefan P and Hewson, John C and Kumar, Pritvi Raj and Ling, Julia and Najm, Habib N and Ruiz, Anthony and Safta, Cosmin and Sargsyan, Khachik and Stewart, Alessia and Wagner, Gregory},
 doi = {10.2172/1221181}
}

@article{
 title = {Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence},
 type = {article},
 year = {2011},
 pages = {261-268},
 volume = {18},
 websites = {https://www.nonlin-processes-geophys.net/18/261/2011/},
 month = {4},
 id = {8f32c50d-8599-33b6-a5d8-0a33019102dd},
 created = {2021-04-09T15:23:22.180Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:22.180Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.},
 bibtype = {article},
 author = {Wu, C C and Chang, T},
 doi = {10.5194/npg-18-261-2011},
 journal = {Nonlinear Processes in Geophysics},
 number = {2}
}

@inproceedings{
 title = {Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder},
 type = {inproceedings},
 year = {2016},
 websites = {http://arc.aiaa.org/doi/10.2514/6.2016-1048},
 month = {4},
 publisher = {American Institute of Aeronautics and Astronautics},
 id = {064e72ac-06e5-3458-8c9e-86c71f12040e},
 created = {2021-04-09T15:23:22.630Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:22.630Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {© 2016, American Institute of Aeronautics and Astronautics Inc, AIAA . All rights reserved. Instantaneous and time-resolved pressure is evaluated in a 6-liter measurement volume by making use of tomographic PTV with Helium-filled soap bubbles (HFSB) as tracers. This volume is two orders of magnitude larger than conventional tomographic experiments. The experiment considers the near-wake of a surface mounted cylinder (Re D = 3.6×10 4 ), which is highly unsteady and fully three-dimensional. Pressure is calculated from the tomographic velocity measurement by invoking the incompressible momentum equation. The time-averaged, RMS and instantaneous pressure is validated against simultaneous and independent pressure measurements made by pressure transducers in the surface. The mean and RMS pressure is in good correspondence to the reference measurements. Cross-correlation of the instantaneous pressure time-series with the reference measurement signal yields a cross-correlation coefficient peak value of 0.6. The present study shows that instantaneous pressure can be measured non-intrusively in a large measurement volume by making use of tomographic PTV with HFSB as tracers, which allows significantly reduced model complexity as the use of pressure transducers is avoided.},
 bibtype = {inproceedings},
 author = {Schneiders, Jan and Caridi, Giuseppe Carlo Alp and Sciacchitano, Andrea and Scarano, Fulvio},
 doi = {10.2514/6.2016-1048},
 booktitle = {54th AIAA Aerospace Sciences Meeting}
}

@article{
 title = {Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows},
 type = {article},
 year = {2014},
 pages = {14501},
 volume = {112},
 websites = {https://link.aps.org/doi/10.1103/PhysRevLett.112.014501},
 month = {4},
 publisher = {American Physical Society},
 id = {3894f9ae-c4f5-365a-9482-522b9a30d427},
 created = {2021-04-09T15:23:23.153Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:23.153Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of Lagrangian correlation functions. These capture preferential sampling of the fluid gradients which in turn can give rise to differences in the tumbling rates of disks and rods. We show that this is a weak effect in Gaussian random flows. But in turbulent flows persistent regions of high vorticity cause disks to tumble much faster than rods, as observed in direct numerical simulations [Parsa et al., Phys. Rev. Lett. 109 (2012) 134501]. For larger particles (at finite Stokes numbers), rotational and translational inertia affects the tumbling rate and the angle at which particles collide, due to the formation of rotational caustics.},
 bibtype = {article},
 author = {Gustavsson, K and Einarsson, J and Mehlig, B},
 doi = {10.1103/PhysRevLett.112.014501},
 journal = {Physical Review Letters},
 number = {1}
}

@article{
 title = {Complex Networks Unveiling Spatial Patterns in Turbulence},
 type = {article},
 year = {2016},
 keywords = {Complex networks,spatial correlation,spatiotemporal patterns,time series analysis,turbulent flows},
 pages = {1650223},
 volume = {26},
 websites = {http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230},
 month = {4},
 publisher = {World Scientific Publishing Company},
 id = {90dfeab9-ddc5-3436-b6a3-2af6cf730f25},
 created = {2021-04-09T15:23:23.612Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:23.612Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.},
 bibtype = {article},
 author = {Scarsoglio, Stefania and Iacobello, Giovanni and Ridolfi, Luca},
 doi = {10.1142/S0218127416502230},
 journal = {International Journal of Bifurcation and Chaos},
 number = {13}
}

@article{
 title = {Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence},
 type = {article},
 year = {2018},
 keywords = {remesh smoothed particle hydrodynamics,three-dimensional isotropic decaying turbulence,turbulent flow},
 pages = {1-19},
 volume = {86},
 websites = {http://doi.wiley.com/10.1002/fld.4405},
 month = {4},
 publisher = {Wiley-Blackwell},
 id = {51235906-1632-379f-8de3-6d3c18134f8b},
 created = {2021-04-09T15:23:24.693Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:24.693Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Copyright © 2017 John Wiley & Sons, Ltd. We present a remeshed particle-mesh method for the simulation of three-dimensional compressible turbulent flow. The method is related to the meshfree smoothed particle hydrodynamics method, but the present method introduces a mesh for efficient calculation of the pressure gradient, and laminar and turbulent diffusion. In addition, the mesh is used to remesh (reorganise uniformly) the particles to ensure a regular particle distribution and convergence of the method. The accuracy of the presented methodology is tested for a number of benchmark problems involving two- and three-dimensional Taylor-Green flow, thin double shear layer, and three-dimensional isotropic turbulence. Two models were implemented, direct numerical simulations, and Smagorinsky model. Taking advantage of the Lagrangian advection, and the finite difference efficiency, the method is capable of providing quality simulations while maintaining its robustness and versatility.},
 bibtype = {article},
 author = {Obeidat, Anas and Bordas, Stéphane P A},
 doi = {10.1002/fld.4405},
 journal = {International Journal for Numerical Methods in Fluids},
 number = {1}
}

@article{
 title = {Kolmogorov spectrum consistent optimization for multi-scale flow decomposition},
 type = {article},
 year = {2014},
 pages = {55106},
 volume = {26},
 websites = {http://aip.scitation.org/doi/10.1063/1.4871106},
 month = {4},
 id = {489c5ab7-e1ff-3915-994f-e4aae3de0d50},
 created = {2021-04-09T15:23:25.571Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:25.571Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide ...},
 bibtype = {article},
 author = {Mishra, M and Liu, X and Skote, M and Fu, C W},
 doi = {10.1063/1.4871106},
 journal = {Physics of Fluids},
 number = {5}
}

@article{
 title = {A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data},
 type = {article},
 year = {2016},
 keywords = {experimental fluid mechanics,image processing,outlier detection,particle image velocimetry,proper orthogonal decomposition},
 pages = {125303},
 volume = {27},
 websites = {http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b},
 month = {4},
 id = {dba5bfce-3af7-344f-b0c3-c53a04d6e84e},
 created = {2021-04-09T15:23:26.054Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:26.054Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.},
 bibtype = {article},
 author = {Higham, J E and Brevis, W and Keylock, C J},
 doi = {10.1088/0957-0233/27/12/125303},
 journal = {Measurement Science and Technology},
 number = {12}
}

@article{
 title = {GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution},
 type = {article},
 year = {2019},
 pages = {58},
 volume = {60},
 websites = {http://link.springer.com/10.1007/s00348-019-2700-y},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {d7556610-b073-3556-97e4-8438c2bb3eb2},
 created = {2021-04-09T15:23:26.564Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:26.564Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Jin and Zhang, Cao and Katz, Joseph},
 doi = {10.1007/s00348-019-2700-y},
 journal = {Experiments in Fluids},
 number = {4}
}

@article{
 title = {Local and nonlocal dynamics in superfluid turbulence},
 type = {article},
 year = {2015},
 pages = {104517},
 volume = {91},
 websites = {https://link.aps.org/doi/10.1103/PhysRevB.91.104517},
 month = {4},
 publisher = {American Physical Society},
 id = {7bb1275f-e165-3b14-a23e-732c494ccda4},
 created = {2021-04-09T15:23:27.432Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:27.432Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Turbulence in superfluid helium~II is a tangle of quantized vortex lines which interact via the classical Biot-Savart law. We show that vortex tangles with the same vortex line density will have different energy spectra, depending on the normal fluid which feeds energy into the superfluid component, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the 'worms` of ordinary turbulence.},
 bibtype = {article},
 author = {Sherwin-Robson, L K and Barenghi, C F and Baggaley, A W},
 doi = {10.1103/PhysRevB.91.104517},
 journal = {Physical Review B},
 number = {10}
}

@article{
 title = {On coarse-grained simulations of turbulent material mixing},
 type = {article},
 year = {2012},
 pages = {58203},
 volume = {86},
 websites = {http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27},
 month = {4},
 publisher = {IOP Publishing},
 id = {b59e8f66-df49-356c-9971-4e3390d30396},
 created = {2021-04-09T15:23:28.097Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:28.097Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.},
 bibtype = {article},
 author = {Grinstein, F F and Gowardhan, A A and Ristorcelli, J R and Wachtor, A J},
 doi = {10.1088/0031-8949/86/05/058203},
 journal = {Physica Scripta},
 number = {5}
}

@article{
 title = {Full-field pressure from snapshot and time-resolved volumetric PIV},
 type = {article},
 year = {2016},
 pages = {1-14},
 volume = {57},
 websites = {http://link.springer.com/10.1007/s00348-016-2129-5},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {7301db0a-bf15-37e9-a0f6-62747dd8aaab},
 created = {2021-04-09T15:23:29.050Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:29.050Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Laskari, A and de Kat, R and Ganapathisubramani, B},
 doi = {10.1007/s00348-016-2129-5},
 journal = {Experiments in Fluids},
 number = {3}
}

@article{
 title = {An irrotation correction on pressure gradient and orthogonal-path integration for PIV-based pressure reconstruction},
 type = {article},
 year = {2016},
 pages = {104},
 volume = {57},
 websites = {http://link.springer.com/10.1007/s00348-016-2189-6},
 month = {4},
 id = {450552f0-5512-3d43-b994-555bf6625074},
 created = {2021-04-09T15:23:29.744Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:29.744Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Zhongyi and Gao, Qi and Wang, Chengyue and Wei, Runjie and Wang, Jinjun},
 doi = {10.1007/s00348-016-2189-6},
 journal = {Experiments in Fluids},
 number = {6}
}

@article{
 title = {Dependence of small-scale energetics on large scales in turbulent flows},
 type = {article},
 year = {2018},
 keywords = {turbulence modelling,turbulence theory,turbulent boundary layers},
 pages = {641-662},
 volume = {852},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {20a15fd0-0e26-3049-909b-f48f7d0eab96},
 created = {2021-04-09T15:23:30.767Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:30.767Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In a turbulent flow, small- and large-scale fluid motions are coupled. In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. The evidence suggests that the existence of nonlinear interscale interactions in the form of amplitude modulation does not rely on the presence of a non-penetrating boundary, but on the presence of a range of viscosity-dominated scales and a range of inertial-dominated scales.},
 bibtype = {article},
 author = {Howland, M F and Yang, X I A},
 doi = {10.1017/jfm.2018.554},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows},
 type = {article},
 year = {2018},
 keywords = {Two-level simulation,backscatter,large eddy simulation,turbulent transport,vorticity},
 pages = {334-364},
 volume = {19},
 websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616},
 month = {4},
 publisher = {Taylor & Francis},
 id = {b6889d9f-7732-377a-8249-5a2127ff4b74},
 created = {2021-04-09T15:23:31.280Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:31.280Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {ABSTRACTThe two-level simulation (TLS) method evolves both the large-and the small-scale fields in a two-scale approach and has shown good predictive capabilities in both isotropic and wall-bounded...},
 bibtype = {article},
 author = {Ranjan, R and Menon, S},
 doi = {10.1080/14685248.2018.1438616},
 journal = {Journal of Turbulence},
 number = {4}
}

@inproceedings{
 title = {Group Anomaly Detection using Flexible Genre Models},
 type = {inproceedings},
 year = {2011},
 pages = {1071-1079},
 websites = {https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models},
 publisher = {Neural Information Processing Systems},
 id = {8a5cc374-2abf-3d97-ac43-391fd8dc4019},
 created = {2021-04-09T15:23:31.713Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:31.713Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {An important task in exploring and analyzing real-world data sets is to detect unusual and interesting phenomena. In this paper, we study the group anomaly detection problem. Unlike traditional anomaly detection research that focuses on data points, our goal is to discover anomalous aggregated behaviors of groups of points. For this purpose, we propose the Flexible Genre Model (FGM). FGM is designed to characterize data groups at both the point level and the group level so as to detect various types of group anomalies. We evaluate the effectiveness of FGM on both synthetic and real data sets including images and turbulence data, and show that it is superior to existing approaches in detecting group anomalies.},
 bibtype = {inproceedings},
 author = {Xiong, Liang and Poczos, Barnabas and Schneider, Jeff},
 doi = {10.5591/978-1-57735-516-8/IJCAI11-254},
 booktitle = {Advances in Neural Information Processing Systems}
}

@inproceedings{
 title = {Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation},
 type = {inproceedings},
 year = {2018},
 websites = {https://arc.aiaa.org/doi/10.2514/6.2018-0594},
 month = {4},
 publisher = {American Institute of Aeronautics and Astronautics},
 id = {c66ecc3c-d9e9-3b91-acdb-d8a24046714d},
 created = {2021-04-09T15:23:32.376Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:32.376Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Doronina, Olga and Christopher, Jason and Towery, Colin A Z and Hamlington, Peter and Dahm, Werner J A},
 doi = {10.2514/6.2018-0594},
 booktitle = {2018 AIAA Aerospace Sciences Meeting}
}

@article{
 title = {Time-reversal-symmetry breaking in turbulence},
 type = {article},
 year = {2014},
 pages = {54501},
 volume = {113},
 websites = {https://link.aps.org/doi/10.1103/PhysRevLett.113.054501},
 month = {4},
 id = {63563e3e-b931-33fc-928b-86829f9249e1},
 created = {2021-04-09T15:23:32.941Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:32.941Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In three-dimensional turbulent flows, the flux of energy from large to small scales breaks time symmetry. We show here that this irreversibility can be quantified by following the relative motion of several Lagrangian tracers. We find by analytical calculation, numerical analysis and experimental observation that the existence of the energy flux implies that, at short times, two particles separate temporally slower forwards than backwards, and the difference between forward and backward dispersion grows as t^3. We also find the geometric deformation of material volumes, surrogated by four points spanning an initially regular tetrahedron, to show sensitivity to the time-reversal with an effect growing linearly in t. We associate this with the structure of the strain rate in the flow.},
 bibtype = {article},
 author = {Jucha, Jennifer and Xu, Haitao and Pumir, Alain and Bodenschatz, Eberhard},
 doi = {10.1103/PhysRevLett.113.054501},
 journal = {Physical Review Letters},
 number = {5}
}

@article{
 title = {A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking},
 type = {article},
 year = {2019},
 pages = {45302},
 volume = {30},
 websites = {http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c},
 month = {4},
 publisher = {IOP Publishing},
 id = {6f742a18-ef05-39f4-8e72-5916fb799b83},
 created = {2021-04-09T15:23:33.577Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:33.577Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Clark, A and Machicoane, N and Aliseda, A},
 doi = {10.1088/1361-6501/ab0786},
 journal = {Measurement Science and Technology},
 number = {4}
}

@article{
 title = {Flight-crash events in turbulence},
 type = {article},
 year = {2014},
 keywords = {Lagrangian description,direct and inverse turbulent energy cascades,nonequilibrium statistical mechanics,nonequilibrium systems,turbulent mixing},
 pages = {7558-7563},
 volume = {111},
 websites = {http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111},
 month = {4},
 publisher = {National Academy of Sciences},
 id = {fda3961e-245e-3a03-a910-a65e04ccf982},
 created = {2021-04-09T15:23:34.122Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:34.122Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The statistical properties of turbulence differ in an essential way from those of systems in or near thermal equilibrium because of the flux of energy between vastly different scales at which energy is supplied and at which it is dissipated. We elucidate this difference by studying experimentally and numerically the fluctuations of the energy of a small fluid particle moving in a turbulent fluid. We demonstrate how the fundamental property of detailed balance is broken, so that the probabilities of forward and backward transitions are not equal for turbulence. In physical terms, we found that in a large set of flow configurations, fluid elements decelerate faster than accelerate, a feature known all too well from driving in dense traffic. The statistical signature of rare "flight-crash" events, associated with fast particle deceleration, provides a way to quantify irreversibility in a turbulent flow. Namely, we find that the third moment of the power fluctuations along a trajectory, nondimensionalized by the energy flux, displays a remarkable power law as a function of the Reynolds number, both in two and in three spatial dimensions. This establishes a relation between the irreversibility of the system and the range of active scales. We speculate that the breakdown of the detailed balance characterized here is a general feature of other systems very far from equilibrium, displaying a wide range of spatial scales.},
 bibtype = {article},
 author = {Xu, Haitao and Pumir, Alain and Falkovich, Gregory and Bodenschatz, Eberhard and Shats, Michael and Xia, Hua and Francois, Nicolas and Boffetta, Guido},
 doi = {10.1073/pnas.1321682111},
 journal = {Proceedings of the National Academy of Sciences},
 number = {21}
}

@article{
 title = {Deformation of a compliant wall in a turbulent channel flow},
 type = {article},
 year = {2017},
 keywords = {Turbulent boundary Layers,Turbulent flows},
 pages = {345-390},
 volume = {823},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {b7254578-dcde-3f36-a742-ff0536faf242},
 created = {2021-04-09T15:23:34.928Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:34.928Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Interaction of a compliant wall with a turbulent channel flow is investigated experimentally by simultaneously measuring the time-resolved, three-dimensional (3D) flow field and the two-dimensional (2D) surface deformation. The optical set-up integrates tomographic particle image velocimetry to measure the flow with Mach–Zehnder interferometry to map the deformation. The Reynolds number is Re_[STIX]x1D70F=2300 , and the Young’s modulus of the wall is 0.93 MPa, resulting in a ratio of shear speed to the centreline velocity ( U_0 ) of 6.8. The wavenumber–frequency spectra of deformation show the surface motions consist of a non-advected low-frequency component and advected modes, some travelling downstream at approximately U_0 and others at ~0.72U_0 . The r.m.s. values of the advected and non-advected modes are 0.04~[STIX]x03BCm (0.004[STIX]x1D6FF_[STIX]x1D708) and 0.2~[STIX]x03BCm ( 0.02[STIX]x1D6FF_[STIX]x1D708 ), respectively, much smaller than the wall unit ( [STIX]x1D6FF_[STIX]x1D708 ), hence they do not affect the flow. Trends in the wall dynamics are elucidated by correlating the deformation with flow variables, including the 3D pressure distribution calculated by spatially integrating the material acceleration. Predictions by the Chase [ J. Acoust. Soc. Am. , vol. 89 (6), pp. 2589–2596] linear model are also calculated and compared to the measured trends. The spatial deformation–pressure correlations peak at y/h 0.12 ( h is half channel height), the elevation of Reynolds shear stress maximum in the log-layer. Streamwise lagging of the deformation behind the pressure is caused in part by phase lag of the pressure with decreasing distance from the wall, and in part by material damping. Positive deformations (bumps) caused by negative pressure fluctuations are preferentially associated with ejections involving spanwise vortices located downstream and quasi-streamwise vortices with spanwise offset. Results of conditional correlations are consistent with the presence of hairpin-like structures. The negative deformations (dimples) are preferentially associated with positive pressure fluctuations at the transition between an upstream sweep to a downstream ejection.},
 bibtype = {article},
 author = {Zhang, Cao and Wang, Jin and Blake, William and Katz, Joseph},
 doi = {10.1017/jfm.2017.299},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1902.07358},
 month = {4},
 id = {bf1067d7-1a27-31e0-9024-7edb31cc4c99},
 created = {2021-04-09T15:23:35.428Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:35.428Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance with traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.},
 bibtype = {article},
 author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan}
}

@article{
 title = {Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence},
 type = {article},
 year = {2019},
 keywords = {intermittency,isotropic turbulence,particle/fluid flows},
 pages = {465-486},
 volume = {860},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {0aeeba05-23f0-32cf-918a-2aeba6c223e8},
 created = {2021-04-09T15:23:36.064Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:36.064Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We examine the dynamics of slender, rigid rods in direct numerical simulation of isotropic turbulence. The focus is on the statistics of three quantities and how they vary as rod length increases from the dissipation range to the inertial range. These quantities are (i) the steady-state rod alignment with respect to the perceived velocity gradients in the surrounding flow, (ii) the rate of rod reorientation (tumbling) and (iii) the rate at which the rod end points move apart (stretching). Under the approximations of slender-body theory, the rod inertia is neglected and rods are modelled as passive particles in the flow that do not affect the fluid velocity field. We find that the average rod alignment changes qualitatively as rod length increases from the dissipation range to the inertial range. While rods in the dissipation range align most strongly with fluid vorticity, rods in the inertial range align most strongly with the most extensional eigenvector of the perceived strain-rate tensor. For rods in the inertial range, we find that the variance of rod stretching and the variance of rod tumbling both scale as l^-4/3 , where l is the rod length. However, when rod dynamics are compared to two-point fluid velocity statistics (structure functions), we see non-monotonic behaviour in the variance of rod tumbling due to the influence of small-scale fluid motions. Additionally, we find that the skewness of rod stretching does not show scale invariance in the inertial range, in contrast to the skewness of longitudinal fluid velocity increments as predicted by Kolmogorov’s 4/5 law. Finally, we examine the power-law scaling exponents of higher-order moments of rod tumbling and rod stretching for rods with lengths in the inertial range and find that they show anomalous scaling. We compare these scaling exponents to predictions from Kolmogorov’s refined similarity hypotheses.},
 bibtype = {article},
 author = {Pujara, Nimish and Voth, Greg A and Variano, Evan A},
 doi = {10.1017/jfm.2018.866},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing},
 type = {article},
 year = {2016},
 keywords = {Compressible flows,DNS,Density fluctuations,Favre average,Homogeneous turbulence,Linear Interaction Approximation,Mixing,RANS,Rayleigh-Taylor,Reynolds stress,Richtmyer-Meshkov,Shear,Turbulence,Two-length scale,Two-time scale,Variable density},
 pages = {1-43},
 volume = {96},
 websites = {http://link.springer.com/10.1007/s10494-015-9643-z},
 month = {4},
 publisher = {Springer Netherlands},
 id = {cbacad99-a22a-316d-ba88-7841c0cd0d26},
 created = {2021-04-09T15:23:36.618Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:36.618Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.},
 bibtype = {article},
 author = {Schwarzkopf, J D and Livescu, D and Baltzer, J R and Gore, R A and Ristorcelli, J R},
 doi = {10.1007/s10494-015-9643-z},
 journal = {Flow, Turbulence and Combustion},
 number = {1}
}

@article{
 title = {TTHRESH: Tensor Compression for Multidimensional Visual Data},
 type = {article},
 year = {2019},
 pages = {1},
 websites = {http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/},
 month = {4},
 id = {42be9489-0a16-33a0-83cb-d7f6a51e32f6},
 created = {2021-04-09T15:23:37.189Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:37.189Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression algorithm for N-dimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to 3 and more dimensions, together with adaptive quantization, run-length and arithmetic coding to store the HOSVD transform coefficients' relative positions as sorted by their absolute magnitude. Our scheme degrades the data particularly smoothly and outperforms other state-of-the-art volume compressors at low-to-medium bit rates, as required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include extremely fine bit rate selection granularity, bounded resulting l^2 error, and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct subsampled or filtered-resampled versions of all (or selected parts) of the data set.},
 bibtype = {article},
 author = {Ballester-Ripoll, Rafael and Lindstrom, Peter and Pajarola, Renato},
 doi = {10.1109/TVCG.2019.2904063},
 journal = {IEEE Transactions on Visualization and Computer Graphics}
}

@article{
 title = {The spanwise spectra in wall-bounded turbulence},
 type = {article},
 year = {2018},
 keywords = {Inner/outer peak,Scale separation,Streamwise/spanwise spectra,Wall-bounded turbulence},
 pages = {452-461},
 volume = {34},
 websites = {http://link.springer.com/10.1007/s10409-017-0731-2},
 month = {4},
 publisher = {The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences},
 id = {bb01c65f-b97c-3004-b791-211a96563468},
 created = {2021-04-09T15:23:37.690Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:37.690Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Hong-Ping and Wang, Shi-Zhao and He, Guo-Wei},
 doi = {10.1007/s10409-017-0731-2},
 journal = {Acta Mechanica Sinica},
 number = {3}
}

@article{
 title = {Beyond Kolmogorov cascades},
 type = {article},
 year = {2019},
 keywords = {intermittency,turbulence theory},
 pages = {P1},
 volume = {867},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {1012b117-456b-32d9-b1ba-3795e219b594},
 created = {2021-04-09T15:23:38.322Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:38.322Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The large-scale structure of many turbulent flows encountered in practical situations such as aeronautics, industry, meteorology is nowadays successfully computed using the Kolmogorov–Kármán–Howarth energy cascade picture. This theory appears increasingly inaccurate when going down the energy cascade that terminates through intermittent spots of energy dissipation, at variance with the assumed homogeneity. This is problematic for the modelling of all processes that depend on small scales of turbulence, such as combustion instabilities or droplet atomization in industrial burners or cloud formation. This paper explores a paradigm shift where the homogeneity hypothesis is replaced by the assumption that turbulence contains singularities, as suggested by Onsager. This paradigm leads to a weak formulation of the Kolmogorov–Kármán–Howarth–Monin equation (WKHE) that allows taking into account explicitly the presence of singularities and their impact on the energy transfer and dissipation. It provides a local in scale, space and time description of energy transfers and dissipation, valid for any inhomogeneous, anisotropic flow, under any type of boundary conditions. The goal of this article is to discuss WKHE as a tool to get a new description of energy cascades and dissipation that goes beyond Kolmogorov and allows the description of small-scale intermittency. It puts the problem of intermittency and dissipation in turbulence into a modern framework, compatible with recent mathematical advances on the proof of Onsager’s conjecture.},
 bibtype = {article},
 author = {Dubrulle, Bérengère},
 doi = {10.1017/jfm.2019.98},
 journal = {Journal of Fluid Mechanics}
}

@misc{
 title = {Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow},
 type = {misc},
 year = {2019},
 keywords = {analysis,computational fluid dynamics,reference turbine,simulations,wind energy},
 websites = {http://www.osti.gov/servlets/purl/1493479/},
 month = {4},
 institution = {National Renewable Energy Laboratory (NREL)},
 id = {70cedc58-3373-3d60-afe1-61d2bbed6131},
 created = {2021-04-09T15:23:38.930Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:38.930Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {report},
 private_publication = {false},
 bibtype = {misc},
 author = {Lawson, Michael J and Melvin, Jeremy and Ananthan, Shreyas and Gruchalla, Kenny M and Rood, Jonathan S and Sprague, Michael A},
 doi = {10.2172/1493479}
}

@article{
 title = {Analysis of geometrical and statistical features of Lagrangian stretching in turbulent channel flow using a database task-parallel particle tracking algorithm},
 type = {article},
 year = {2017},
 pages = {14605},
 volume = {2},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605},
 month = {4},
 publisher = {American Physical Society},
 id = {e74b8566-4274-3b1a-a739-79796c7ef4f6},
 created = {2021-04-09T15:23:39.680Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:39.680Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Johnson, Perry L and Hamilton, Stephen S and Burns, Randal and Meneveau, Charles},
 doi = {10.1103/PhysRevFluids.2.014605},
 journal = {Physical Review Fluids},
 number = {1}
}

@article{
 title = {Compression and heuristic caching for GPU particle tracing in turbulent vector fields},
 type = {article},
 year = {2016},
 keywords = {Data compression,Data streaming,Particle tracing,Turbulence,Vector fields},
 pages = {144-165},
 volume = {598},
 websites = {http://link.springer.com/10.1007/978-3-319-29971-6_8},
 publisher = {Springer, Cham},
 id = {c967ab18-170c-3561-9b15-cf0969b9566f},
 created = {2021-04-09T15:23:40.216Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:40.216Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© Springer International Publishing Switzerland 2016. Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.},
 bibtype = {article},
 author = {Treib, Marc and Bürger, Kai and Wu, Jun and Westermann, Rüdiger},
 doi = {10.1007/978-3-319-29971-6_8},
 journal = {Communications in Computer and Information Science}
}

@article{
 title = {Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements},
 type = {article},
 year = {2018},
 keywords = {Dynamic estimation,Linear stochastic estimation,PIV,Proper orthogonal decomposition},
 pages = {119-130},
 volume = {93},
 websites = {https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941},
 month = {4},
 publisher = {Elsevier},
 id = {cdac6288-8a17-349d-91de-b4fe36f68248},
 created = {2021-04-09T15:23:40.778Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:40.778Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {A method for the estimation of time-resolved turbulent fields from the combination of non-time-resolved field measurements and time-resolved point measurements is proposed. The approach poses its fundaments on a stochastic estimation based on the Proper Orthogonal Decomposition (POD) of the field measurements and of the time-resolved point measurements. The correlation between the temporal modes of the field measurements and the temporal modes of the point measurements at synchronized instants is evaluated; this correlation is extended to the “out-of-sample” time instants for the field measurements, i.e. those in which field data are not available. In the “out-of-sample” instants, POD modes time coefficients are estimated and the flow fields are reconstructed. The proposed method extends the work by Hosseini et al. (Experiments in fluids, 56, 2015) by proposing a truncation criterion which allows removing the uncorrelated part of the signal from the reconstruction of the flow fields. The truncation is fundamental in case of turbulent flow fields, in which a great wealth of scales is involved, thus reducing the correlation between the probe signal and the field measurements. The threshold selection is based on the random distribution of the uncorrelated signal. Additionally, the selection of the probe time-span to perform the POD analysis on the probe signal is discussed. The method is validated with a synthetic test case and an experimental one. A Direct Numerical Simulation database of a channel flow is selected since its spectral richness is expected to represent a significant challenge for this method. This dataset allows isolating the effects of correlation between field measurements and point measurements, removing issues connected to noise contamination or to the finite spatial resolution which would inevitably affect experimental data. The experimental test case is the wake-flow behind a high-angle-of-attack airfoil with a relatively small number of samples, affected by significant noise. The quality of the dynamic estimation is found to be affected by the noise contamination of the data and by the poor convergence of the POD modes, which add on the effect of the probe location, i.e. on the correlation between probe events and flow features. The squared correlation coefficient between reconstructed data and in-sample data is proposed as an assessment of the flow fields estimation quality. The use of the squared correlation coefficient directly on in-sample data is allowed by the truncation itself.},
 bibtype = {article},
 author = {Discetti, Stefano and Raiola, Marco and Ianiro, Andrea},
 doi = {10.1016/j.expthermflusci.2017.12.011},
 journal = {Experimental Thermal and Fluid Science}
}

@article{
 title = {A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport},
 type = {article},
 year = {2012},
 pages = {n/a-n/a},
 volume = {117},
 websites = {http://doi.wiley.com/10.1029/2011JF002127},
 month = {4},
 id = {cf45c3cd-ec34-3554-a185-77fd023702b3},
 created = {2021-04-09T15:23:41.333Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:41.333Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Kolmogorov�s classic theory for turbulence assumed an independence velocity increments and the value for the velocity itself., recent work has called this assumption in to question, which implications for the structure of atmospheric, oceanic and fluvial. Here we propose a conceptually simple analytical framework studying velocity-intermittency coupling that is similar in essence the popular quadrant analysis method for studying near-wall flows., we study the dominant (longitudinal) velocity component with a measure of the roughness of the signal, given mathematically its series of H�lder exponents. Thus, we permit a possible dependence velocity and intermittency. We compare boundary layer data in a wind tunnel to turbulent jets and wake flows. These classes all have distinct characteristics, which cause them be readily distinguished using our technique and the results are to changes in flow Reynolds numbers. Classification of environmental is then possible based on their similarities to the idealized classes and we demonstrate this using laboratory data for flow a parallel-channel confluence. Our results have clear implications sediment transport in a range of geophysical applications as suggest that the recently proposed impulse-based methods for bed load transport are particularly relevant in domains as gravel bed river flows where the boundary layer is disrupted wake interactions predominate.},
 bibtype = {article},
 author = {Keylock, C J and Nishimura, K and Peinke, J},
 doi = {10.1029/2011JF002127},
 journal = {Journal of Geophysical Research: Earth Surface},
 number = {1}
}

@inproceedings{
 title = {3D Fluid Flow Estimation with Integrated Particle Reconstruction},
 type = {inproceedings},
 year = {2018},
 pages = {315-332},
 websites = {http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22},
 month = {4},
 id = {494766c9-e3b7-399f-9215-806df54ff32a},
 created = {2021-04-09T15:23:41.951Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:41.951Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps: first, a per-frame reconstruction of the particles, usually in the form of soft occupancy likelihoods in a voxel representation; followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model explicitly reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-resolution input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over a recent baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of state-of-the-art tracking-based methods that require much longer sequences.},
 bibtype = {inproceedings},
 author = {Lasinger, Katrin and Vogel, Christoph and Pock, Thomas and Schindler, Konrad},
 doi = {10.1007/978-3-030-12939-2_22},
 booktitle = {40th German Conference on Pattern Recognition, GCPR 2018}
}

@article{
 title = {Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence},
 type = {article},
 year = {2018},
 pages = {1665-1671},
 volume = {382},
 websites = {https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918},
 month = {4},
 publisher = {North-Holland},
 id = {f51f7ca2-fc3f-3dcb-9662-759d1235c5ba},
 created = {2021-04-09T15:23:42.918Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:42.918Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In order to introduce new physics to traditional two-point correlations, we define the second-order correlation of longitudinal velocity increments at three points and obtain the analytical expressions in isotropic turbulence. By introducing the Kolmogorov 4/5 law, this three-point correlation explicitly contains velocity second- and third-order moments, which correspond to energy and energy transfer respectively. The combination of them then shows additional information of non-equilibrium turbulence by comparing to two-point correlations. Moreover, this three-point correlation shows the underlying inconsistency between numerical interpolation and three-point scaling law in numerical calculations, and inspires a preliminary model to correct this problem in isotropic turbulence.},
 bibtype = {article},
 author = {Wu, J Z and Fang, L and Shao, L and Lu, L P},
 doi = {10.1016/j.physleta.2018.04.021},
 journal = {Physics Letters A},
 number = {25}
}

@article{
 title = {Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence},
 type = {article},
 year = {2018},
 keywords = {Isotropic turbulence,correlators,four-fifths law,incompressibility},
 pages = {717-730},
 volume = {19},
 websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055},
 month = {4},
 publisher = {Taylor & Francis},
 id = {ea64be6e-fa7d-30d9-97b6-f2a6881023cd},
 created = {2021-04-09T15:23:43.536Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:43.536Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {ABSTRACTOn the grounds of Kolmogorov's 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are deriv...},
 bibtype = {article},
 author = {Kopyev, A V and Zybin, K P},
 doi = {10.1080/14685248.2018.1511055},
 journal = {Journal of Turbulence},
 number = {9}
}

@article{
 title = {Tensor geometry in the turbulent cascade},
 type = {article},
 year = {2018},
 keywords = {turbulence theory,turbulent flows},
 pages = {1048-1064},
 volume = {835},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {10073d10-c167-3626-bd0c-6712d69b8083},
 created = {2021-04-09T15:23:44.057Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:44.057Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The defining characteristic of highly turbulent flows is the net directed transport of energy from the injection scales to the dissipation scales. This cascade is typically described in Fourier space, obscuring its connection to the mechanics of the flow. Here, we recast the energy cascade in mechanical terms, noting that for some scales to transfer energy to others, they must do mechanical work on them. This work can be expressed as the inner product of a turbulent stress and a rate of strain. But, as with all inner products, the relative alignment of these two tensors matters, and determines how strong the energy transfer will be. We show that this tensor alignment behaves very differently in two and three dimensions; in particular, the tensor eigenvalues affect the inner product in very different ways. By comparing the observed energy flux to the maximum possible if the tensors were in perfect alignment, we define an efficiency for the energy cascade. Using data from a direct numerical simulation of isotropic turbulence, we show that this efficiency is perhaps surprisingly low, with an average value of approximately 25 % in the inertial range, although it is spatially heterogeneous. Our results have implications for how the stress and strain-rate magnitudes influence the flux of energy between scales, and may help to explain why the energy cascades in two and three dimensions are different.},
 bibtype = {article},
 author = {Ballouz, Joseph G and Ouellette, Nicholas T},
 doi = {10.1017/jfm.2017.802},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Line density control in screen-space via balanced line hierarchies},
 type = {article},
 year = {2016},
 keywords = {Flow visualization,Focus + Context,Line fields,Line hierarchy,Scientific visualization},
 pages = {29-39},
 volume = {61},
 websites = {https://www.sciencedirect.com/science/article/pii/S0097849316300899},
 month = {4},
 publisher = {Pergamon},
 id = {02127f1b-afa6-31a9-ad0b-875309b32cf3},
 created = {2021-04-09T15:23:44.570Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:44.570Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {For the visualization of dense sets of 3D lines, view-dependent approaches have been proposed to avoid the occlusion of important structures. Popular concepts consider global line selection based on line importance and screen-space occupancy, and opacity optimization to resolve locally the occlusion problem. In this work, we present a novel approach to improve the spatial perception and enable the interactive visualization of large 3D line sets. Instead of making lines locally transparent, which affects a lines spatial perception and can obscure spatial relationships, we propose to adapt the line density based on line importance and screen-space occupancy. In contrast to global line selection, however, our adaptation is local and only thins out the lines where significant occlusions occur. To achieve this we present a novel approach based on minimum cost perfect matching to construct an optimal, fully balanced line hierarchy. For determining locally the desired line density, we propose a projection-based screen-space measure considering the variation in line direction, line coverage, importance, and depth. This measure can be computed in an order-independent way and evaluated efficiently on the GPU.},
 bibtype = {article},
 author = {Kanzler, Mathias and Ferstl, Florian and Westermann, Rüdiger},
 doi = {10.1016/j.cag.2016.08.001},
 journal = {Computers and Graphics}
}

@article{
 title = {Stochastic flux freezing and magnetic dynamo},
 type = {article},
 year = {2011},
 pages = {56405},
 volume = {83},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.83.056405},
 month = {4},
 publisher = {American Physical Society},
 id = {86fc86ac-22a9-3fa9-917f-b58302cd9209},
 created = {2021-04-09T15:23:45.122Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:45.122Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the "spontaneous stochasticity" of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.},
 bibtype = {article},
 author = {Eyink, Gregory L},
 doi = {10.1103/PhysRevE.83.056405},
 journal = {Physical Review E},
 number = {5}
}

@misc{
 title = {Intermittency and Structure(s) of and/in Turbulence},
 type = {misc},
 year = {2019},
 source = {The Essence of Turbulence as a Physical Phenomenon},
 pages = {157-190},
 websites = {http://link.springer.com/10.1007/978-3-319-99531-1_9},
 publisher = {Springer International Publishing},
 id = {e83f4ea7-2729-3756-b100-dc5719f9e27d},
 created = {2021-04-09T15:23:46.181Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:46.181Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {book_section},
 private_publication = {false},
 bibtype = {misc},
 author = {Tsinober, Arkady},
 doi = {10.1007/978-3-319-99531-1_9}
}

@article{
 title = {Using deformable particles for single particle measurements of velocity gradient tensors},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1906.03075},
 month = {4},
 id = {2d3fb34f-e041-36e5-9b65-9804e1cba455},
 created = {2021-04-09T15:23:46.671Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:46.671Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We measure the deformation of particles made of several slender arms in a two-dimensional (2D) linear shear and a three-dimensional (3D) turbulent flow. We show how these measurements of arm deformations along with the rotation rate of the particle allow us to extract the velocity gradient tensor of the flow. The particles used in the experiments have three symmetric arms in a plane (triads) and are fabricated using 3D printing of a flexible polymeric material. Deformation measurements of a particle free to rotate about a fixed axis in a 2D simple shear flow are used to validate our model relating particle deformations to the fluid strain. We then examine deformable particles in a 3D turbulent flow created by a jet array in a vertical water tunnel. Particle orientations and deformations are measured with high precision using four high speed cameras and have an uncertainty on the order of 10^-4 radians. Measured deformations in 3D turbulence are small and only slightly larger than our orientation measurement uncertainty. Simulation results for triads in turbulence show deformations similar to the experimental observations. Deformable particles offer a promising method for measuring the full local velocity gradient tensor from measurements of a single particle where traditionally a high concentration of tracer particles would be required.},
 bibtype = {article},
 author = {Hejazi, Bardia and Krellenstein, Michael and Voth, Greg A}
}

@article{
 title = {Modeling three-dimensional scalar mixing with forced one-dimensional turbulence},
 type = {article},
 year = {2018},
 keywords = {flow simulation,numerical analysis,turbulence},
 pages = {125103},
 volume = {30},
 websites = {http://aip.scitation.org/doi/10.1063/1.5055752},
 month = {4},
 publisher = {AIP Publishing LLC},
 id = {10740e25-ecd9-3e7a-99bf-da8defaee44c},
 created = {2021-04-09T15:23:47.440Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:47.440Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We study the capability of the One-Dimensional-Turbulence (ODT) model to simulate the turbulent transport and mixing of multiple passive scalars in homogeneous isotropic stationary turbulence. To t...},
 bibtype = {article},
 author = {Giddey, Valentin and Meyer, Daniel W and Jenny, Patrick},
 doi = {10.1063/1.5055752},
 journal = {Physics of Fluids},
 number = {12}
}

@article{
 title = {A Voxel-Based Rendering Pipeline for Large 3D Line Sets},
 type = {article},
 year = {2019},
 keywords = {Ray-casting,global illumination,large 3D line sets,transparency},
 pages = {2378-2391},
 volume = {25},
 websites = {https://ieeexplore.ieee.org/document/8356687/},
 month = {4},
 id = {f26f0e03-62ab-3fb6-a185-654bd2768cf8},
 created = {2021-04-09T15:23:47.931Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:47.931Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We present a voxel-based rendering pipeline for large 3D line sets that employs GPU ray-casting to achieve scalable rendering including transparency and global illumination effects that cannot be achieved with GPU rasterization. Even for opaque lines we demonstrate superior rendering performance compared to GPU rasterization of lines, and when transparency is used we can interactively render large amounts of lines that are infeasible to be rendered via rasterization. To achieve this, we propose a direction-preserving encoding of lines into a regular voxel grid, along with the quantization of directions using face-to-face connectivity in this grid. On the regular grid structure, parallel GPU ray-casting is used to determine visible fragments in correct visibility order. To enable interactive rendering of global illumination effects like low-frequency shadows and ambient occlusions, illumination simulation is performed during ray-casting on a level-of-detail (LoD) line representation that considers the number of lines and their lengths per voxel. In this way we can render effects which are very difficult to render via GPU rasterization. A detailed performance and quality evaluation compares our approach to rasterization-based rendering of lines.},
 bibtype = {article},
 author = {Kanzler, Mathias and Rautenhaus, Marc and Westermann, Rudiger},
 doi = {10.1109/TVCG.2018.2834372},
 journal = {IEEE Transactions on Visualization and Computer Graphics},
 number = {7}
}

@inproceedings{
 title = {Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data},
 type = {inproceedings},
 year = {2019},
 pages = {1-6},
 websites = {https://ieeexplore.ieee.org/document/8817345/},
 month = {4},
 publisher = {IEEE},
 id = {4a0ae990-a42f-3d6c-bb0e-654d5daa9608},
 created = {2021-04-09T15:23:48.365Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:48.365Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Baghaie, Ahmadreza},
 doi = {10.1109/LISAT.2019.8817345},
 booktitle = {2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT)}
}

@article{
 title = {Visibility graph analysis of wall turbulence time-series},
 type = {article},
 year = {2018},
 keywords = {Complex networks,Direct numerical simulations,Time-series analysis,Turbulent channel flows,Visibility graph},
 pages = {1-11},
 volume = {382},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X},
 month = {4},
 publisher = {North-Holland},
 id = {117a628a-3309-3870-811a-5f4e5b726b7e},
 created = {2021-04-09T15:23:49.217Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:49.217Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.},
 bibtype = {article},
 author = {Iacobello, Giovanni and Scarsoglio, Stefania and Ridolfi, Luca},
 doi = {10.1016/j.physleta.2017.10.027},
 journal = {Physics Letters A},
 number = {1}
}

@article{
 title = {Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence},
 type = {article},
 year = {2015},
 pages = {85110},
 volume = {27},
 websites = {http://aip.scitation.org/doi/10.1063/1.4928699},
 month = {4},
 id = {62e0a3b8-f203-3460-bb83-528b9ee3de45},
 created = {2021-04-09T15:23:49.861Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:49.861Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Johnson, Perry L and Meneveau, Charles},
 doi = {10.1063/1.4928699},
 journal = {Physics of Fluids},
 number = {8}
}

@article{
 title = {Tracer particle dispersion around elementary flow patterns},
 type = {article},
 year = {2018},
 keywords = {topological fluid dynamics,turbulence theory,turbulent mixing},
 pages = {872-897},
 volume = {843},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {20461682-0462-316b-935f-97d5994ffecc},
 created = {2021-04-09T15:23:50.515Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:50.515Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The motion of tracer particles is kinematically simulated around three elementary flow patterns; a Burgers vortex, a shear-layer structure with coincident vortices and a node-saddle topology. These patterns are representative for their broader class of coherent structures in turbulence. Therefore, examining the dispersion in these elementary structures can improve the general understanding of turbulent dispersion at short time scales. The shear-layer structure and the node-saddle topology exhibit similar pair dispersion statistics compared to the actual turbulent flow for times up to 3-10[STIX]x1D70F_[STIX]x1D702 , where, [STIX]x1D70F_[STIX]x1D702 is the Kolmogorov time scale. However, oscillations are observed for the pair dispersion in the Burgers vortex. Furthermore, all three structures exhibit Batchelor’s scaling. Richardson’s scaling was observed for initial particle pair separations r_0 4[STIX]x1D702 for the shear-layer topology and the node-saddle topology and was related to the formation of the particle sheets. Moreover, the material line orientation statistics for the shear-layer and node-saddle topology are similar to the actual turbulent flow statistics, up to at least 4[STIX]x1D70F_[STIX]x1D702 . However, only the shear-layer structure can explain the non-perpendicular preferential alignment between the material lines and the direction of the most compressive strain, as observed in actual turbulence. This behaviour is due to shear-layer vorticity, which rotates the particle sheet generated by straining motions and causes the particles to spread in the direction of compressive strain also. The material line statistics in the Burgers vortex clearly differ, due to the presence of two compressive principal straining directions as opposed to two stretching directions in the shear-layer structure and the node-saddle topology. The tetrad dispersion statistics for the shear-layer structure qualitatively capture the behaviour of the shape parameters as observed in actual turbulence. In particular, it shows the initial development towards planar shapes followed by a return to more volumetric tetrads at approximately 10[STIX]x1D70F_[STIX]x1D702 , which is associated with the particles approaching the vortices inside the shear layer. However, a large deviation is observed in such behaviour in the node-saddle topology and the Burgers vortex. It is concluded that the results for the Burgers vortex deviated the most from actual turbulence and the node-saddle topology dispersion exhibits some similarities, but does not capture the geometrical features associated with material lines and tetrad dispersion. Finally, the dispersion around the shear-layer structure shows many quantitative (until 2– 4[STIX]x1D70F_[STIX]x1D702 ) and qualitative (until 20[STIX]x1D70F_[STIX]x1D702 ) similarities to the actual turbulence.},
 bibtype = {article},
 author = {Goudar, Manu V and Elsinga, Gerrit E},
 doi = {10.1017/jfm.2018.146},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes},
 type = {article},
 year = {2019},
 keywords = {CCS Concepts,Graphics systems and interfaces,• Computing methodologies → Computer graphics,• Human‐centered computing → Scientific visualizat},
 pages = {53-66},
 volume = {38},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671},
 month = {4},
 publisher = {John Wiley & Sons, Ltd (10.1111)},
 id = {4b5cd8db-6947-3ac8-b9dd-7f6ed694dab5},
 created = {2021-04-09T15:23:51.035Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:51.035Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Marton, Fabio and Agus, Marco and Gobbetti, Enrico},
 doi = {10.1111/cgf.13671},
 journal = {Computer Graphics Forum},
 number = {3}
}

@article{
 title = {A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks},
 type = {article},
 year = {2018},
 websites = {http://arxiv.org/abs/1804.09269},
 month = {4},
 id = {3506f98e-a070-3139-824c-288b57b0e8d1},
 created = {2021-04-09T15:23:51.617Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:51.617Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Reduced Order Modeling (ROM) for engineering applications has been a major research focus in the past few decades due to the unprecedented physical insight into turbulence offered by high-fidelity CFD. The primary goal of a ROM is to model the key physics/features of a flow-field without computing the full Navier-Stokes (NS) equations. This is accomplished by projecting the high-dimensional dynamics to a low-dimensional subspace, typically utilizing dimensionality reduction techniques like Proper Orthogonal Decomposition (POD), coupled with Galerkin projection. In this work, we demonstrate a deep learning based approach to build a ROM using the POD basis of canonical DNS datasets, for turbulent flow control applications. We find that a type of Recurrent Neural Network, the Long Short Term Memory (LSTM) which has been primarily utilized for problems like speech modeling and language translation, shows attractive potential in modeling temporal dynamics of turbulence. Additionally, we introduce the Hurst Exponent as a tool to study LSTM behavior for non-stationary data, and uncover useful characteristics that may aid ROM development for a variety of applications.},
 bibtype = {article},
 author = {Mohan, Arvind T and Gaitonde, Datta V}
}

@article{
 title = {Viscous tilting and production of vorticity in homogeneous turbulence},
 type = {article},
 year = {2010},
 keywords = {flow simulation,flow visualisation,turbulence,vortices},
 pages = {1-4},
 volume = {22},
 websites = {http://aip.scitation.org/doi/10.1063/1.3442477},
 month = {4},
 publisher = {American Institute of Physics},
 id = {13eeab2c-f93a-38bc-8939-c93fd2904977},
 created = {2021-04-09T15:23:52.216Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:52.216Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Viscous depletion of vorticity is an essential and well known property of turbulent flows, balancing, in the mean, the net vorticity production associated with the vortex stretching mechanism. In this letter we however demonstrate that viscous effects are not restricted to a mere destruction process, but play a more complex role in vorticity dynamics that is as important as vortex stretching. Based on results from particle tracking experiments (3D-PTV) and direct numerical simulation (DNS) of homogeneous and quasi isotropic turbulence, we show that the viscous term in the vorticity equation can also locally induce production of vorticity and changes of its orientation (viscous tilting).},
 bibtype = {article},
 author = {Holzner, M and Guala, M and Lüthi, B and Liberzon, A and Nikitin, N and Kinzelbach, W and Tsinober, A},
 doi = {10.1063/1.3442477},
 journal = {Physics of Fluids},
 number = {6}
}

@article{
 title = {A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields},
 type = {article},
 year = {2016},
 keywords = {isotropic turbulence,turbulence modelling,turbulent flows},
 pages = {387-419},
 volume = {804},
 websites = {http://www.journals.cambridge.org/abstract_S0022112016005516},
 month = {4},
 id = {058be0e8-0927-31b3-a73c-e061a85b4271},
 created = {2021-04-09T15:23:53.201Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:53.201Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The statistics of the velocity gradient tensor in turbulent flows are of both theoretical and practical importance. The Lagrangian view provides a privileged perspective for studying the dynamics of turbulence in general, and of the velocity gradient tensor in particular. Stochastic models for the Lagrangian evolution of velocity gradients in isotropic turbulence, with closure models for the pressure Hesssian and viscous Laplacian, have been shown to reproduce important features such as non-Gaussian probability distributions, skewness and vorticity strain-rate alignments. The Recent Fluid Deformation (RFD) closure introduced the idea of mapping an isotropic Lagrangian pressure Hessian as upstream initial condition using the fluid deformation tensor. Recent work on a Gaussian fields closure, however, has shown that even Gaussian isotropic velocity fields contain significant anisotropy for the conditional pressure Hessian tensor due to the inherent velocity-pressure couplings, and that assuming an isotropic pressure Hessian as upstream condition may not be realistic. In this paper, Gaussian isotropic field statistics are used to generate more physical upstream conditions for the recent fluid deformation mapping. In this new framework, known isotropy relations can be satisfied  a priori and no DNS-tuned coefficients are necessary. A detailed comparison of results from the new model, referred to as the recent deformation of Gaussian fields (RDGF) closure, with existing models and DNS shows the improvements gained, especially in various single-time statistics of the velocity gradient tensor at moderate Reynolds numbers. Application to arbitrarily high Reynolds numbers remains an open challenge for this type of model, however.},
 bibtype = {article},
 author = {Johnson, Perry L and Meneveau, Charles},
 doi = {10.1017/jfm.2016.551},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Weighted divergence correction scheme and its fast implementation},
 type = {article},
 year = {2017},
 pages = {44},
 volume = {58},
 websites = {http://link.springer.com/10.1007/s00348-017-2307-0},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {0192ceee-aab1-3e66-936d-56c4d9b81025},
 created = {2021-04-09T15:23:54.184Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:54.184Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.},
 bibtype = {article},
 author = {Wang, Cheng Yue and Gao, Qi and Wei, Run Jie and Li, Tian and Wang, Jin Jun},
 doi = {10.1007/s00348-017-2307-0},
 journal = {Experiments in Fluids},
 number = {5}
}

@article{
 title = {Estimating large-scale structures in wall turbulence using linear models},
 type = {article},
 year = {2018},
 keywords = {turbulence control,turbulence modelling,turbulent flows},
 pages = {146-162},
 volume = {842},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {3e4a0e2c-0224-3e99-bc54-88aeb5f4790c},
 created = {2021-04-09T15:23:54.716Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:54.716Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of Re_[STIX]x1D70F=1000 . The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon &amp; Sharma ( J. Fluid Mech. , vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.},
 bibtype = {article},
 author = {Illingworth, Simon J and Monty, Jason P and Marusic, Ivan},
 doi = {10.1017/jfm.2018.129},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {On velocity gradient dynamics and turbulent structure},
 type = {article},
 year = {2015},
 keywords = {homogeneous turbulence,turbulence modelling,turbulent flows},
 pages = {60-98},
 volume = {780},
 websites = {http://www.journals.cambridge.org/abstract_S0022112015004528},
 month = {4},
 id = {9b621a34-c3f3-3ac7-b9dd-a490b7dff598},
 created = {2021-04-09T15:23:55.819Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:55.819Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The statistics of the velocity gradient tensor [STIX]x1D63C=u , which embody the fine scales of turbulence, are influenced by turbulent ‘structure’. Whilst velocity gradient statistics and dynamics have been well characterised, the connection between structure and dynamics has largely focused on rotation-dominated flow and relied upon data from numerical simulation alone. Using numerical and spatially resolved experimental datasets of homogeneous turbulence, the role of structure is examined for all local (incompressible) flow topologies characterisable by [STIX]x1D63C . Structures are studied through the footprints they leave in conditional averages of the Q=-Tr([STIX]x1D63C^2)/2 field, pertinent to non-local strain production, obtained using two complementary conditional averaging techniques. The first, stochastic estimation, approximates the Q field conditioned upon [STIX]x1D63C and educes quantitatively similar structure in both datasets, dissimilar to that of random Gaussian velocity fields. Moreover, it strongly resembles a promising model for velocity gradient dynamics recently proposed by Wilczek &amp; Meneveau ( J. Fluid Mech. , vol. 756, 2014, pp. 191–225), but is derived under a less restrictive premise, with explicitly determined closure coefficients. The second technique examines true conditional averages of the Q field, which is used to validate the stochastic estimation and provide insights towards the model’s refinement. Jointly, these approaches confirm that vortex tubes are the predominant feature of rotation-dominated regions and additionally show that shear layer structures are active in strain-dominated regions. In both cases, kinematic features of these structures explain alignment statistics of the pressure Hessian eigenvectors and why local and non-local strain production act in opposition to each other.},
 bibtype = {article},
 author = {Lawson, J M and Dawson, J R},
 doi = {10.1017/jfm.2015.452},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence},
 type = {article},
 year = {2018},
 keywords = {doi:10.1103/PhysRevFluids.3.064301 url:https://doi},
 pages = {64301},
 volume = {3},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301},
 month = {4},
 publisher = {American Physical Society},
 id = {6ee00bf4-b546-3cfe-8cb4-4d8cec83ae01},
 created = {2021-04-09T15:23:57.403Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:57.403Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Fouxon, Itzhak and Schmidt, Lukas and Ditlevsen, Peter and van Reeuwijk, Maarten and Holzner, Markus},
 doi = {10.1103/PhysRevFluids.3.064301},
 journal = {Physical Review Fluids},
 number = {6}
}

@article{
 title = {Main results of the 4th International PIV Challenge},
 type = {article},
 year = {2016},
 pages = {97},
 volume = {57},
 websites = {http://link.springer.com/10.1007/s00348-016-2173-1},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {df1350f7-41d2-3e6d-902b-cadcc3b62429},
 created = {2021-04-09T15:23:57.952Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:57.952Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In the last decade, worldwide PIV development have resulted in significant improvements in terms accuracy, resolution, dynamic range and extension to dimensions. To assess the achievements and to guide development efforts, an International PIV Challenge performed in Lisbon (Portugal) on July 5, 2014. leading participants, including the major system, i.e., Dantec (Denmark), LaVision (Germany), (China), PIVTEC (Germany), TSI (USA), have 5 cases. The cases and analysis explore challenges to 2D microscopic PIV (case A), 2D timeresolved (case B), 3D tomographic PIV (cases C and) and stereoscopic PIV (case E). During the event, 2D PIV images (case F) were provided to all 80 of the workshop in Lisbon, with the aim to assess impact of the user’s experience on the evaluation result. paper describes the cases and specific algorithms evaluation parameters applied by the participants and reviews the main results. For future analysis and comparison, full image database},
 bibtype = {article},
 author = {Kähler, Christian J and Astarita, Tommaso and Vlachos, Pavlos P and Sakakibara, Jun and Hain, Rainer and Discetti, Stefano and Foy, Roderick La and Cierpka, Christian},
 doi = {10.1007/s00348-016-2173-1},
 journal = {Experiments in Fluids},
 number = {6}
}

@article{
 title = {Uncertainty quantification in LES of channel flow},
 type = {article},
 year = {2017},
 keywords = {Bayesian framework,Rosenblatt transformation,calibration,large eddy simulation,model error,polynomial chaos},
 pages = {376-401},
 volume = {83},
 websites = {http://doi.wiley.com/10.1002/fld.4272},
 month = {4},
 id = {0e749df6-9a68-34cb-a517-ccc9d4a029c0},
 created = {2021-04-09T15:23:58.644Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:58.644Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Dis- crepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.},
 bibtype = {article},
 author = {Safta, Cosmin and Blaylock, Myra and Templeton, Jeremy and Domino, Stefan and Sargsyan, Khachik and Najm, Habib},
 doi = {10.1002/fld.4272},
 journal = {International Journal for Numerical Methods in Fluids},
 number = {4}
}

@article{
 title = {From Deep to Physics-Informed Learning of Turbulence: Diagnostics},
 type = {article},
 year = {2018},
 websites = {http://arxiv.org/abs/1810.07785},
 month = {4},
 id = {c2ce5c72-f100-31b5-9cac-81b8dc4415c7},
 created = {2021-04-09T15:23:59.239Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:59.239Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of turbulence. Even the bare DL solutions, which do not take into account any physics of turbulence explicitly, are impressively good overall when it comes to qualitative description of important features of turbulence. However, the early tests have also uncovered some caveats of the DL approaches. We observe that the static DL scheme, implementing Convolutional GAN and trained on spatial snapshots of turbulence, fails to reproduce intermittency of turbulent fluctuations at small scales and details of the turbulence geometry at large scales. We show that the dynamic NN schemes, namely LAT-NET and Compressed Convolutional LSTM, trained on a temporal sequence of turbulence snapshots are capable to correct for the caveats of the static NN. We suggest a path forward towards improving reproducibility of the large-scale geometry of turbulence with NN.},
 bibtype = {article},
 author = {King, Ryan and Hennigh, Oliver and Mohan, Arvind and Chertkov, Michael}
}

@inproceedings{
 title = {Active Pointillistic Pattern Search},
 type = {inproceedings},
 year = {2015},
 pages = {672-680},
 websites = {http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf},
 month = {4},
 id = {87abb4bb-fb22-349d-bf7c-053866f19df0},
 created = {2021-04-09T15:23:59.817Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:23:59.817Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {We introduce the problem of active pointillistic pattern search (APPS), which seeks to discover regions of a domain exhibiting desired behavior with limited observations. Unusually, the patterns we consider are defined by large-scale proper-ties of an underlying function that we can only observe at a limited number of points. Given a description of the desired patterns (in the form of a classifier taking functional inputs), we se-quentially decide where to query function values to identify as many regions matching the pattern as possible, with high confience. For one broad class of models the expected reward of each un-observed point can be computed analytically. We demonstrate the proposed algorithm on three dif-ficult search problems: locating polluted regions in a lake via mobile sensors, forecasting winning electoral districts with minimal polling, and iden-tifying vortices in a fluid flow simulation.},
 bibtype = {inproceedings},
 author = {Ma, Yifei and Sutherland, Dougal J and Garnett, Roman and Schneider, Jeff},
 booktitle = {AISTATS}
}

@article{
 title = {Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence},
 type = {article},
 year = {2019},
 pages = {53202},
 volume = {99},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.99.053202},
 month = {4},
 publisher = {American Physical Society},
 id = {f3da8baa-5c3d-344e-87ea-28d5bbeac4a0},
 created = {2021-04-09T15:24:00.465Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:00.465Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Kuzzay, Denis and Alexandrova, Olga and Matteini, Lorenzo},
 doi = {10.1103/PhysRevE.99.053202},
 journal = {Physical Review E},
 number = {5}
}

@article{
 title = {Dual channels of helicity cascade in turbulent flows},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1907.03634},
 month = {4},
 id = {f1f0d347-1a37-3f18-bb4c-677bb59ee33c},
 created = {2021-04-09T15:24:01.743Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:01.743Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.},
 bibtype = {article},
 author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Chen, Shiyi}
}

@article{
 title = {Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence},
 type = {article},
 year = {2019},
 pages = {64602},
 volume = {4},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602},
 month = {4},
 publisher = {American Physical Society},
 id = {021f32d8-a291-3056-a16b-dc980553a5b4},
 created = {2021-04-09T15:24:02.532Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:02.532Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Sosa-Correa, W and Pereira, R M and Macêdo, A M S and Raposo, E P and Salazar, D S P and Vasconcelos, G L},
 doi = {10.1103/PhysRevFluids.4.064602},
 journal = {Physical Review Fluids},
 number = {6}
}

@article{
 title = {Velocity and pressure visualization of three-dimensional flow in porous textiles},
 type = {article},
 year = {2019},
 keywords = {and systems engineering,flow visualization,magnetic resonance velocimetry,management of systems,materials,measurement,pressure visualization,product,product design,structure-properties},
 pages = {5041-5052},
 volume = {89},
 websites = {http://journals.sagepub.com/doi/10.1177/0040517519846078},
 month = {4},
 publisher = {SAGE PublicationsSage UK: London, England},
 id = {6aaefaff-4247-3be7-b4e8-2ed4fff906f5},
 created = {2021-04-09T15:24:03.314Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:03.314Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Advances in flow visualization techniques based on optics, such as lasers and digital cameras, have contributed considerably to the development of various flow models. However, the uses of optical techniques for flow visualization in porous media are limited owing to the complexity or opaqueness of the medium. This study demonstrates the utilization of magnetic resonance velocimetry to visualize a flow field in a textile material. By using phase-contrast magnetic resonance imaging, a three-dimensional, three-component velocity vector field was obtained for induced flow through a cut-pile carpet owing to the suction of a vacuum cleaner nozzle. As a result, we were able to experimentally identify the flow-dominant region in the carpet. Specifically, velocity vector plots and flow streamlines facilitated the identification of the flow paths, and indicated that the flow was strongest beneath the narrow walls of the vacuum nozzle. In addition, the pressure field in the carpet was estimated by an omni-directional integral method based on the utilization of the visualized velocity field, which showed where the pressure loss was maximized.},
 bibtype = {article},
 author = {Lee, Jeesoo and Yang, Byungkuen and Cho, Jee-Hyun and Song, Simon},
 doi = {10.1177/0040517519846078},
 journal = {Textile Research Journal},
 number = {23-24}
}

@article{
 title = {A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence},
 type = {article},
 year = {2011},
 pages = {N45},
 volume = {12},
 websites = {http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047},
 month = {4},
 id = {d9d6d4ff-bbf2-3017-9a97-263565beec5a},
 created = {2021-04-09T15:24:03.970Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:03.970Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The specification of inlet conditions for eddy-resolving simulations is an important research question in turbulence research. A large number of schemes have been proposed but comparisons to a benchmark simulation are usually undertaken in such a way that it is ambiguous as to whether the source of the improved preservation of the properties of the benchmark case is due to the physics captured in the inlet generation algorithm or to differences in the precise values or spectra generated at a particular position. This article uses gradual wavelet reconstruction to degrade a precursor simulation such that the time series input at each cell has the same histogram and Fourier spectrum as the original precursor case, thereby removing this source of variability. A parameter, ρ, is used to index the nature of the degraded inlets and as ρ increases from 0 to 1 the cross-correlative and nonlinear properties of the precursor are increasingly preserved too. We compare the results of four large-eddy simulations for the flow over a wall-mounted square rib and show that there are clear differences between these simulations for the flow before and over the rib, and in the far-field. However, in the wake, the intense shearing and mixing means that any differences are harder to attribute to the nature of the inlet. Hence, for flows that are mixed strongly, there is less of a need to preserve the cross-correlative structure of the inlet condition as long as the individual velocity components are modelled with an appropriate set of values and Fourier spectrum. By comparing particular inlet generation algorithms in terms of the value for ρ that they can attain, their suitability for modelling flows of particular configurations may be determined.},
 bibtype = {article},
 author = {Keylock, C J and Tokyay, T E and Constantinescu, G},
 doi = {10.1080/14685248.2011.636047},
 journal = {Journal of Turbulence}
}

@article{
 title = {Multilevel techniques for compression and reduction of scientific data—the univariate case},
 type = {article},
 year = {2018},
 pages = {65-76},
 volume = {19},
 websites = {http://link.springer.com/10.1007/s00791-018-00303-9},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {b18efc62-6fe3-3e73-b604-803dc1772fcf},
 created = {2021-04-09T15:24:04.997Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:04.997Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},
 doi = {10.1007/s00791-018-00303-9},
 journal = {Computing and Visualization in Science},
 number = {5-6}
}

@article{
 title = {Invariants of the reduced velocity gradient tensor in turbulent flows},
 type = {article},
 year = {2013},
 keywords = {isotropic turbulence,turbulence theory,turbulent flows},
 pages = {597-615},
 volume = {716},
 websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5},
 month = {4},
 id = {c1df0993-9b68-35fd-9b00-e89c04ec2e25},
 created = {2021-04-09T15:24:05.475Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:05.475Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In this paper we examine the invariants p and q of the reduced 2 × 2 velocity gradient tensor (VGT) formed from a two-dimensional (2D) slice of an incompressible three-dimensional (3D) flow. Using data from both 2D particle image velocimetry (PIV) measurements and 3D direct numerical simulations of various turbulent flows, we show that the joint probability density functions (p.d.f.s) of p and q exhibit a common characteristic asymmetric shape consistent with < 0. An explanation for this inequality is proposed. Assuming local homogeneity we derive = 0 and = 0. With the addition of local isotropy the sign of is proved to be the same as that of the skewness of ∂u 1 /∂x 1 , hence negative. This suggests that the observed asymmetry in the joint p.d.f.s of p–q stems from the universal predominance of vortex stretching at the smallest scales. Some advantages of this joint p.d.f. compared with that of Q–R obtained from the full 3 × 3 VGT are discussed. Analysing the eigenvalues of the reduced strain-rate matrix associated with the reduced VGT, we prove that in some cases the 2D data can unambiguously discriminate between the bi-axial (sheet-forming) and axial (tube-forming) strain-rate configurations of the full 3 × 3 strain-rate tensor. 1. Introduction With the arrival of data sets providing access to the full three-dimensional velocity gradient tensor (3D VGT), new ways of analysing this wealth of information have been introduced. The 3D VGT can be written as A ij = ∂u i /∂x j = S ij + W ij , where S ij is the symmetric rate-of-strain tensor and W ij is the antisymmetric rate-of-rotation tensor. One approach is to examine the eigenvalues of S ij . They indicate if the strain-rate tensor is compressing or extending along its principal axes, which in turn determines whether or not the overall strain-rate configuration at a point is sheet forming or tube forming. Another approach is to analyse the local flow topology using the invariants of A ij , as set out by the work of Chong, Perry & Cantwell (1990). In an incompressible flow the number of non-vanishing similarity invariants of the second-order tensor A ij reduces to two, namely Q and R. These two quantities can fully characterize the category to which the local flow topology belongs. The local flow topology refers to the streamline pattern of a region of the flow in the immediate vicinity of the point},
 bibtype = {article},
 author = {Cardesa, J A I and Mistry, D and Gan, L and Dawson, J A R},
 doi = {10.1017/jfm.2012.558},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Spatiotemporal velocity-velocity correlation function in fully developed turbulence},
 type = {article},
 year = {2017},
 pages = {23107},
 volume = {95},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.95.023107},
 month = {4},
 id = {154cc137-ce6e-3f00-84dd-862eaefbfbb8},
 created = {2021-04-09T15:24:06.109Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:06.109Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Turbulence is an ubiquitous phenomenon in natural and industrial flows. Since the celebrated work of Kolmogorov in 1941, understanding the statistical properties of fully developed turbulence has remained a major quest. In particular, deriving the properties of turbulent flows from a mesoscopic description, that is from Navier-Stokes equation, has eluded most theoretical attempts. Here, we provide a theoretical prediction for the  space and time dependent velocity-velocity correlation function of homogeneous and isotropic turbulence from the field theory associated to Navier-Stokes equation with stochastic forcing. This prediction is the analytical fixed-point solution of Non-Perturbative Renormalisation Group flow equations, which are exact in a certain large wave-number limit. This solution is compared to two-point two-times correlation functions computed in direct numerical simulations. We obtain a remarkable agreement both in the inertial and in the dissipative ranges.},
 bibtype = {article},
 author = {Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás and Balarac, Guillaume},
 doi = {10.1103/PhysRevE.95.023107},
 journal = {Physical Review E},
 number = {2}
}

@article{
 title = {Extracting the spectrum of a flow by spatial filtering},
 type = {article},
 year = {2018},
 pages = {124610},
 volume = {3},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610},
 month = {4},
 publisher = {American Physical Society},
 id = {6af5bb72-a429-33a8-9102-fa8f60b255d8},
 created = {2021-04-09T15:24:06.594Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:06.594Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Sadek, Mahmoud and Aluie, Hussein},
 doi = {10.1103/PhysRevFluids.3.124610},
 journal = {Physical Review Fluids},
 number = {12}
}

@article{
 title = {Dense motion estimation of particle images via a convolutional neural network},
 type = {article},
 year = {2019},
 pages = {73},
 volume = {60},
 websites = {http://link.springer.com/10.1007/s00348-019-2717-2},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {e0ac0c33-5c62-3be2-976c-160d3a74533a},
 created = {2021-04-09T15:24:07.101Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:07.101Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Cai, Shengze and Zhou, Shichao and Xu, Chao and Gao, Qi},
 doi = {10.1007/s00348-019-2717-2},
 journal = {Experiments in Fluids},
 number = {4}
}

@article{
 title = {Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind},
 type = {article},
 year = {2015},
 pages = {25001},
 volume = {115},
 websites = {https://link.aps.org/doi/10.1103/PhysRevLett.115.025001},
 month = {4},
 id = {4a6557a7-2f59-3fed-9845-28f0b8412a15},
 created = {2021-04-09T15:24:07.560Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:07.560Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In situ spacecraft data on the solar wind show events identified as magnetic reconnection with wide outflows and extended “X lines,” 103–104 times ion scales. To understand the role of turbulence at these scales, we make a case study of an inertial-range reconnection event in a magnetohydrodynamic simulation. We observe stochastic wandering of field lines in space, breakdown of standard magnetic flux freezing due to Richardson dispersion, and a broadened reconnection zone containing many current sheets. The coarse-grain magnetic geometry is like large-scale reconnection in the solar wind, however, with a hyperbolic flux tube or apparent X line extending over integral length scales.},
 bibtype = {article},
 author = {Lalescu, Cristian C and Shi, Yi Kang and Eyink, Gregory L and Drivas, Theodore D and Vishniac, Ethan T and Lazarian, Alexander},
 doi = {10.1103/PhysRevLett.115.025001},
 journal = {Physical Review Letters},
 number = {2}
}

@article{
 title = {Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments},
 type = {article},
 year = {2011},
 pages = {34106},
 volume = {23},
 websites = {http://aip.scitation.org/doi/10.1063/1.3555635},
 month = {4},
 id = {4c17b164-a584-3e14-b6d0-bb2be167808d},
 created = {2021-04-09T15:24:08.268Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:08.268Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper-flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer-Meshkov instabilities in planar shock-tube laboratory experiments is reported. Our particular focus is devoted to the initial material interface characterization and modeling difficulties, and effects of initial condition specifics (resolved spectral content) on transitional and late-time turbulent mixing-which were not previously addressed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3555635]},
 bibtype = {article},
 author = {Grinstein, F F and Gowardhan, A A and Wachtor, A J},
 doi = {10.1063/1.3555635},
 journal = {Physics of Fluids},
 number = {3}
}

@article{
 title = {Pulsed, high-power LED illumination for tomographic particle image velocimetry},
 type = {article},
 year = {2012},
 pages = {1545-1560},
 volume = {53},
 websites = {http://link.springer.com/10.1007/s00348-012-1374-5},
 month = {4},
 publisher = {Springer-Verlag},
 id = {20ac55ec-3931-33b8-bee4-44ff227b4ec7},
 created = {2021-04-09T15:24:08.857Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:08.857Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 mu s duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of approximate to 3-4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2-0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.},
 bibtype = {article},
 author = {Buchmann, Nicolas A and Willert, Christian E and Soria, Julio},
 doi = {10.1007/s00348-012-1374-5},
 journal = {Experiments in Fluids},
 number = {5}
}

@article{
 title = {Assessment of the modulated gradient model in decaying isotropic turbulence},
 type = {article},
 year = {2011},
 keywords = {isotropic turbulence,large-eddy simulation,subgrid-scale model},
 pages = {41004},
 volume = {1},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611},
 id = {946ab0e5-f9b6-3355-95e1-780cbcb83d88},
 created = {2021-04-09T15:24:09.345Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:09.345Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Lu, Hao},
 doi = {10.1063/2.1104104},
 journal = {Theoretical and Applied Mechanics Letters},
 number = {4}
}

@article{
 title = {Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence},
 type = {article},
 year = {2015},
 pages = {125102},
 volume = {27},
 websites = {http://aip.scitation.org/doi/10.1063/1.4936140},
 month = {4},
 id = {f140aa79-c55c-3afc-8d4e-6b5afcb58f77},
 created = {2021-04-09T15:24:09.828Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:09.828Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© 2015 AIP Publishing LLC. We show by direct numerical simulation (DNS) that the Lagrangian cross correlation of velocity gradients in homogeneous isotropic turbulence increases at short times, whereas its auto-correlation decreases. Kinematic considerations allow to show that two invariants of the turbulent velocity field determine the short-time velocity gradient correlations. In order to get a more intuitive understanding of the dynamics for longer times, heuristic models are proposed involving the combined action of local shear and rotation. These models quantitatively reproduce the effects and disentangle the different physical mechanisms leading to the observations in the DNS.},
 bibtype = {article},
 author = {Fang, L and Bos, W J T and Jin, G D},
 doi = {10.1063/1.4936140},
 journal = {Physics of Fluids},
 number = {12}
}

@article{
 title = {Shape-dependence of particle rotation in isotropic turbulence},
 type = {article},
 year = {2015},
 pages = {35101},
 volume = {27},
 websites = {http://aip.scitation.org/doi/10.1063/1.4913501},
 month = {4},
 id = {fcd7cc5c-da75-3d52-a57a-f3d9ead99673},
 created = {2021-04-09T15:24:10.552Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:10.552Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We consider the rotation of neutrally buoyant axisymmetric particles suspended in isotropic turbulence. Using laboratory experiments as well as numerical and analytical calculations, we explore how particle rotation depends upon particle shape. We find that shape strongly affects orientational trajectories, but that it has negligible effect on the variance of the particle angular velocity. Previous work has shown that shape significantly affects the variance of the tumbling rate of axisymmetric particles. It follows that shape affects the spinning rate in a way that is, on average, complementary to the shape-dependence of the tumbling rate. We confirm this relationship using direct numerical simulations, showing how tumbling rate and spinning rate variances show complementary trends for rod-shaped and disk-shaped particles. We also consider a random but non-turbulent flow. This allows us to explore which of the features observed for rotation in turbulent flow are due to the effects of particle alignment in vortex tubes.},
 bibtype = {article},
 author = {Byron, M and Einarsson, J and Gustavsson, K and Voth, G and Mehlig, B and Variano, E},
 doi = {10.1063/1.4913501},
 journal = {Physics of Fluids},
 number = {3}
}

@article{
 title = {Dot-Tracking Methodology for Background Oriented Schlieren (BOS)},
 type = {article},
 year = {2018},
 websites = {http://arxiv.org/abs/1812.10870},
 month = {4},
 id = {55e1a8fa-d58c-383c-91dc-41eb42ac2471},
 created = {2021-04-09T15:24:11.040Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:11.040Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a "correlation correction", whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in th exit plane of a converging-diverging nozzle.},
 bibtype = {article},
 author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P}
}

@article{
 title = {On the inherent bias of swirling strength in defining vortical structure},
 type = {article},
 year = {2019},
 pages = {35107},
 volume = {31},
 websites = {http://aip.scitation.org/doi/10.1063/1.5089883},
 month = {4},
 publisher = {AIP Publishing LLC},
 id = {1bcc598a-709e-3005-a0d9-7596e55ee9b5},
 created = {2021-04-09T15:24:12.031Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:12.031Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The traditional practice of using rotational motion as the principal attribute of coherent vortical structures in the buffer region of near-wall turbulent flow is shown to create a biased accountin...},
 bibtype = {article},
 author = {Bernard, Peter S},
 doi = {10.1063/1.5089883},
 journal = {Physics of Fluids},
 number = {3}
}

@inproceedings{
 title = {Interactive visual exploration of line clusters},
 type = {inproceedings},
 year = {2018},
 pages = {155-163},
 websites = {https://dl.acm.org/citation.cfm?id=3307680},
 publisher = {Eurographics Association},
 id = {3af76be2-f576-3cff-afa8-adcecb7e50bb},
 created = {2021-04-09T15:24:13.073Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:13.073Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Kanzler, Mathias and Westermann, Rüdiger},
 editor = {Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip},
 doi = {10.2312/VMV.20181265},
 booktitle = {EG VMV '18 Proceedings of the Conference on Vision, Modeling, and Visualization}
}

@article{
 title = {Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence},
 type = {article},
 year = {2010},
 keywords = {Direct numerical simulation,Isotropic turbulence,Lagrangian statistics,Refined Kolomogorov similarity hypothesis,Turbulence database},
 pages = {457-472},
 volume = {85},
 websites = {http://link.springer.com/10.1007/s10494-010-9256-5},
 month = {4},
 publisher = {Springer Netherlands},
 id = {4f1f9075-6def-3580-8365-e90f69ed1485},
 created = {2021-04-09T15:24:13.990Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:13.990Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We study Lagrangian statistics of the magnitudes of velocity and pressure gradients in isotropic turbulence by quantifying their correlation functions and their characteristic time scales. In a recent work (Yu and Meneveau, Phys Rev Lett 104:084502, 2010), it has been found that the Lagrangian time-correlations of the velocity and pressure gradient tensor and vector elements scale with the locally- definedKolmogorov time scale, evaluated from the locally-averaged dissipation-rate (?r) and viscosity (ν) according to τK,r = √ν/?r. In thiswork, we study theLagrangian time-correlations of the absolute values of velocity and pressure gradients. It has long been known that such correlations display longer memories into the inertial- range as well as possible intermittency effects. We explore the appropriate temporal scales with the aim to achieve collapse of the correlation functions. The data used in this study are sampled from the web-services accessible public turbulence database (http://turbulence.pha.jhu.edu). The database archives a 10244 (space+time) pseudo- spectral direct numerical simulation of forced isotropic turbulence with Taylor- scale Reynolds number Reλ = 433, and supports spatial differentiation and spa- tial/temporal interpolation inside the database. The analysis shows that the temporal auto-correlations of the absolute values extend deep into the inertial range where they are determined not by the local Kolmogorov time-scale but by the local eddy-turnover time scale defined as τe,r = r2/3?−1/3 r .However, considerable scatter remains and appears to be reduced only after a further (intermittency) correction factor of the form of (r/L)χ is introduced, where L is the turbulence integral scale. The exponent χ varies for different variables. The collapse of the correlation functions for absolute values is, however, less satisfactory than the collapse observed for the more rapidly decaying strain-rate tensor element correlation functions in the viscous range.},
 bibtype = {article},
 author = {Yu, Huidan and Meneveau, Charles},
 doi = {10.1007/s10494-010-9256-5},
 journal = {Flow, Turbulence and Combustion},
 number = {3-4}
}

@article{
 title = {Turbulence visualization at the terascale on desktop PCs},
 type = {article},
 year = {2012},
 keywords = {Visualization system and toolkit design,data compression,data streaming,vector fields,volume rendering},
 pages = {2169-2177},
 volume = {18},
 websites = {http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124},
 month = {4},
 id = {40c4dabb-3c4d-39df-998a-492543c75ed1},
 created = {2021-04-09T15:24:14.491Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:14.491Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small-and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. © 1995-2012 IEEE.},
 bibtype = {article},
 author = {Treib, Marc and Burger, Kai and Reichl, Florian and Meneveau, Charles and Szalay, Alex and Westermann, Rudiger},
 doi = {10.1109/TVCG.2012.274},
 journal = {IEEE Transactions on Visualization and Computer Graphics},
 number = {12}
}

@article{
 title = {Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems},
 type = {article},
 year = {2019},
 keywords = {Algorithms,Computer software,Graphics processing units,Particulate matter},
 volume = {141},
 websites = {https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource},
 month = {4},
 publisher = {American Society of Mechanical Engineers Digital Collection},
 id = {cc217224-e312-3428-96b2-ee61491e548c},
 created = {2021-04-09T15:24:14.978Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:14.978Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Particle image velocimetry (PIV) data processing time can constrain data set size and limit the types of statistical analyses performed. General purpose graphics processing unit (GPGPU) computing can accelerate PIV data processing allowing for larger datasets and accompanying higher order statistical analyses. However, this has not been widespread likely due to limited accessibility to the GPU-PIV hardware and software. Most GPU-PIV software is platform dependent and proprietary, which restricts the computing systems that can be used and makes the details of the algorithm unknown. This work highlights the development of an open-source, cross-platform, GPU-accelerated, PIV algorithm. Validation of the algorithm is done using both synthetic and experimental images. The algorithm was found to accurately resolve the time-averaged flow, instantaneous velocity fluctuations, and vortices. All data processing was done on a GPU supercomputing cluster and notably outperformed the central processing unit version of the software by a factor of 175. The algorithm is freely available and included in the OpenPIV distribution.},
 bibtype = {article},
 author = {Dallas, Cameron and Wu, Maria and Chou, Vincent and Liberzon, Alex and Sullivan, Pierre E},
 doi = {10.1115/1.4043422},
 journal = {Journal of Fluids Engineering},
 number = {11}
}

@article{
 title = {Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence},
 type = {article},
 year = {2018},
 keywords = {Isotropic turbulence,chaos and fractals,direct numerical simulation},
 pages = {297-321},
 volume = {19},
 websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995},
 month = {4},
 publisher = {Taylor & Francis},
 id = {32a620b0-6e74-3b93-806b-efbd3195b9c1},
 created = {2021-04-09T15:24:15.454Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:15.454Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Motivated by interest in the geometry of high intensity events of turbulent flows, we examine spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analyzed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation, and velocity gradient invariants Q and R and their joint spatial distibutions, using data from a direct numerical simulation of isotropic turbulence at  Re_λ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus a geometric characterization in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behavior. Nevertheless the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on the multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow. We show that sets defined by joint conditions on strain and enstrophy, and on Q and R, also display power law scaling of correlation functions, providing further characterization of the complex spatial structure of these intersection sets.},
 bibtype = {article},
 author = {Elsas, José Hugo and Szalay, Alexander S and Meneveau, Charles},
 doi = {10.1080/14685248.2018.1424995},
 journal = {Journal of Turbulence},
 number = {4}
}

@article{
 title = {Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence},
 type = {article},
 year = {2019},
 websites = {https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X},
 month = {4},
 publisher = {Elsevier},
 id = {b6773a3d-bb0f-3392-b88a-44c5aaaa5583},
 created = {2021-04-09T15:24:15.979Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:15.979Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The subgrid-scale effects on particle motion were investigated in forced isotropic turbulence by DNS and prior-LES methods. In the DNS field, the importance of Kolmogorov scaling to preferential accumulation was validated by comparing the radial distribution functions under various particle Stokes numbers. The prior-LES fields were generated by filtering the DNS data. The subgrid-scale Stokes number (StSGS) is a useful tool for determining the effects of subgrid-scale eddies on particle motion. The subgrid-scale eddies tend to accumulate particles with StSGS < 1 and disperse particles with 1 < StSGS < 10. For particles with StSGS ≫ 1, the effects of subgrid-scale eddies on particle motion can be neglected. In order to restore the subgrid-scale effects, the Langevin-type stochastic model with optimized parameters was adopted in this study. This model is effective for the particles with StSGS > 1 while has an adverse impact on the particles with StSGS < 1. The results show that the Langevin-type stochastic model tends to smooth the particle distribution in the isotropic turbulence.},
 bibtype = {article},
 author = {Shen, Haoshu and Wu, Yuxin and Zhou, Minmin and Zhang, Hai and Yue, Guangxi},
 doi = {10.1016/j.cjche.2019.05.007},
 journal = {Chinese Journal of Chemical Engineering}
}

@article{
 title = {PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design},
 type = {article},
 year = {2019},
 pages = {85302},
 volume = {30},
 websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8},
 month = {4},
 publisher = {IOP Publishing},
 id = {694f4e21-cf49-34b6-a913-a707e0253073},
 created = {2021-04-09T15:24:16.417Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:16.417Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P},
 doi = {10.1088/1361-6501/ab1ca8},
 journal = {Measurement Science and Technology},
 number = {8}
}

@misc{
 title = {Accurate and Efficient Autonomic Closure for Turbulent Flows},
 type = {misc},
 year = {2019},
 websites = {https://search.proquest.com/docview/2226592272?pq-origsite=gscholar},
 institution = {ARIZONA STATE UNIVERSITY},
 id = {30a18ab6-0157-38f8-9532-b74068f5a841},
 created = {2021-04-09T15:24:17.608Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:17.608Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {thesis},
 private_publication = {false},
 bibtype = {misc},
 author = {Kshitij, Abhinav}
}

@article{
 title = {Singular value decomposition of noisy data: noise filtering},
 type = {article},
 year = {2019},
 pages = {126},
 volume = {60},
 websites = {http://link.springer.com/10.1007/s00348-019-2768-4},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {4b1ae409-ef40-393c-94fd-d0ed9c3d2f1d},
 created = {2021-04-09T15:24:18.163Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:18.163Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Epps, Brenden P and Krivitzky, Eric M},
 doi = {10.1007/s00348-019-2768-4},
 journal = {Experiments in Fluids},
 number = {8}
}

@article{
 title = {Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters},
 type = {article},
 year = {2016},
 pages = {1-21},
 volume = {57},
 websites = {http://link.springer.com/10.1007/s00348-015-2110-8},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {f3a9a6ab-3a9a-3167-8cfb-b879798e7980},
 created = {2021-04-09T15:24:18.620Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:18.620Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© 2016, The Author(s). The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096–1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.},
 bibtype = {article},
 author = {Masullo, Alessandro and Theunissen, Raf},
 doi = {10.1007/s00348-015-2110-8},
 journal = {Experiments in Fluids},
 number = {3}
}

@misc{
 title = {Scale and rotation invariant detection of singular patterns in vector flow fields},
 type = {misc},
 year = {2010},
 source = {Structural, Syntactic, and Statistical Pattern Recognition},
 pages = {522-531},
 volume = {6218},
 websites = {http://link.springer.com/10.1007/978-3-642-14980-1_51},
 publisher = {Springer, Berlin, Heidelberg},
 id = {87624f2f-71c5-35a8-8049-4b22ce15c2a2},
 created = {2021-04-09T15:24:19.096Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:19.096Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {book_section},
 private_publication = {false},
 abstract = {We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based inner-product. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.},
 bibtype = {misc},
 author = {Liu, Wei and Ribeiro, Eraldo},
 doi = {10.1007/978-3-642-14980-1_51}
}

@article{
 title = {Regularized inverse holographic volume reconstruction for 3D particle tracking},
 type = {article},
 year = {2019},
 keywords = {Compressive holography,High speed photography,Image metrics,Image processing,Image quality,Phase retrieval},
 pages = {18069},
 volume = {27},
 websites = {https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069},
 month = {4},
 publisher = {Optical Society of America},
 id = {77ebf8f3-d916-351b-8ed0-2df7438d554d},
 created = {2021-04-09T15:24:19.672Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:19.672Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.},
 bibtype = {article},
 author = {Mallery, Kevin and Hong, Jiarong},
 doi = {10.1364/OE.27.018069},
 journal = {Optics Express},
 number = {13}
}

@article{
 title = {A Declarative Grammar of Flexible Volume Visualization Pipelines},
 type = {article},
 year = {2019},
 pages = {1050-1059},
 volume = {25},
 websites = {https://ieeexplore.ieee.org/document/8440063/},
 month = {4},
 id = {d2fa3e23-d58f-3188-801f-b9802e93fb62},
 created = {2021-04-09T15:24:20.241Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:20.241Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Shih, Min and Rozhon, Charles and Ma, Kwan-Liu},
 doi = {10.1109/TVCG.2018.2864841},
 journal = {IEEE Transactions on Visualization and Computer Graphics},
 number = {1}
}

@article{
 title = {Structure of the velocity gradient tensor in turbulent shear flows},
 type = {article},
 year = {2017},
 pages = {74602},
 volume = {2},
 websites = {http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602},
 month = {4},
 publisher = {American Physical Society},
 id = {03d44fe9-4542-3cf6-90b0-3277cd950651},
 created = {2021-04-09T15:24:20.716Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:20.716Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The expected universality of small-scale properties of turbulent flows implies isotropic properties of the velocity gradient tensor in the very large Reynolds number limit. Using direct numerical simulations, we determine the tensors formed by n = 2 and 3 velocity gradients at a single point in turbulent homogeneous shear flows, and in the log-layer of a turbulent channel flow, and we characterize the departure of these tensors from the corresponding isotropic prediction. Specifically, we separate the even components of the tensors, invariant under reflexion with respect to all axes, from the odd ones, which identically vanish in the absence of shear. Our results indicate that the largest deviation from isotropy comes from the odd component of the third velocity gradient correlation function, especially from the third moment of the derivative along the normal direction of the streamwise velocity component. At the Reynolds numbers considered (R_lambda ~ 140), we observe that these second and third order correlation functions are significantly larger in turbulent channel flows than in homogeneous shear flow. Overall, our work demonstrates that a mean shear leads to relatively simple structure of the velocity gradient tensor. How isotropy is restored in the very large Reynolds limit remains to be understood.},
 bibtype = {article},
 author = {Pumir, Alain},
 doi = {10.1103/PhysRevFluids.2.074602},
 journal = {Physical Review Fluids},
 number = {7}
}

@article{
 title = {Small-scale anisotropy in turbulent boundary layers},
 type = {article},
 year = {2016},
 keywords = {turbulence theory,turbulent boundary layers,turbulent flows},
 pages = {5-23},
 volume = {804},
 websites = {http://www.journals.cambridge.org/abstract_S0022112016005292},
 month = {4},
 id = {d2a55492-2a18-3e31-81e7-c7585aa3805c},
 created = {2021-04-09T15:24:21.280Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:21.280Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ( Re_[STIX]x1D70F 1000 ), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is R_[STIX]x1D706 150 . This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of R_[STIX]x1D706 . In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.},
 bibtype = {article},
 author = {Pumir, Alain and Xu, Haitao and Siggia, Eric D},
 doi = {10.1017/jfm.2016.529},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {On the Reynolds number dependence of velocity-gradient structure and dynamics},
 type = {article},
 year = {2019},
 keywords = {intermittency,isotropic turbulence,turbulent flows},
 pages = {163-179},
 volume = {861},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {ae410480-9dcc-3981-b2c4-c727efa02cc1},
 created = {2021-04-09T15:24:21.799Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:21.799Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We seek to examine the changes in velocity-gradient structure (local streamline topology) and related dynamics as a function of Reynolds number ( Re_[STIX]x1D706 ). The analysis factorizes the velocity gradient ( [STIX]x1D608_ij ) into the magnitude ( A^2 ) and normalized-gradient tensor ( [STIX]x1D623_ij [STIX]x1D608_ij/A^2 ). The focus is on bounded [STIX]x1D623_ij as (i) it describes small-scale structure and local streamline topology, and (ii) its dynamics is shown to determine magnitude evolution. Using direct numerical simulation (DNS) data, the moments and probability distributions of [STIX]x1D623_ij and its scalar invariants are shown to attain Re_[STIX]x1D706 independence. The critical values beyond which each feature attains Re_[STIX]x1D706 independence are established. We proceed to characterize the Re_[STIX]x1D706 dependence of [STIX]x1D623_ij -conditioned statistics of key non-local pressure and viscous processes. Overall, the analysis provides further insight into velocity-gradient dynamics and offers an alternative framework for investigating intermittency, multifractal behaviour and for developing closure models.},
 bibtype = {article},
 author = {Das, Rishita and Girimaji, Sharath S},
 doi = {10.1017/jfm.2018.924},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1905.02657},
 month = {4},
 id = {280c93e9-f450-3915-b1f9-260517c43d49},
 created = {2021-04-09T15:24:22.355Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:22.355Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Homogeneous and isotropic turbulent fields obtained from two DNS databases (with Re_λ equal to 150 and 418) were seeded with point particles that moved with the local fluid velocity to obtain Lagrangian pressure histories. Motivated by cavitation inception modeling, the statistics of events in which such particles undergo low-pressure fluctuations were computed, parameterized by the amplitude of the fluctuations and by their duration. The main results are the average frequencies of these events and the probabilistic distribution of their duration, which are of predictive value. A connection is also established between these average frequencies and the pressure probability density function, thus justifying experimental methods proposed in the literature. Further analyses of the data show that the occurrence of very-low-pressure events is highly intermittent and is associated with worm-like vortical structures of length comparable to the integral scale of the flow.},
 bibtype = {article},
 author = {Bappy, Mehedi and Carrica, Pablo M and Buscaglia, Gustavo C}
}

@inproceedings{
 title = {Identifying the Wall Signature of Large-Scale Motions with Extended POD},
 type = {inproceedings},
 year = {2019},
 pages = {75-80},
 websites = {http://link.springer.com/10.1007/978-3-030-22196-6_12},
 month = {4},
 publisher = {Springer, Cham},
 id = {d61dbfb7-bdc7-3a6d-be6f-dd3b8a1f6f86},
 created = {2021-04-09T15:24:22.820Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:22.820Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Güemes, A and Vaquero, A and Flores, O and Discetti, S and Ianiro, A},
 editor = {Örlü, R and Talamelli, A and Peinke, J and Oberlack, M},
 doi = {10.1007/978-3-030-22196-6_12},
 booktitle = {8th iTi Conference on Turbulence}
}

@article{
 title = {Robust Principal Component Analysis for Particle Image Velocimetry},
 type = {article},
 year = {2019},
 websites = {http://arxiv.org/abs/1905.07062},
 month = {4},
 id = {b2b8c1c5-c3df-3831-acee-24a087c7762f},
 created = {2021-04-09T15:24:23.533Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:23.533Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Particle image velocimetry (PIV) is an experimental technique used to measure fluid flow fields. However, PIV fields often have spurious and missing velocity vectors that degrade subsequent analyses. Standard post-processing involves the identification and replacement of outliers based on local information. We present a method to identify and fill in erroneous or missing PIV vectors using global information via robust principal component analysis (RPCA), a statistical technique developed for outlier rejection. RPCA decomposes a data matrix into a low-rank matrix containing coherent structures and a sparse matrix of outliers. We explore RPCA on a range of fluid simulations and experiments of varying complexity. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificially added outliers, alongside similar PIV measurements at Reynolds number 413. Next, we apply RPCA to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are maintained and the turbulent kinetic energy spectrum remains largely intact. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA extracts dominant fluid coherent structures and identifies and fills in corruption and outliers, with minimal degradation of small scale structures.},
 bibtype = {article},
 author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L}
}

@article{
 title = {Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field},
 type = {article},
 year = {2013},
 keywords = {Flow structure interactions,Shear layer turbulence,Vortex dynamics},
 pages = {417-457},
 volume = {728},
 websites = {http://www.journals.cambridge.org/abstract_S0022112013002759},
 month = {4},
 publisher = {Cambridge University Press},
 id = {f07ba240-7dc8-3d45-90d2-e2f8bd3cee75},
 created = {2021-04-09T15:24:24.005Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:24.005Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The flow structure and turbulence in an open cavity shear layer has been investigated experimentally at a Reynolds number of 4.0 × 104, with an emphasis on interactions of the unsteady pressure field with the cavity corners. A large database of time-resolved two-dimensional PIV measurements has been used to obtain the velocity distributions and calculate the pressure by spatially integrating the material acceleration at a series of sample areas covering the entire shear layer and the flow surrounding the corners. Conditional sampling, low-pass filtering and time correlations among variables enable us to elucidate several processes, which have distinctly different frequency ranges, that dominate the shear layer interactions with the corners. Kelvin-Helmholtz shear layer eddies have the expected Strouhal number range of 0.5-3.2. Their interactions with the trailing corner introduce two sources of vorticity fluctuations above the corner. The first is caused by the expected advection of remnants of the shear layer eddies. The second source involves fluctuations in local viscous vorticity flux away from the wall caused by periodic variations in the streamwise pressure gradients. This local production peaks when the shear layer vortices are located away from the corner, creating a lingering region with peak vorticity just above the corner. The associated periodic pressure minima there are lower than any other point in the entire flow field, making the region above the corner most prone to cavitation inception. Flapping of the shear layer and boundary layer upstream of the leading corner occurs at very low Strouhal numbers of ~0.05, affecting all the flow and turbulence quantities around both corners. Time-dependent correlations of the shear layer elevation show that the flapping starts in the boundary layer upstream of the leading corner and propagates downstream at the free stream speed. Near the trailing corner, when the shear layer elevation is low, the stagnation pressure in front of the wall, the downward jetting flow along this wall, the fraction of shear layer vorticity entrained back into the cavity, and the magnitude of the pressure minimum above the corner are higher than those measured when the shear layer is high. However, the variations in downward jetting decay rapidly with increasing distance from the trailing corner, indicating that it does not play a direct role in a feedback mechanism that sustains the flapping. There is also low correlation between the boundary/shear layer elevation and the returning flow along the upstream vertical wall, providing little evidence that this returning flow affects the flapping directly. However, the characteristic period of flapping, ~0.6 s, is consistent with recirculation time of the fluid within the cavity away from boundaries. The high negative correlations of shear/boundary layer elevation with the streamwise pressure gradient above the leading corner introduce a plausible mechanism that sustains the flapping: when the shear layer is low, the boundary layer is subjected to high adverse streamwise pressure gradients that force it to widen, and when the shear layer is high, the pressure gradients decrease, allowing the boundary layer to thin down. Flow mechanisms that would cause the flapping-induced pressure changes, and their relations to the flow within the cavity are discussed. © 2013 Cambridge University Press.},
 bibtype = {article},
 author = {Liu, Xiaofeng and Katz, Joseph},
 doi = {10.1017/jfm.2013.275},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence},
 type = {article},
 year = {2017},
 pages = {84607},
 volume = {2},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607},
 month = {4},
 id = {07452386-7dbf-3811-a8de-be917350f3f1},
 created = {2021-04-09T15:24:24.548Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:24.548Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Keylock, Christopher J},
 doi = {10.1103/PhysRevFluids.2.084607},
 journal = {Physical Review Fluids},
 number = {8}
}

@article{
 title = {Inhomogeneous preferential concentration of inertial particles in turbulent channel flow},
 type = {article},
 year = {2017},
 websites = {http://arxiv.org/abs/1702.01438},
 month = {4},
 id = {969b0689-e176-3ccf-97c1-524f2b1d503b},
 created = {2021-04-09T15:24:25.148Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:25.148Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Turbophoresis leading to preferential concentration of inertial particles in regions of low turbulent diffusivity is a unique feature of inhomogeneous turbulent flows, such as free shear flows or wall-bounded flows. In this work, the theory for clustering of weakly inertial particles in homogeneous turbulence is extended to the inhomogeneous case of a turbulent channel flow. The inhomogeneity contributes to the cluster formation in addition to clustering in homogeneous turbulence. A space-dependent rate for the creation of inhomogeneous particle concentration is derived in terms of local statistics of turbulence. We provide the formula for the pair-correlation function of concentration that factorizes in product of time and space-dependent average concentrations and time-independent factor of clustering that obeys a power-law in the distance between the points. This power-law characterizes inhomogeneous multifractality of the particle distribution. A unique demonstration and quantification of the combined effects of turbophoresis and fractal clustering in a direct numerical simulation of particle motion in a turbulent channel flow is performed according to the presented theory. The strongest contribution to clustering coming from the inhomogeneity of the flow occurs in the transitional region between viscous sublayer and the buffer layer. Further the ratio of homogeneous and inhomogeneous term depends on the wall distance. The inhomogeneous terms may significantly increase the preferential concentration of inertial particles, thus the overall degree of clustering in inhomogeneous turbulence is potentially stronger compared to particles with the same inertia in purely homogeneous turbulence.},
 bibtype = {article},
 author = {Schmidt, Lukas and Fouxon, Itzhak and Ditlevsen, Peter and Holzner, Markus}
}

@article{
 title = {Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence},
 type = {article},
 year = {2018},
 keywords = {turbulence modelling,turbulence simulation,turbulent flows},
 pages = {80-114},
 volume = {837},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {7ec7ca23-80fc-34ff-a1d2-9fbfa4fdf7c8},
 created = {2021-04-09T15:24:25.619Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:25.619Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The detailed dynamics of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modelling challenge, because many micro-physical processes such as deformation of aggregates, drops, bubbles and polymers dynamics depend strongly on the velocity gradient tensor, which is dominated by the turbulence structure in the viscous range. In this paper, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with coarse-grained fluid simulations to recover small-scale physics without resorting to direct numerical simulations (DNS). The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modelling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out and results are again compared to DNS results. Results illustrate the ability of the proposed model to predict the influence of small-scale turbulence on droplet micro-physics in the context of LES.},
 bibtype = {article},
 author = {Johnson, Perry L and Meneveau, Charles},
 doi = {10.1017/jfm.2017.838},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model},
 type = {article},
 year = {2018},
 keywords = {Channel,Mixing Length,Pipe,Turbulent Flow},
 pages = {677-692},
 volume = {06},
 websites = {http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061},
 month = {4},
 publisher = {Scientific Research Publishing},
 id = {15314fa1-afcd-3437-82f0-3af0189ff9a2},
 created = {2021-04-09T15:24:26.097Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:26.097Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This research used the common decomposition of the velocity and pressure in an average part and a fluctuating part, for high Reynolds number, of the Navier-Stokes equation, which leads to the classic problem of turbulent closure. The Prandtl’s mixing length model, based on the Boussinesq hypothesis and traditionally used for free shear flows, was chosen and adapted for internal flows to solve the closure problem. For channel flows, Johann Nikuradse proposed a model for the Prandtl mixing length. In the present paper, which has an academic character, the authors made a return to the model of the mixing length of Prandtl and the model of Nikuradse, to solve turbulent flows inside a plane channel. It was possible to develop an ordinary differential model for the velocity in the direction of the flow whose solution occurs computationally in a simple but extremely accurate way when compared with Direct Numerical Simulation databases. For the viscous stress on the wall, it was possible to determine the exact mathematical solution of the ordinary differential equation. It is a model of great academic value and even to be used as reference for verification of computational codes destined to the solution of complete numerical and computational models.},
 bibtype = {article},
 author = {Antonialli, Luigi A and Silveira-Neto, Aristeu and Mecânica, Faculdade De Engenharia and Uberlândia, Universidade Federal De and Gerais, Minas},
 doi = {10.4236/jamp.2018.64061},
 journal = {Journal of Applied Mathematics and Physics},
 number = {04}
}

@misc{
 title = {A new two-scale model for large eddy simulation of wall-bounded flows},
 type = {misc},
 year = {2010},
 source = {Progress in Aerospace Sciences},
 keywords = {Large eddy simulation,Near-wall modeling,Two-scale model,Wall-bounded flows},
 pages = {28-45},
 volume = {46},
 issue = {1},
 websites = {https://www.sciencedirect.com/science/article/pii/S0376042109000335},
 month = {4},
 publisher = {Pergamon},
 id = {4ccb1c94-15b2-3ba4-bb44-eb3f823029b8},
 created = {2021-04-09T15:24:26.762Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:26.762Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {generic},
 private_publication = {false},
 abstract = {A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS-LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS-LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS-LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS-LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number. © 2009 Elsevier Ltd. All rights reserved.},
 bibtype = {misc},
 author = {Gungor, Ayse Gul and Menon, Suresh},
 doi = {10.1016/j.paerosci.2009.10.001}
}

@article{
 title = {Fluid particle dynamics and the non-local origin of the Reynolds shear stress},
 type = {article},
 year = {2018},
 keywords = {turbulence modelling,turbulence theory,turbulent flows},
 pages = {520-551},
 volume = {847},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {42c6b162-4fe6-3fc0-897e-a0b8228970c7},
 created = {2021-04-09T15:24:27.317Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:27.317Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The causative factors leading to the Reynolds shear stress distribution in turbulent channel flow are analysed via a backward particle path analysis. It is found that the classical displacement transport mechanism, by which changes in the mean velocity field over a mixing time correlate with the wall-normal velocity, is the dominant source of Reynolds shear stress. Approximately 20 % of channel flow at any given time contains fluid motions that contribute to displacement transport. Much rarer events provide a small but non-negligible contribution to the Reynolds shear stress due to fluid particle accelerations and long-lived correlations deriving from structural features of the near-wall flow. The Reynolds shear stress in channel flow is shown to be a non-local phenomenon that is not conducive to description via a local model and particularly one depending directly on the local mean velocity gradient.},
 bibtype = {article},
 author = {Bernard, Peter S and Erinin, Martin A},
 doi = {10.1017/jfm.2018.333},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {POD-based background removal for particle image velocimetry},
 type = {article},
 year = {2017},
 keywords = {PIV image pre-processing,POD decomposition of video sequences,Reduced Order Modeling (ROM)},
 pages = {181-192},
 volume = {80},
 websites = {https://www.sciencedirect.com/science/article/pii/S0894177716302266},
 month = {4},
 publisher = {Elsevier},
 id = {ae00564d-5c14-3b61-bdab-99f9cbbc9812},
 created = {2021-04-09T15:24:27.798Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:27.798Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.},
 bibtype = {article},
 author = {Mendez, M A and Raiola, M and Masullo, A and Discetti, S and Ianiro, A and Theunissen, R and Buchlin, J M},
 doi = {10.1016/j.expthermflusci.2016.08.021},
 journal = {Experimental Thermal and Fluid Science}
}

@article{
 title = {Long-range μPIV to resolve the small scales in a jet at high Reynolds number},
 type = {article},
 year = {2014},
 keywords = {High Reynolds number,Long-range μPIV,Small scales},
 pages = {1-15},
 volume = {55},
 websites = {http://link.springer.com/10.1007/s00348-014-1812-7},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {7ec67954-6936-3b40-80b4-1bcddac0c0ad},
 created = {2021-04-09T15:24:28.325Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:28.325Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a self- similar round jet at high Reynolds numbers (Rek ? 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and kci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vor- ticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissi- pation tend to organize in the form of sheets with a char- acteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of long- range lPIV for characterizing turbulent flow structures at high Reynolds number. D.},
 bibtype = {article},
 author = {Fiscaletti, D and Westerweel, J and Elsinga, G E},
 doi = {10.1007/s00348-014-1812-7},
 journal = {Experiments in Fluids},
 number = {9}
}

@article{
 title = {Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities},
 type = {article},
 year = {2019},
 keywords = {68P30,94A24,big data,data compression,data reduction},
 pages = {A2146-A2171},
 volume = {41},
 websites = {https://epubs.siam.org/doi/10.1137/18M1208885},
 month = {4},
 publisher = {Society for Industrial and Applied Mathematics},
 id = {c4627576-776b-3e42-afb9-47c6f4432697},
 created = {2021-04-09T15:24:28.816Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:28.816Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may ...},
 bibtype = {article},
 author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},
 doi = {10.1137/18M1208885},
 journal = {SIAM Journal on Scientific Computing},
 number = {4}
}

@inproceedings{
 title = {High Spatial Resolution 3D Fluid Velocimetry by Tomographic Particle Flow Velocimetry},
 type = {inproceedings},
 year = {2019},
 websites = {https://arc.aiaa.org/doi/10.2514/6.2019-0269},
 month = {4},
 publisher = {American Institute of Aeronautics and Astronautics},
 id = {7092cfa0-40fc-3f5a-9dc4-623b16b65db8},
 created = {2021-04-09T15:24:29.312Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:29.312Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Kumashiro, Keishi and Steinberg, Adam M and Yano, Masayuki},
 doi = {10.2514/6.2019-0269},
 booktitle = {AIAA Scitech 2019 Forum}
}

@article{
 title = {Hypothesis Testing For Nonlinear Phenomena In The Geosciences Using Synthetic, Surrogate Data},
 type = {article},
 year = {2018},
 keywords = {Fourier transform,chaos,gradual reconstruction,nonlinearity,surrogate data,wavelets},
 pages = {2018EA000435},
 volume = {6},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435},
 month = {4},
 publisher = {John Wiley & Sons, Ltd},
 id = {e44a6f1f-eb36-366b-aae3-126fdaaf70f8},
 created = {2021-04-09T15:24:29.792Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:29.792Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Keylock, C J},
 doi = {10.1029/2018EA000435},
 journal = {Earth and Space Science},
 number = {1}
}

@article{
 title = {Expanding the Q-R space to three dimensions},
 type = {article},
 year = {2009},
 keywords = {Dynamics,Isotropic,Theory},
 pages = {497-507},
 volume = {641},
 websites = {http://www.journals.cambridge.org/abstract_S0022112009991947},
 month = {4},
 publisher = {Cambridge University Press},
 id = {55fd8e33-1071-34c1-9965-1831405aefe6},
 created = {2021-04-09T15:24:30.382Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:30.382Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The two-dimensional space spanned by the velocity gradient invariants Q and R is expanded to three dimensions by the decomposition of R into its strain production −1/3sijsjkski and enstrophy production 1/4ωiωjsij terms. The Q; R space is a planar projection of the new three-dimensional representation. In the Q; −sss; ωωs space the Lagrangian evolution of the velocity gradient tensor Aij is studied via conditional mean trajectories (CMTs) as introduced by Martín et al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence of Reλ ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to the Q–R plane. The relatively weak cyclic evolution in the Q–R space is thus only a projection of a much stronger cycle in the Q; −sss; ωωs space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian of Aij, on the other hand, seems the main responsible for intermittently alternating between low and high intensity Aij states.},
 bibtype = {article},
 author = {Lthi, Beat and Holzner, Markus and Tsinober, Arkady},
 doi = {10.1017/S0022112009991947},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Asymptotic results for backwards two-particle dispersion in a turbulent flow},
 type = {article},
 year = {2014},
 pages = {41003},
 volume = {89},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.89.041003},
 month = {4},
 id = {c0be1397-382a-3ab4-a087-8d8134ed9ee6},
 created = {2021-04-09T15:24:30.893Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:30.893Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We derive an exact equation governing two-particle backwards mean-squared dispersion for both deterministic and stochastic tracer particles in turbulent flows. For the deterministic trajectories, we probe the consequences of our formula for short times and arrive at approximate expressions for the mean-squared dispersion which involve second order structure functions of the velocity and acceleration fields. For the stochastic trajectories, we analytically compute an exact t^3 contribution to the squared separation of stochastic paths. We argue that this contribution appears also for deterministic paths at long times and present direct numerical simulation results for incompressible Navier-Stokes flows to support this claim. We also numerically compute the probability distribution of particle separations for the deterministic paths and the stochastic paths and show their strong self-similar nature.},
 bibtype = {article},
 author = {Benveniste, Damien and Drivas, Theodore D},
 doi = {10.1103/PhysRevE.89.041003},
 journal = {Physical Review E},
 number = {4}
}

@article{
 title = {Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database},
 type = {article},
 year = {2015},
 pages = {1-11},
 websites = {http://arc.aiaa.org/doi/10.2514/6.2016-3403},
 month = {4},
 publisher = {American Institute of Aeronautics and Astronautics},
 id = {719dacb2-6fd9-3d09-a4d7-a80d14f4bac6},
 created = {2021-04-09T15:24:31.394Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:31.394Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Liu, Xiaofeng and Siddle-mitchel, Seth and Rybarczyk, Rachel and Katz, Joseph},
 doi = {10.2514/6.2016-3403},
 journal = {32nd AIAA Aerodynamic Measurement Technology and Ground Testing Conference}
}

@misc{
 title = {High-End Volume Visualization},
 type = {misc},
 year = {2018},
 pages = {135},
 websites = {https://search.proquest.com/docview/2133012476},
 institution = {University of California, Davis},
 id = {e72c3b4c-0dd6-3e15-87f9-c049e8ff0df1},
 created = {2021-04-09T15:24:31.948Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:31.948Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {thesis},
 private_publication = {false},
 bibtype = {misc},
 author = {Shih, Min}
}

@article{
 title = {Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3},
 type = {article},
 year = {2019},
 pages = {132138},
 websites = {https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573},
 month = {4},
 publisher = {North-Holland},
 id = {b9e7ee8b-2fc2-36aa-9dba-abcc4c501d46},
 created = {2021-04-09T15:24:32.670Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:32.670Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We are concerned with the inviscid limit of the Navier–Stokes equations to the Euler equations for compressible fluids in R3. Motivated by the Kolmogorov hypothesis (1941) for incompressible flow, we introduce a Kolmogorov-type hypothesis for barotropic flows, in which the density and the sonic speed normally vary significantly. We then observe that the compressible Kolmogorov-type hypothesis implies the uniform boundedness of some fractional derivatives of the weighted velocity and sonic speed in the space variables in L2, which is independent of the viscosity coefficient μ>0. It is shown that this key observation yields the equicontinuity in both space and time of the density in Lγ and the momentum in L2, as well as the uniform bound of the density in Lq1 and the velocity in Lq2 for some fixed q1>γ and q2>2, independent of μ>0, where γ>1 is the adiabatic exponent. These results lead to the strong convergence of solutions of the Navier–Stokes equations to a solution of the Euler equations for barotropic fluids in R3. Not only do we offer a framework for mathematical existence theories, but also we offer a framework for the interpretation of numerical solutions through the identification of a function space in which convergence should take place, with the bounds that are independent of μ>0, that is in the high Reynolds number limit.},
 bibtype = {article},
 author = {Chen, Gui-Qiang G and Glimm, James},
 doi = {10.1016/j.physd.2019.06.004},
 journal = {Physica D: Nonlinear Phenomena}
}

@article{
 title = {Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling},
 type = {article},
 year = {2018},
 pages = {33301},
 volume = {10},
 websites = {http://aip.scitation.org/doi/10.1063/1.5004710},
 month = {4},
 publisher = {AIP Publishing LLC},
 id = {6cce001b-5f00-397b-b895-e112dad1bbb1},
 created = {2021-04-09T15:24:33.156Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:33.156Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Large-eddy simulation (LES) of a wind turbine under uniform inflow is performed using an actuator line model (ALM). Predictions from four LES research codes from the wind energy community are compa...},
 bibtype = {article},
 author = {Martínez-Tossas, Luis A and Churchfield, Matthew J and Yilmaz, Ali Emre and Sarlak, Hamid and Johnson, Perry L and Sørensen, Jens N and Meyers, Johan and Meneveau, Charles},
 doi = {10.1063/1.5004710},
 journal = {Journal of Renewable and Sustainable Energy},
 number = {3}
}

@article{
 title = {Accurate estimate of turbulent dissipation rate using PIV data},
 type = {article},
 year = {2013},
 keywords = {Energy spectra,PIV,Structure function,Turbulent dissipation rate},
 pages = {662-672},
 volume = {44},
 websites = {https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464},
 month = {4},
 publisher = {Elsevier},
 id = {eb9c0ce8-55c3-3c88-a7b6-067038618599},
 created = {2021-04-09T15:24:33.718Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:33.718Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the -5/3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes. © 2012 Elsevier Inc.},
 bibtype = {article},
 author = {Xu, Duo and Chen, Jun},
 doi = {10.1016/j.expthermflusci.2012.09.006},
 journal = {Experimental Thermal and Fluid Science}
}

@article{
 title = {Angular dynamics of a small particle in turbulence},
 type = {article},
 year = {2016},
 pages = {204501},
 volume = {117},
 websites = {https://link.aps.org/doi/10.1103/PhysRevLett.117.204501},
 month = {4},
 id = {9868f702-ead3-3e01-8357-e5578df0b81f},
 created = {2021-04-09T15:24:34.259Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:34.259Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We compute the angular dynamics of a neutrally buoyant nearly spherical particle immersed in an unsteady fluid. We assume that the particle is small, that its translational slip velocity is negligible, and that unsteady and convective inertia are small perturbations. We derive an approximation for the torque on the particle that determines the first inertial corrections to Jeffery's equation. These corrections arise as a consequence of local vortex stretching, and can be substantial in turbulence where local vortex stretching is strong and closely linked to the irreversibility of turbulence.},
 bibtype = {article},
 author = {Candelier, F and Einarsson, J and Mehlig, B},
 doi = {10.1103/PhysRevLett.117.204501},
 journal = {Physical Review Letters},
 number = {20}
}

@article{
 title = {Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry},
 type = {article},
 year = {2017},
 pages = {118},
 volume = {58},
 websites = {http://link.springer.com/10.1007/s00348-017-2395-x},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {fb414d52-e7c1-3c6d-96c0-a6059b9dcc40},
 created = {2021-04-09T15:24:34.718Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:34.718Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© 2017, The Author(s). The experimental evaluation of the topological characteristics of the turbulent flow in a ‘box’ of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.},
 bibtype = {article},
 author = {Lian, Huan and Soulopoulos, Nikolaos and Hardalupas, Yannis},
 doi = {10.1007/s00348-017-2395-x},
 journal = {Experiments in Fluids},
 number = {9}
}

@article{
 title = {Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations},
 type = {article},
 year = {2018},
 keywords = {Adaptive mesh refinement,Atmospheric boundary layer,Direct numerical simulations,Large-eddy simulations,Turbulence},
 pages = {421-443},
 volume = {167},
 websites = {http://link.springer.com/10.1007/s10546-018-0335-9},
 month = {4},
 publisher = {Springer Netherlands},
 id = {4bc7706d-0fde-3429-a0b5-d729ea5cdb3f},
 created = {2021-04-09T15:24:35.225Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:35.225Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {© 2018 The Author(s) We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.},
 bibtype = {article},
 author = {van Hooft, J Antoon and Popinet, Stéphane and van Heerwaarden, Chiel C and van der Linden, Steven J A A and de Roode, Stephan R and van de Wiel, Bas J H H},
 doi = {10.1007/s10546-018-0335-9},
 journal = {Boundary-Layer Meteorology},
 number = {3}
}

@article{
 title = {Redistribution of kinetic energy in turbulent flows},
 type = {article},
 year = {2014},
 keywords = {Fluid dynamics,Nonlinear dynamics,Statistical physics},
 pages = {41006},
 volume = {4},
 websites = {https://link.aps.org/doi/10.1103/PhysRevX.4.041006},
 month = {4},
 id = {078fb0f4-b620-36e6-ab06-b4a0bbf5dce8},
 created = {2021-04-09T15:24:35.860Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:35.860Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In statistically homogeneous turbulent flows, pressure forces provide the main mechanism to redistribute kinetic energy among fluid elements, without net contribution to the overall energy budget. This holds true in both two-dimensional (2D) and three-dimensional (3D) flows, which show fundamentally different physics. As we demonstrate here, pressure forces act on fluid elements very differently in these two cases. We find in numerical simulations that in 3D pressure forces strongly accelerate the fastest fluid elements, and that in 2D this effect is absent. In 3D turbulence, our findings put forward a mechanism for a possibly singular buildup of energy, and thus may shed new light on the smoothness problem of the solution of the Navier-Stokes equation in 3D.},
 bibtype = {article},
 author = {Pumir, Alain and Xu, Haitao and Boffetta, Guido and Falkovich, Gregory and Bodenschatz, Eberhard},
 doi = {10.1103/PhysRevX.4.041006},
 journal = {Physical Review X},
 number = {4}
}

@article{
 title = {A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows},
 type = {article},
 year = {2019},
 pages = {137},
 volume = {60},
 websites = {http://link.springer.com/10.1007/s00348-019-2777-3},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {1c8096ee-c7d7-33c2-a56c-6a2f7ef84968},
 created = {2021-04-09T15:24:36.419Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:36.419Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Kozul, Melissa and Koothur, Vipin and Worth, Nicholas A and Dawson, James R},
 doi = {10.1007/s00348-019-2777-3},
 journal = {Experiments in Fluids},
 number = {8}
}

@article{
 title = {Pressure from 2D snapshot PIV},
 type = {article},
 year = {2019},
 pages = {32},
 volume = {60},
 websites = {http://link.springer.com/10.1007/s00348-019-2678-5},
 month = {4},
 publisher = {Springer Berlin Heidelberg},
 id = {ba00cf84-a72d-3998-a269-642fe5c25cf6},
 created = {2021-04-09T15:24:36.935Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:36.935Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {der Kindere, J W Van and Laskari, A and Ganapathisubramani, B and de Kat, R},
 doi = {10.1007/s00348-019-2678-5},
 journal = {Experiments in Fluids},
 number = {2}
}

@article{
 title = {Vorticity statistics and the time scales of turbulent strain},
 type = {article},
 year = {2013},
 pages = {13005},
 volume = {88},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.88.013005},
 month = {4},
 publisher = {American Physical Society},
 id = {9326f9aa-e723-3f33-8803-969549fd326b},
 created = {2021-04-09T15:24:37.611Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:37.611Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of Lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual “1/s” strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.},
 bibtype = {article},
 author = {Moriconi, L and Pereira, R M},
 doi = {10.1103/PhysRevE.88.013005},
 journal = {Physical Review E},
 number = {1}
}

@article{
 title = {Spurious noise in direct noise computation with a finite volume method for automotive applications},
 type = {article},
 year = {2018},
 pages = {243-256},
 volume = {72},
 websites = {https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923},
 month = {4},
 publisher = {Elsevier},
 id = {e3f14195-dd58-3ff8-9dcc-5636fa237eeb},
 created = {2021-04-09T15:24:38.065Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:38.065Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The present paper represents a study on spurious noise generated in direct noise computation using finite volume methods. Different sources of spurious noise are examined as well as the mechanism of their generation. This investigation involves two test cases. The first one consists of a turbulence box convected by a uniform flow field. This case serves to identify spurious noise sources and qualitatively evaluate their relevance. The second test case involves a single side mirror mounted on a flat plate, which serves to quantify the level of spurious noise produced and its relevance compared to physical sound generated by the flow past the mirror. Both test cases are calculated using a compressible flow solver for low Mach-number flows utilised with an IDDES approach for turbulence modelling. A new acoustic damping model which damps out acoustic waves without affecting hydrodynamic turbulent fluctuations has been implemented. Furthermore, special emphasis on refinement interfaces is given. Since no measurements are available, the results of the direct noise computation are compared to the results of a method based on Kirchhoff integral.},
 bibtype = {article},
 author = {Dawi, Ali H and Akkermans, Rinie A D},
 doi = {10.1016/j.ijheatfluidflow.2018.06.008},
 journal = {International Journal of Heat and Fluid Flow}
}

@article{
 title = {Detecting singular patterns in 2D vector fields using weighted Laurent polynomial},
 type = {article},
 year = {2012},
 keywords = {Complex-valued function,Laurent polynomials,Scale- and rotation-invariance,Singular-pattern detection,Vector fields},
 pages = {3912-3925},
 volume = {45},
 websites = {https://www.sciencedirect.com/science/article/pii/S0031320312002051},
 month = {4},
 publisher = {Pergamon},
 id = {cbfa91e7-6cad-35ed-9166-39b6d4808341},
 created = {2021-04-09T15:24:38.546Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:38.546Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. © 2012 Elsevier Ltd. All rights reserved.},
 bibtype = {article},
 author = {Liu, Wei and Ribeiro, Eraldo},
 doi = {10.1016/j.patcog.2012.04.025},
 journal = {Pattern Recognition},
 number = {11}
}

@article{
 title = {Matrix exponential-based closures for the turbulent subgrid-scale stress tensor},
 type = {article},
 year = {2009},
 pages = {16305},
 volume = {79},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.79.016305},
 month = {4},
 publisher = {American Physical Society},
 id = {10a7b192-a61d-398c-87e8-0b2c2e32adc1},
 created = {2021-04-09T15:24:39.135Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:39.135Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Two approaches for closing the turbulence subgrid-scale stress tensor in terms of matrix exponentials are introduced and compared. The first approach is based on a formal solution of the stress transport equation in which the production terms can be integrated exactly in terms of matrix exponentials. This formal solution of the subgrid-scale stress transport equation is shown to be useful to explore special cases, such as the response to constant velocity gradient, but neglecting pressure-strain correlations and diffusion effects. The second approach is based on an Eulerian-Lagrangian change of variables, combined with the assumption of isotropy for the conditionally averaged Lagrangian velocity gradient tensor and with the recent fluid deformation approximation. It is shown that both approaches lead to the same basic closure in which the stress tensor is expressed as the matrix exponential of the resolved velocity gradient tensor multiplied by its transpose. Short-time expansions of the matrix exponentials are shown to provide an eddy-viscosity term and particular quadratic terms, and thus allow a reinterpretation of traditional eddy-viscosity and nonlinear stress closures. The basic feasibility of the matrix-exponential closure is illustrated by implementing it successfully in large eddy simulation of forced isotropic turbulence. The matrix-exponential closure employs the drastic approximation of entirely omitting the pressure-strain correlation and other nonlinear scrambling terms. But unlike eddy-viscosity closures, the matrix exponential approach provides a simple and local closure that can be derived directly from the stress transport equation with the production term, and using physically motivated assumptions about Lagrangian decorrelation and upstream isotropy.},
 bibtype = {article},
 author = {Li, Yi and Chevillard, Laurent and Eyink, Gregory and Meneveau, Charles},
 doi = {10.1103/PhysRevE.79.016305},
 journal = {Physical Review E},
 number = {1}
}

@article{
 title = {A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence},
 type = {article},
 year = {2016},
 keywords = {High-order methods,Large-Eddy simulation,Spectral Difference method},
 pages = {261-280},
 volume = {139},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512},
 month = {4},
 id = {eb50f798-2dbb-3002-b3d1-ac088b613ddd},
 created = {2021-04-09T15:24:39.658Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:39.658Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper aims at understanding the numerical dissipation mechanisms related to the Spectral Difference (SD) method in the context of three-dimensional (3D) turbulence. The numerical dissipation stemming from the discretization of the convective terms is studied by performing inviscid computations of the transitional Taylor–Green vortex and isotropic turbulence configurations. The Taylor–Green vortex computations show that the increase in the order of accuracy restricts the numerical dissipation to smaller scales which, in turn, leads to a better representation of transitional mechanisms. However, isotropic turbulence computations using a fifth-order accuracy or above show obvious manifestations of under-resolution (such as the onset of oscillations and numerical noise), which suggests that the high-order numerical dissipation alone is unable to mimic the dissipation originating from sub-grid scales in the case freely decaying turbulence. Computations of the channel flow configuration at Reτ=1000 at typical large-eddy simulation resolutions show that under-resolved SD discretizations using a high order of accuracy (fifth and sixth) lead to an excellent prediction of the wall-friction, the velocity profiles, the turbulent structures near the wall and the energy spectra, while lower order discretizations lead to an underestimation of the wall-friction and globally a poor representation of wall-bounded turbulence. The present study emphasizes the benefit of using high-order SD discretizations for an accurate representation of turbulent phenomena (namely, transitional and wall-bounded turbulence) but also the necessity of combining this approach with dynamic large-eddy simulation models or appropriate regularization techniques which would activate only where needed to recover physically consistent results, e.g., in regions where fully developed turbulence is present.},
 bibtype = {article},
 author = {Chapelier, J B and Lodato, G and Jameson, A},
 doi = {10.1016/j.compfluid.2016.03.006},
 journal = {Computers and Fluids}
}

@article{
 title = {Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence},
 type = {article},
 year = {2018},
 pages = {44604},
 volume = {3},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604},
 month = {4},
 publisher = {American Physical Society},
 id = {ebeac5a4-3763-3b93-bf27-ee587aebb8e5},
 created = {2021-04-09T15:24:40.168Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:40.168Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Danish, Mohammad and Meneveau, Charles},
 doi = {10.1103/PhysRevFluids.3.044604},
 journal = {Physical Review Fluids},
 number = {4}
}

@article{
 title = {Nonlinear effects in buoyancy-driven variable-density turbulence},
 type = {article},
 year = {2017},
 keywords = {Navier–Stokes equations,buoyancy-driven instability,mathematical foundations},
 pages = {362-377},
 volume = {810},
 websites = {http://www.journals.cambridge.org/abstract_S0022112016007199},
 month = {4},
 publisher = {Cambridge University Press},
 id = {d4f5f478-aada-3f5f-87d3-74e0200b074e},
 created = {2021-04-09T15:24:40.792Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:40.792Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We consider the time dependence of a hierarchy of scaled L^2m -norms D_m,[STIX]x1D714 and D_m,[STIX]x1D703 of the vorticity [STIX]x1D74E=[STIX]x1D735 u and the density gradient [STIX]x1D735[STIX]x1D703 , where [STIX]x1D703= ([STIX]x1D70C^ /[STIX]x1D70C_0^ ) , in a buoyancy-driven turbulent flow as simulated by Livescu &amp; Ristorcelli ( J. Fluid Mech. , vol. 591, 2007, pp. 43–71). Here, [STIX]x1D70C^ (x,t) is the composition density of a mixture of two incompressible miscible fluids with fluid densities [STIX]x1D70C_2^ >[STIX]x1D70C_1^  , and [STIX]x1D70C_0^  is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the L^2 -spatial average of the density gradient [STIX]x1D735[STIX]x1D703 can reach extremely large values at intermediate times, even in flows with low Atwood number At=([STIX]x1D70C_2^ -[STIX]x1D70C_1^ )/([STIX]x1D70C_2^ +[STIX]x1D70C_1^ )=0.05 , implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient [STIX]x1D735[STIX]x1D703 might blow up in a finite time.},
 bibtype = {article},
 author = {Rao, P and Caulfield, C P and Gibbon, J D},
 doi = {10.1017/jfm.2016.719},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows},
 type = {article},
 year = {2017},
 keywords = {mathematical foundations,turbulence theory,turbulent mixing},
 pages = {236-279},
 volume = {829},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {ab7a41aa-5bfe-3e00-be27-392ff5926cb1},
 created = {2021-04-09T15:24:41.296Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:41.296Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We derive here Lagrangian fluctuation–dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values, boundary values and internal sources, as those are sampled backward in time by stochastic Lagrangian trajectories. New probabilistic concepts are required to represent scalar boundary conditions at the walls: the boundary local-time density at points on the wall where scalar fluxes are imposed and the boundary first hitting time at points where scalar values are imposed. These concepts are illustrated both by analytical results for the problem of pure heat conduction and by numerical results from a database of channel-flow turbulence, which also demonstrate the scalar mixing properties of near-wall turbulence. As an application of the fluctuation–dissipation relation, we examine for wall-bounded flows the relation between anomalous scalar dissipation and Lagrangian spontaneous stochasticity, i.e. the persistent non-determinism of Lagrangian particle trajectories in the limit of vanishing viscosity and diffusivity. In Part I of this series, we showed that spontaneous stochasticity is the only possible mechanism for anomalous dissipation of passive or active scalars, away from walls. Here it is shown that this remains true when there are no scalar fluxes through walls. Simple examples show, on the other hand, that a distinct mechanism of non-vanishing scalar dissipation can be thin scalar boundary layers near the walls. Nevertheless, we prove for general wall-bounded flows that spontaneous stochasticity is another possible mechanism of anomalous scalar dissipation.},
 bibtype = {article},
 author = {Drivas, Theodore D and Eyink, Gregory L},
 doi = {10.1017/jfm.2017.571},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic Web},
 type = {article},
 year = {2015},
 keywords = {Fractals,ROMA,cosmic gas,fluid turbulence,magnetospheric cusp},
 pages = {2025-2043},
 volume = {172},
 websites = {http://link.springer.com/10.1007/s00024-014-0874-z},
 month = {4},
 publisher = {Springer Basel},
 id = {b553ef8e-fc2f-38f3-a3c1-dacf3828984f},
 created = {2021-04-09T15:24:41.947Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:41.947Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Chang, Tom and chin Wu, Cheng and Echim, Marius and Lamy, Hervé and Vogelsberger, Mark and Hernquist, Lars and Sijacki, Debora},
 doi = {10.1007/s00024-014-0874-z},
 journal = {Pure and Applied Geophysics},
 number = {7}
}

@article{
 title = {Building a scientific workflow framework to enable real-time machine learning and visualization},
 type = {article},
 year = {2018},
 keywords = {DataSpaces,computational fluid dynamics,high performance computing,machine learning,real‐time online data analytics,scientific workflows},
 pages = {e4703},
 volume = {31},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703},
 month = {4},
 publisher = {Wiley-Blackwell},
 id = {643d3582-6581-3ebb-b923-a79c94872b63},
 created = {2021-04-09T15:24:42.504Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:42.504Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Li, Feng and Song, Fengguang},
 doi = {10.1002/cpe.4703},
 journal = {Concurrency and Computation: Practice and Experience},
 number = {16}
}

@article{
 title = {Generalization of Turbulent Pair Dispersion to Large Initial Separations},
 type = {article},
 year = {2018},
 pages = {244502},
 volume = {120},
 websites = {https://link.aps.org/doi/10.1103/PhysRevLett.120.244502},
 month = {4},
 publisher = {American Physical Society},
 id = {19f0e616-4624-396b-90a8-7e7edd4ffb39},
 created = {2021-04-09T15:24:43.155Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:43.155Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Shnapp, Ron and Liberzon, Alex},
 doi = {10.1103/PhysRevLett.120.244502},
 journal = {Physical Review Letters},
 number = {24}
}

@article{
 title = {On Visualizing Continuous Turbulence Scales},
 type = {article},
 year = {2019},
 keywords = {Human‐centered computing∼Scientific visualization,flow visualization,scientific visualization,visualization,volume visualization},
 pages = {300-315},
 volume = {38},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532},
 month = {4},
 publisher = {John Wiley & Sons, Ltd (10.1111)},
 id = {e60aa66b-61a5-3dc9-a8a9-4d541b501276},
 created = {2021-04-09T15:24:43.766Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:43.766Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Liu, Xiaopei and Mishra, Maneesh and Skote, Martin and Fu, Chi‐Wing},
 doi = {10.1111/cgf.13532},
 journal = {Computer Graphics Forum},
 number = {1}
}

@article{
 title = {Renormalization of viscosity in wavelet-based model of turbulence},
 type = {article},
 year = {2018},
 pages = {33116},
 volume = {98},
 websites = {https://link.aps.org/doi/10.1103/PhysRevE.98.033116},
 month = {4},
 publisher = {American Physical Society},
 id = {c93ca499-6722-3c06-8166-73943def56c5},
 created = {2021-04-09T15:24:44.383Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:44.383Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Altaisky, M V and Hnatich, M and Kaputkina, N E},
 doi = {10.1103/PhysRevE.98.033116},
 journal = {Physical Review E},
 number = {3}
}

@article{
 title = {Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow},
 type = {article},
 year = {2018},
 pages = {24602},
 volume = {3},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602},
 month = {4},
 publisher = {American Physical Society},
 id = {4d7dc155-2758-3e9a-b31c-49fcd1d57167},
 created = {2021-04-09T15:24:45.029Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:45.029Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The kinetic energy spectrum of high-Reynolds turbulent swirling flows is experimentally studied. This spectrum, obtained from direct measurements in space, exhibits nearly two decades of Kolmogorov k −5/3 decay in the inertial range of scales. Beyond this regime, in the dissipative range of scales, a crossover to a stretched exponential decay on scale k 2/3 is observed, in full agreement with a recent theoretical prediction based on nonperturbative renormalization group theory.},
 bibtype = {article},
 author = {Debue, Paul and Kuzzay, Denis and Saw, Ewe-Wei and Daviaud, François and Dubrulle, Bérengère and Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás},
 doi = {10.1103/PhysRevFluids.3.024602},
 journal = {Physical Review Fluids},
 number = {2}
}

@article{
 title = {Remote visual analysis of large turbulence databases at multiple scales},
 type = {article},
 year = {2018},
 pages = {115-126},
 volume = {120},
 websites = {https://www.sciencedirect.com/science/article/pii/S0743731518303927},
 month = {4},
 publisher = {Academic Press},
 id = {35837047-3f06-3d53-b882-ecb1c35bd473},
 created = {2021-04-09T15:24:46.266Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:46.266Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. We present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. The database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.},
 bibtype = {article},
 author = {Pulido, Jesus and Livescu, Daniel and Kanov, Kalin and Burns, Randal and Canada, Curtis and Ahrens, James and Hamann, Bernd},
 doi = {10.1016/J.JPDC.2018.05.011},
 journal = {Journal of Parallel and Distributed Computing}
}

@article{
 title = {Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements},
 type = {article},
 year = {2020},
 pages = {54604},
 volume = {5},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604},
 month = {4},
 publisher = {American Physical Society},
 id = {f211ca87-c1f5-30ae-b860-b03aca46a225},
 created = {2021-04-09T15:24:46.917Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:46.917Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Krishna, C Vamsi and Wang, Mengying and Hemati, Maziar S and Luhar, Mitul},
 doi = {10.1103/PhysRevFluids.5.054604},
 journal = {Physical Review Fluids},
 number = {5}
}

@article{
 title = {High-Reynolds-number fractal signature of nascent turbulence during transition},
 type = {article},
 year = {2020},
 keywords = {Fractal dimension,Transitional boundary layer,Turbulent spots},
 pages = {3461-3468},
 volume = {117},
 websites = {http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117},
 month = {4},
 publisher = {National Academy of Sciences},
 id = {961c0616-69f2-3de4-b644-445021490b1f},
 created = {2021-04-09T15:24:47.453Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:47.453Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension D ≈ 7 / 3 , where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume–area fractal scaling exponent. Measurements show a dimension of D = 2.36 ± 0.03 over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.},
 bibtype = {article},
 author = {Wu, Zhao and Zaki, Tamer A and Meneveau, Charles},
 doi = {10.1073/pnas.1916636117},
 journal = {Proceedings of the National Academy of Sciences},
 number = {7}
}

@article{
 title = {Geometric constraints on energy transfer in the turbulent cascade},
 type = {article},
 year = {2020},
 pages = {34603},
 volume = {5},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603},
 month = {4},
 publisher = {American Physical Society},
 id = {a82e659f-7268-3e32-b8f7-441f609d4224},
 created = {2021-04-09T15:24:48.171Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:48.171Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The energy cascade is the most significant feature that separates turbulence from other unsteady flows, and results from the behavior of the nonlinear term in the Navier-Stokes equations. The mathematical form of this term, however, places constraints on exactly how it can act. Here we consider the action of the nonlinear term in physical space rather than in Fourier space, where the energy transfer between scales can be interpreted as a mechanical process where some scales do work on others. This formulation reveals the fundamental role played by geometry, as work can only be done when the eigenframes of the turbulent stress and strain rate are appropriately aligned. By comparing a direct numerical simulation of the Navier-Stokes equations, an ensemble of random solenoidal vector fields, and a random sampling of uniform eigenframe alignments, we show that this geometric alignment plays a much stronger role in determining the flux between scales than do the magnitudes of the stress and strain rate. We also show that when the alignment is effectively two dimensional, even when embedded in a three-dimensional flow, the energy flux is typically inverse, suggesting that the inverse cascade in two-dimensional turbulence may have a kinematic origin. Our results point to some potentially fruitful directions for turbulence modeling.},
 bibtype = {article},
 author = {Ballouz, Joseph G and Ouellette, Nicholas T},
 doi = {10.1103/PhysRevFluids.5.034603},
 journal = {Physical Review Fluids},
 number = {3}
}

@article{
 title = {Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow},
 type = {article},
 year = {2019},
 pages = {23902},
 volume = {4},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902},
 month = {4},
 publisher = {American Physical Society},
 id = {ec287cd3-c0fe-353a-a570-e6ae60c03bac},
 created = {2021-04-09T15:24:48.752Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:48.752Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Existing methods to identify the interfaces separating different regions in turbulent flows, such as turbulent/nonturbulent interfaces, typically rely on subjectively chosen thresholds, often including visual verification that the resulting surface meaningfully separates the different regions. Since machine learning tools are known to help automate such classification tasks, we here propose to use an unsupervised self-organizing map (SOM) machine learning algorithm as an automatic classifier. We use it to separate a boundary layer undergoing bypass transition into two distinct spatial regions, the turbulent boundary layer (TBL) and non-TBL regions, the latter including the laminar portion prior to transition and the outer flow which possibly contains weak free-stream turbulence. Both regions are separated by the turbulent boundary layer interface (TBLI). The data used in this study are from a direct numerical simulation and are available on an open database system. In our analysis of one snapshot in time, every spatial point is characterized by a 16-dimensional vector containing the magnitudes of the components of total and fluctuating velocity, magnitudes of the velocity gradient tensor elements, and the streamwise and wall-normal coordinates, all normalized by their global standard deviation. In an unsupervised fashion, the SOM classifier separates the points into TBL and non-TBL regions, thus identifying the TBLI without the need for user-specified thresholds. Remarkably, it avoids including vortical streaky structures that exist in the laminar portion prior to transition as well as the weak free-stream turbulence in the turbulent boundary layer region. The approach is compared quantitatively with existing methods to determine the TBLI (vorticity magnitude, cross-stream velocity fluctuation). Also, the SOM classifier is cast as a linear hyperplane that separates the two clusters of data points, and the method is tested by finding the TBLI of other snapshots in the transitional boundary layer data set, as well as in a fully turbulent boundary layer with similar levels of free-stream turbulence. Variants in which the approach failed are also summarized.},
 bibtype = {article},
 author = {Wu, Zhao and Lee, Jin and Meneveau, Charles and Zaki, Tamer},
 doi = {10.1103/PhysRevFluids.4.023902},
 journal = {Physical Review Fluids},
 number = {2}
}

@article{
 title = {Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow},
 type = {article},
 year = {2019},
 keywords = {Turbulent channel flow,quiescent core,spheroidal inertialess particles},
 pages = {424-438},
 volume = {20},
 websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747},
 month = {4},
 publisher = {Taylor and Francis Ltd.},
 id = {bde9b67c-cc56-3e5a-ba15-32edb1794316},
 created = {2021-04-09T15:24:49.272Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:49.272Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Numerical studies into the dynamics of non-spherical particles in turbulent channel flow have, until now, been mostly confined to low Reynolds numbers. In this paper, we investigate the dynamics of tracer non-spherical particles in a channel flow at (Formula presented.) for the first time. Tracer spheroidal particles suspended in a turbulent channel flow are computed by means of direct numerical simulation coupled with a Lagrangian point-particle approach. We examine the rotational dynamics and alignment of tracer spheroids of different aspect ratio in both the near-wall region and, in particular, the quiescent core which is not observed at lower Reynolds numbers. In the near-wall region, the effect of Reynolds number on preferential alignment is negligible with particle rotation exhibiting a weak dependence for all aspect ratios investigated. However, the particle rotation is strongly damped in the quiescent core demonstrating that the motion of tracer spheroids becomes quiescent. The striking difference in spheroids' rotational dynamics observed inside and outside of the quiescent core is correlated with the local Kolmogorov time scale in the core and outside of it.},
 bibtype = {article},
 author = {Jie, Yucheng and Xu, Chunxiao and Dawson, James R and Andersson, Helge I and Zhao, Lihao},
 doi = {10.1080/14685248.2019.1664747},
 journal = {Journal of Turbulence},
 number = {7}
}

@article{
 title = {Sensing the turbulent large-scale motions with their wall signature},
 type = {article},
 year = {2019},
 pages = {125112},
 volume = {31},
 websites = {http://aip.scitation.org/doi/10.1063/1.5128053},
 month = {4},
 publisher = {American Institute of Physics Inc.},
 id = {34785306-ab75-301c-9fe7-4a8b56499b9d},
 created = {2021-04-09T15:24:50.032Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:50.032Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.},
 bibtype = {article},
 author = {Güemes, A and Discetti, S and Ianiro, A},
 doi = {10.1063/1.5128053},
 journal = {Physics of Fluids},
 number = {12}
}

@article{
 title = {Mean dynamics and transition to turbulence in oscillatory channel flow},
 type = {article},
 year = {2019},
 keywords = {boundary layer structure,transition to turbulence,turbulent boundary layers},
 pages = {864-889},
 volume = {880},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {2b9bc248-7bec-3add-aaf3-c815e69e4177},
 created = {2021-04-09T15:24:50.517Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:50.517Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The mean dynamics in oscillatory channel flow is examined to investigate the dynamical mechanisms underlying the transition to turbulence in oscillatory wall-bounded flow. The analyses employ direct numerical simulation data acquired at three Stokes Reynolds numbers: Re_s=648 , 801 and 1009, where the lower Re_s flow is transitional over the entire cycle and the two higher Re_s flows exhibit flow characteristics similar to steady turbulent wall-bounded flow during part of the cycle. The flow evolution over a half-period of oscillation for all three Re_s is as follows: near-wall streamwise velocity streaks develop during the early accelerating portion of the cycle; then at some later point in the cycle that depends on Re_s , the near-wall streaks breakdown (demarking the onset of the nonlinear development stage), and the near-wall Reynolds stress grows explosively; the Reynolds stress remains elevated for part of the cycle before diminishing (yet remaining finite) during the late decelerating portion of the cycle. This process is then repeated indefinitely. The present findings demonstrate that transition to turbulence occurs when the nonlinear development stage begins during the accelerating portion of the cycle. This crucially leads to the diminishing importance of the centreline momentum source, the emergence of a locally accelerating/decelerating internal layer centred about the edge of the Stokes layer and the wall-normal rearrangement of the mean forces prior to the start of the decelerating portion of the cycle. The rearrangement of mean forces culminates in a four layer structure in the mean balance of forces. This is significant on a number of accounts since empirical and theoretical evidence suggests that the formation of a four layer structure is an important characteristic of a self-similar hierarchal structure that underlies logarithmic dependence of the mean velocity profile in steady turbulent wall-bounded flows (Klewicki et al. , J. Fluid Mech. , vol. 638, 2009, pp. 73–93). When the nonlinear development stage begins during the decelerating portion of the cycle (i.e. at Re_s=648 ), a four layer structure is not observed in the mean balance of forces and the flow remains weakly transitional over the entire cycle.},
 bibtype = {article},
 author = {Ebadi, Alireza and White, Christopher M and Pond, Ian and Dubief, Yves},
 doi = {10.1017/jfm.2019.706},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate},
 type = {article},
 year = {2019},
 keywords = {isotropic turbulence,turbulence theory,vortex dynamics},
 pages = {283-312},
 volume = {881},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {0acc8cd3-af07-36ae-9efd-4e068111d3af},
 created = {2021-04-09T15:24:50.978Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:50.978Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper uses a tight mathematical bound on the degree of the non-normality of the turbulent velocity gradient tensor to classify flow behaviour within vortical regions (where the eigenvalues of the tensor contain a conjugate pair). Structures attaining this bound are preferentially generated where enstrophy exceeds total strain and there is a positive balance between strain production and enstrophy production. Lagrangian analysis of homogeneous, isotropic turbulence shows that attainment of this bound is associated with relatively short durations and an upper limit to the spatial extent of the flow structures that is similar to the Taylor scale. An analysis of the dynamically relevant terms using a recently developed formulation (Keylock, J. Fluid Mech. , vol. 848, 2018, pp. 876–904), highlights the controls on this dynamics. In particular, in high enstrophy regions it is shown that the bound is attained when normal strain decreases rather than when non-normality increases. The near absence of normal total strain results in a source of intermittency in the dynamics of dissipation that is hidden in standard analyses. It is shown that of the two terms that contribute to the non-normal production dynamics, it is the one that is typically smallest in magnitude that is of greatest importance within these  =1 filaments. The typical distance between filament centroids is just less than a Taylor scale, implying a connection to the manner in which flow topology at the Taylor scale explains dissipation at smaller scales.},
 bibtype = {article},
 author = {Keylock, Christopher J},
 doi = {10.1017/jfm.2019.779},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Predictive large-eddy-simulation wall modeling via physics-informed neural networks},
 type = {article},
 year = {2019},
 pages = {34602},
 volume = {4},
 websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602},
 month = {4},
 publisher = {American Physical Society},
 id = {3981fbac-dbaf-3646-acef-d3d887d228e4},
 created = {2021-04-09T15:24:52.317Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:52.317Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {While data-based approaches were found to be useful for subgrid scale (SGS) modeling in Reynolds-averaged Navier-Stokes (RANS) simulations, there have not been many attempts at using machine learning techniques for wall modeling in large-eddy simulations (LESs). Large-eddy simulation differs from RANS simulation in many aspects. For one thing, LES is scale resolving. For another, LES is in and of itself a high-fidelity tool. Because data sets of higher fidelity are in general not frequently accessible or available, this poses additional challenges to data-based modeling in LES. Further, SGS modeling usually needs flow information at only large scales, in contrast with wall modeling, which needs to account for both near-wall small scales and large scales above the wall. In this work we discuss how the above-noted challenges may be addressed when taking a data-based approach for wall modeling. We also show the necessity of incorporating physical insights in model inputs, i.e., using inputs that are inspired by the vertically integrated thin-boundary-layer equations and the eddy population density scalings. We show that the inclusion of the above physics-based considerations would enhance extrapolation capabilities of a neural network to flow conditions that are not within the train data. Being cheap to evaluate and using only channel flow data at Reτ=1000, the trained networks are found to capture the law of the wall at arbitrary Reynolds numbers and outperform the conventional equilibrium model in a nonequilibrium flow.},
 bibtype = {article},
 author = {Yang, X I A and Zafar, S and Wang, J.-X. and Xiao, H},
 doi = {10.1103/PhysRevFluids.4.034602},
 journal = {Physical Review Fluids},
 number = {3}
}

@article{
 title = {Double-frame tomographic PTV at high seeding densities},
 type = {article},
 year = {2020},
 keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},
 pages = {23},
 volume = {61},
 websites = {http://link.springer.com/10.1007/s00348-019-2859-2},
 month = {4},
 publisher = {Springer},
 id = {f97dbeff-e7dd-31f8-8835-6edc9b4add50},
 created = {2021-04-09T15:24:52.904Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:52.904Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {A novel method performing 3D PTV from double-frame multi-camera images is introduced. Particle velocities are estimated by following three steps: First, separate particle reconstructions with a sparsity based algorithm are performed on a fine grid. Second, they are expanded on a coarser grid on which 3D correlation is performed, yielding a predictor displacement field that allows to efficiently match particles at the two time instants. As these particles are still located on a voxel grid, the third, final step achieves particle position refinement to their actual subvoxel position by a global optimization process, also accounting for their intensities. As it strongly leverages on principles from tomographic reconstruction, the technique is termed Double-Frame Tomo-PTV (DF-TPTV). Standard synthetic tests on a complex turbulent flow show that the method achieves high particle and vector detection efficiency, up to seeding densities of around 0.08 particles per pixel (ppp). On these tests, it also shows a higher robustness to noise and lower root-mean-square errors on velocity estimation than similar state-of-the-art methods. Results from an experimental campaign on a transitional round air jet at Reynolds number 4600 are also presented. Average seeding density varies in time from 0.06 to 0.03 ppp during the considered run, with different densities and signal-to-noise ratios being observed with time in the jet and ambient air regions, supplied by two different seeding systems. The strong polydisperse nature of the seeding, as well as the coexistence of two spatial zones of significantly different particle densities and signal-to-noise ratios, are observed to be the most influential sources of limitation for DF-TPTV performance. However, the method still successfully reconstructs a large amount of particles, and, associated with an outlier rejection scheme based on temporal statistics, truthfully reconstructs the instantaneous jet dynamics. Further quantitative performance assessment is then provided by introducing statistics performed by bin averaging, upon assuming statistical axisymmetry of the jet. Mean and fluctuating axial velocity components in the jet near-field are compared with reference results obtained from planar PIV at higher seeding density, with an interrogation window of size comparable to that of the bins. Results are found to be in excellent agreement with one another, confirming the high performance of DF-TPTV to yield reliable volumetric vector fields at seeding densities usually considered for tomographic PIV processing.},
 bibtype = {article},
 author = {Cornic, Philippe and Leclaire, Benjamin and Champagnat, Frédéric and Besnerais, Guy Le and Cheminet, Adam and Illoul, Cédric and Losfeld, Gilles},
 doi = {10.1007/s00348-019-2859-2},
 journal = {Experiments in Fluids},
 number = {2}
}

@article{
 title = {Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence},
 type = {article},
 year = {2020},
 keywords = {buoyancy-driven instability,homogeneous turbulence,turbulent mixing},
 pages = {A12},
 volume = {895},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {e07b1214-d2e2-3f30-b087-fa980a509277},
 created = {2021-04-09T15:24:53.393Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:53.393Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Aslangil, Denis and Livescu, Daniel and Banerjee, Arindam},
 doi = {10.1017/jfm.2020.268},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Developing particle image velocimetry software based on a deep neural network},
 type = {article},
 year = {2020},
 keywords = {deep neural networks,fluid motion estimation,particle image velocimetry},
 pages = {359-376},
 volume = {27},
 websites = {http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},
 publisher = {Begell House},
 id = {06f51761-ca9e-36a5-9636-b609c6c8f2c7},
 created = {2021-04-09T15:24:54.071Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:54.071Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},
 doi = {10.1615/JFlowVisImageProc.2020033180},
 journal = {Journal of Flow Visualization and Image Processing},
 number = {4}
}

@article{
 title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},
 type = {article},
 year = {2020},
 keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},
 pages = {45-56},
 volume = {88},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285},
 month = {4},
 publisher = {Elsevier Ltd},
 id = {363377e2-48c9-3547-a8c4-1cf8706456c9},
 created = {2021-04-09T15:24:54.552Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:54.552Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},
 bibtype = {article},
 author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},
 doi = {10.1016/j.cag.2020.03.002},
 journal = {Computers & Graphics}
}

@article{
 title = {A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study},
 type = {article},
 year = {2020},
 pages = {55102},
 volume = {32},
 websites = {http://aip.scitation.org/doi/10.1063/1.5128379},
 month = {4},
 publisher = {AIP Publishing LLCAIP Publishing},
 id = {8c44d1e5-9a8d-3934-8a8e-5c4f91bf7721},
 created = {2021-04-09T15:24:55.310Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:55.310Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian ...},
 bibtype = {article},
 author = {Samiee, Mehdi and Akhavan-Safaei, Ali and Zayernouri, Mohsen},
 doi = {10.1063/1.5128379},
 journal = {Physics of Fluids},
 number = {5}
}

@article{
 title = {Wall-attached and wall-detached eddies in wall-bounded turbulent flows},
 type = {article},
 year = {2020},
 keywords = {boundary layer structure,turbulence theory,turbulent boundary layers},
 pages = {A30},
 volume = {885},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {3bd35814-20d4-35a0-a335-1615f7927ae3},
 created = {2021-04-09T15:24:55.789Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:55.789Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Hu, Ruifeng and Yang, Xiang I A and Zheng, Xiaojing},
 doi = {10.1017/jfm.2019.980},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking},
 type = {article},
 year = {2020},
 keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},
 pages = {47},
 volume = {61},
 websites = {http://link.springer.com/10.1007/s00348-019-2875-2},
 month = {4},
 publisher = {Springer},
 id = {a329aa66-d78d-3813-af6b-87dfe61107eb},
 created = {2021-04-09T15:24:56.527Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:56.527Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {We developed an open-source Lagrangian particle tracking (OpenLPT) based on the Shake-the-Box (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) method. The source code of OpenLPT is available on GitHub repository (@JHU-NI-LAB). The code features a new method that removes the majority of ghost particles at a high particle image density. The resulting percentage of ghost particles drops from 110% to 26% for image density at 0.125 ppp—nearly 84% of ghost particles are removed. Extensive tests of OpenLPT using synthetic data sets show that the code produces tracks with accuracy and processing time similar to the previously-reported values. In addition, OpenLPT has been parallelized to run on high-performance computing clusters to drastically increase its processing speed. To examine the code’s capability of tracking shadows of small tracers for backlit experiments, the blurred-particle effect was also included on synthetic images and OpenLPT was tested to process these noisy images. The results show that OpenLPT can also track shadows of a high-concentration of particles reliably in 3D. Based on the test, the optimal depth of field (DoF) and particle concentration for future experiments using Lagrangian shadow tracking are provided. For example, DoF controlled by the aperture should be set at around half of the size of the view area. At this DoF, most particles in the interrogation volume can be tracked, whereas particles outside the interrogation volume become too dim to affect results. 40 experimental data sets for a wide range of particle concentrations were also used for evaluating the code, and the results show a nice agreement with the synthetic tests.},
 bibtype = {article},
 author = {Tan, Shiyong and Salibindla, Ashwanth and Masuk, Ashik Ullah Mohammad and Ni, Rui},
 doi = {10.1007/s00348-019-2875-2},
 journal = {Experiments in Fluids},
 number = {2}
}

@article{
 title = {The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow},
 type = {article},
 year = {2020},
 pages = {13302},
 volume = {32},
 websites = {http://aip.scitation.org/doi/10.1063/1.5139028},
 month = {4},
 publisher = {American Institute of Physics Inc.},
 id = {39347325-914b-3dc5-abf4-3bffa7a604d6},
 created = {2021-04-09T15:24:57.014Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:57.014Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Particle stress is known to play a vital role in turbulence modulation. However, the earlier studies on particle stress were mostly confined to the cases of spherical and elongated particles. In the present study, we investigated the stress generated in dilute suspensions of inertialess spheroids with various shapes in wall-bounded turbulence. We performed direct numerical simulations of turbulent particle-laden channel flows utilizing a one-way coupled Eulerian-Lagrangian approach. The stress in the suspension of oblate spheroids was examined in detail and compared with prolate spheroid cases for the first time. The results show that particle stress is strongly dependent on particle shape and the stress of the oblate spheroid is qualitatively different from the case of prolate particles. However, we found that the fluctuating spanwise shear stress of flat oblate spheroids, which makes a significant contribution to turbulence dissipation, is in the same order of magnitude of the term generated by elongated prolate spheroids at a constant volume fraction. We also examined the effect of the Reynolds number on the particle stress in channel flows at Reτ = 180 and 1000. The results reveal a negligible influence on the mean stresses, but the fluctuating stresses are significantly Reynolds number dependent. In the buffer layer, we observed the correlations between the particle stress of spheroids and the fluctuating velocity of the fluid in the streamwise direction, which could be attributed to the different orientation of spheroids and fluid strain rate in low- and high-speed streaks of near-wall turbulence.},
 bibtype = {article},
 author = {Wang, Ze and Zhao, Lihao},
 doi = {10.1063/1.5139028},
 journal = {Physics of Fluids},
 number = {1}
}

@article{
 title = {Pressure power spectrum in high-Reynolds number wall-bounded flows},
 type = {article},
 year = {2020},
 pages = {108620},
 volume = {84},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916},
 month = {4},
 publisher = {Elsevier},
 id = {b85f5b6f-a0aa-376a-ad98-fc145ff5b768},
 created = {2021-04-09T15:24:57.575Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:57.575Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Xu, Haosen H A and Towne, Aaron and Yang, Xiang I A and Marusic, Ivan},
 doi = {10.1016/j.ijheatfluidflow.2020.108620},
 journal = {International Journal of Heat and Fluid Flow}
}

@article{
 title = {A Comparison of Rendering Techniques for 3D Line Sets with Transparency},
 type = {article},
 year = {2020},
 pages = {1},
 websites = {https://ieeexplore.ieee.org/document/9007507/},
 month = {4},
 publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
 id = {77692821-f40f-3cb9-9904-265929f62c49},
 created = {2021-04-09T15:24:58.040Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:58.040Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visualizing trajectories of tracer particles in flow fields. Transparency is then used to fade out lines deemed unimportant, based on, for instance, geometric properties or attributes defined along them. Since accurate blending of transparent lines requires rendering the lines in back-to-front or front-to-back order, enforcing this order for 3D line sets with tens or even hundreds of thousands of elements becomes challenging. In this paper, we study CPU and GPU rendering techniques for large transparent 3D line sets. We compare accurate and approximate techniques using optimized implementations and a number of benchmark data sets. We discuss the effects of data size and transparency on quality, performance and memory consumption. Based on our study, we propose two improvements to per-pixel fragment lists and multi-layer alpha blending. The first improves the rendering speed via an improved GPU sorting operation, and the second improves rendering quality via a transparency-based bucketing.},
 bibtype = {article},
 author = {Kern, Michael and Neuhauser, Christoph and Maack, Torben and Han, Mengjiao and Usher, Will and Westermann, Ruediger},
 doi = {10.1109/TVCG.2020.2975795},
 journal = {IEEE Transactions on Visualization and Computer Graphics}
}

@article{
 title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020},
 type = {article},
 year = {2020},
 keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},
 pages = {1-15},
 websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},
 month = {4},
 publisher = {Taylor and Francis Ltd.},
 id = {5fb83e3f-627a-3eb4-98b2-e71bbadefb97},
 created = {2021-04-09T15:24:58.541Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:58.541Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},
 bibtype = {article},
 author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},
 doi = {10.1080/00221686.2020.1729265},
 journal = {Journal of Hydraulic Research}
}

@article{
 title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},
 type = {article},
 year = {2020},
 pages = {94013},
 volume = {31},
 websites = {https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d},
 month = {4},
 publisher = {Institute of Physics Publishing},
 id = {48519ba0-b237-3437-bb93-5ee1105659c9},
 created = {2021-04-09T15:24:59.283Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:59.283Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},
 bibtype = {article},
 author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},
 doi = {10.1088/1361-6501/ab848d},
 journal = {Measurement Science and Technology},
 number = {9}
}

@article{
 title = {Adaptive ensemble PTV},
 type = {article},
 year = {2020},
 keywords = {PIV,PTV,spatial resolution,turbulent flow statistics},
 pages = {85301},
 volume = {31},
 websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta},
 month = {4},
 publisher = {Institute of Physics Publishing},
 id = {40b7bc2d-a36e-33e4-8f93-3ef9a1935879},
 created = {2021-04-09T15:24:59.778Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:24:59.778Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out.},
 bibtype = {article},
 author = {Raiola, Marco and Lopez-Nuñez, Elena and Cafiero, Gioacchino and Discetti, Stefano},
 doi = {10.1088/1361-6501/ab82bf},
 journal = {Measurement Science and Technology},
 number = {8}
}

@article{
 title = {A Priori Sub-grid Modelling Using Artificial Neural Networks},
 type = {article},
 year = {2020},
 keywords = {ANN,LES,turbulence},
 pages = {397-417},
 volume = {34},
 websites = {https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116},
 month = {4},
 publisher = {Taylor and Francis Ltd.},
 id = {d7410cf0-8ad5-3cc3-afea-2ec408731071},
 created = {2021-04-09T15:25:00.319Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:00.319Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation of Homogeneous Isotropic Turbulence at different Reynolds numbers. The results show that the correlation coefficients are superior to other sub-grid models, using a similar set of input variables. As the ANN model extrapolates to larger Reynolds, the correlation coefficient decreases. However, it remains higher than other sub-grid approaches, and suggest that the combined LES-ANN methodology can potentially be used as a sub-grid model at realistic Reynolds numbers. Models derived from Homogeneous Isotropic Turbulence can also be used in different simple flows and provide relatively good agreement.},
 bibtype = {article},
 author = {Prat, Alvaro and Sautory, Theophile and Navarro-Martinez, S},
 doi = {10.1080/10618562.2020.1789116},
 journal = {International Journal of Computational Fluid Dynamics},
 number = {6}
}

@article{
 title = {Robust principal component analysis for modal decomposition of corrupt fluid flows},
 type = {article},
 year = {2020},
 keywords = {doi:10.1103/PhysRevFluids.5.054401 url:https://doi},
 pages = {54401},
 volume = {5},
 websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401},
 month = {4},
 publisher = {American Physical Society},
 id = {0d4e9077-a45a-3e73-b1bf-865c5c74c7c8},
 created = {2021-04-09T15:25:00.870Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:00.870Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Modal analysis techniques are used to identify patterns and develop reduced-order models in a variety of fluid applications. However, experimentally acquired flow fields may be corrupted with incorrect and missing entries, which may degrade modal decomposition. Here we use robust principal component analysis (RPCA) to improve the quality of flow-field data by leveraging global coherent structures to identify and replace spurious data points. RPCA is a robust variant of principal component analysis, also known as proper orthogonal decomposition in fluids, that decomposes a data matrix into the sum of a low-rank matrix containing coherent structures and a sparse matrix of outliers and corrupt entries. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. The performance is particularly striking when flow fields are analyzed using dynamic mode decomposition, which is sensitive to noise and outliers.},
 bibtype = {article},
 author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L},
 doi = {10.1103/PhysRevFluids.5.054401},
 journal = {Physical Review Fluids},
 number = {5}
}

@article{
 title = {Nanoflare Theory and Stochastic Reconnection},
 type = {article},
 year = {2020},
 pages = {89},
 volume = {4},
 websites = {https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta},
 month = {4},
 publisher = {American Astronomical Society},
 id = {e476ace8-2be9-37fa-8534-8643d2ebfb1b},
 created = {2021-04-09T15:25:01.361Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:01.361Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Jafari, Amir and Vishniac, Ethan T and Xu, Siyao},
 doi = {10.3847/2515-5172/ab9e02},
 journal = {Research Notes of the AAS},
 number = {6}
}

@inproceedings{
 title = {A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity},
 type = {inproceedings},
 year = {2020},
 websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060},
 month = {4},
 publisher = {American Institute of Aeronautics and Astronautics},
 id = {2178269a-95b7-37d7-9746-7dadf37353f3},
 created = {2021-04-09T15:25:02.054Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:02.054Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {inproceedings},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Myhre, Nicodemus and Prazenica, Richard J and Balas, Mark and Gnanamanickam, Ebenezer P},
 doi = {10.2514/6.2020-3060},
 booktitle = {AIAA AVIATION 2020 FORUM}
}

@article{
 title = {Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes},
 type = {article},
 year = {2020},
 keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},
 pages = {A27},
 volume = {900},
 websites = {https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article},
 month = {4},
 publisher = {Cambridge University Press},
 id = {a9e970dd-84ff-353a-9f37-6fb053ef372c},
 created = {2021-04-09T15:25:02.534Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:02.534Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},
 doi = {10.1017/jfm.2020.495},
 journal = {Journal of Fluid Mechanics}
}

@article{
 title = {Vision-based correspondence using relaxation algorithms for particle tracking velocimetry},
 type = {article},
 year = {2021},
 pages = {25303},
 volume = {32},
 websites = {https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta},
 month = {4},
 publisher = {IOP Publishing},
 id = {750f71b5-9fd8-3a2b-96db-645511a456fb},
 created = {2021-04-09T15:25:03.224Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:03.224Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Benkovic, Théo and Krawczynski, Jean-François and Druault, Philippe},
 doi = {10.1088/1361-6501/abb437},
 journal = {Measurement Science and Technology},
 number = {2}
}

@article{
 title = {Dense particle tracking using a learned predictive model},
 type = {article},
 year = {2020},
 keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},
 pages = {223},
 volume = {61},
 websites = {http://link.springer.com/10.1007/s00348-020-03061-y},
 month = {4},
 publisher = {Springer},
 id = {fa0bf048-fc79-3234-9569-946909b0b385},
 created = {2021-04-09T15:25:03.814Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:03.814Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle's velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases-turbulent channel flow, flow through a T-junction, and swimming microorganisms-demonstrate the broad applicability of the proposed method to different fields with unique challenges. Graphic abstract 1 Introduction},
 bibtype = {article},
 author = {Mallery, Kevin and Shao, Siyao and Hong, Jiarong},
 doi = {10.1007/s00348-020-03061-y},
 journal = {Experiments in Fluids},
 number = {10}
}

@article{
 title = {Spectral energy analysis of bulk three-dimensional active nematic turbulence},
 type = {article},
 year = {2020},
 pages = {9059-9068},
 volume = {16},
 websites = {http://xlink.rsc.org/?DOI=C9SM02492A},
 publisher = {Royal Society of Chemistry (RSC)},
 id = {2dcd947a-1b83-353a-a5c2-c938a56fe531},
 created = {2021-04-09T15:25:04.756Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:04.756Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {Energy spectrum analysis of 3D active nematic turbulence is perfomed and combined with geometrical analysis of ordering and flow fields.},
 bibtype = {article},
 author = {Krajnik, Žiga and Kos, Žiga and Ravnik, Miha},
 doi = {10.1039/C9SM02492A},
 journal = {Soft Matter},
 number = {39}
}

@article{
 title = {Shallow neural networks for fluid flow reconstruction with limited sensors},
 type = {article},
 year = {2020},
 keywords = {flow field estimation,fluid dynamics,machine learning,neural networks,sensors},
 pages = {20200097},
 volume = {476},
 websites = {https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097},
 month = {4},
 publisher = {The Royal Society},
 id = {0bae8a3f-c6d6-3a4c-a627-b21c29e1dee7},
 created = {2021-04-09T15:25:05.426Z},
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 last_modified = {2021-04-09T15:25:05.426Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {<p>In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.</p>},
 bibtype = {article},
 author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan},
 doi = {10.1098/rspa.2020.0097},
 journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences},
 number = {2238}
}

@article{
 title = {Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method},
 type = {article},
 year = {2020},
 keywords = {Poisson equation,boundary condition,error-embedded data,pressure,pressure gradient,pressure reconstruction},
 pages = {55301},
 volume = {31},
 websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta},
 month = {4},
 publisher = {Institute of Physics Publishing},
 id = {7dfa7c22-5ab5-345b-bbd0-3f7dd6656c75},
 created = {2021-04-09T15:25:06.098Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-09T15:25:06.098Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
 private_publication = {false},
 abstract = {This paper reports a theoretical analysis and the corresponding numerical and experimental validation results of the error propagation characteristics of the omnidirectional integration method used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omnidirectional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise embedded in the measured pressure gradient. Accurate determination of the boundary pressure values is the first step in ensuring the accuracy of the reconstructed pressure. The boundary pressure error consists of two parts, with one part decreasing exponentially in magnitude and eventually vanishing, and the other remaining as a constant with small magnitude through iteration. These results are verified by using a direct numerical simulation database of isotropic turbulence flow superimposed with noise at various noise levels and spatial distribution schemes to simulate noise embedded data. The nondimensionalized average error of the reconstructed pressure based on 1000 statistically independent pressure gradient field realizations with a 40% added noise level is 0.854 ± 0.406 for the pressure Poisson equation with Neumann boundary condition, 0.154 ± 0.015 for the circular virtual boundary omnidirectional integration and 0.149 ± 0.015 for the rotating parallel ray omnidirectional integration. If the converged boundary pressure values obtained by the rotating parallel ray are used as Dirichlet boundary conditions, the average pressure error by Poisson is reduced to 0.151 ± 0.015. Of the different variations of the omnidirectional methods, the parallel ray method shows the best performance and therefore is the method of choice. Comparisons of the performance of these pressure reconstruction methods using an experimentally obtained turbulent shear layer flow over an open cavity are in agreement with the conclusions obtained with the DNS simulation data. With the noise added DNS data, limitations regarding the pressure reconstruction methods in determining pressure fluctuation statistics are also identified and quantified.},
 bibtype = {article},
 author = {Liu, Xiaofeng and Moreto, Jose Roberto},
 doi = {10.1088/1361-6501/ab6c28},
 journal = {Measurement Science and Technology},
 number = {5}
}

@article{
 title = {A perspective on machine learning methods in turbulence modeling},
 type = {article},
 year = {2021},
 keywords = {LES,RANS,closure models,machine learning,turbulence simulation},
 pages = {e202100002},
 volume = {44},
 websites = {https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002},
 month = {3},
 publisher = {John Wiley and Sons Inc},
 day = {4},
 id = {6e94090b-dae2-3ea5-ac66-dbb72308e871},
 created = {2021-04-13T18:26:48.366Z},
 accessed = {2021-04-13},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-13T18:26:49.437Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues but also on the advantages and promises of machine learning (ML) methods applied to parameter estimation, model identification, closure term reconstruction, and beyond, mostly from the perspective of large Eddy simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics, and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. In this study, we present a survey of the current data-driven model concepts and methods, highlight important developments, and put them into the context of the discussed challenges.},
 bibtype = {article},
 author = {Beck, Andrea and Kurz, Marius},
 doi = {10.1002/gamm.202100002},
 journal = {GAMM-Mitteilungen},
 number = {1}
}

@techreport{
 title = {Learning Similarity Metrics for Numerical Simulations},
 type = {techreport},
 year = {2020},
 keywords = {CNNs,PDEs,metric learning,numerical simulation,perceptual evaluation,physics simulation},
 pages = {5349-5360},
 websites = {https://github.com/tum-pbs/LSIM.},
 month = {11},
 publisher = {PMLR},
 day = {21},
 id = {5b1c7a6a-a307-3046-be8c-474af85470ca},
 created = {2021-04-13T18:41:19.893Z},
 accessed = {2021-04-13},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-13T18:41:20.784Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of nu­ merical simulation sources. We focus on scalar time-dependent 2D data that commonly arises from motion and transport-based partial differen­ tial equations (PDEs). Our method employs a Siamese network architecture that is motivated by the mathematical properties of a metric. We leverage a controllable data generation setup with PDE solvers to create increasingly different out­ puts from a reference simulation in a controlled environment. A central component of our learned metric is a specialized loss function that intro­ duces knowledge about the correlation between single data samples into the training process. To demonstrate that the proposed approach outper­ forms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the dif­ ferent methods on a large range of test data. Addi­ tionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.},
 bibtype = {techreport},
 author = {Kohl, Georg and Um, Kiwon and Thuerey, Nils}
}

@inproceedings{
 title = {Drilling dataset exploration, processing and interpretation using volve field data},
 type = {inproceedings},
 year = {2020},
 keywords = {Catalysts,Drilling,Gages},
 volume = {11},
 month = {12},
 publisher = {American Society of Mechanical Engineers (ASME)},
 day = {18},
 id = {d0725421-9955-38ea-af18-eb63688a8a6f},
 created = {2021-04-13T18:50:47.936Z},
 accessed = {2021-04-13},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-13T18:50:47.936Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {In 2018 Equinor made an unprecedented step for an energy company and made a multi-terabyte dataset from Volve field open. However, there is a long way from downloading data to executing meaningful analysis. With no way of quickly evaluating the data due to its size and unfamiliar file formats the use of Volve data was so far limited. This paper presents our exploratory work related to the real-time drilling part of the dataset. We provide description of common obstacles and approaches for overcoming them. We also describe specific contents of the dataset for others to gauge the potential for case studies. We hope that this will lower the bar for Volve field data accessibility, promote research, and become a catalyst for other data science projects.},
 bibtype = {inproceedings},
 author = {Tunkiel, Andrzej T. and Wiktorski, Tomasz and Sui, Dan},
 doi = {10.1115/OMAE2020-18151},
 booktitle = {Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE}
}

@article{
 title = {Advanced Rendering of Line Data with Ambient Occlusion and Transparency},
 type = {article},
 year = {2021},
 keywords = {Scientific visualization,line rendering,ray-casting,transparency},
 pages = {614-624},
 volume = {27},
 month = {2},
 publisher = {IEEE Computer Society},
 day = {1},
 id = {5529d502-fd6d-310f-afa4-2deafd97a98c},
 created = {2021-04-13T18:57:54.824Z},
 accessed = {2021-04-13},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2021-04-13T18:57:54.824Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.},
 bibtype = {article},
 author = {Gross, David and Gumhold, Stefan},
 doi = {10.1109/TVCG.2020.3028954},
 journal = {IEEE Transactions on Visualization and Computer Graphics},
 number = {2}
}

@article{
 title = {Model-based multi-sensor fusion for reconstructing wall-bounded turbulence},
 type = {article},
 year = {2021},
 pages = {683-707},
 volume = {35},
 month = {10},
 day = {22},
 id = {349c86f2-eb91-3217-a7db-d8f1c622711a},
 created = {2022-02-20T21:37:29.373Z},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-20T21:37:29.373Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Wang, Mengying and Krishna, C. Vamsi and Luhar, Mitul and Hemati, Maziar S.},
 doi = {10.1007/s00162-021-00586-8},
 journal = {Theoretical and Computational Fluid Dynamics},
 number = {5}
}

@article{
 title = {Law of bounded dissipation and its consequences in turbulent wall flows},
 type = {article},
 year = {2022},
 keywords = {pipe flow boundary layer,turbulence theory,turbulent boundary layers},
 pages = {20},
 volume = {933},
 websites = {https://doi.org/10.1017/jfm.2021.1052},
 id = {cf4fc9f3-21d2-35ea-8c00-b82c5a72d9d3},
 created = {2022-02-20T23:23:59.301Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-20T23:24:00.230Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The dominant paradigm in turbulent wall flows is that the mean velocity near the wall, when scaled on wall variables, is independent of the friction Reynolds number Re τ. This paradigm faces challenges when applied to fluctuations but has received serious attention only recently. Here, by extending our earlier work (Chen & Sreenivasan, J. Fluid Mech., vol. 908, 2021, p. R3) we present a promising perspective, and support it with data, that fluctuations displaying non-zero wall values, or near-wall peaks, are bounded for large values of Re τ , owing to the natural constraint that the dissipation rate is bounded. Specifically, Φ ∞ − Φ = C Φ Re −1/4 τ , where Φ represents the maximum value of any of the following quantities: energy dissipation rate, turbulent diffusion, fluctuations of pressure, streamwise and spanwise velocities, squares of vorticity components, and the wall values of pressure and shear stresses; the subscript ∞ denotes the bounded asymptotic value of Φ, and the coefficient C Φ depends on Φ but not on Re τ. Moreover, there exists a scaling law for the maximum value in the wall-normal direction of high-order moments, of the form ϕ 2q 1/q max = α q − β q Re −1/4 τ , where ϕ represents the streamwise or spanwise velocity fluctuation, and α q and β q are independent of Re τ. Excellent agreement with available data is observed. A stochastic process for which the random variable has the form just mentioned, referred to here as the 'linear q-norm Gaussian', is proposed to explain the observed linear dependence of α q on q.},
 bibtype = {article},
 author = {Chen, Xi and Sreenivasan, Katepalli R},
 doi = {10.1017/jfm.2021.1052},
 journal = {J. Fluid Mech}
}

@article{
 title = {Multiresolution classification of turbulence features in image data through machine learning},
 type = {article},
 year = {2021},
 keywords = {Image processing,Machine learning,Turbulence,Vortex detection},
 pages = {104770},
 volume = {214},
 month = {1},
 publisher = {Pergamon},
 day = {15},
 id = {052413a3-fcdc-3dff-ab3b-f7d91f97b7aa},
 created = {2022-02-20T23:29:14.961Z},
 accessed = {2022-02-20},
 file_attached = {false},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-20T23:29:14.961Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. We present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.},
 bibtype = {article},
 author = {Pulido, Jesus and da Silva, Ricardo Dutra and Livescu, Daniel and Hamann, Bernd},
 doi = {10.1016/J.COMPFLUID.2020.104770},
 journal = {Computers & Fluids}
}

@article{
 title = {Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes},
 type = {article},
 year = {2021},
 pages = {101703},
 volume = {33},
 websites = {https://doi.org/10.1063/5.0066332},
 id = {d887d298-1140-3521-b80b-f8178cac337a},
 created = {2022-02-20T23:33:36.678Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-20T23:33:37.243Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Liu, Xiaofeng and Moreto, Jose Roberto},
 doi = {10.1063/5.0066332},
 journal = {Phys. Fluids}
}

@article{
 title = {Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows},
 type = {article},
 year = {2021},
 keywords = {turbulence modelling,turbulence theory †},
 pages = {6},
 volume = {914},
 websites = {https://doi.org/10.1017/jfm.2020.977},
 id = {d17dc74f-091c-3ad3-9876-dbe551c5865f},
 created = {2022-02-20T23:35:02.757Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-20T23:35:03.347Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {By analysing the Karman-Howarth equation for filtered-velocity fields in turbulent flows, we show that the two-point correlation between the filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlation-based statistical a priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence, we show that local eddy-viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain-rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 (where α is the fractional gradient order) rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional-gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows. Hence, non-local operators thus exhibit interesting modelling capabilities and potential for large-eddy simulations although more developments are required, both on the theoretical and computational implementation fronts.},
 bibtype = {article},
 author = {Clark, Patricio and Leoni, Di and Zaki, Tamer A and Karniadakis, George and Meneveau, Charles and Clark, P and Zaki, T A and Karniadakis, G and Meneveau, C},
 doi = {10.1017/jfm.2020.977},
 journal = {J. Fluid Mech}
}

@article{
 title = {DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data},
 type = {article},
 year = {2021},
 keywords = {Lossy compression,PCA,information retrieval},
 id = {a1abcec3-2790-3c53-a0ab-83f79ddd347a},
 created = {2022-02-21T19:17:28.173Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-21T19:17:28.724Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and ZFP, show promising rate-distortion efficiency. However, as the data storage burden and need for feature-preserving compression continue to grow, relying on unitary or single-stage compression is becoming insufficient for obtaining desirable data reductions and feature preservation. This paper aims to improve the compression ratio by taking advantage of information retrieval (IR), a well-established topic but under-explored in lossy compression for scientific data. We propose our lossy compression technique, called DPZ, based on multi-stage feature extractions, a commonly employed step in IR. Unlike the prior works where the compression is either done by predicting or bit-plane encoding, this work focuses on preserving the key data content from each stage to the maximum extent, ultimately elevates the compression ratio. With the application of discrete cosine transform, principal component analysis, and quantization, DPZ obtains the dominant features with the least amount of bits possible. Specifically, a knee-point detection and an explained variance variation method are designed for finding optimal tradeoffs. DPZ also employs a sampling strategy to reduce computational overhead and estimate compressibility and parameters before compression. We evaluate the performance of DPZ using real-world scientific datasets. Experiments demonstrate that DPZ achieves superior compression ratios through multi-stage retrievals and outperforms SZ and ZFP at medium to high accuracy on most of the evaluated datasets.},
 bibtype = {article},
 author = {Zhang, Jialing and Chen, Jiaxi and Zhuo, Xiaoyan and Moon, Aekyeung and Woo Son, Seung},
 doi = {10.1109/Cluster48925.2021.00056},
 journal = {2021 IEEE International Conference on Cluster Computing (CLUSTER)}
}

@article{
 title = {LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry},
 type = {article},
 year = {2021},
 pages = {2021},
 volume = {70},
 websites = {https://www.ieee.org/publications/rights/index.html},
 id = {a770ec53-7b70-3157-8e6a-cd62f806e33f},
 created = {2022-02-21T19:20:57.099Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-21T19:20:58.051Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en. Index Terms-Deep learning (DL), fluid motion estimation, lightweight, optical flow, particle image velocimetry (PIV).},
 bibtype = {article},
 author = {Yu, Changdong and Bi, Xiaojun and Fan, Yiwei and Han, Yang and Kuai, Yunfei},
 doi = {10.1109/TIM.2021.3082313},
 journal = {IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT}
}

@article{
 title = {Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression},
 type = {article},
 year = {2021},
 id = {89d9254b-bf2f-354a-8f06-5ec1df0284b5},
 created = {2022-02-21T19:20:57.493Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-21T19:20:58.433Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Continual advances in high-performance computing have enabled the development of higher resolution and more realistic simulations of a wide variety of scientific phenomena. As a result, many computational science communities are increasingly constrained by the massive volumes of data produced,for example, strict storage constraints often force reductions in the number of output variables, data output frequency, or simulation length. Accordingly, modelers across many scientific domains are beginning to adopt purpose-built scientific data compression techniques as an effective mitigation for these challenges. The origins of scientific data compression tools every so often lie in image and video compression. Recently, compression researchers have achieved state-of-the-art performance using neural networks for natural image compression, but this achievement has yet to be adapted to scientific data. This paper assesses the performance of an existing autoencoder neural network compression algorithm on two sets of two-dimensional floating-point scientific data. Compared to state-of-the-art scientific data compression algorithms SZ and ZFP, this out-of-the-box neural network achieves higher peak signal-to-noise ratios at low bit rates, and remains competitive in controlling maximum point-wise error. This preliminary assessment paves the way for future research into neural network compression on floating-point scientific data.},
 bibtype = {article},
 author = {Hayne, Lucas and Clyne, John and Li, Shaomeng},
 doi = {10.1109/BigData52589.2021.9671627}
}

@article{
 title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},
 type = {article},
 year = {2021},
 keywords = {turbulence simulation},
 pages = {29},
 volume = {910},
 websites = {https://doi.org/10.1017/jfm.2020.1028},
 id = {4720e5ff-e367-373c-8a45-62e9091085f7},
 created = {2022-02-21T19:25:34.158Z},
 file_attached = {true},
 profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},
 group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},
 last_modified = {2022-02-21T19:25:34.724Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
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 abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},
 bibtype = {article},
 author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},
 doi = {10.1017/jfm.2020.1028},
 journal = {J. Fluid Mech}
}

@article{
 title = {Deep particle image velocimetry supervised learning under light conditions},
 type = {article},
 year = {2021},
 pages = {102000},
 volume = {80},
 publisher = {Elsevier},
 id = {495815cf-b476-3500-8e87-c593e9700f09},
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 author = {Yu, Chang-Dong and Fan, Yi-Wei and Bi, Xiao-Jun and Han, Yang and Kuai, Yun-Fei},
 journal = {Flow Measurement and Instrumentation}
}

@inproceedings{
 title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},
 type = {inproceedings},
 year = {2021},
 pages = {V010T10A062},
 volume = {85666},
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 author = {Nandal, Tanishk and Tyagi, Prince and Singh, Raj Kumar},
 booktitle = {ASME International Mechanical Engineering Congress and Exposition}
}

@article{
 title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R e τ= 150, 400 and 1020},
 type = {article},
 year = {2021},
 pages = {36-50},
 volume = {59},
 publisher = {Taylor & Francis},
 id = {4b757602-02db-3a90-b756-e6de5d0be789},
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 starred = {false},
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 bibtype = {article},
 author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},
 journal = {Journal of Hydraulic Research},
 number = {1}
}

@article{
 title = {A robust single-pixel particle image velocimetry based on fully convolutional networks with cross-correlation embedded},
 type = {article},
 year = {2021},
 pages = {127125},
 volume = {33},
 publisher = {AIP Publishing LLC},
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 author = {Gao, Qi and Lin, Hongtao and Tu, Han and Zhu, Haoran and Wei, Runjie and Zhang, Guoping and Shao, Xueming},
 journal = {Physics of Fluids},
 number = {12}
}

@article{
 title = {Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget},
 type = {article},
 year = {2022},
 keywords = {homogeneous turbulence,isotropic turbulence,pipe flow},
 pages = {87-109},
 volume = {931},
 websites = {https://doi.org/10.1017/jfm.2021.986},
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 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {In this study, we propose a scale-by-scale (SBS) energy budget equation for flows with homogeneity in at least one direction. This SBS budget represents a modified form of the equation first proposed by Danaila et al. (J. for the channel centreline-the primary difference is that, here, we consider the role of pressure along with the errors associated with the isotropic approximations of the interscale divergence and Laplacian of the squared velocity increment. The term encompassing the effects of mean shear is also characterised such that the present analysis can be extended straightforwardly to locations away from the centreline. We show, based on a detailed analysis of previously published channel flow direct numerical simulations and pipe flow experiments near the centreline, how several terms in the present SBS budget equation (including the third-order velocity structure function) behave with increasing Reynolds number. The behaviour of these terms is shown to imply a rate of emergence and subsequent growth of the 4/3 law scale subrange at the channel centreline and pipe axis. The analysis also suggests that the peak magnitude of the third-order velocity structure function occurs at a scale that is fixed in proportion to the Taylor microscale at sufficiently high Reynolds number.},
 bibtype = {article},
 author = {Zimmerman, Spencer J and Antonia, R A and Djenidi, L and Philip, J and Klewicki, J C},
 doi = {10.1017/jfm.2021.986},
 journal = {A28, Fluid Mech}
}

@article{
 title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},
 type = {article},
 year = {2021},
 pages = {45120},
 volume = {33},
 websites = {https://doi.org/10.1063/5.0046502},
 id = {e964db44-a8b8-3b7c-8083-764c8ca4795b},
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 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},
 bibtype = {article},
 author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},
 doi = {10.1063/5.0046502},
 journal = {Phys. Fluids}
}

@article{
 title = {Time-resolved particle image velocimetry algorithm based on deep learning},
 type = {article},
 year = {2021},
 keywords = {Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow},
 websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},
 id = {f2410f9e-f814-3ae7-86c6-4d2a103081f3},
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 last_modified = {2022-02-21T19:34:20.654Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.},
 bibtype = {article},
 author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},
 doi = {10.1109/TIM.2022.3141750}
}

@article{
 title = {DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks},
 type = {article},
 year = {2021},
 keywords = {Particle tracking velocimetry,deep learning,deep neural networks,fluid motion estimation,point clouds},
 volume = {PP},
 websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},
 id = {62e473c0-ea0f-3ba2-bcd2-3c3aea1e9c09},
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 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Particle tracking velocimetry (PTV) is a powerful technique for global and non-intrusive flow field measurement , which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called DeepPTV, for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles are aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multi-scale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely from large scale motion to small scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.},
 bibtype = {article},
 author = {Liang, Jiaming and Cai, Shengze and Xu, Chao and Chen, Tehuan and Chu, Jian},
 doi = {10.1109/TIM.2021.3120127},
 journal = {IEEE Transactions on Instrumentation and Measurement}
}

@inproceedings{
 title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},
 type = {inproceedings},
 year = {2021},
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}

@article{
 title = {On closures for reduced order models—A spectrum of first-principle to machine-learned avenues},
 type = {article},
 year = {2021},
 pages = {91301},
 volume = {33},
 publisher = {AIP Publishing LLC},
 id = {ce06d381-1a1c-374f-b451-90ac4b12aaf3},
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 bibtype = {article},
 author = {Ahmed, Shady E and Pawar, Suraj and San, Omer and Rasheed, Adil and Iliescu, Traian and Noack, Bernd R},
 journal = {Physics of Fluids},
 number = {9}
}

@article{
 title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},
 type = {article},
 year = {2021},
 pages = {45120},
 volume = {33},
 websites = {https://doi.org/10.1063/5.0046502},
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 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},
 bibtype = {article},
 author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},
 doi = {10.1063/5.0046502},
 journal = {Phys. Fluids}
}

@article{
 title = {Time-resolved particle image velocimetry algorithm based on deep learning},
 type = {article},
 year = {2021},
 keywords = {Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow},
 websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},
 id = {bfd59ac7-a0c6-37f1-8e98-fd473976cd16},
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 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.},
 bibtype = {article},
 author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},
 doi = {10.1109/TIM.2022.3141750}
}

@article{
 title = {Geometry of turbulent dissipation and the Navier–Stokes regularity problem},
 type = {article},
 year = {2021},
 pages = {1-9},
 volume = {11},
 publisher = {Nature Publishing Group},
 id = {d4914d45-1f3b-3900-abd0-cebdf83c4fe8},
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 bibtype = {article},
 author = {Rafner, Janet and Grujić, Zoran and Bach, Christian and Bærentzen, Jakob Andreas and Gervang, Bo and Jia, Ruo and Leinweber, Scott and Misztal, Marek and Sherson, Jacob},
 journal = {Scientific Reports},
 number = {1}
}

@article{
 title = {Third-order structure function in the logarithmic layer of boundary-layer turbulence},
 type = {article},
 year = {2021},
 pages = {74602},
 volume = {6},
 publisher = {APS},
 id = {dc7713fc-fc69-3719-a107-f3e04a13d433},
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 bibtype = {article},
 author = {Xie, Jin-Han and De Silva, Charitha and Baidya, Rio and Yang, Xiang I A and Hu, Ruifeng},
 journal = {Physical Review Fluids},
 number = {7}
}

@article{
 title = {Wall model based on neural networks for LES of turbulent flows over periodic hills},
 type = {article},
 year = {2021},
 pages = {54610},
 volume = {6},
 publisher = {APS},
 id = {287b1ea2-125d-3f4f-b076-194d70e30478},
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 author = {Zhou, Zhideng and He, Guowei and Yang, Xiaolei},
 journal = {Physical Review Fluids},
 number = {5}
}

@inproceedings{
 title = {Adaptive Scale-Similar Closure for Large Eddy Simulations. Part 1: Subgrid Stress Closure},
 type = {inproceedings},
 year = {2022},
 pages = {595},
 id = {caa0cd99-5473-3269-a7f6-2a4ef972e1a2},
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 source_type = {inproceedings},
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 bibtype = {inproceedings},
 author = {Stallcup, Eric W and Kshitij, Abhinav and Dahm, Werner J},
 booktitle = {AIAA SCITECH 2022 Forum}
}

@article{
 title = {Systematic generation of moment invariant bases for 2D and 3D tensor fields},
 type = {article},
 year = {2022},
 pages = {108313},
 volume = {123},
 publisher = {Elsevier},
 id = {964a4532-86de-313c-8ca2-6cc48d4cdd16},
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 bibtype = {article},
 author = {Bujack, Roxana and Zhang, Xinhua and Suk, Tomá\^s and Rogers, David},
 journal = {Pattern Recognition}
}

@inproceedings{
 title = {Compressive neural representations of volumetric scalar fields},
 type = {inproceedings},
 year = {2021},
 pages = {135-146},
 volume = {40},
 issue = {3},
 id = {ab19791e-a418-34fb-9e02-0a8fc802642e},
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@article{
 title = {An attention-mechanism incorporated deep recurrent optical flow network for particle image velocimetry},
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@article{
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 pages = {R6},
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 title = {Computer and Physical Modeling for the Estimation of the Pos-sibility of Application of Convolutional Neural Networks in Close-Range Photogrammetry},
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 year = {2023},
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 author = {Pinchukov, V V and Poroykov, A Yu and Shmatko, E V and Sivov, N Yu},
 journal = {Computer},
 number = {1}
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@article{
 title = {Experimental investigation of pressure statistics in laboratory homogeneous isotropic turbulence},
 type = {article},
 year = {2023},
 volume = {35},
 publisher = {AIP Publishing},
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@article{
 title = {Universal alignment in turbulent pair dispersion},
 type = {article},
 year = {2023},
 pages = {4195},
 volume = {14},
 publisher = {Nature Publishing Group UK London},
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}\">\n            <i class=\"fa fa-download fa-fw\"></i> Download BibTeX\n          </a>\n        </li>\n        <li>\n          <a href=\"//bibbase.org/rss?bib=\">\n            <i class=\"fa fa-rss fa-fw\"></i> RSS Feed\n          </a>\n          </li>\n      </ul>\n      </li>\n\n      \n\n\n      \n    </ul>\n\n\n    <div class=\"alert alert-success bibbase_msg\" id=\"bibbase_msg_embed\"\n         style=\"display: none;\">\n\n      Excellent! 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In order to keep using Mendeley with BibBase past April\n        14th, you need to:\n        <ol>\n          <li>renew the authorization for BibBase on Mendeley, and</li>\n          <li>update the BibBase URL\n            in your page the same way you did when you initially set up\n            this page.\n          </li>\n        </ol>\n      </p>\n\n      <p>\n        <a href=\"http://bibbase.org/cgi-bin/mendeley2/get.py\">\n          <i class=\"fa fa-angle-double-right\"></i>\n          Fix it now</a>\n      </p>\n    </div>\n\n  </div>\n\n\n  <div id=\"bibbase_body\">\n    \n  \n  <div class=\"bibbase_group_whole\" id=\"group_2024\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2024')\"\n      onkeypress=\"toggleGroup('group_2024')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2024</span>\n      <span class=\"bibbase_group_count\">\n        \n        (7)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"granerobelinchon-roux-garnier-multiscaleandanisotropiccharacterizationofimagesbasedoncomplexityanapplicationtoturbulence-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Multiscale and anisotropic characterization of images based on complexity: An application to turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Granero-Belinchon,  C.; Roux,  S., G.;  and Garnier,  N., B.\n</span>\n\n  \n\n</span>\n\n  <i>Physica D: Nonlinear Phenomena</i>, 459: 134027.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/granerobelinchon-roux-garnier-multiscaleandanisotropiccharacterizationofimagesbasedoncomplexityanapplicationtoturbulence-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('granerobelinchon-roux-garnier-multiscaleandanisotropiccharacterizationofimagesbasedoncomplexityanapplicationtoturbulence-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multiscale and anisotropic characterization of images based on complexity: An application to turbulence},\n type = {article},\n year = {2024},\n pages = {134027},\n volume = {459},\n publisher = {Elsevier},\n id = {98bfa4cd-16e6-3e74-94c2-210ab25bab26},\n created = {2024-02-20T06:34:00.248Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:00.248Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Granero-Belinchon, Carlos and Roux, Stéphane G and Garnier, Nicolas B},\n journal = {Physica D: Nonlinear Phenomena}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-chang-liang-liang-xie-deeplearningforparticleimagevelocimetrywithattentionaltransformerandcrosscorrelationembedded-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep learning for particle image velocimetry with attentional transformer and cross-correlation embedded.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Chang,  Y.; Liang,  X.; Liang,  C.;  and Xie,  Z.\n</span>\n\n  \n\n</span>\n\n  <i>Ocean Engineering</i>, 292: 116522.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-chang-liang-liang-xie-deeplearningforparticleimagevelocimetrywithattentionaltransformerandcrosscorrelationembedded-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-chang-liang-liang-xie-deeplearningforparticleimagevelocimetrywithattentionaltransformerandcrosscorrelationembedded-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep learning for particle image velocimetry with attentional transformer and cross-correlation embedded},\n type = {article},\n year = {2024},\n pages = {116522},\n volume = {292},\n publisher = {Elsevier},\n id = {47258ac3-5550-3dff-91b7-1e72db39272b},\n created = {2024-02-20T06:34:01.407Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:01.407Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yu, Changdong and Chang, Yongpeng and Liang, Xiao and Liang, Chen and Xie, Zhengpeng},\n journal = {Ocean Engineering}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kearney-laurent-kearney-maximumlikelihoodfilteringforparticletrackinginturbulentflows-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Maximum likelihood filtering for particle tracking in turbulent flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kearney,  G., M.; Laurent,  K., M.;  and Kearney,  R., V.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 65(2): 1-11.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kearney-laurent-kearney-maximumlikelihoodfilteringforparticletrackinginturbulentflows-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kearney-laurent-kearney-maximumlikelihoodfilteringforparticletrackinginturbulentflows-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Maximum likelihood filtering for particle tracking in turbulent flows},\n type = {article},\n year = {2024},\n pages = {1-11},\n volume = {65},\n publisher = {Springer},\n id = {73915d90-1373-3cde-988f-b52e5f945f7b},\n created = {2024-02-20T06:34:04.906Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:04.906Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Kearney, Griffin M and Laurent, Kasey M and Kearney, Reece V},\n journal = {Experiments in Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shan-lou-hong-xiong-jian-kong-particleimagevelocimetrycombiningunsupervisedlearningandopticalflowmodel-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Particle image velocimetry combining unsupervised learning and optical flow model.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shan,  L.; Lou,  X.; Hong,  B.; Xiong,  J.; Jian,  J.;  and Kong,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Optics Communications</i>, 554: 130200.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shan-lou-hong-xiong-jian-kong-particleimagevelocimetrycombiningunsupervisedlearningandopticalflowmodel-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shan-lou-hong-xiong-jian-kong-particleimagevelocimetrycombiningunsupervisedlearningandopticalflowmodel-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Particle image velocimetry combining unsupervised learning and optical flow model},\n type = {article},\n year = {2024},\n pages = {130200},\n volume = {554},\n publisher = {Elsevier},\n id = {a6f11d8e-6a30-3073-a2fb-c134c5bc4ca6},\n created = {2024-02-20T06:34:07.231Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:07.231Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Shan, Liang and Lou, Xiao-Ying and Hong, Bo and Xiong, Jun-Zhe and Jian, Juan and Kong, Ming},\n journal = {Optics Communications}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bouchahda-ayari-majewski-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  STUDY OF CARDIAC FLUID DYNAMICS IN THE RIGHT SIDE OF THE HEART WITH AI PIV.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bouchahda,  N.; Ayari,  R.; Majewski,  W.;  and Wei,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Flow Visualization and Image Processing</i>, 31.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bouchahda-ayari-majewski-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bouchahda-ayari-majewski-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {STUDY OF CARDIAC FLUID DYNAMICS IN THE RIGHT SIDE OF THE HEART WITH AI PIV},\n type = {article},\n year = {2024},\n volume = {31},\n publisher = {Begel House Inc.},\n id = {b837cc4a-0811-3cd6-8e3a-d3d5245a58c7},\n created = {2024-02-20T06:34:15.307Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:15.307Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bouchahda, Nidhal and Ayari, Rim and Majewski, Wojciech and Wei, Runjie},\n journal = {Journal of Flow Visualization and Image Processing}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yao-schnaubelt-szalay-zaki-meneveau-comparinglocalenergycascaderatesinisotropicturbulenceusingstructurefunctionandfilteringformulations-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Comparing local energy cascade rates in isotropic turbulence using structure-function and filtering formulations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yao,  H.; Schnaubelt,  M.; Szalay,  A., S.; Zaki,  T., A.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 980: A42.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yao-schnaubelt-szalay-zaki-meneveau-comparinglocalenergycascaderatesinisotropicturbulenceusingstructurefunctionandfilteringformulations-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yao-schnaubelt-szalay-zaki-meneveau-comparinglocalenergycascaderatesinisotropicturbulenceusingstructurefunctionandfilteringformulations-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Comparing local energy cascade rates in isotropic turbulence using structure-function and filtering formulations},\n type = {article},\n year = {2024},\n pages = {A42},\n volume = {980},\n publisher = {Cambridge University Press},\n id = {fad0f578-2b86-3d0b-a51c-1c68e664c9ef},\n created = {2024-02-20T06:34:16.442Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:16.442Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yao, Hanxun and Schnaubelt, Michael and Szalay, Alexander S and Zaki, Tamer A and Meneveau, Charles},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"encinasbartos-haller-vorticityalignmentwithlyapunovvectorsandrateofstraineigenvectors-2024\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Vorticity alignment with Lyapunov vectors and rate-of-strain eigenvectors.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Encinas-Bartos,  A.;  and Haller,  G.\n</span>\n\n  \n\n</span>\n\n  <i>European Journal of Mechanics-B/Fluids</i>.  2024.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/encinasbartos-haller-vorticityalignmentwithlyapunovvectorsandrateofstraineigenvectors-2024\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('encinasbartos-haller-vorticityalignmentwithlyapunovvectorsandrateofstraineigenvectors-2024')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vorticity alignment with Lyapunov vectors and rate-of-strain eigenvectors},\n type = {article},\n year = {2024},\n publisher = {Elsevier},\n id = {885584e3-16f0-37ae-bd78-4afcf823b7d7},\n created = {2024-02-20T06:34:19.891Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:19.891Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Encinas-Bartos, Alex and Haller, George},\n journal = {European Journal of Mechanics-B/Fluids}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2023\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2023')\"\n      onkeypress=\"toggleGroup('group_2023')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2023</span>\n      <span class=\"bibbase_group_count\">\n        \n        (57)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A sparse optical flow inspired method for 3D velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lu,  G.; Steinberg,  A.;  and Yano,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(4): 66.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A sparse optical flow inspired method for 3D velocimetry},\n type = {article},\n year = {2023},\n pages = {66},\n volume = {64},\n publisher = {Springer},\n id = {46a72009-8827-38df-8d9b-983690056eb6},\n created = {2023-06-10T00:46:32.729Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:32.729Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lu, George and Steinberg, Adam and Yano, Masayuki},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fenelon-zhang-cattafesta-optimizingdtformpstbinparticletrackingvelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Optimizing Dt for MP-STB in Particle Tracking Velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fenelon,  M., R.; Zhang,  Y.;  and Cattafesta,  L., N.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2023 Forum</i>, pages 634,  2023. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fenelon-zhang-cattafesta-optimizingdtformpstbinparticletrackingvelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fenelon-zhang-cattafesta-optimizingdtformpstbinparticletrackingvelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Optimizing Dt for MP-STB in Particle Tracking Velocimetry},\n type = {inproceedings},\n year = {2023},\n pages = {634},\n id = {2a14fbfc-0496-337c-9af3-333323dda479},\n created = {2023-06-10T00:46:33.196Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:33.196Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Fenelon, Michael R and Zhang, Yang and Cattafesta, Louis N},\n booktitle = {AIAA SCITECH 2023 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hu-johnson-meneveau-modelingtheresuspensionofsmallinertialparticlesinturbulentflowoverafractallikemultiscaleroughsurface-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Modeling the resuspension of small inertial particles in turbulent flow over a fractal-like multiscale rough surface.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hu,  R.; Johnson,  P., L.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(2): 24304.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hu-johnson-meneveau-modelingtheresuspensionofsmallinertialparticlesinturbulentflowoverafractallikemultiscaleroughsurface-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hu-johnson-meneveau-modelingtheresuspensionofsmallinertialparticlesinturbulentflowoverafractallikemultiscaleroughsurface-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modeling the resuspension of small inertial particles in turbulent flow over a fractal-like multiscale rough surface},\n type = {article},\n year = {2023},\n pages = {24304},\n volume = {8},\n publisher = {APS},\n id = {ea9bbd0e-99c4-3a20-82ed-47f079572e83},\n created = {2023-06-10T00:46:33.636Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:33.636Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hu, Ruifeng and Johnson, Perry L and Meneveau, Charles},\n journal = {Physical Review Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhou-yang-zhang-yang-awallmodellearnedfromtheperiodichilldataandthelawofthewall-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A wall model learned from the periodic hill data and the law of the wall.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhou,  Z.; Yang,  X., I., A.; Zhang,  F.;  and Yang,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(5).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhou-yang-zhang-yang-awallmodellearnedfromtheperiodichilldataandthelawofthewall-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhou-yang-zhang-yang-awallmodellearnedfromtheperiodichilldataandthelawofthewall-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A wall model learned from the periodic hill data and the law of the wall},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {7870a67d-7d05-342d-b5f0-d32b05e35a69},\n created = {2023-06-10T00:46:34.078Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:34.078Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhou, Zhideng and Yang, Xiang I A and Zhang, Fengshun and Yang, Xiaolei},\n journal = {Physics of Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Assessment of implicit LES modelling for bypass transition of a boundary layer.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Perrin,  R.;  and Lamballais,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Computers & Fluids</i>, 251: 105728.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessment of implicit LES modelling for bypass transition of a boundary layer},\n type = {article},\n year = {2023},\n pages = {105728},\n volume = {251},\n publisher = {Elsevier},\n id = {9e834ad9-d180-32fd-bbb4-9966c5dd4690},\n created = {2023-06-10T00:46:34.513Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:34.513Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Perrin, Rodolphe and Lamballais, Eric},\n journal = {Computers &amp; Fluids}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lawson-ganapathisubramani-mechanismsofmasstransfertosmallspheressinkinginturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Mechanisms of mass transfer to small spheres sinking in turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lawson,  J., M.;  and Ganapathisubramani,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 954: A15.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lawson-ganapathisubramani-mechanismsofmasstransfertosmallspheressinkinginturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lawson-ganapathisubramani-mechanismsofmasstransfertosmallspheressinkinginturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Mechanisms of mass transfer to small spheres sinking in turbulence},\n type = {article},\n year = {2023},\n pages = {A15},\n volume = {954},\n publisher = {Cambridge University Press},\n id = {d2f32a14-4e7b-3a3a-b758-132e8dd2cdcd},\n created = {2023-06-10T00:46:41.636Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:41.636Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lawson, John M and Ganapathisubramani, Bharathram},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"laurie-baggaley-vorticitylockingandpressuredynamicsinfinitetemperaturesuperfluidturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Vorticity locking and pressure dynamics in finite-temperature superfluid turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Laurie,  J.;  and Baggaley,  A., W.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(5): 54604.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/laurie-baggaley-vorticitylockingandpressuredynamicsinfinitetemperaturesuperfluidturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('laurie-baggaley-vorticitylockingandpressuredynamicsinfinitetemperaturesuperfluidturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vorticity locking and pressure dynamics in finite-temperature superfluid turbulence},\n type = {article},\n year = {2023},\n pages = {54604},\n volume = {8},\n publisher = {APS},\n id = {9848644f-7f4a-3f8f-9583-d7e67cc1e326},\n created = {2023-06-10T00:46:42.118Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:42.118Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Laurie, Jason and Baggaley, Andrew W},\n journal = {Physical Review Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zenati-vishniac-conservinglocalmagnetichelicityinnumericalsimulations-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Conserving Local Magnetic Helicity in Numerical Simulations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zenati,  Y.;  and Vishniac,  E., T.\n</span>\n\n  \n\n</span>\n\n  <i>The Astrophysical Journal</i>, 948(1): 11.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zenati-vishniac-conservinglocalmagnetichelicityinnumericalsimulations-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zenati-vishniac-conservinglocalmagnetichelicityinnumericalsimulations-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Conserving Local Magnetic Helicity in Numerical Simulations},\n type = {article},\n year = {2023},\n pages = {11},\n volume = {948},\n publisher = {IOP Publishing},\n id = {eff59491-2b44-3f87-adf0-39f69c4f1424},\n created = {2023-06-10T00:46:42.577Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:42.577Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zenati, Yossef and Vishniac, Ethan T},\n journal = {The Astrophysical Journal},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"matsuzawa-mitchell-perrard-irvine-creationofanisolatedturbulentblobfedbyvortexrings-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Creation of an isolated turbulent blob fed by vortex rings.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Matsuzawa,  T.; Mitchell,  N., P.; Perrard,  S.;  and Irvine,  W., T., M.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Physics</i>,1-8.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/matsuzawa-mitchell-perrard-irvine-creationofanisolatedturbulentblobfedbyvortexrings-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('matsuzawa-mitchell-perrard-irvine-creationofanisolatedturbulentblobfedbyvortexrings-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Creation of an isolated turbulent blob fed by vortex rings},\n type = {article},\n year = {2023},\n pages = {1-8},\n publisher = {Nature Publishing Group UK London},\n id = {67b51284-6010-37da-bc49-898f2c2073b1},\n created = {2023-06-10T00:46:43.017Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:43.017Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Matsuzawa, Takumi and Mitchell, Noah P and Perrard, Stéphane and Irvine, William T M},\n journal = {Nature Physics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hu-dong-vinuesa-generalattachededdiesscalinglawsandcascadeselfsimilarity-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  General attached eddies: Scaling laws and cascade self-similarity.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hu,  R.; Dong,  S.;  and Vinuesa,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(4): 44603.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hu-dong-vinuesa-generalattachededdiesscalinglawsandcascadeselfsimilarity-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hu-dong-vinuesa-generalattachededdiesscalinglawsandcascadeselfsimilarity-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {General attached eddies: Scaling laws and cascade self-similarity},\n type = {article},\n year = {2023},\n pages = {44603},\n volume = {8},\n publisher = {APS},\n id = {cb1c2f0c-b1fd-3f81-bfed-9e48ef338915},\n created = {2023-06-10T00:46:43.474Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:43.474Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hu, Ruifeng and Dong, Siwei and Vinuesa, Ricardo},\n journal = {Physical Review Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhou-li-hong-grauer-stochasticparticleadvectionvelocimetryspavtheorysimulationsandproofofconceptexperiments-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Stochastic particle advection velocimetry (SPAV): theory, simulations, and proof-of-concept experiments.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhou,  K.; Li,  J.; Hong,  J.;  and Grauer,  S., J.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 34(6): 65302.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhou-li-hong-grauer-stochasticparticleadvectionvelocimetryspavtheorysimulationsandproofofconceptexperiments-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhou-li-hong-grauer-stochasticparticleadvectionvelocimetryspavtheorysimulationsandproofofconceptexperiments-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Stochastic particle advection velocimetry (SPAV): theory, simulations, and proof-of-concept experiments},\n type = {article},\n year = {2023},\n pages = {65302},\n volume = {34},\n publisher = {IOP Publishing},\n id = {17652bfa-3e57-39de-82ab-579773e0c0ff},\n created = {2023-06-10T00:46:43.921Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:43.921Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhou, Ke and Li, Jiaqi and Hong, Jiarong and Grauer, Samuel J},\n journal = {Measurement Science and Technology},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pradhan-duraisamy-aunifiedunderstandingofscaleresolvingsimulationsandnearwallmodellingofturbulentflowsusingoptimalfiniteelementprojections-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A unified understanding of scale-resolving simulations and near-wall modelling of turbulent flows using optimal finite-element projections.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pradhan,  A.;  and Duraisamy,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 955: A6.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pradhan-duraisamy-aunifiedunderstandingofscaleresolvingsimulationsandnearwallmodellingofturbulentflowsusingoptimalfiniteelementprojections-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pradhan-duraisamy-aunifiedunderstandingofscaleresolvingsimulationsandnearwallmodellingofturbulentflowsusingoptimalfiniteelementprojections-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A unified understanding of scale-resolving simulations and near-wall modelling of turbulent flows using optimal finite-element projections},\n type = {article},\n year = {2023},\n pages = {A6},\n volume = {955},\n publisher = {Cambridge University Press},\n id = {f03c6267-43e6-3178-8ad6-cad6887d197f},\n created = {2023-06-10T00:46:44.388Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:44.388Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Pradhan, Aniruddhe and Duraisamy, Karthik},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep-learning-based image preprocessing for particle image velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fan,  Y.; Guo,  C.; Han,  Y.; Qiao,  W.; Xu,  P.;  and Kuai,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Applied Ocean Research</i>, 130: 103406.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep-learning-based image preprocessing for particle image velocimetry},\n type = {article},\n year = {2023},\n pages = {103406},\n volume = {130},\n publisher = {Elsevier},\n id = {16f768bc-f1cf-3e8a-b940-42d944642588},\n created = {2023-06-10T00:46:44.849Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:44.849Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fan, Yiwei and Guo, Chunyu and Han, Yang and Qiao, Weizheng and Xu, Peng and Kuai, Yunfei},\n journal = {Applied Ocean Research}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tirelli-ianiro-discetti-anendtoendknnbasedptvapproachforhighresolutionmeasurementsanduncertaintyquantification-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tirelli,  I.; Ianiro,  A.;  and Discetti,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 140: 110756.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tirelli-ianiro-discetti-anendtoendknnbasedptvapproachforhighresolutionmeasurementsanduncertaintyquantification-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tirelli-ianiro-discetti-anendtoendknnbasedptvapproachforhighresolutionmeasurementsanduncertaintyquantification-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification},\n type = {article},\n year = {2023},\n pages = {110756},\n volume = {140},\n publisher = {Elsevier},\n id = {adc49db6-5b0c-3bd1-b599-22120de4759a},\n created = {2023-06-10T00:46:45.308Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:45.308Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Tirelli, Iacopo and Ianiro, Andrea and Discetti, Stefano},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jassal-schmidt-accuratenearwallmeasurementsinwallboundedflowswithwofvviaanexplicitnoslipboundarycondition-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Accurate Near Wall Measurements in Wall Bounded Flows with wOFV via an Explicit No-Slip Boundary Condition.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jassal,  G., R.;  and Schmidt,  B., E.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2023 Forum</i>, pages 2444,  2023. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jassal-schmidt-accuratenearwallmeasurementsinwallboundedflowswithwofvviaanexplicitnoslipboundarycondition-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jassal-schmidt-accuratenearwallmeasurementsinwallboundedflowswithwofvviaanexplicitnoslipboundarycondition-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Accurate Near Wall Measurements in Wall Bounded Flows with wOFV via an Explicit No-Slip Boundary Condition},\n type = {inproceedings},\n year = {2023},\n pages = {2444},\n id = {735d4e72-3909-301a-8bbf-5f732546ab62},\n created = {2023-06-10T00:46:45.757Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:45.757Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Jassal, Gauresh R and Schmidt, Bryan E},\n booktitle = {AIAA SCITECH 2023 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"torres-dahm-rationalbooleanstabilizationofsubgridmodelsforlargeeddysimulation-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Rational Boolean Stabilization of Subgrid Models for Large Eddy Simulation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Torres,  E., E.;  and Dahm,  W., J.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2023 Forum</i>, pages 2485,  2023. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/torres-dahm-rationalbooleanstabilizationofsubgridmodelsforlargeeddysimulation-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('torres-dahm-rationalbooleanstabilizationofsubgridmodelsforlargeeddysimulation-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Rational Boolean Stabilization of Subgrid Models for Large Eddy Simulation},\n type = {inproceedings},\n year = {2023},\n pages = {2485},\n id = {14120141-02c9-3137-94e7-6e513a92d6e5},\n created = {2023-06-10T00:46:46.208Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:46.208Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Torres, Emilio E and Dahm, Werner J},\n booktitle = {AIAA SCITECH 2023 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tan-zhong-ni-3dlagrangiantrackingofpolydispersedbubblesathighimagedensities-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  3D Lagrangian tracking of polydispersed bubbles at high image densities.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tan,  S.; Zhong,  S.;  and Ni,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(4): 85.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tan-zhong-ni-3dlagrangiantrackingofpolydispersedbubblesathighimagedensities-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tan-zhong-ni-3dlagrangiantrackingofpolydispersedbubblesathighimagedensities-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {3D Lagrangian tracking of polydispersed bubbles at high image densities},\n type = {article},\n year = {2023},\n pages = {85},\n volume = {64},\n publisher = {Springer},\n id = {2b14cdb9-f501-3a71-91ff-f8e2566c4863},\n created = {2023-06-10T00:46:46.662Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:46.662Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Tan, Shiyong and Zhong, Shijie and Ni, Rui},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tirelli-ianiro-discetti-asimpletricktoimprovetheaccuracyofpivptvdata-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A simple trick to improve the accuracy of PIV/PTV data.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tirelli,  I.; Ianiro,  A.;  and Discetti,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 145: 110872.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tirelli-ianiro-discetti-asimpletricktoimprovetheaccuracyofpivptvdata-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tirelli-ianiro-discetti-asimpletricktoimprovetheaccuracyofpivptvdata-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A simple trick to improve the accuracy of PIV/PTV data},\n type = {article},\n year = {2023},\n pages = {110872},\n volume = {145},\n publisher = {Elsevier},\n id = {cc81f93a-2aef-3a57-bdcc-51f26a081345},\n created = {2023-06-10T00:46:47.116Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:47.116Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Tirelli, Iacopo and Ianiro, Andrea and Discetti, Stefano},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ding-li-chen-ji-yu-ye-fullvolume3dfluidflowreconstructionwithlightfieldpiv-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Full-Volume 3D Fluid Flow Reconstruction With Light Field PIV.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ding,  Y.; Li,  Z.; Chen,  Z.; Ji,  Y.; Yu,  J.;  and Ye,  J.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ding-li-chen-ji-yu-ye-fullvolume3dfluidflowreconstructionwithlightfieldpiv-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ding-li-chen-ji-yu-ye-fullvolume3dfluidflowreconstructionwithlightfieldpiv-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Full-Volume 3D Fluid Flow Reconstruction With Light Field PIV},\n type = {article},\n year = {2023},\n publisher = {IEEE},\n id = {bfa8fa43-a11c-3e44-bf8e-518e22cc6fc7},\n created = {2023-06-10T00:46:47.580Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:47.580Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ding, Yuqi and Li, Zhong and Chen, Zhang and Ji, Yu and Yu, Jingyi and Ye, Jinwei},\n journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lin-zhang-jin-guan-ma-cui-yang-threedimensionalparticletrackingalgorithmbasedonthespecialellipsoids-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Three-dimensional particle tracking algorithm based on the special ellipsoids.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lin,  Y.; Zhang,  Y.; Jin,  Y.; Guan,  K.; Ma,  Q.; Cui,  Y.;  and Yang,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement</i>, 216: 112883.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lin-zhang-jin-guan-ma-cui-yang-threedimensionalparticletrackingalgorithmbasedonthespecialellipsoids-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lin-zhang-jin-guan-ma-cui-yang-threedimensionalparticletrackingalgorithmbasedonthespecialellipsoids-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Three-dimensional particle tracking algorithm based on the special ellipsoids},\n type = {article},\n year = {2023},\n pages = {112883},\n volume = {216},\n publisher = {Elsevier},\n id = {b65ebbeb-c6c5-3fbc-b24c-740be8a91d28},\n created = {2023-06-10T00:46:48.020Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:48.020Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lin, Yuanwei and Zhang, Yang and Jin, Yuqi and Guan, Kaiyuan and Ma, Qimin and Cui, Yutong and Yang, Bin},\n journal = {Measurement}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"qi-meneveau-voth-ni-foldingdynamicsanditsintermittencyinturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Folding dynamics and its intermittency in turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Qi,  Y.; Meneveau,  C.; Voth,  G., A.;  and Ni,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 130(15): 154001.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/qi-meneveau-voth-ni-foldingdynamicsanditsintermittencyinturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('qi-meneveau-voth-ni-foldingdynamicsanditsintermittencyinturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Folding dynamics and its intermittency in turbulence},\n type = {article},\n year = {2023},\n pages = {154001},\n volume = {130},\n publisher = {APS},\n id = {c8525eb1-e225-3c9c-824d-6264df066626},\n created = {2023-06-10T00:46:48.456Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:48.456Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Qi, Yinghe and Meneveau, Charles and Voth, Greg A and Ni, Rui},\n journal = {Physical Review Letters},\n number = {15}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nicolas-zentgraf-linne-dreizler-peterson-assessmentandapplicationofwaveletbasedopticalflowvelocimetrywofvtowallboundedturbulentflows-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Assessment and application of wavelet-based optical flow velocimetry (wOFV) to wall-bounded turbulent flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nicolas,  A.; Zentgraf,  F.; Linne,  M.; Dreizler,  A.;  and Peterson,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in fluids</i>, 64(3): 50.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nicolas-zentgraf-linne-dreizler-peterson-assessmentandapplicationofwaveletbasedopticalflowvelocimetrywofvtowallboundedturbulentflows-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nicolas-zentgraf-linne-dreizler-peterson-assessmentandapplicationofwaveletbasedopticalflowvelocimetrywofvtowallboundedturbulentflows-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessment and application of wavelet-based optical flow velocimetry (wOFV) to wall-bounded turbulent flows},\n type = {article},\n year = {2023},\n pages = {50},\n volume = {64},\n publisher = {Springer},\n id = {57072bf5-8344-303b-81c2-0a64dd56e2e8},\n created = {2023-06-10T00:46:48.986Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:48.986Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Nicolas, Alexander and Zentgraf, Florian and Linne, Mark and Dreizler, Andreas and Peterson, Brian},\n journal = {Experiments in fluids},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yang-yang-yin-superresolutionreconstructionforthethreedimensionalturbulenceflowswithabackprojectionnetwork-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Super-resolution reconstruction for the three-dimensional turbulence flows with a back-projection network.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yang,  Z.; Yang,  H.;  and Yin,  Z.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(5).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yang-yang-yin-superresolutionreconstructionforthethreedimensionalturbulenceflowswithabackprojectionnetwork-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yang-yang-yin-superresolutionreconstructionforthethreedimensionalturbulenceflowswithabackprojectionnetwork-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Super-resolution reconstruction for the three-dimensional turbulence flows with a back-projection network},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {1a8fc7dd-05d7-37f2-b223-0960e737903b},\n created = {2023-06-10T00:46:49.474Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:49.474Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yang, Zhen and Yang, Hua and Yin, Zhouping},\n journal = {Physics of Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prakash-jansen-evans-extensionofthesmagorinskysubgridstressmodeltoanisotropicfilters-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Extension of the Smagorinsky Subgrid Stress Model to Anisotropic Filters.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Prakash,  A.; Jansen,  K., E.;  and Evans,  J., A.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2023 Forum</i>, pages 2486,  2023. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prakash-jansen-evans-extensionofthesmagorinskysubgridstressmodeltoanisotropicfilters-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prakash-jansen-evans-extensionofthesmagorinskysubgridstressmodeltoanisotropicfilters-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Extension of the Smagorinsky Subgrid Stress Model to Anisotropic Filters},\n type = {inproceedings},\n year = {2023},\n pages = {2486},\n id = {2abf00ef-6b31-3446-bd69-7223d497ed14},\n created = {2023-06-10T00:46:49.933Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:49.933Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Prakash, Aviral and Jansen, Kenneth E and Evans, John A},\n booktitle = {AIAA SCITECH 2023 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-ponce-brunton-kutz-multiresolutionconvolutionalautoencoders-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Multiresolution convolutional autoencoders.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  Y.; Ponce,  C.; Brunton,  S., L.;  and Kutz,  J., N.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Computational Physics</i>, 474: 111801.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-ponce-brunton-kutz-multiresolutionconvolutionalautoencoders-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-ponce-brunton-kutz-multiresolutionconvolutionalautoencoders-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multiresolution convolutional autoencoders},\n type = {article},\n year = {2023},\n pages = {111801},\n volume = {474},\n publisher = {Elsevier},\n id = {301e079d-45ea-37a7-a948-ec88ff6dcc5f},\n created = {2023-06-10T00:46:50.390Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:50.390Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Liu, Yuying and Ponce, Colin and Brunton, Steven L and Kutz, J Nathan},\n journal = {Journal of Computational Physics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aksamit-mappingtheshapeanddimensionofthreedimensionallagrangiancoherentstructuresandinvariantmanifolds-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Mapping the shape and dimension of three-dimensional Lagrangian coherent structures and invariant manifolds.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aksamit,  N., O.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 958: A11.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aksamit-mappingtheshapeanddimensionofthreedimensionallagrangiancoherentstructuresandinvariantmanifolds-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aksamit-mappingtheshapeanddimensionofthreedimensionallagrangiancoherentstructuresandinvariantmanifolds-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Mapping the shape and dimension of three-dimensional Lagrangian coherent structures and invariant manifolds},\n type = {article},\n year = {2023},\n pages = {A11},\n volume = {958},\n publisher = {Cambridge University Press},\n id = {3dc67900-1b1f-35cd-83b0-3d549f65e3da},\n created = {2023-06-10T00:46:50.889Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:50.889Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Aksamit, Nikolas Olson},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-bi-fan-deeplearningforfluidvelocityfieldestimationareview-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep learning for fluid velocity field estimation: A review.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Bi,  X.;  and Fan,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Ocean Engineering</i>, 271: 113693.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-bi-fan-deeplearningforfluidvelocityfieldestimationareview-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-bi-fan-deeplearningforfluidvelocityfieldestimationareview-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep learning for fluid velocity field estimation: A review},\n type = {article},\n year = {2023},\n pages = {113693},\n volume = {271},\n publisher = {Elsevier},\n id = {9bb2a2ff-29ac-3099-8be5-b5c20f149c19},\n created = {2023-06-10T00:46:51.351Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:51.351Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yu, Changdong and Bi, Xiaojun and Fan, Yiwei},\n journal = {Ocean Engineering}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liang-xu-cai-recurrentgraphoptimaltransportforlearning3dflowmotioninparticletracking-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Recurrent graph optimal transport for learning 3D flow motion in particle tracking.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liang,  J.; Xu,  C.;  and Cai,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Machine Intelligence</i>,1-13.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liang-xu-cai-recurrentgraphoptimaltransportforlearning3dflowmotioninparticletracking-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liang-xu-cai-recurrentgraphoptimaltransportforlearning3dflowmotioninparticletracking-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Recurrent graph optimal transport for learning 3D flow motion in particle tracking},\n type = {article},\n year = {2023},\n pages = {1-13},\n publisher = {Nature Publishing Group UK London},\n id = {611e02d9-cb53-30d1-9c21-8fb09362f12a},\n created = {2023-06-10T00:46:51.834Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:51.834Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Liang, Jiaming and Xu, Chao and Cai, Shengze},\n journal = {Nature Machine Intelligence}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"duan-liu-yin-onlinemeasurementofgranularvelocityofrotarydrumsbyafastpivdeepnetworkfpnflownet-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Online measurement of granular velocity of rotary drums by a fast PIV deep network FPN-FlowNet.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Duan,  J.; Liu,  X.;  and Yin,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement</i>, 209: 112529.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/duan-liu-yin-onlinemeasurementofgranularvelocityofrotarydrumsbyafastpivdeepnetworkfpnflownet-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('duan-liu-yin-onlinemeasurementofgranularvelocityofrotarydrumsbyafastpivdeepnetworkfpnflownet-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Online measurement of granular velocity of rotary drums by a fast PIV deep network FPN-FlowNet},\n type = {article},\n year = {2023},\n pages = {112529},\n volume = {209},\n publisher = {Elsevier},\n id = {120cf393-f1be-3ac8-9b04-a026d114d1f8},\n created = {2023-06-10T00:46:52.294Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:52.294Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Duan, Jiaxu and Liu, Xiaoyan and Yin, Yufeng},\n journal = {Measurement}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yousif-zhang-yu-vinuesa-lim-atransformerbasedsyntheticinflowgeneratorforspatiallydevelopingturbulentboundarylayers-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A transformer-based synthetic-inflow generator for spatially developing turbulent boundary layers.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yousif,  M., Z.; Zhang,  M.; Yu,  L.; Vinuesa,  R.;  and Lim,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 957: A6.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yousif-zhang-yu-vinuesa-lim-atransformerbasedsyntheticinflowgeneratorforspatiallydevelopingturbulentboundarylayers-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yousif-zhang-yu-vinuesa-lim-atransformerbasedsyntheticinflowgeneratorforspatiallydevelopingturbulentboundarylayers-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A transformer-based synthetic-inflow generator for spatially developing turbulent boundary layers},\n type = {article},\n year = {2023},\n pages = {A6},\n volume = {957},\n publisher = {Cambridge University Press},\n id = {597515a7-cde2-3c59-9439-4d1d95114272},\n created = {2023-06-10T00:46:52.755Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:52.755Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yousif, Mustafa Z and Zhang, Meng and Yu, Linqi and Vinuesa, Ricardo and Lim, HeeChang},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhou-yang-homogeneityconstraintsonthemixedmomentsofvelocitygradientandpressurehessianinincompressibleturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Homogeneity constraints on the mixed moments of velocity gradient and pressure Hessian in incompressible turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhou,  Z.;  and Yang,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(2): 24601.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhou-yang-homogeneityconstraintsonthemixedmomentsofvelocitygradientandpressurehessianinincompressibleturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhou-yang-homogeneityconstraintsonthemixedmomentsofvelocitygradientandpressurehessianinincompressibleturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Homogeneity constraints on the mixed moments of velocity gradient and pressure Hessian in incompressible turbulence},\n type = {article},\n year = {2023},\n pages = {24601},\n volume = {8},\n publisher = {APS},\n id = {6c9f1024-eafa-3fe6-8a1d-63e8fa13f059},\n created = {2023-06-10T00:46:53.197Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:53.197Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhou, Zhideng and Yang, Ping-Fan},\n journal = {Physical Review Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"you-wang-liu-pressurereconstructionfromthemeasuredpressuregradientusinggaussianprocessregression-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Pressure Reconstruction from the Measured Pressure Gradient Using Gaussian Process Regression.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  You,  Z.; Wang,  Q.;  and Liu,  X.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2023 Forum</i>, pages 414,  2023. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/you-wang-liu-pressurereconstructionfromthemeasuredpressuregradientusinggaussianprocessregression-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('you-wang-liu-pressurereconstructionfromthemeasuredpressuregradientusinggaussianprocessregression-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Pressure Reconstruction from the Measured Pressure Gradient Using Gaussian Process Regression},\n type = {inproceedings},\n year = {2023},\n pages = {414},\n id = {a18e0952-eb5d-3576-981e-dbf21286c5c0},\n created = {2023-06-10T00:46:53.662Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:53.662Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {You, Zejian and Wang, Qi and Liu, Xiaofeng},\n booktitle = {AIAA SCITECH 2023 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"clarkdileoni-agarwal-zaki-meneveau-katz-reconstructingturbulentvelocityandpressurefieldsfromunderresolvednoisyparticletracksusingphysicsinformedneuralnetworks-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Clark Di Leoni,  P.; Agarwal,  K.; Zaki,  T., A.; Meneveau,  C.;  and Katz,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(5): 95.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/clarkdileoni-agarwal-zaki-meneveau-katz-reconstructingturbulentvelocityandpressurefieldsfromunderresolvednoisyparticletracksusingphysicsinformedneuralnetworks-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('clarkdileoni-agarwal-zaki-meneveau-katz-reconstructingturbulentvelocityandpressurefieldsfromunderresolvednoisyparticletracksusingphysicsinformedneuralnetworks-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks},\n type = {article},\n year = {2023},\n pages = {95},\n volume = {64},\n publisher = {Springer},\n id = {9291fe32-5936-3f21-94cb-15258cd0415d},\n created = {2023-06-10T00:46:54.118Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T00:46:54.118Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Clark Di Leoni, Patricio and Agarwal, Karuna and Zaki, Tamer A and Meneveau, Charles and Katz, Joseph},\n journal = {Experiments in Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"benkovic-krawczynski-druault-opticalflowforparticleimageswithoptimizationbasedonaprioriknowledgeoftheflow-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Optical flow for particle images with optimization based on a priori knowledge of the flow.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Benkovic,  T.; Krawczynski,  J.;  and Druault,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/benkovic-krawczynski-druault-opticalflowforparticleimageswithoptimizationbasedonaprioriknowledgeoftheflow-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('benkovic-krawczynski-druault-opticalflowforparticleimageswithoptimizationbasedonaprioriknowledgeoftheflow-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Optical flow for particle images with optimization based on a priori knowledge of the flow},\n type = {article},\n year = {2023},\n id = {4395a323-ed0a-3e4b-976b-6df9a117870f},\n created = {2024-02-20T06:33:48.604Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:48.604Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Benkovic, Théo and Krawczynski, Jean-Francois and Druault, Philippe},\n journal = {Measurement Science and Technology}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A sparse optical flow inspired method for 3D velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lu,  G.; Steinberg,  A.;  and Yano,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(4): 66.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lu-steinberg-yano-asparseopticalflowinspiredmethodfor3dvelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A sparse optical flow inspired method for 3D velocimetry},\n type = {article},\n year = {2023},\n pages = {66},\n volume = {64},\n publisher = {Springer},\n id = {b88b42db-9bab-3806-8016-3e89dbd75496},\n created = {2024-02-20T06:33:49.757Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:49.757Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lu, George and Steinberg, Adam and Yano, Masayuki},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pan-brunton-kutz-neuralimplicitflowameshagnosticdimensionalityreductionparadigmofspatiotemporaldata-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pan,  S.; Brunton,  S., L.;  and Kutz,  J., N.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Machine Learning Research</i>, 24(41): 1-60.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pan-brunton-kutz-neuralimplicitflowameshagnosticdimensionalityreductionparadigmofspatiotemporaldata-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pan-brunton-kutz-neuralimplicitflowameshagnosticdimensionalityreductionparadigmofspatiotemporaldata-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data},\n type = {article},\n year = {2023},\n pages = {1-60},\n volume = {24},\n id = {c74e37ab-2290-310a-a62d-96fa6a148d28},\n created = {2024-02-20T06:33:50.940Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:50.940Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Pan, Shaowu and Brunton, Steven L and Kutz, J Nathan},\n journal = {Journal of Machine Learning Research},\n number = {41}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fan-xu-wang-wang-comparativeassessmentforpressurefieldreconstructionbasedonphysicsinformedneuralnetwork-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Comparative assessment for pressure field reconstruction based on physics-informed neural network.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fan,  D.; Xu,  Y.; Wang,  H.;  and Wang,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(7).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fan-xu-wang-wang-comparativeassessmentforpressurefieldreconstructionbasedonphysicsinformedneuralnetwork-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fan-xu-wang-wang-comparativeassessmentforpressurefieldreconstructionbasedonphysicsinformedneuralnetwork-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Comparative assessment for pressure field reconstruction based on physics-informed neural network},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {f0a4e5be-4efb-3204-8b7b-63a420921002},\n created = {2024-02-20T06:33:52.095Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:52.095Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fan, Di and Xu, Yang and Wang, Hongping and Wang, Jinjun},\n journal = {Physics of Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"barois-viggiano-basset-cal-volk-gibert-bourgoin-compensationofseedingbiasforparticletrackingvelocimetryinturbulentflows-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Compensation of seeding bias for particle tracking velocimetry in turbulent flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Barois,  T.; Viggiano,  B.; Basset,  T.; Cal,  R., B.; Volk,  R.; Gibert,  M.;  and Bourgoin,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(7): 74603.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/barois-viggiano-basset-cal-volk-gibert-bourgoin-compensationofseedingbiasforparticletrackingvelocimetryinturbulentflows-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('barois-viggiano-basset-cal-volk-gibert-bourgoin-compensationofseedingbiasforparticletrackingvelocimetryinturbulentflows-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Compensation of seeding bias for particle tracking velocimetry in turbulent flows},\n type = {article},\n year = {2023},\n pages = {74603},\n volume = {8},\n publisher = {APS},\n id = {78ef183d-ad4f-38dc-8310-4b1c7a087cb0},\n created = {2024-02-20T06:33:53.248Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:53.248Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Barois, Thomas and Viggiano, Bianca and Basset, Thomas and Cal, Raúl Bayoán and Volk, Romain and Gibert, Mathieu and Bourgoin, Mickaël},\n journal = {Physical Review Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lin-xu-divergencecurlcorrectionforpressurefieldreconstructionfromaccelerationinturbulentflows-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Divergence–curl correction for pressure field reconstruction from acceleration in turbulent flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lin,  Y.;  and Xu,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(8): 137.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lin-xu-divergencecurlcorrectionforpressurefieldreconstructionfromaccelerationinturbulentflows-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lin-xu-divergencecurlcorrectionforpressurefieldreconstructionfromaccelerationinturbulentflows-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Divergence–curl correction for pressure field reconstruction from acceleration in turbulent flows},\n type = {article},\n year = {2023},\n pages = {137},\n volume = {64},\n publisher = {Springer},\n id = {b1eabdd3-07b4-3a36-a34e-f8b181a36359},\n created = {2024-02-20T06:33:54.425Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:54.425Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lin, Yuhe and Xu, Haitao},\n journal = {Experiments in Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Assessment of implicit LES modelling for bypass transition of a boundary layer.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Perrin,  R.;  and Lamballais,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Computers & Fluids</i>, 251: 105728.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('perrin-lamballais-assessmentofimplicitlesmodellingforbypasstransitionofaboundarylayer-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessment of implicit LES modelling for bypass transition of a boundary layer},\n type = {article},\n year = {2023},\n pages = {105728},\n volume = {251},\n publisher = {Elsevier},\n id = {8f6311e0-bba1-37b5-bb66-9f6bb9fb4268},\n created = {2024-02-20T06:33:55.584Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:55.584Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Perrin, Rodolphe and Lamballais, Eric},\n journal = {Computers &amp; Fluids}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"iacobello-rival-identifyingdominantflowfeaturesfromverysparselagrangiandataamultiscalerecurrencenetworkbasedapproach-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Identifying dominant flow features from very-sparse Lagrangian data: a multiscale recurrence network-based approach.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Iacobello,  G.;  and Rival,  D., E.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in fluids</i>, 64(10): 157.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/iacobello-rival-identifyingdominantflowfeaturesfromverysparselagrangiandataamultiscalerecurrencenetworkbasedapproach-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('iacobello-rival-identifyingdominantflowfeaturesfromverysparselagrangiandataamultiscalerecurrencenetworkbasedapproach-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Identifying dominant flow features from very-sparse Lagrangian data: a multiscale recurrence network-based approach},\n type = {article},\n year = {2023},\n pages = {157},\n volume = {64},\n publisher = {Springer},\n id = {db0672a8-9abe-3762-b742-fe225a82253a},\n created = {2024-02-20T06:33:56.731Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:56.731Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Iacobello, Giovanni and Rival, David E},\n journal = {Experiments in fluids},\n number = {10}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep-learning-based image preprocessing for particle image velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fan,  Y.; Guo,  C.; Han,  Y.; Qiao,  W.; Xu,  P.;  and Kuai,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Applied Ocean Research</i>, 130: 103406.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fan-guo-han-qiao-xu-kuai-deeplearningbasedimagepreprocessingforparticleimagevelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep-learning-based image preprocessing for particle image velocimetry},\n type = {article},\n year = {2023},\n pages = {103406},\n volume = {130},\n publisher = {Elsevier},\n id = {8fb9171a-a1fb-3886-a811-7a795aa0270f},\n created = {2024-02-20T06:33:57.962Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:57.962Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fan, Yiwei and Guo, Chunyu and Han, Yang and Qiao, Weizheng and Xu, Peng and Kuai, Yunfei},\n journal = {Applied Ocean Research}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aligolzadeh-holzner-dawson-entrainmentdetrainmentandenstrophytransportbysmallscalevortexstructures-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Entrainment, detrainment and enstrophy transport by small-scale vortex structures.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aligolzadeh,  F.; Holzner,  M.;  and Dawson,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 973: A5.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aligolzadeh-holzner-dawson-entrainmentdetrainmentandenstrophytransportbysmallscalevortexstructures-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aligolzadeh-holzner-dawson-entrainmentdetrainmentandenstrophytransportbysmallscalevortexstructures-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Entrainment, detrainment and enstrophy transport by small-scale vortex structures},\n type = {article},\n year = {2023},\n pages = {A5},\n volume = {973},\n publisher = {Cambridge University Press},\n id = {32b7d00c-acd2-3b75-a9f2-0ae3b09dc379},\n created = {2024-02-20T06:33:59.113Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:33:59.113Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Aligolzadeh, Farid and Holzner, Markus and Dawson, James R},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shirinzad-jaber-xu-sullivan-anenhancedpythonbasedopensourceparticleimagevelocimetrysoftwareforusewithcentralprocessingunits-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shirinzad,  A.; Jaber,  K.; Xu,  K.;  and Sullivan,  P., E.\n</span>\n\n  \n\n</span>\n\n  <i>Fluids</i>, 8(11): 285.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shirinzad-jaber-xu-sullivan-anenhancedpythonbasedopensourceparticleimagevelocimetrysoftwareforusewithcentralprocessingunits-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shirinzad-jaber-xu-sullivan-anenhancedpythonbasedopensourceparticleimagevelocimetrysoftwareforusewithcentralprocessingunits-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An Enhanced Python-Based Open-Source Particle Image Velocimetry Software for Use with Central Processing Units},\n type = {article},\n year = {2023},\n pages = {285},\n volume = {8},\n publisher = {MDPI},\n id = {6dac77e8-ae07-3c79-a237-817903ad5f38},\n created = {2024-02-20T06:34:02.585Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:02.585Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Shirinzad, Ali and Jaber, Khodr and Xu, Kecheng and Sullivan, Pierre E},\n journal = {Fluids},\n number = {11}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-fan-bi-kuai-chang-deepdualrecurrenceopticalflowlearningfortimeresolvedparticleimagevelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep dual recurrence optical flow learning for time-resolved particle image velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Fan,  Y.; Bi,  X.; Kuai,  Y.;  and Chang,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(4).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-fan-bi-kuai-chang-deepdualrecurrenceopticalflowlearningfortimeresolvedparticleimagevelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-fan-bi-kuai-chang-deepdualrecurrenceopticalflowlearningfortimeresolvedparticleimagevelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep dual recurrence optical flow learning for time-resolved particle image velocimetry},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {d986bc72-b7e1-3a10-a7b4-5d41494e0551},\n created = {2024-02-20T06:34:03.745Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:03.745Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yu, Changdong and Fan, Yiwei and Bi, Xiaojun and Kuai, Yunfei and Chang, Yongpeng},\n journal = {Physics of Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bahamonde-cornejo-seplveda-laminartoturbulenttransitionintermsofinformationtheory-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Laminar to turbulent transition in terms of information theory.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bahamonde,  A., D.; Cornejo,  P.;  and Sepúlveda,  H., H.\n</span>\n\n  \n\n</span>\n\n  <i>Physica A: Statistical Mechanics and its Applications</i>, 629: 129190.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bahamonde-cornejo-seplveda-laminartoturbulenttransitionintermsofinformationtheory-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bahamonde-cornejo-seplveda-laminartoturbulenttransitionintermsofinformationtheory-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Laminar to turbulent transition in terms of information theory},\n type = {article},\n year = {2023},\n pages = {129190},\n volume = {629},\n publisher = {Elsevier},\n id = {ec2e67ef-306f-3929-afe6-d07f2bd8cd7a},\n created = {2024-02-20T06:34:06.073Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:06.073Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bahamonde, Adolfo D and Cornejo, Pablo and Sepúlveda, Héctor H},\n journal = {Physica A: Statistical Mechanics and its Applications}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-dong-sun-xu-anunsuperviseddeeplearningmodelfordensevelocityfieldreconstructioninparticleimagevelocimetrypivmeasurements-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  An unsupervised deep learning model for dense velocity field reconstruction in particle image velocimetry (PIV) measurements.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  W.; Dong,  X.; Sun,  Z.;  and Xu,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(7).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-dong-sun-xu-anunsuperviseddeeplearningmodelfordensevelocityfieldreconstructioninparticleimagevelocimetrypivmeasurements-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-dong-sun-xu-anunsuperviseddeeplearningmodelfordensevelocityfieldreconstructioninparticleimagevelocimetrypivmeasurements-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An unsupervised deep learning model for dense velocity field reconstruction in particle image velocimetry (PIV) measurements},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {199b8794-ab35-3790-8639-806d175beb94},\n created = {2024-02-20T06:34:08.375Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:08.375Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhang, Wei and Dong, Xue and Sun, Zhiwei and Xu, Shuogui},\n journal = {Physics of Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kang-yang-yin-gao-liu-avelocitydecompositionbased3dopticalflowmethodforaccuratetomopivmeasurement-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A velocity decomposition-based 3D optical flow method for accurate Tomo-PIV measurement.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kang,  M.; Yang,  H.; Yin,  Z.; Gao,  Q.;  and Liu,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 64(7): 135.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kang-yang-yin-gao-liu-avelocitydecompositionbased3dopticalflowmethodforaccuratetomopivmeasurement-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kang-yang-yin-gao-liu-avelocitydecompositionbased3dopticalflowmethodforaccuratetomopivmeasurement-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A velocity decomposition-based 3D optical flow method for accurate Tomo-PIV measurement},\n type = {article},\n year = {2023},\n pages = {135},\n volume = {64},\n publisher = {Springer},\n id = {17b28c81-7056-32f3-b791-b4f20cfefea3},\n created = {2024-02-20T06:34:09.528Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:09.528Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Kang, Menggang and Yang, Hua and Yin, Zhouping and Gao, Qi and Liu, Xiaoyu},\n journal = {Experiments in Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grenga,  T.; Nista,  L.; Schumann,  C.; Karimi,  A., N.; Scialabba,  G.; Attili,  A.;  and Pitsch,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Combustion Science and Technology</i>, 195(15): 3923-3946.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes},\n type = {article},\n year = {2023},\n pages = {3923-3946},\n volume = {195},\n publisher = {Taylor &amp; Francis},\n id = {4ff412db-a039-33f9-b4bb-b4b9fc929a7e},\n created = {2024-02-20T06:34:10.688Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:10.688Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Grenga, Temistocle and Nista, Ludovico and Schumann, Christoph and Karimi, Amir Noughabi and Scialabba, Gandolfo and Attili, Antonio and Pitsch, Heinz},\n journal = {Combustion Science and Technology},\n number = {15}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schwab-rehmann-estimatingturbulentkineticenergywithanacousticdopplercurrentprofiler-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Estimating turbulent kinetic energy with an acoustic Doppler current profiler.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schwab,  L., E.;  and Rehmann,  C., R.\n</span>\n\n  \n\n</span>\n\n  <i>Flow Measurement and Instrumentation</i>, 94: 102435.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schwab-rehmann-estimatingturbulentkineticenergywithanacousticdopplercurrentprofiler-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schwab-rehmann-estimatingturbulentkineticenergywithanacousticdopplercurrentprofiler-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Estimating turbulent kinetic energy with an acoustic Doppler current profiler},\n type = {article},\n year = {2023},\n pages = {102435},\n volume = {94},\n publisher = {Elsevier},\n id = {b07d7b4e-b97a-33f9-aa19-79f942fbdc23},\n created = {2024-02-20T06:34:11.854Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:11.854Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Schwab, Lauren E and Rehmann, Chris R},\n journal = {Flow Measurement and Instrumentation}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yang-bodenschatz-he-pumir-xu-dynamicsoftheperceivedvelocitygradienttensoranditsmodelling-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Dynamics of the perceived velocity gradient tensor and its modelling.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yang,  P.; Bodenschatz,  E.; He,  G., W.; Pumir,  A.;  and Xu,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 8(9): 94604.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yang-bodenschatz-he-pumir-xu-dynamicsoftheperceivedvelocitygradienttensoranditsmodelling-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yang-bodenschatz-he-pumir-xu-dynamicsoftheperceivedvelocitygradienttensoranditsmodelling-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dynamics of the perceived velocity gradient tensor and its modelling},\n type = {article},\n year = {2023},\n pages = {94604},\n volume = {8},\n publisher = {APS},\n id = {49314ba8-614a-3137-be28-c020f98b72e9},\n created = {2024-02-20T06:34:13.006Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:13.006Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yang, Ping-Fan and Bodenschatz, Eberhard and He, Guo Wei and Pumir, Alain and Xu, Haitao},\n journal = {Physical Review Fluids},\n number = {9}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-yousif-yu-lim-aswintransformerbasedmodelforefficientcompressionofturbulentflowdata-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A Swin-transformer-based model for efficient compression of turbulent flow data.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  M.; Yousif,  M., Z.; Yu,  L.;  and Lim,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(8).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-yousif-yu-lim-aswintransformerbasedmodelforefficientcompressionofturbulentflowdata-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-yousif-yu-lim-aswintransformerbasedmodelforefficientcompressionofturbulentflowdata-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Swin-transformer-based model for efficient compression of turbulent flow data},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {de7de501-9d51-3bef-84d8-91f88876b757},\n created = {2024-02-20T06:34:14.151Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:14.151Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhang, Meng and Yousif, Mustafa Z and Yu, Linqi and Lim, Hee-Chang},\n journal = {Physics of Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"han-wang-anattentionmechanismincorporateddeeprecurrentopticalflownetworkforparticleimagevelocimetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  An attention-mechanism incorporated deep recurrent optical flow network for particle image velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Han,  Y.;  and Wang,  Q.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(7).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/han-wang-anattentionmechanismincorporateddeeprecurrentopticalflownetworkforparticleimagevelocimetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('han-wang-anattentionmechanismincorporateddeeprecurrentopticalflownetworkforparticleimagevelocimetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An attention-mechanism incorporated deep recurrent optical flow network for particle image velocimetry},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {b2996320-fe2d-35fe-bf25-81bc41579aba},\n created = {2024-02-20T06:34:17.585Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:17.585Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Han, Yuxuan and Wang, Qian},\n journal = {Physics of Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yao-zaki-meneveau-entropyandfluctuationrelationsinisotropicturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Entropy and fluctuation relations in isotropic turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yao,  H.; Zaki,  T., A.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 973: R6.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yao-zaki-meneveau-entropyandfluctuationrelationsinisotropicturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yao-zaki-meneveau-entropyandfluctuationrelationsinisotropicturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Entropy and fluctuation relations in isotropic turbulence},\n type = {article},\n year = {2023},\n pages = {R6},\n volume = {973},\n publisher = {Cambridge University Press},\n id = {3bbc3ba0-3db4-3b93-b43c-9e7f609bb31e},\n created = {2024-02-20T06:34:18.737Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:18.737Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yao, Hanxun and Zaki, Tamer A and Meneveau, Charles},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pinchukov-poroykov-shmatko-sivov-computerandphysicalmodelingfortheestimationofthepossibilityofapplicationofconvolutionalneuralnetworksincloserangephotogrammetry-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Computer and Physical Modeling for the Estimation of the Pos-sibility of Application of Convolutional Neural Networks in Close-Range Photogrammetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pinchukov,  V., V.; Poroykov,  A., Y.; Shmatko,  E., V.;  and Sivov,  N., Y.\n</span>\n\n  \n\n</span>\n\n  <i>Computer</i>, 15(1): 71-82.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pinchukov-poroykov-shmatko-sivov-computerandphysicalmodelingfortheestimationofthepossibilityofapplicationofconvolutionalneuralnetworksincloserangephotogrammetry-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pinchukov-poroykov-shmatko-sivov-computerandphysicalmodelingfortheestimationofthepossibilityofapplicationofconvolutionalneuralnetworksincloserangephotogrammetry-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Computer and Physical Modeling for the Estimation of the Pos-sibility of Application of Convolutional Neural Networks in Close-Range Photogrammetry},\n type = {article},\n year = {2023},\n pages = {71-82},\n volume = {15},\n id = {de21b94e-3488-3d18-a56a-467035255110},\n created = {2024-02-20T06:34:21.101Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:21.101Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Pinchukov, V V and Poroykov, A Yu and Shmatko, E V and Sivov, N Yu},\n journal = {Computer},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lin-xu-experimentalinvestigationofpressurestatisticsinlaboratoryhomogeneousisotropicturbulence-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Experimental investigation of pressure statistics in laboratory homogeneous isotropic turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lin,  Y.;  and Xu,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 35(6).  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lin-xu-experimentalinvestigationofpressurestatisticsinlaboratoryhomogeneousisotropicturbulence-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lin-xu-experimentalinvestigationofpressurestatisticsinlaboratoryhomogeneousisotropicturbulence-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Experimental investigation of pressure statistics in laboratory homogeneous isotropic turbulence},\n type = {article},\n year = {2023},\n volume = {35},\n publisher = {AIP Publishing},\n id = {a4ad0676-e583-3d05-a7c7-9d41bd42e5bc},\n created = {2024-02-20T06:34:22.244Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:22.244Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lin, Yuhe and Xu, Haitao},\n journal = {Physics of Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shnapp-brizzolara-neamtuhalic-gambino-holzner-universalalignmentinturbulentpairdispersion-2023\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Universal alignment in turbulent pair dispersion.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shnapp,  R.; Brizzolara,  S.; Neamtu-Halic,  M., M.; Gambino,  A.;  and Holzner,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Communications</i>, 14(1): 4195.  2023.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shnapp-brizzolara-neamtuhalic-gambino-holzner-universalalignmentinturbulentpairdispersion-2023\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shnapp-brizzolara-neamtuhalic-gambino-holzner-universalalignmentinturbulentpairdispersion-2023')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Universal alignment in turbulent pair dispersion},\n type = {article},\n year = {2023},\n pages = {4195},\n volume = {14},\n publisher = {Nature Publishing Group UK London},\n id = {1fc88bee-0abf-3ae6-934e-efcaeb39d4f0},\n created = {2024-02-20T06:34:23.385Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2024-02-20T06:34:23.385Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Shnapp, Ron and Brizzolara, Stefano and Neamtu-Halic, Marius M and Gambino, Alessandro and Holzner, Markus},\n journal = {Nature Communications},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2022\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2022')\"\n      onkeypress=\"toggleGroup('group_2022')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2022</span>\n      <span class=\"bibbase_group_count\">\n        \n        (60)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3d9a7c68-32bd-0e95-2339-f9246e7a2185/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3d9a7c68-32bd-0e95-2339-f9246e7a2185/full_text.pdf.pdf', event);\">\n    Law of bounded dissipation and its consequences in turbulent wall flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  X.;  and Sreenivasan,  K., R.\n</span>\n\n  \n\n</span>\n\n  <i>J. Fluid Mech</i>, 933: 20.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3d9a7c68-32bd-0e95-2339-f9246e7a2185/full_text.pdf.pdf\"\n     onclick=\"log_download('chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3d9a7c68-32bd-0e95-2339-f9246e7a2185/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Law of bounded dissipation and its consequences in turbulent wall flows [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1017/jfm.2021.1052\"\n     onclick=\"log_download('chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022', 'https://doi.org/10.1017/jfm.2021.1052', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Law of bounded dissipation and its consequences in turbulent wall flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2021.1052\"\n     onclick=\"log_download('chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022', 'http://doi.org/10.1017/jfm.2021.1052', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-sreenivasan-lawofboundeddissipationanditsconsequencesinturbulentwallflows-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Law of bounded dissipation and its consequences in turbulent wall flows},\n type = {article},\n year = {2022},\n keywords = {pipe flow boundary layer,turbulence theory,turbulent boundary layers},\n pages = {20},\n volume = {933},\n websites = {https://doi.org/10.1017/jfm.2021.1052},\n id = {cf4fc9f3-21d2-35ea-8c00-b82c5a72d9d3},\n created = {2022-02-20T23:23:59.301Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-20T23:24:00.230Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {The dominant paradigm in turbulent wall flows is that the mean velocity near the wall, when scaled on wall variables, is independent of the friction Reynolds number Re τ. This paradigm faces challenges when applied to fluctuations but has received serious attention only recently. Here, by extending our earlier work (Chen &amp; Sreenivasan, J. Fluid Mech., vol. 908, 2021, p. R3) we present a promising perspective, and support it with data, that fluctuations displaying non-zero wall values, or near-wall peaks, are bounded for large values of Re τ , owing to the natural constraint that the dissipation rate is bounded. Specifically, Φ ∞ − Φ = C Φ Re −1/4 τ , where Φ represents the maximum value of any of the following quantities: energy dissipation rate, turbulent diffusion, fluctuations of pressure, streamwise and spanwise velocities, squares of vorticity components, and the wall values of pressure and shear stresses; the subscript ∞ denotes the bounded asymptotic value of Φ, and the coefficient C Φ depends on Φ but not on Re τ. Moreover, there exists a scaling law for the maximum value in the wall-normal direction of high-order moments, of the form ϕ 2q 1/q max = α q − β q Re −1/4 τ , where ϕ represents the streamwise or spanwise velocity fluctuation, and α q and β q are independent of Re τ. Excellent agreement with available data is observed. A stochastic process for which the random variable has the form just mentioned, referred to here as the &#x27;linear q-norm Gaussian&#x27;, is proposed to explain the observed linear dependence of α q on q.},\n bibtype = {article},\n author = {Chen, Xi and Sreenivasan, Katepalli R},\n doi = {10.1017/jfm.2021.1052},\n journal = {J. Fluid Mech}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The dominant paradigm in turbulent wall flows is that the mean velocity near the wall, when scaled on wall variables, is independent of the friction Reynolds number Re τ. This paradigm faces challenges when applied to fluctuations but has received serious attention only recently. Here, by extending our earlier work (Chen & Sreenivasan, J. Fluid Mech., vol. 908, 2021, p. R3) we present a promising perspective, and support it with data, that fluctuations displaying non-zero wall values, or near-wall peaks, are bounded for large values of Re τ , owing to the natural constraint that the dissipation rate is bounded. Specifically, Φ ∞ − Φ = C Φ Re −1/4 τ , where Φ represents the maximum value of any of the following quantities: energy dissipation rate, turbulent diffusion, fluctuations of pressure, streamwise and spanwise velocities, squares of vorticity components, and the wall values of pressure and shear stresses; the subscript ∞ denotes the bounded asymptotic value of Φ, and the coefficient C Φ depends on Φ but not on Re τ. Moreover, there exists a scaling law for the maximum value in the wall-normal direction of high-order moments, of the form ϕ 2q 1/q max = α q − β q Re −1/4 τ , where ϕ represents the streamwise or spanwise velocity fluctuation, and α q and β q are independent of Re τ. Excellent agreement with available data is observed. A stochastic process for which the random variable has the form just mentioned, referred to here as the 'linear q-norm Gaussian', is proposed to explain the observed linear dependence of α q on q.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/17798f52-75f5-dc15-28f4-6b63dfdc2001/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/17798f52-75f5-dc15-28f4-6b63dfdc2001/full_text.pdf.pdf', event);\">\n    Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zimmerman,  S., J.; Antonia,  R., A.; Djenidi,  L.; Philip,  J.;  and Klewicki,  J., C.\n</span>\n\n  \n\n</span>\n\n  <i>A28, Fluid Mech</i>, 931: 87-109.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/17798f52-75f5-dc15-28f4-6b63dfdc2001/full_text.pdf.pdf\"\n     onclick=\"log_download('zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/17798f52-75f5-dc15-28f4-6b63dfdc2001/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1017/jfm.2021.986\"\n     onclick=\"log_download('zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022', 'https://doi.org/10.1017/jfm.2021.986', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2021.986\"\n     onclick=\"log_download('zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022', 'http://doi.org/10.1017/jfm.2021.986', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zimmerman-antonia-djenidi-philip-klewicki-approachtothe43lawforturbulentpipeandchannelflowsexaminedthroughareformulatedscalebyscaleenergybudget-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Approach to the 4/3 law for turbulent pipe and channel flows examined through a reformulated scale-by-scale energy budget},\n type = {article},\n year = {2022},\n keywords = {homogeneous turbulence,isotropic turbulence,pipe flow},\n pages = {87-109},\n volume = {931},\n websites = {https://doi.org/10.1017/jfm.2021.986},\n id = {9e83d349-397e-3751-a3d9-b216cbfbaefc},\n created = {2022-02-21T19:34:17.825Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:34:20.081Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In this study, we propose a scale-by-scale (SBS) energy budget equation for flows with homogeneity in at least one direction. This SBS budget represents a modified form of the equation first proposed by Danaila et al. (J. for the channel centreline-the primary difference is that, here, we consider the role of pressure along with the errors associated with the isotropic approximations of the interscale divergence and Laplacian of the squared velocity increment. The term encompassing the effects of mean shear is also characterised such that the present analysis can be extended straightforwardly to locations away from the centreline. We show, based on a detailed analysis of previously published channel flow direct numerical simulations and pipe flow experiments near the centreline, how several terms in the present SBS budget equation (including the third-order velocity structure function) behave with increasing Reynolds number. The behaviour of these terms is shown to imply a rate of emergence and subsequent growth of the 4/3 law scale subrange at the channel centreline and pipe axis. The analysis also suggests that the peak magnitude of the third-order velocity structure function occurs at a scale that is fixed in proportion to the Taylor microscale at sufficiently high Reynolds number.},\n bibtype = {article},\n author = {Zimmerman, Spencer J and Antonia, R A and Djenidi, L and Philip, J and Klewicki, J C},\n doi = {10.1017/jfm.2021.986},\n journal = {A28, Fluid Mech}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this study, we propose a scale-by-scale (SBS) energy budget equation for flows with homogeneity in at least one direction. This SBS budget represents a modified form of the equation first proposed by Danaila et al. (J. for the channel centreline-the primary difference is that, here, we consider the role of pressure along with the errors associated with the isotropic approximations of the interscale divergence and Laplacian of the squared velocity increment. The term encompassing the effects of mean shear is also characterised such that the present analysis can be extended straightforwardly to locations away from the centreline. We show, based on a detailed analysis of previously published channel flow direct numerical simulations and pipe flow experiments near the centreline, how several terms in the present SBS budget equation (including the third-order velocity structure function) behave with increasing Reynolds number. The behaviour of these terms is shown to imply a rate of emergence and subsequent growth of the 4/3 law scale subrange at the channel centreline and pipe axis. The analysis also suggests that the peak magnitude of the third-order velocity structure function occurs at a scale that is fixed in proportion to the Taylor microscale at sufficiently high Reynolds number.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"stallcup-kshitij-dahm-adaptivescalesimilarclosureforlargeeddysimulationspart1subgridstressclosure-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Adaptive Scale-Similar Closure for Large Eddy Simulations. Part 1: Subgrid Stress Closure.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Stallcup,  E., W.; Kshitij,  A.;  and Dahm,  W., J.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA SCITECH 2022 Forum</i>, pages 595,  2022. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/stallcup-kshitij-dahm-adaptivescalesimilarclosureforlargeeddysimulationspart1subgridstressclosure-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('stallcup-kshitij-dahm-adaptivescalesimilarclosureforlargeeddysimulationspart1subgridstressclosure-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Adaptive Scale-Similar Closure for Large Eddy Simulations. Part 1: Subgrid Stress Closure},\n type = {inproceedings},\n year = {2022},\n pages = {595},\n id = {caa0cd99-5473-3269-a7f6-2a4ef972e1a2},\n created = {2022-02-21T20:13:41.934Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:41.934Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Stallcup, Eric W and Kshitij, Abhinav and Dahm, Werner J},\n booktitle = {AIAA SCITECH 2022 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Systematic generation of moment invariant bases for 2D and 3D tensor fields.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bujack,  R.; Zhang,  X.; Suk,  T.;  and Rogers,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Pattern Recognition</i>, 123: 108313.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Systematic generation of moment invariant bases for 2D and 3D tensor fields},\n type = {article},\n year = {2022},\n pages = {108313},\n volume = {123},\n publisher = {Elsevier},\n id = {964a4532-86de-313c-8ca2-6cc48d4cdd16},\n created = {2022-02-21T20:13:42.303Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:42.303Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bujack, Roxana and Zhang, Xinhua and Suk, Tomá\\^s and Rogers, David},\n journal = {Pattern Recognition}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"eyink-kumar-quan-theonsagertheoryofwallboundedturbulenceandtaylorsmomentumanomaly-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  The Onsager theory of wall-bounded turbulence and Taylor’s momentum anomaly.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eyink,  G., L.; Kumar,  S.;  and Quan,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Philosophical Transactions of the Royal Society A</i>, 380(2218): 20210079.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eyink-kumar-quan-theonsagertheoryofwallboundedturbulenceandtaylorsmomentumanomaly-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eyink-kumar-quan-theonsagertheoryofwallboundedturbulenceandtaylorsmomentumanomaly-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The Onsager theory of wall-bounded turbulence and Taylor’s momentum anomaly},\n type = {article},\n year = {2022},\n pages = {20210079},\n volume = {380},\n publisher = {The Royal Society},\n id = {d5d828dc-c635-3568-948d-27cce66ae623},\n created = {2022-02-21T20:13:43.424Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:43.424Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Eyink, Gregory L and Kumar, Samvit and Quan, Hao},\n journal = {Philosophical Transactions of the Royal Society A},\n number = {2218}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"friedrich-viggiano-bourgoin-cal-chevillard-singleinertialparticlestatisticsinturbulentflowsfromlagrangianvelocitymodels-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Single inertial particle statistics in turbulent flows from Lagrangian velocity models.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Friedrich,  J.; Viggiano,  B.; Bourgoin,  M.; Cal,  R., B.;  and Chevillard,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 7(1): 14303.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/friedrich-viggiano-bourgoin-cal-chevillard-singleinertialparticlestatisticsinturbulentflowsfromlagrangianvelocitymodels-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('friedrich-viggiano-bourgoin-cal-chevillard-singleinertialparticlestatisticsinturbulentflowsfromlagrangianvelocitymodels-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Single inertial particle statistics in turbulent flows from Lagrangian velocity models},\n type = {article},\n year = {2022},\n pages = {14303},\n volume = {7},\n publisher = {APS},\n id = {055dc99f-8e37-3b47-ae00-33a5767fe66d},\n created = {2022-02-21T20:13:45.310Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:45.310Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Friedrich, Jan and Viggiano, Bianca and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},\n journal = {Physical Review Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhao-betti-aluie-scaleinteractionsandanisotropyinrayleightaylorturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Scale interactions and anisotropy in Rayleigh–Taylor turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhao,  D.; Betti,  R.;  and Aluie,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 930.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhao-betti-aluie-scaleinteractionsandanisotropyinrayleightaylorturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhao-betti-aluie-scaleinteractionsandanisotropyinrayleightaylorturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Scale interactions and anisotropy in Rayleigh–Taylor turbulence},\n type = {article},\n year = {2022},\n volume = {930},\n publisher = {Cambridge University Press},\n id = {4ad90724-7c0b-32fb-adb1-eaf456d634d3},\n created = {2022-02-21T20:31:00.972Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:00.972Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhao, Dongxiao and Betti, Riccardo and Aluie, Hussein},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Reinforcement Learning for Load-balanced Parallel Particle Tracing.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xu,  J.; Guo,  H.; Shen,  H.; Raj,  M.; Wurster,  S., W.;  and Peterka,  T.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reinforcement Learning for Load-balanced Parallel Particle Tracing},\n type = {article},\n year = {2022},\n publisher = {IEEE},\n id = {60e22e2d-0e6f-3e22-8b73-d13715109487},\n created = {2022-03-22T18:52:31.647Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-03-22T18:52:31.647Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Xu, Jiayi and Guo, Hanqi and Shen, Han-Wei and Raj, Mukund and Wurster, Skylar Wolfgang and Peterka, Tom},\n journal = {IEEE Transactions on Visualization and Computer Graphics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Systematic generation of moment invariant bases for 2D and 3D tensor fields.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bujack,  R.; Zhang,  X.; Suk,  T.;  and Rogers,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Pattern Recognition</i>, 123: 108313.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bujack-zhang-suk-rogers-systematicgenerationofmomentinvariantbasesfor2dand3dtensorfields-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Systematic generation of moment invariant bases for 2D and 3D tensor fields},\n type = {article},\n year = {2022},\n pages = {108313},\n volume = {123},\n publisher = {Elsevier},\n id = {1d059987-dfea-3c08-9246-1ec2aa1cc63e},\n created = {2022-03-22T18:52:32.066Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-03-22T18:52:32.066Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bujack, Roxana and Zhang, Xinhua and Suk, Tomá\\^s and Rogers, David},\n journal = {Pattern Recognition}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mukherjee-mascini-portela-correlationanddecompositionconceptsforidentifyinganddisentanglingflowstructuresframeworkandinsightsintoturbulenceorganization-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Correlation and decomposition concepts for identifying and disentangling flow structures: Framework and insights into turbulence organization.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mukherjee,  S.; Mascini,  M.;  and Portela,  L., M.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 34(1): 15119.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mukherjee-mascini-portela-correlationanddecompositionconceptsforidentifyinganddisentanglingflowstructuresframeworkandinsightsintoturbulenceorganization-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mukherjee-mascini-portela-correlationanddecompositionconceptsforidentifyinganddisentanglingflowstructuresframeworkandinsightsintoturbulenceorganization-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Correlation and decomposition concepts for identifying and disentangling flow structures: Framework and insights into turbulence organization},\n type = {article},\n year = {2022},\n pages = {15119},\n volume = {34},\n publisher = {AIP Publishing LLC},\n id = {62a9239a-cabf-3e54-aa9d-63285f23900e},\n created = {2022-03-22T18:52:32.479Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-03-22T18:52:32.479Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Mukherjee, Siddhartha and Mascini, Merlijn and Portela, Luis M},\n journal = {Physics of Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"luo-shi-meneveau-multifractalityinanestedvelocitygradientmodelforintermittentturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Multifractality in a nested velocity gradient model for intermittent turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Luo,  Y.; Shi,  Y.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 7(1): 14609.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/luo-shi-meneveau-multifractalityinanestedvelocitygradientmodelforintermittentturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('luo-shi-meneveau-multifractalityinanestedvelocitygradientmodelforintermittentturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multifractality in a nested velocity gradient model for intermittent turbulence},\n type = {article},\n year = {2022},\n pages = {14609},\n volume = {7},\n publisher = {APS},\n id = {a00425c4-d651-30a5-a362-bd212d2e55fd},\n created = {2022-03-22T18:52:32.898Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-03-22T18:52:32.898Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Luo, Yuan and Shi, Yipeng and Meneveau, Charles},\n journal = {Physical Review Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mteling-schrder-analysisofspatiotemporalinnerouterlargescaleinteractionsinturbulentchannelflowbymultivariateempiricalmodedecomposition-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Analysis of spatiotemporal inner-outer large-scale interactions in turbulent channel flow by multivariate empirical mode decomposition.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mäteling,  E.;  and Schröder,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 7(3): 34603.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mteling-schrder-analysisofspatiotemporalinnerouterlargescaleinteractionsinturbulentchannelflowbymultivariateempiricalmodedecomposition-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mteling-schrder-analysisofspatiotemporalinnerouterlargescaleinteractionsinturbulentchannelflowbymultivariateempiricalmodedecomposition-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Analysis of spatiotemporal inner-outer large-scale interactions in turbulent channel flow by multivariate empirical mode decomposition},\n type = {article},\n year = {2022},\n pages = {34603},\n volume = {7},\n id = {65bc8450-c242-3b03-ae30-53cd485ede7e},\n created = {2022-03-22T18:52:33.305Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-03-22T18:52:33.305Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Mäteling, Esther and Schröder, Wolfgang},\n journal = {Physical Review Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"huang-jiang-motioninducednoisemodelingoftowedmagneticantenna-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Motion-Induced Noise Modeling of Towed Magnetic Antenna.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Huang,  Z.;  and Jiang,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Antennas and Propagation</i>.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/huang-jiang-motioninducednoisemodelingoftowedmagneticantenna-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('huang-jiang-motioninducednoisemodelingoftowedmagneticantenna-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Motion-Induced Noise Modeling of Towed Magnetic Antenna},\n type = {article},\n year = {2022},\n publisher = {IEEE},\n id = {4b03d0c0-8e50-35bf-b153-55236f3caf2d},\n created = {2022-05-05T19:50:33.048Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:33.048Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Huang, Zhi and Jiang, Yuzhong},\n journal = {IEEE Transactions on Antennas and Propagation}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-hu-yan-li-helicitydistributionsandtransferinturbulentchannelflowswithstreamwiserotation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Helicity distributions and transfer in turbulent channel flows with streamwise rotation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Hu,  R.; Yan,  Z.;  and Li,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 940: A18.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-hu-yan-li-helicitydistributionsandtransferinturbulentchannelflowswithstreamwiserotation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-hu-yan-li-helicitydistributionsandtransferinturbulentchannelflowswithstreamwiserotation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Helicity distributions and transfer in turbulent channel flows with streamwise rotation},\n type = {article},\n year = {2022},\n pages = {A18},\n volume = {940},\n publisher = {Cambridge University Press},\n id = {37d3576e-0a51-3d99-8d51-6a01b619cb8c},\n created = {2022-05-05T19:50:33.542Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:33.542Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yu, Changping and Hu, Running and Yan, Zheng and Li, Xinliang},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Origin of enhanced skin friction at the onset of boundary-layer transition.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  M.; Eyink,  G., L.;  and Zaki,  T., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 941: 2022.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Origin of enhanced skin friction at the onset of boundary-layer transition},\n type = {article},\n year = {2022},\n pages = {2022},\n volume = {941},\n publisher = {Cambridge University Press},\n id = {963817a3-1593-3b84-b661-95405c301726},\n created = {2022-05-05T19:50:33.947Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:33.947Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Mengze and Eyink, Gregory L and Zaki, Tamer A},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"elnahhas-johnson-ontheenhancementofboundarylayerskinfrictionbyturbulenceanangularmomentumapproach-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  On the enhancement of boundary layer skin friction by turbulence: an angular momentum approach.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Elnahhas,  A.;  and Johnson,  P., L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 940: A36.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/elnahhas-johnson-ontheenhancementofboundarylayerskinfrictionbyturbulenceanangularmomentumapproach-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('elnahhas-johnson-ontheenhancementofboundarylayerskinfrictionbyturbulenceanangularmomentumapproach-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On the enhancement of boundary layer skin friction by turbulence: an angular momentum approach},\n type = {article},\n year = {2022},\n pages = {A36},\n volume = {940},\n publisher = {Cambridge University Press},\n id = {344dfb22-a64a-3933-8964-8394921b393e},\n created = {2022-05-05T19:50:34.774Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:34.774Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Elnahhas, Ahmed and Johnson, Perry L},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aksamit-haller-objectivemomentumbarriersinwallturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Objective momentum barriers in wall turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aksamit,  N., O.;  and Haller,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 941: A3.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aksamit-haller-objectivemomentumbarriersinwallturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aksamit-haller-objectivemomentumbarriersinwallturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Objective momentum barriers in wall turbulence},\n type = {article},\n year = {2022},\n pages = {A3},\n volume = {941},\n publisher = {Cambridge University Press},\n id = {5e905819-22f8-39ef-9b21-bf70b4bd48c7},\n created = {2022-05-05T19:50:35.190Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:35.190Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Aksamit, Nikolas O and Haller, George},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fiscaletti-ragni-overmars-westerweel-elsinga-tomographiclongdistancepivtoinvestigatethesmallscalesofturbulenceinajetathighreynoldsnumber-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Tomographic long-distance μPIV to investigate the small scales of turbulence in a jet at high Reynolds number.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fiscaletti,  D.; Ragni,  D.; Overmars,  E., F., J.; Westerweel,  J.;  and Elsinga,  G., E.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 63(1): 1-16.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fiscaletti-ragni-overmars-westerweel-elsinga-tomographiclongdistancepivtoinvestigatethesmallscalesofturbulenceinajetathighreynoldsnumber-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fiscaletti-ragni-overmars-westerweel-elsinga-tomographiclongdistancepivtoinvestigatethesmallscalesofturbulenceinajetathighreynoldsnumber-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Tomographic long-distance μPIV to investigate the small scales of turbulence in a jet at high Reynolds number},\n type = {article},\n year = {2022},\n pages = {1-16},\n volume = {63},\n publisher = {Springer},\n id = {993e1867-08db-3d38-9a9f-712bcfc60569},\n created = {2022-05-05T19:50:35.662Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:35.662Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fiscaletti, Daniele and Ragni, Daniele and Overmars, Edwin F J and Westerweel, Jerry and Elsinga, Gerrit E},\n journal = {Experiments in Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sarnitsky-heinz-nonparametricinferencefordiffusionprocessesinsystemswithsmoothevolution-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Nonparametric inference for diffusion processes in systems with smooth evolution.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sarnitsky,  G.;  and Heinz,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Physica A: Statistical Mechanics and its Applications</i>,127386.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sarnitsky-heinz-nonparametricinferencefordiffusionprocessesinsystemswithsmoothevolution-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sarnitsky-heinz-nonparametricinferencefordiffusionprocessesinsystemswithsmoothevolution-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Nonparametric inference for diffusion processes in systems with smooth evolution},\n type = {article},\n year = {2022},\n pages = {127386},\n publisher = {Elsevier},\n id = {6e0a7582-620b-3e5b-88c1-3008f79c2f63},\n created = {2022-05-05T19:50:36.075Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:36.075Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Sarnitsky, Grigory and Heinz, Stefan},\n journal = {Physica A: Statistical Mechanics and its Applications}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jeon-mller-michaelis-finescalereconstructionvicbyimplementingadditionalconstraintsandcoarsegridapproximationintovic-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Fine scale reconstruction (VIC#) by implementing additional constraints and coarse-grid approximation into VIC+.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jeon,  Y., J.; Müller,  M.;  and Michaelis,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 63(4): 1-24.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jeon-mller-michaelis-finescalereconstructionvicbyimplementingadditionalconstraintsandcoarsegridapproximationintovic-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jeon-mller-michaelis-finescalereconstructionvicbyimplementingadditionalconstraintsandcoarsegridapproximationintovic-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Fine scale reconstruction (VIC#) by implementing additional constraints and coarse-grid approximation into VIC+},\n type = {article},\n year = {2022},\n pages = {1-24},\n volume = {63},\n publisher = {Springer},\n id = {947c6865-1ed4-3b6b-861d-2e59933a6724},\n created = {2022-05-05T19:50:36.487Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:36.487Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Jeon, Young Jin and Müller, Markus and Michaelis, Dirk},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-raiola-discetti-pressurefromdatadrivenestimatedvelocityfieldsusingsnapshotpivandfastprobes-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Pressure from data-driven-estimated velocity fields using snapshot PIV and fast probes.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  J.; Raiola,  M.;  and Discetti,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>,110647.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-raiola-discetti-pressurefromdatadrivenestimatedvelocityfieldsusingsnapshotpivandfastprobes-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-raiola-discetti-pressurefromdatadrivenestimatedvelocityfieldsusingsnapshotpivandfastprobes-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pressure from data-driven-estimated velocity fields using snapshot PIV and fast probes},\n type = {article},\n year = {2022},\n pages = {110647},\n publisher = {Elsevier},\n id = {221923d4-7aa2-3871-bdab-cf9be04306c1},\n created = {2022-05-05T19:50:36.904Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:50:36.904Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chen, Junwei and Raiola, Marco and Discetti, Stefano},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wu-tsai-wu-probabilisticcharacterizationofsweepandejectioneventsinturbulentflowsanditsimplicationsonsedimenttransport-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Probabilistic Characterization of Sweep and Ejection Events in Turbulent Flows and its Implications on Sediment Transport.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  K.; Tsai,  C., W.;  and Wu,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Water Resources Research</i>,e2021WR030417.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-tsai-wu-probabilisticcharacterizationofsweepandejectioneventsinturbulentflowsanditsimplicationsonsedimenttransport-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-tsai-wu-probabilisticcharacterizationofsweepandejectioneventsinturbulentflowsanditsimplicationsonsedimenttransport-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Probabilistic Characterization of Sweep and Ejection Events in Turbulent Flows and its Implications on Sediment Transport},\n type = {article},\n year = {2022},\n pages = {e2021WR030417},\n publisher = {Wiley Online Library},\n id = {d014e146-5b8f-3049-ac95-71db058ff136},\n created = {2022-05-05T19:51:38.931Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T19:51:38.931Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wu, Kuan-Ting and Tsai, Christina W and Wu, Meng-Jie},\n journal = {Water Resources Research}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fowler-zaki-meneveau-alagrangianrelaxationtowardsequilibriumwallmodelforlargeeddysimulation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A Lagrangian relaxation towards equilibrium wall model for large eddy simulation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fowler,  M.; Zaki,  T., A.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 934: A44.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fowler-zaki-meneveau-alagrangianrelaxationtowardsequilibriumwallmodelforlargeeddysimulation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fowler-zaki-meneveau-alagrangianrelaxationtowardsequilibriumwallmodelforlargeeddysimulation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Lagrangian relaxation towards equilibrium wall model for large eddy simulation},\n type = {article},\n year = {2022},\n pages = {A44},\n volume = {934},\n publisher = {Cambridge University Press},\n id = {49e7ec4d-bc3d-3530-89fa-a099e9b92298},\n created = {2022-05-05T20:14:35.996Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-05-05T20:14:35.996Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fowler, Mitchell and Zaki, Tamer A and Meneveau, Charles},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"monthiller-loisy-koehl-favier-eloy-surfingonturbulenceastrategyforplanktonicnavigation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Surfing on Turbulence: A Strategy for Planktonic Navigation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Monthiller,  R.; Loisy,  A.; Koehl,  M., A., R.; Favier,  B.;  and Eloy,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 129(6): 64502.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/monthiller-loisy-koehl-favier-eloy-surfingonturbulenceastrategyforplanktonicnavigation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('monthiller-loisy-koehl-favier-eloy-surfingonturbulenceastrategyforplanktonicnavigation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Surfing on Turbulence: A Strategy for Planktonic Navigation},\n type = {article},\n year = {2022},\n pages = {64502},\n volume = {129},\n publisher = {APS},\n id = {0eb68d08-1b02-3d0b-9b63-d859b26dbeb4},\n created = {2022-08-16T18:18:53.581Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:18:53.581Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Monthiller, Rémi and Loisy, Aurore and Koehl, Mimi A R and Favier, Benjamin and Eloy, Christophe},\n journal = {Physical Review Letters},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kumar-meneveau-eyink-perturbativemodelforthesecondordervelocitystructurefunctiontensorinturbulentshearflows-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Perturbative model for the second-order velocity structure function tensor in turbulent shear flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kumar,  S.; Meneveau,  C.;  and Eyink,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Physical review fluids</i>, 7(6): 64601.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kumar-meneveau-eyink-perturbativemodelforthesecondordervelocitystructurefunctiontensorinturbulentshearflows-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kumar-meneveau-eyink-perturbativemodelforthesecondordervelocitystructurefunctiontensorinturbulentshearflows-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Perturbative model for the second-order velocity structure function tensor in turbulent shear flows},\n type = {article},\n year = {2022},\n pages = {64601},\n volume = {7},\n publisher = {APS},\n id = {a813e8c5-9cdf-3068-a914-ae7969b1c89a},\n created = {2022-08-16T18:49:42.622Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:42.622Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Kumar, Samvit and Meneveau, Charles and Eyink, Gregory},\n journal = {Physical review fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"apolinrio-moriconi-pereira-valado-eddyviscousmodelingandthetopologyofextremecirculationeventsinthreedimensionalturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Eddy-Viscous Modeling and the Topology of Extreme Circulation Events in Three-Dimensional Turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Apolinário,  G., B.; Moriconi,  L.; Pereira,  R., M.;  and Valadão,  V., J.\n</span>\n\n  \n\n</span>\n\n  <i>Physics Letters A</i>,128360.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/apolinrio-moriconi-pereira-valado-eddyviscousmodelingandthetopologyofextremecirculationeventsinthreedimensionalturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('apolinrio-moriconi-pereira-valado-eddyviscousmodelingandthetopologyofextremecirculationeventsinthreedimensionalturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Eddy-Viscous Modeling and the Topology of Extreme Circulation Events in Three-Dimensional Turbulence},\n type = {article},\n year = {2022},\n pages = {128360},\n publisher = {Elsevier},\n id = {05366e88-a800-3821-b2de-16fb210f03d1},\n created = {2022-08-16T18:49:43.039Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:43.039Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Apolinário, G B and Moriconi, L and Pereira, R M and Valadão, V J},\n journal = {Physics Letters A}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jassal-dobrosotskaya-schmidt-opticalflowvelocimetryusingaquasioptimalbasiswithimplicitregularization-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Optical Flow Velocimetry using a Quasi-Optimal Basis with Implicit Regularization.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jassal,  G., R.; Dobrosotskaya,  J., A.;  and Schmidt,  B., E.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA AVIATION 2022 Forum</i>, pages 3336,  2022. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jassal-dobrosotskaya-schmidt-opticalflowvelocimetryusingaquasioptimalbasiswithimplicitregularization-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jassal-dobrosotskaya-schmidt-opticalflowvelocimetryusingaquasioptimalbasiswithimplicitregularization-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Optical Flow Velocimetry using a Quasi-Optimal Basis with Implicit Regularization},\n type = {inproceedings},\n year = {2022},\n pages = {3336},\n id = {dd3566e5-2ea5-3617-8da5-fee36030197d},\n created = {2022-08-16T18:49:43.443Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:43.443Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Jassal, Gauresh R and Dobrosotskaya, Julia A and Schmidt, Bryan E},\n booktitle = {AIAA AVIATION 2022 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gevelber-schmidt-mustafa-shekhtman-parziale-determiningvelocityfromtaggingvelocimetryimagesusingopticalflow-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Determining velocity from tagging velocimetry images using optical flow.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gevelber,  T., S.; Schmidt,  B., E.; Mustafa,  M., A.; Shekhtman,  D.;  and Parziale,  N., J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 63(6): 1-15.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gevelber-schmidt-mustafa-shekhtman-parziale-determiningvelocityfromtaggingvelocimetryimagesusingopticalflow-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gevelber-schmidt-mustafa-shekhtman-parziale-determiningvelocityfromtaggingvelocimetryimagesusingopticalflow-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Determining velocity from tagging velocimetry images using optical flow},\n type = {article},\n year = {2022},\n pages = {1-15},\n volume = {63},\n publisher = {Springer},\n id = {0d29e8ac-43ca-33a6-9c38-4a5b81d6a30c},\n created = {2022-08-16T18:49:43.837Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:43.837Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Gevelber, T S and Schmidt, B E and Mustafa, M A and Shekhtman, D and Parziale, N J},\n journal = {Experiments in Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Origin of enhanced skin friction at the onset of boundary-layer transition.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  M.; Eyink,  G., L.;  and Zaki,  T., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 941: A32.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-eyink-zaki-originofenhancedskinfrictionattheonsetofboundarylayertransition-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Origin of enhanced skin friction at the onset of boundary-layer transition},\n type = {article},\n year = {2022},\n pages = {A32},\n volume = {941},\n publisher = {Cambridge University Press},\n id = {c46b8478-8366-33d0-a14b-778c5c409cb1},\n created = {2022-08-16T18:49:44.339Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:44.339Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Mengze and Eyink, Gregory L and Zaki, Tamer A},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hu-zheng-dong-extractingdiscretehierarchiesoftownsendswallattachededdies-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Extracting discrete hierarchies of Townsend's wall-attached eddies.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hu,  R.; Zheng,  X.;  and Dong,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 34(6): 61701.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hu-zheng-dong-extractingdiscretehierarchiesoftownsendswallattachededdies-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hu-zheng-dong-extractingdiscretehierarchiesoftownsendswallattachededdies-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Extracting discrete hierarchies of Townsend&#x27;s wall-attached eddies},\n type = {article},\n year = {2022},\n pages = {61701},\n volume = {34},\n publisher = {AIP Publishing LLC},\n id = {a6453ac5-96cb-31bd-b415-e73216e58a8d},\n created = {2022-08-16T18:49:44.759Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:44.759Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hu, Ruifeng and Zheng, Xiaojing and Dong, Siwei},\n journal = {Physics of Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nath-roy-govindarajan-ravichandran-transportofcondensingdropletsintaylorgreenvortexflowinthepresenceofthermalnoise-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Transport of condensing droplets in Taylor-Green vortex flow in the presence of thermal noise.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nath,  A., V., S.; Roy,  A.; Govindarajan,  R.;  and Ravichandran,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 105(3): 35101.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nath-roy-govindarajan-ravichandran-transportofcondensingdropletsintaylorgreenvortexflowinthepresenceofthermalnoise-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nath-roy-govindarajan-ravichandran-transportofcondensingdropletsintaylorgreenvortexflowinthepresenceofthermalnoise-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Transport of condensing droplets in Taylor-Green vortex flow in the presence of thermal noise},\n type = {article},\n year = {2022},\n pages = {35101},\n volume = {105},\n publisher = {APS},\n id = {87280d04-1257-3f66-9a5e-42ce27eff4f7},\n created = {2022-08-16T18:49:45.252Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:45.252Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Nath, Anu V S and Roy, Anubhab and Govindarajan, Rama and Ravichandran, Sivaramakrishnan},\n journal = {Physical Review E},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhu-sun-liu-zhang-oneneuralnetworkapproachforthesurrogateturbulencemodelintransonicflows-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  One neural network approach for the surrogate turbulence model in transonic flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhu,  L.; Sun,  X.; Liu,  Y.;  and Zhang,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Acta Mechanica Sinica</i>, 38(3): 1-14.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhu-sun-liu-zhang-oneneuralnetworkapproachforthesurrogateturbulencemodelintransonicflows-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhu-sun-liu-zhang-oneneuralnetworkapproachforthesurrogateturbulencemodelintransonicflows-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {One neural network approach for the surrogate turbulence model in transonic flows},\n type = {article},\n year = {2022},\n pages = {1-14},\n volume = {38},\n publisher = {Springer},\n id = {15d7a7fe-b2ce-345b-abb6-eaafc91e5043},\n created = {2022-08-16T18:49:45.701Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:45.701Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhu, Linyang and Sun, Xuxiang and Liu, Yilang and Zhang, Weiwei},\n journal = {Acta Mechanica Sinica},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grenga,  T.; Nista,  L.; Schumann,  C.; Karimi,  A., N.; Scialabba,  G.; Attili,  A.;  and Pitsch,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Combustion Science and Technology</i>,1-24.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grenga-nista-schumann-karimi-scialabba-attili-pitsch-predictivedatadrivenmodelbasedongenerativeadversarialnetworkforpremixedturbulencecombustionregimes-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes},\n type = {article},\n year = {2022},\n pages = {1-24},\n publisher = {Taylor &amp; Francis},\n id = {c8d52a5d-65cc-36bc-92cc-214d04349259},\n created = {2022-08-16T18:49:46.188Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:46.188Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Grenga, Temistocle and Nista, Ludovico and Schumann, Christoph and Karimi, Amir Noughabi and Scialabba, Gandolfo and Attili, Antonio and Pitsch, Heinz},\n journal = {Combustion Science and Technology}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prakash-jansen-evans-invariantdatadrivensubgridstressmodelinginthestrainrateeigenframeforlargeeddysimulation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Invariant data-driven subgrid stress modeling in the strain-rate eigenframe for large eddy simulation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Prakash,  A.; Jansen,  K., E.;  and Evans,  J., A.\n</span>\n\n  \n\n</span>\n\n  <i>Computer Methods in Applied Mechanics and Engineering</i>, 399: 115457.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prakash-jansen-evans-invariantdatadrivensubgridstressmodelinginthestrainrateeigenframeforlargeeddysimulation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prakash-jansen-evans-invariantdatadrivensubgridstressmodelinginthestrainrateeigenframeforlargeeddysimulation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Invariant data-driven subgrid stress modeling in the strain-rate eigenframe for large eddy simulation},\n type = {article},\n year = {2022},\n pages = {115457},\n volume = {399},\n publisher = {Elsevier},\n id = {2017dacf-506b-3021-8011-41fea46991b6},\n created = {2022-08-16T18:49:46.628Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:46.628Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Prakash, Aviral and Jansen, Kenneth E and Evans, John A},\n journal = {Computer Methods in Applied Mechanics and Engineering}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"das-girimaji-theeffectoflargescaleforcingonsmallscaledynamicsofincompressibleturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  The effect of large-scale forcing on small-scale dynamics of incompressible turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Das,  R.;  and Girimaji,  S., S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 941.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/das-girimaji-theeffectoflargescaleforcingonsmallscaledynamicsofincompressibleturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('das-girimaji-theeffectoflargescaleforcingonsmallscaledynamicsofincompressibleturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The effect of large-scale forcing on small-scale dynamics of incompressible turbulence},\n type = {article},\n year = {2022},\n volume = {941},\n publisher = {Cambridge University Press},\n id = {bb958bb7-b9eb-3c56-9b27-50d5c2ed19c0},\n created = {2022-08-16T18:49:47.038Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:47.038Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Das, Rishita and Girimaji, Sharath S},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gharaati-xiao-wei-martineztossas-dabiri-yang-largeeddysimulationofhelicalandstraightbladedverticalaxiswindturbinesinboundarylayerturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Large Eddy Simulation of Helical-and Straight-Bladed Vertical Axis Wind Turbines in Boundary Layer Turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gharaati,  M.; Xiao,  S.; Wei,  N., J.; Martinez-Tossas,  L., A.; Dabiri,  J., O.;  and Yang,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Renewable and Sustainable Energy</i>.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gharaati-xiao-wei-martineztossas-dabiri-yang-largeeddysimulationofhelicalandstraightbladedverticalaxiswindturbinesinboundarylayerturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gharaati-xiao-wei-martineztossas-dabiri-yang-largeeddysimulationofhelicalandstraightbladedverticalaxiswindturbinesinboundarylayerturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Large Eddy Simulation of Helical-and Straight-Bladed Vertical Axis Wind Turbines in Boundary Layer Turbulence},\n type = {article},\n year = {2022},\n publisher = {AIP Publishing LLC},\n id = {eff2bb57-09e6-3b4e-85a5-24b0a50efa33},\n created = {2022-08-16T18:49:47.435Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:47.435Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Gharaati, Masoumeh and Xiao, Shuolin and Wei, Nathaniel J and Martinez-Tossas, Luis A and Dabiri, John O and Yang, Di},\n journal = {Journal of Renewable and Sustainable Energy}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bresci-lemoine-gremillet-comisso-sironi-demidem-nonresonantparticleaccelerationinstrongturbulencecomparisontokineticandmhdsimulations-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Nonresonant particle acceleration in strong turbulence: Comparison to kinetic and MHD simulations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bresci,  V.; Lemoine,  M.; Gremillet,  L.; Comisso,  L.; Sironi,  L.;  and Demidem,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review D</i>, 106(2): 23028.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bresci-lemoine-gremillet-comisso-sironi-demidem-nonresonantparticleaccelerationinstrongturbulencecomparisontokineticandmhdsimulations-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bresci-lemoine-gremillet-comisso-sironi-demidem-nonresonantparticleaccelerationinstrongturbulencecomparisontokineticandmhdsimulations-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Nonresonant particle acceleration in strong turbulence: Comparison to kinetic and MHD simulations},\n type = {article},\n year = {2022},\n pages = {23028},\n volume = {106},\n publisher = {APS},\n id = {f0e1548e-a76a-3356-b4c1-a2ab4d414601},\n created = {2022-08-16T18:49:47.833Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:47.833Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bresci, Virginia and Lemoine, Martin and Gremillet, Laurent and Comisso, Luca and Sironi, Lorenzo and Demidem, Camilia},\n journal = {Physical Review D},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lee-park-kim-han-hwang-theeffectofperspectiveerroron2dpivmeasurementsofhomogeneousisotropicturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  The effect of perspective error on 2D PIV Measurements of homogeneous isotropic turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lee,  H.; Park,  H., J.; Kim,  M.; Han,  J.;  and Hwang,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 63(8): 1-17.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lee-park-kim-han-hwang-theeffectofperspectiveerroron2dpivmeasurementsofhomogeneousisotropicturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lee-park-kim-han-hwang-theeffectofperspectiveerroron2dpivmeasurementsofhomogeneousisotropicturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The effect of perspective error on 2D PIV Measurements of homogeneous isotropic turbulence},\n type = {article},\n year = {2022},\n pages = {1-17},\n volume = {63},\n publisher = {Springer},\n id = {8ff024a1-ac23-3655-a0ce-fbfa63b94689},\n created = {2022-08-16T18:49:48.238Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:48.238Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lee, Hoonsang and Park, Han June and Kim, Museong and Han, Joungho and Hwang, Wontae},\n journal = {Experiments in Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nakamura-fukagata-robusttrainingapproachofneuralnetworksforfluidflowstateestimations-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Robust training approach of neural networks for fluid flow state estimations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nakamura,  T.;  and Fukagata,  K.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Heat and Fluid Flow</i>, 96: 108997.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nakamura-fukagata-robusttrainingapproachofneuralnetworksforfluidflowstateestimations-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nakamura-fukagata-robusttrainingapproachofneuralnetworksforfluidflowstateestimations-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Robust training approach of neural networks for fluid flow state estimations},\n type = {article},\n year = {2022},\n pages = {108997},\n volume = {96},\n publisher = {Elsevier},\n id = {97c79d6b-6815-378b-b963-982078f57a29},\n created = {2022-08-16T18:49:48.707Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:48.707Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Nakamura, Taichi and Fukagata, Koji},\n journal = {International Journal of Heat and Fluid Flow}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"motoori-wong-goto-roleofthehierarchyofcoherentstructuresinthetransportofheavysmallparticlesinturbulentchannelflow-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Role of the hierarchy of coherent structures in the transport of heavy small particles in turbulent channel flow.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Motoori,  Y.; Wong,  C.;  and Goto,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 942: A3.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/motoori-wong-goto-roleofthehierarchyofcoherentstructuresinthetransportofheavysmallparticlesinturbulentchannelflow-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('motoori-wong-goto-roleofthehierarchyofcoherentstructuresinthetransportofheavysmallparticlesinturbulentchannelflow-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Role of the hierarchy of coherent structures in the transport of heavy small particles in turbulent channel flow},\n type = {article},\n year = {2022},\n pages = {A3},\n volume = {942},\n publisher = {Cambridge University Press},\n id = {388e4333-78b2-33c6-a860-659f125ee780},\n created = {2022-08-16T18:49:49.291Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:49.291Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Motoori, Yutaro and Wong, ChiKuen and Goto, Susumu},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-fischer-avila-xu-measurementerroroftracerbasedvelocimetryinsinglephaseturbulentflowswithinhomogeneousrefractiveindices-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Measurement error of tracer-based velocimetry in single-phase turbulent flows with inhomogeneous refractive indices.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  H.; Fischer,  A.; Avila,  M.;  and Xu,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 136: 110681.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-fischer-avila-xu-measurementerroroftracerbasedvelocimetryinsinglephaseturbulentflowswithinhomogeneousrefractiveindices-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-fischer-avila-xu-measurementerroroftracerbasedvelocimetryinsinglephaseturbulentflowswithinhomogeneousrefractiveindices-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Measurement error of tracer-based velocimetry in single-phase turbulent flows with inhomogeneous refractive indices},\n type = {article},\n year = {2022},\n pages = {110681},\n volume = {136},\n publisher = {Elsevier},\n id = {da354753-86fa-3a69-a7da-6b8ddffc70ca},\n created = {2022-08-16T18:49:49.689Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:49.689Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Li, Huixin and Fischer, Andreas and Avila, Marc and Xu, Duo},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Time-resolved particle image velocimetry algorithm based on deep learning.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Guo,  C.; Fan,  Y.; Yu,  C.; Han,  Y.;  and Bi,  X.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Instrumentation and Measurement</i>, 71: 1-13.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Time-resolved particle image velocimetry algorithm based on deep learning},\n type = {article},\n year = {2022},\n pages = {1-13},\n volume = {71},\n publisher = {IEEE},\n id = {9c49832a-6f04-3f0f-8540-796901d759b3},\n created = {2022-08-16T18:49:50.093Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:50.093Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},\n journal = {IEEE Transactions on Instrumentation and Measurement}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-zhou-zhang-yang-anewsingleformulaforthelawofthewallanditsapplicationtowallmodeledlargeeddysimulation-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A new single formula for the law of the wall and its application to wall-modeled large-eddy simulation.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  F.; Zhou,  Z.; Zhang,  H.;  and Yang,  X.\n</span>\n\n  \n\n</span>\n\n  <i>European Journal of Mechanics-B/Fluids</i>, 94: 350-365.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-zhou-zhang-yang-anewsingleformulaforthelawofthewallanditsapplicationtowallmodeledlargeeddysimulation-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-zhou-zhang-yang-anewsingleformulaforthelawofthewallanditsapplicationtowallmodeledlargeeddysimulation-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A new single formula for the law of the wall and its application to wall-modeled large-eddy simulation},\n type = {article},\n year = {2022},\n pages = {350-365},\n volume = {94},\n publisher = {Elsevier},\n id = {7a93d5b9-8cff-39c6-9077-5beda17ae76b},\n created = {2022-08-16T18:49:50.525Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:50.525Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhang, Fengshun and Zhou, Zhideng and Zhang, Huan and Yang, Xiaolei},\n journal = {European Journal of Mechanics-B/Fluids}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bauer-schiepel-wagner-assimilationandextensionofparticleimagevelocimetrydataofturbulentrayleighbnardconvectionusingdirectnumericalsimulations-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Assimilation and extension of particle image velocimetry data of turbulent Rayleigh–Bénard convection using direct numerical simulations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bauer,  C.; Schiepel,  D.;  and Wagner,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 63(1): 1-17.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bauer-schiepel-wagner-assimilationandextensionofparticleimagevelocimetrydataofturbulentrayleighbnardconvectionusingdirectnumericalsimulations-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bauer-schiepel-wagner-assimilationandextensionofparticleimagevelocimetrydataofturbulentrayleighbnardconvectionusingdirectnumericalsimulations-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assimilation and extension of particle image velocimetry data of turbulent Rayleigh–Bénard convection using direct numerical simulations},\n type = {article},\n year = {2022},\n pages = {1-17},\n volume = {63},\n publisher = {Springer},\n id = {aa882f1e-7074-35ad-8323-95a3e0a83cf5},\n created = {2022-08-16T18:49:50.917Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:50.917Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bauer, Christian and Schiepel, Daniel and Wagner, Claus},\n journal = {Experiments in Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"engelmann-ihme-wlokas-kempf-towardsthesuitabilityofinformationentropyasanlesqualityindicator-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Towards the Suitability of Information Entropy as an LES Quality Indicator.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Engelmann,  L.; Ihme,  M.; Wlokas,  I.;  and Kempf,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Flow, Turbulence and Combustion</i>, 108(2): 353-385.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/engelmann-ihme-wlokas-kempf-towardsthesuitabilityofinformationentropyasanlesqualityindicator-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('engelmann-ihme-wlokas-kempf-towardsthesuitabilityofinformationentropyasanlesqualityindicator-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Towards the Suitability of Information Entropy as an LES Quality Indicator},\n type = {article},\n year = {2022},\n pages = {353-385},\n volume = {108},\n publisher = {Springer},\n id = {7714b46d-1937-3ca8-aed8-5f602a042e84},\n created = {2022-08-16T18:49:51.321Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:51.321Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Engelmann, L and Ihme, M and Wlokas, I and Kempf, A},\n journal = {Flow, Turbulence and Combustion},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Reinforcement Learning for Load-balanced Parallel Particle Tracing.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xu,  J.; Guo,  H.; Shen,  H.; Raj,  M.; Wurster,  S., W.;  and Peterka,  T.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xu-guo-shen-raj-wurster-peterka-reinforcementlearningforloadbalancedparallelparticletracing-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reinforcement Learning for Load-balanced Parallel Particle Tracing},\n type = {article},\n year = {2022},\n publisher = {IEEE},\n id = {84a43f5f-2bf0-3cc9-af06-a8457a0d5982},\n created = {2022-08-16T18:49:51.750Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:51.750Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Xu, Jiayi and Guo, Hanqi and Shen, Han-Wei and Raj, Mukund and Wurster, Skylar Wolfgang and Peterka, Tom},\n journal = {IEEE Transactions on Visualization and Computer Graphics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"asadi-kamruzzaman-hearst-theeffectofinletturbulenceonthequiescentcoreofturbulentchannelflow-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  The effect of inlet turbulence on the quiescent core of turbulent channel flow.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Asadi,  M.; Kamruzzaman,  M.;  and Hearst,  R., J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 935: A37.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/asadi-kamruzzaman-hearst-theeffectofinletturbulenceonthequiescentcoreofturbulentchannelflow-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('asadi-kamruzzaman-hearst-theeffectofinletturbulenceonthequiescentcoreofturbulentchannelflow-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The effect of inlet turbulence on the quiescent core of turbulent channel flow},\n type = {article},\n year = {2022},\n pages = {A37},\n volume = {935},\n publisher = {Cambridge University Press},\n id = {96824876-d7f8-331b-8e85-9a64b1213b5b},\n created = {2022-08-16T18:49:52.149Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-08-16T18:49:52.149Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Asadi, Masoud and Kamruzzaman, Md and Hearst, R Jason},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-duan-song-tang-cai-cnnbasedfluidmotionestimationusingcorrelationcoefficientandmultiscalecostvolume-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  CNN-Based Fluid Motion Estimation Using Correlation Coefficient and Multiscale Cost Volume.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  J.; Duan,  H.; Song,  Y.; Tang,  M.;  and Cai,  Z.\n</span>\n\n  \n\n</span>\n\n  <i>Electronics</i>, 11(24): 4159.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-duan-song-tang-cai-cnnbasedfluidmotionestimationusingcorrelationcoefficientandmultiscalecostvolume-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-duan-song-tang-cai-cnnbasedfluidmotionestimationusingcorrelationcoefficientandmultiscalecostvolume-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {CNN-Based Fluid Motion Estimation Using Correlation Coefficient and Multiscale Cost Volume},\n type = {article},\n year = {2022},\n pages = {4159},\n volume = {11},\n publisher = {MDPI},\n id = {0253b401-3565-3ce3-939e-1678d0fadaba},\n created = {2023-01-16T19:38:11.986Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:11.986Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chen, Jun and Duan, Hui and Song, Yuanxin and Tang, Ming and Cai, Zemin},\n journal = {Electronics},\n number = {24}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mamidala-weingrtner-fransson-acomparativestudyofexperimentswithnumericalsimulationsoffreestreamturbulencetransition-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A comparative study of experiments with numerical simulations of free-stream turbulence transition.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mamidala,  S., B.; Weingärtner,  A.;  and Fransson,  J., H., M.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 951: A46.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mamidala-weingrtner-fransson-acomparativestudyofexperimentswithnumericalsimulationsoffreestreamturbulencetransition-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mamidala-weingrtner-fransson-acomparativestudyofexperimentswithnumericalsimulationsoffreestreamturbulencetransition-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A comparative study of experiments with numerical simulations of free-stream turbulence transition},\n type = {article},\n year = {2022},\n pages = {A46},\n volume = {951},\n publisher = {Cambridge University Press},\n id = {325b7a53-196c-3339-8885-a83068d36477},\n created = {2023-01-16T19:38:12.459Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:12.459Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Mamidala, Santhosh B and Weingärtner, André and Fransson, Jens H M},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ross-matulis-bindra-astatisticalapproachtoquantifytaylormicroscaleforturbulentflowsurrogatemodel-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A Statistical Approach to Quantify Taylor Microscale for Turbulent Flow Surrogate Model.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ross,  M.; Matulis,  J.;  and Bindra,  H.\n</span>\n\n  \n\n</span>\n\n  In <i>International Conference on Nuclear Engineering</i>, volume 86502, pages V015T16A045,  2022. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ross-matulis-bindra-astatisticalapproachtoquantifytaylormicroscaleforturbulentflowsurrogatemodel-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ross-matulis-bindra-astatisticalapproachtoquantifytaylormicroscaleforturbulentflowsurrogatemodel-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {A Statistical Approach to Quantify Taylor Microscale for Turbulent Flow Surrogate Model},\n type = {inproceedings},\n year = {2022},\n pages = {V015T16A045},\n volume = {86502},\n id = {d2ef8307-0962-3e09-8403-4dccb69c227e},\n created = {2023-01-16T19:38:12.904Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:12.904Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Ross, Molly and Matulis, John and Bindra, Hitesh},\n booktitle = {International Conference on Nuclear Engineering}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"meneveau-colmcille-introducingjfmnotebooks-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Introducing JFM Notebooks.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Meneveau,  C.;  and Colm-cille,  P., C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 952: E1.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/meneveau-colmcille-introducingjfmnotebooks-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('meneveau-colmcille-introducingjfmnotebooks-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Introducing JFM Notebooks},\n type = {article},\n year = {2022},\n pages = {E1},\n volume = {952},\n publisher = {Cambridge University Press},\n id = {d6d08684-afea-34be-8623-15d934a43b4e},\n created = {2023-01-16T19:38:13.352Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:13.352Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Meneveau, Charles and Colm-cille, P Caulfield},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gemes-sanmiguelvila-discetti-superresolutiongenerativeadversarialnetworksofrandomlyseededfields-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Super-resolution generative adversarial networks of randomly-seeded fields.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Güemes,  A.; Sanmiguel Vila,  C.;  and Discetti,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Machine Intelligence</i>, 4(12): 1165-1173.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gemes-sanmiguelvila-discetti-superresolutiongenerativeadversarialnetworksofrandomlyseededfields-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gemes-sanmiguelvila-discetti-superresolutiongenerativeadversarialnetworksofrandomlyseededfields-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Super-resolution generative adversarial networks of randomly-seeded fields},\n type = {article},\n year = {2022},\n pages = {1165-1173},\n volume = {4},\n publisher = {Nature Publishing Group},\n id = {19179399-f840-335e-8a66-ae9396e7f781},\n created = {2023-01-16T19:38:13.794Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:13.794Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Güemes, Alejandro and Sanmiguel Vila, Carlos and Discetti, Stefano},\n journal = {Nature Machine Intelligence},\n number = {12}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bi-liu-fan-yu-zhang-flowsrnetamultiscaleintegrationnetworkforsuperresolutionreconstructionoffluidflows-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  FlowSRNet: A multi-scale integration network for super-resolution reconstruction of fluid flows.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bi,  X.; Liu,  A.; Fan,  Y.; Yu,  C.;  and Zhang,  Z.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 34(12): 127104.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bi-liu-fan-yu-zhang-flowsrnetamultiscaleintegrationnetworkforsuperresolutionreconstructionoffluidflows-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bi-liu-fan-yu-zhang-flowsrnetamultiscaleintegrationnetworkforsuperresolutionreconstructionoffluidflows-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {FlowSRNet: A multi-scale integration network for super-resolution reconstruction of fluid flows},\n type = {article},\n year = {2022},\n pages = {127104},\n volume = {34},\n publisher = {AIP Publishing LLC},\n id = {5b9ead7e-22cb-32f0-8e8b-6276d20a6a77},\n created = {2023-01-16T19:38:14.257Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:14.257Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bi, Xiaojun and Liu, Ankang and Fan, Yiwei and Yu, Changdong and Zhang, Zefeng},\n journal = {Physics of Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chong-liang-chen-xu-pan-unsupervisedlearningonparticleimagevelocimetrywithembeddedcrosscorrelationanddivergencefreeconstraint-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Unsupervised learning on particle image velocimetry with embedded cross-correlation and divergence-free constraint.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chong,  Y.; Liang,  J.; Chen,  T.; Xu,  C.;  and Pan,  C.\n</span>\n\n  \n\n</span>\n\n  <i>IET Cyber-Systems and Robotics</i>, 4(3): 200-211.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chong-liang-chen-xu-pan-unsupervisedlearningonparticleimagevelocimetrywithembeddedcrosscorrelationanddivergencefreeconstraint-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chong-liang-chen-xu-pan-unsupervisedlearningonparticleimagevelocimetrywithembeddedcrosscorrelationanddivergencefreeconstraint-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Unsupervised learning on particle image velocimetry with embedded cross-correlation and divergence-free constraint},\n type = {article},\n year = {2022},\n pages = {200-211},\n volume = {4},\n publisher = {Wiley Online Library},\n id = {62352bc3-1ed2-35d3-8fca-cc011af11df7},\n created = {2023-01-16T19:38:14.686Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:14.686Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chong, Yiwei and Liang, Jiaming and Chen, Tehuan and Xu, Chao and Pan, Changchun},\n journal = {IET Cyber-Systems and Robotics},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hsu-kaufman-glimm-scalinglawsforpartiallydevelopedturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Scaling laws for partially developed turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hsu,  A.; Kaufman,  R.;  and Glimm,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Frontiers in Applied Mathematics and Statistics</i>, 7: 91.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hsu-kaufman-glimm-scalinglawsforpartiallydevelopedturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hsu-kaufman-glimm-scalinglawsforpartiallydevelopedturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Scaling laws for partially developed turbulence},\n type = {article},\n year = {2022},\n pages = {91},\n volume = {7},\n publisher = {Frontiers},\n id = {7f7c7f7c-6741-325d-86e1-cc299943ae28},\n created = {2023-01-16T19:38:15.123Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:15.123Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hsu, Abigail and Kaufman, Ryan and Glimm, James},\n journal = {Frontiers in Applied Mathematics and Statistics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"manickathan-mucignat-lunati-kinematictrainingofconvolutionalneuralnetworksforparticleimagevelocimetry-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Kinematic training of convolutional neural networks for particle image velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Manickathan,  L.; Mucignat,  C.;  and Lunati,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 33(12): 124006.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/manickathan-mucignat-lunati-kinematictrainingofconvolutionalneuralnetworksforparticleimagevelocimetry-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('manickathan-mucignat-lunati-kinematictrainingofconvolutionalneuralnetworksforparticleimagevelocimetry-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Kinematic training of convolutional neural networks for particle image velocimetry},\n type = {article},\n year = {2022},\n pages = {124006},\n volume = {33},\n publisher = {IOP Publishing},\n id = {9d411d45-c4cb-348e-9ced-640d705fecf9},\n created = {2023-01-16T19:38:15.568Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:15.568Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Manickathan, Lento and Mucignat, Claudio and Lunati, Ivan},\n journal = {Measurement Science and Technology},\n number = {12}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lemoine-firstprinciplesfermiaccelerationinmagnetizedturbulence-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  First-principles Fermi acceleration in magnetized turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lemoine,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 129(21): 215101.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lemoine-firstprinciplesfermiaccelerationinmagnetizedturbulence-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lemoine-firstprinciplesfermiaccelerationinmagnetizedturbulence-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {First-principles Fermi acceleration in magnetized turbulence},\n type = {article},\n year = {2022},\n pages = {215101},\n volume = {129},\n publisher = {APS},\n id = {ada389de-a192-3a29-a6c0-cb07b7975146},\n created = {2023-01-16T19:38:15.996Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:15.996Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lemoine, Martin},\n journal = {Physical Review Letters},\n number = {21}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-chen-wu-ruan-li-depositionvelocityofinertialparticlesdrivenbywallnormalexternalforceinturbulentchannelflow-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deposition velocity of inertial particles driven by wall-normal external force in turbulent channel flow.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  P.; Chen,  S.; Wu,  T.; Ruan,  X.;  and Li,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 7(10): 104301.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-chen-wu-ruan-li-depositionvelocityofinertialparticlesdrivenbywallnormalexternalforceinturbulentchannelflow-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-chen-wu-ruan-li-depositionvelocityofinertialparticlesdrivenbywallnormalexternalforceinturbulentchannelflow-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deposition velocity of inertial particles driven by wall-normal external force in turbulent channel flow},\n type = {article},\n year = {2022},\n pages = {104301},\n volume = {7},\n publisher = {APS},\n id = {26bdcf78-8605-3892-ba0a-4175b474c7c4},\n created = {2023-01-16T19:38:16.436Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-01-16T19:38:16.436Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chen, Pinzhuo and Chen, Sheng and Wu, Tianyi and Ruan, Xuan and Li, Shuiqing},\n journal = {Physical Review Fluids},\n number = {10}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"karpov-huang-sitdikov-fryer-woosley-pilania-physicsinformedmachinelearningformodelingturbulenceinsupernovae-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Physics-informed Machine Learning for Modeling Turbulence in Supernovae.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Karpov,  P., I.; Huang,  C.; Sitdikov,  I.; Fryer,  C., L.; Woosley,  S.;  and Pilania,  G.\n</span>\n\n  \n\n</span>\n\n  <i>The Astrophysical Journal</i>, 940(1): 26.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/karpov-huang-sitdikov-fryer-woosley-pilania-physicsinformedmachinelearningformodelingturbulenceinsupernovae-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('karpov-huang-sitdikov-fryer-woosley-pilania-physicsinformedmachinelearningformodelingturbulenceinsupernovae-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Physics-informed Machine Learning for Modeling Turbulence in Supernovae},\n type = {article},\n year = {2022},\n pages = {26},\n volume = {940},\n publisher = {IOP Publishing},\n id = {22d36f4f-b027-336e-827d-7bea81c25139},\n created = {2023-06-10T01:46:17.632Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T01:46:17.632Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Karpov, Platon I and Huang, Chengkun and Sitdikov, Iskandar and Fryer, Chris L and Woosley, Stan and Pilania, Ghanshyam},\n journal = {The Astrophysical Journal},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"majewski-bouchahda-ayari-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2022\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Study of cardiac fluid dynamics in the right side of the heart with AI PIV.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Majewski,  W.; Bouchahda,  N.; Ayari,  R.;  and Wei,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Flow Visualization and Image Processing</i>.  2022.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/majewski-bouchahda-ayari-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2022\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('majewski-bouchahda-ayari-wei-studyofcardiacfluiddynamicsintherightsideoftheheartwithaipiv-2022')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Study of cardiac fluid dynamics in the right side of the heart with AI PIV.},\n type = {article},\n year = {2022},\n publisher = {Begel House Inc.},\n id = {7733a508-6bea-334c-93a8-5b2818334bc6},\n created = {2023-06-10T01:46:18.086Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2023-06-10T01:46:18.086Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Majewski, Wojciech and Bouchahda, Nidhal and Ayari, Rim and Wei, Runjie},\n journal = {Journal of Flow Visualization and Image Processing}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2021\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2021')\"\n      onkeypress=\"toggleGroup('group_2021')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2021</span>\n      <span class=\"bibbase_group_count\">\n        \n        (48)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/6f43832b-e4b2-6c9f-215b-68e89bbcee1d/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/6f43832b-e4b2-6c9f-215b-68e89bbcee1d/full_text.pdf.pdf', event);\">\n    Learning dominant physical processes with data-driven balance models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Callaham,  J., L.; Koch,  J., V.; Brunton,  B., W.; Kutz,  J., N.;  and Brunton,  S., L.\n</span>\n\n  \n\n</span>\n\n  <i>Nature Communications</i>, 12(1): 1-10. 12 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/6f43832b-e4b2-6c9f-215b-68e89bbcee1d/full_text.pdf.pdf\"\n     onclick=\"log_download('callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/6f43832b-e4b2-6c9f-215b-68e89bbcee1d/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Learning dominant physical processes with data-driven balance models [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1038/s41467-021-21331-z\"\n     onclick=\"log_download('callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021', 'https://doi.org/10.1038/s41467-021-21331-z', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Learning dominant physical processes with data-driven balance models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/s41467-021-21331-z\"\n     onclick=\"log_download('callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021', 'http://doi.org/10.1038/s41467-021-21331-z', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Learning dominant physical processes with data-driven balance models},\n type = {article},\n year = {2021},\n keywords = {Applied mathematics,Computational science,Physics},\n pages = {1-10},\n volume = {12},\n websites = {https://doi.org/10.1038/s41467-021-21331-z},\n month = {12},\n publisher = {Nature Research},\n day = {1},\n id = {65773184-a381-3802-8cef-979c7b013b38},\n created = {2021-04-09T15:23:02.935Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:10.405Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only applies in asymptotic regimes where there is a strict separation of scales in the physics. Here, we automate and generalize this approach to non-asymptotic regimes by introducing the idea of an equation space, in which different local balances appear as distinct subspace clusters. Unsupervised learning can then automatically identify regions where groups of terms may be neglected. We show that our data-driven balance models successfully delineate dominant balance physics in a much richer class of systems. In particular, this approach uncovers key mechanistic models in turbulence, combustion, nonlinear optics, geophysical fluids, and neuroscience.},\n bibtype = {article},\n author = {Callaham, Jared L. and Koch, James V. and Brunton, Bingni W. and Kutz, J. Nathan and Brunton, Steven L.},\n doi = {10.1038/s41467-021-21331-z},\n journal = {Nature Communications},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only applies in asymptotic regimes where there is a strict separation of scales in the physics. Here, we automate and generalize this approach to non-asymptotic regimes by introducing the idea of an equation space, in which different local balances appear as distinct subspace clusters. Unsupervised learning can then automatically identify regions where groups of terms may be neglected. We show that our data-driven balance models successfully delineate dominant balance physics in a much richer class of systems. In particular, this approach uncovers key mechanistic models in turbulence, combustion, nonlinear optics, geophysical fluids, and neuroscience.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jin,  X.; Cai,  S.; Li,  H.;  and Karniadakis,  G., E.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Computational Physics</i>, 426: 109951. 2 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jcp.2020.109951\"\n     onclick=\"log_download('jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021', 'http://doi.org/10.1016/j.jcp.2020.109951', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations},\n type = {article},\n year = {2021},\n keywords = {Ill-posed problems,PINNs,Transfer learning,Turbulence,Velocity-pressure formulation,Vorticity-velocity formulation},\n pages = {109951},\n volume = {426},\n month = {2},\n publisher = {Academic Press Inc.},\n day = {1},\n id = {e3efa042-5d37-39e7-bce7-85eb007e210c},\n created = {2021-04-09T15:23:03.649Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:03.649Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at Reτ∼1,000, but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. We also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.},\n bibtype = {article},\n author = {Jin, Xiaowei and Cai, Shengze and Li, Hui and Karniadakis, George Em},\n doi = {10.1016/j.jcp.2020.109951},\n journal = {Journal of Computational Physics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In the last 50 years there has been a tremendous progress in solving numerically the Navier-Stokes equations using finite differences, finite elements, spectral, and even meshless methods. Yet, in many real cases, we still cannot incorporate seamlessly (multi-fidelity) data into existing algorithms, and for industrial-complexity applications the mesh generation is time consuming and still an art. Moreover, solving ill-posed problems (e.g., lacking boundary conditions) or inverse problems is often prohibitively expensive and requires different formulations and new computer codes. Here, we employ physics-informed neural networks (PINNs), encoding the governing equations directly into the deep neural network via automatic differentiation, to overcome some of the aforementioned limitations for simulating incompressible laminar and turbulent flows. We develop the Navier-Stokes flow nets (NSFnets) by considering two different mathematical formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. Since this is a new approach, we first select some standard benchmark problems to assess the accuracy, convergence rate, computational cost and flexibility of NSFnets; analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. This is unsupervised learning and, hence, no labeled data are required beyond boundary and initial conditions and the fluid properties. The residuals of the VP or VV governing equations, together with the initial and boundary conditions, are embedded into the loss function of the NSFnets. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without extra computational cost. Unlike the traditional numerical methods, NSFnets inherit the properties of neural networks (NNs), hence the total error is composed of the approximation, the optimization, and the generalization errors. Here, we empirically attempt to quantify these errors by varying the sampling (“residual”) points, the iterative solvers, and the size of the NN architecture. For the laminar flow solutions, we show that both the VP and the VV formulations are comparable in accuracy but their best performance corresponds to different NN architectures. The initial convergence rate is fast but the error eventually saturates to a plateau due to the dominance of the optimization error. For the turbulent channel flow, we show that NSFnets can sustain turbulence at Reτ∼1,000, but due to expensive training we only consider part of the channel domain and enforce velocity boundary conditions on the subdomain boundaries provided by the DNS data base. We also perform a systematic study on the weights used in the loss function for balancing the data and physics components, and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. In the last part, we demonstrate how NSFnets should be used in practice, namely for ill-posed problems with incomplete or noisy boundary conditions as well as for inverse problems. We obtain reasonably accurate solutions for such cases as well without the need to change the NSFnets and at the same computational cost as in the forward well-posed problems. We also present a simple example of transfer learning that will aid in accelerating the training of NSFnets for different parameter settings.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021', 'https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756', event);\">\n    Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jie,  Y.; Andersson,  H., I.;  and Zhao,  L.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Multiphase Flow</i>,103627. 3 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756\"\n     onclick=\"log_download('jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021', 'https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ijmultiphaseflow.2021.103627\"\n     onclick=\"log_download('jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021', 'http://doi.org/10.1016/j.ijmultiphaseflow.2021.103627', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles},\n type = {article},\n year = {2021},\n pages = {103627},\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0301932221000756},\n month = {3},\n publisher = {Pergamon},\n day = {13},\n id = {f2cc069f-bc29-3f68-8cc6-734cd5d5244a},\n created = {2021-04-09T15:23:04.654Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:04.654Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Jie, Yucheng and Andersson, Helge I. and Zhao, Lihao},\n doi = {10.1016/j.ijmultiphaseflow.2021.103627},\n journal = {International Journal of Multiphase Flow}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021', 'https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665', event);\">\n    Optimal clipping of the gradient model for subgrid stress closure.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Prakash,  A.; Jansen,  K., E.;  and Evans,  J., A.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA Scitech 2021 Forum</i>, pages 1-16,  2021. American Institute of Aeronautics and Astronautics Inc, AIAA\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665\"\n     onclick=\"log_download('prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021', 'https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Optimal clipping of the gradient model for subgrid stress closure [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2021-1665\"\n     onclick=\"log_download('prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021', 'http://doi.org/10.2514/6.2021-1665', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Optimal clipping of the gradient model for subgrid stress closure},\n type = {inproceedings},\n year = {2021},\n pages = {1-16},\n websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2021-1665},\n publisher = {American Institute of Aeronautics and Astronautics Inc, AIAA},\n id = {2a8d900a-b84e-3601-9ead-56f37770b12a},\n created = {2021-04-09T15:23:05.122Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:05.122Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Large Eddy Simulation (LES) involves modeling of the Subgrid Stress (SGS) tensor to close the set of filtered Navier-Stokes equations. The gradient model is a well-known candidate for SGS closure. Stresses obtained using the gradient model have high structural accuracy, that is, these stresses are in high correlation with those from the filtered DNS data in a priori studies. However, a posteriori simulations at a high Reynolds number are subject to energy pileup at small resolved scales due in part to model backscatter that often cascades to numerical instabilities. The modeled stresses are often clipped to eliminate model backscatter and, thereby, improve the dissipative performance and stability of these simulations. However, this comes at the cost of reduced structural accuracy. In this paper, we propose an optimal clipping procedure that recasts the operation as a minimization problem. The proposed clipping ensures that the impact of clipping on the structural accuracy is minimal and, at the same time, there is no model backscatter. We demonstrate the resulting model form is similar to that of mixed models. We conduct a series of a priori and a posteriori tests to investigate the impact of the traditional and optimal clipping procedures. We observe that optimal clipping leads to a significant improvement in model predictions as compared to the traditional clipping procedure for select forced homogeneous isotropic turbulence, Taylor-Green vortex, and channel flow cases.},\n bibtype = {inproceedings},\n author = {Prakash, Aviral and Jansen, Kenneth E. and Evans, John A.},\n doi = {10.2514/6.2021-1665},\n booktitle = {AIAA Scitech 2021 Forum}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Large Eddy Simulation (LES) involves modeling of the Subgrid Stress (SGS) tensor to close the set of filtered Navier-Stokes equations. The gradient model is a well-known candidate for SGS closure. Stresses obtained using the gradient model have high structural accuracy, that is, these stresses are in high correlation with those from the filtered DNS data in a priori studies. However, a posteriori simulations at a high Reynolds number are subject to energy pileup at small resolved scales due in part to model backscatter that often cascades to numerical instabilities. The modeled stresses are often clipped to eliminate model backscatter and, thereby, improve the dissipative performance and stability of these simulations. However, this comes at the cost of reduced structural accuracy. In this paper, we propose an optimal clipping procedure that recasts the operation as a minimization problem. The proposed clipping ensures that the impact of clipping on the structural accuracy is minimal and, at the same time, there is no model backscatter. We demonstrate the resulting model form is similar to that of mixed models. We conduct a series of a priori and a posteriori tests to investigate the impact of the traditional and optimal clipping procedures. We observe that optimal clipping leads to a significant improvement in model predictions as compared to the traditional clipping procedure for select forced homogeneous isotropic turbulence, Taylor-Green vortex, and channel flow cases.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0d1359ff-3618-0b5d-7f96-5a53b43cf77d/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0d1359ff-3618-0b5d-7f96-5a53b43cf77d/full_text.pdf.pdf', event);\">\n    A study of inner-outer interactions in turbulent channel flows by interactive POD.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  H.;  and Gao,  Q.\n</span>\n\n  \n\n</span>\n\n  <i>Theoretical and Applied Mechanics Letters</i>,100222. 2 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0d1359ff-3618-0b5d-7f96-5a53b43cf77d/full_text.pdf.pdf\"\n     onclick=\"log_download('wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0d1359ff-3618-0b5d-7f96-5a53b43cf77d/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"A study of inner-outer interactions in turbulent channel flows by interactive POD [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.taml.2021.100222\"\n     onclick=\"log_download('wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021', 'http://doi.org/10.1016/j.taml.2021.100222', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-gao-astudyofinnerouterinteractionsinturbulentchannelflowsbyinteractivepod-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A study of inner-outer interactions in turbulent channel flows by interactive POD},\n type = {article},\n year = {2021},\n pages = {100222},\n month = {2},\n publisher = {Elsevier BV},\n day = {17},\n id = {277fb85f-9a1c-3648-bf9c-83b446322b79},\n created = {2021-04-09T15:23:06.538Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:12.377Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Hongping and Gao, Qi},\n doi = {10.1016/j.taml.2021.100222},\n journal = {Theoretical and Applied Mechanics Letters}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/099473ef-efff-cf7b-6b5d-b881174cf8a9/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/099473ef-efff-cf7b-6b5d-b881174cf8a9/full_text.pdf.pdf', event);\">\n    Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R <sub>eτ</sub> = 150, 400 and 1020.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ahmed,  U.; Apsley,  D.; Stallard,  T.; Stansby,  P.;  and Afgan,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydraulic Research</i>, 59(1): 36-50. 1 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/099473ef-efff-cf7b-6b5d-b881174cf8a9/full_text.pdf.pdf\"\n     onclick=\"log_download('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/099473ef-efff-cf7b-6b5d-b881174cf8a9/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R &lt;sub&gt;eτ&lt;/sub&gt; = 150, 400 and 1020 [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\"\n     onclick=\"log_download('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021', 'https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R &lt;sub&gt;eτ&lt;/sub&gt; = 150, 400 and 1020 [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/00221686.2020.1729265\"\n     onclick=\"log_download('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021', 'http://doi.org/10.1080/00221686.2020.1729265', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersrsubesub150400and1020-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R &lt;sub&gt;eτ&lt;/sub&gt; = 150, 400 and 1020},\n type = {article},\n year = {2021},\n keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},\n pages = {36-50},\n volume = {59},\n websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},\n month = {1},\n publisher = {Taylor and Francis Ltd.},\n day = {2},\n id = {bff8a865-3735-375b-b7b6-a81a95dfcd66},\n created = {2021-04-09T15:23:07.047Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:12.855Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},\n bibtype = {article},\n author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},\n doi = {10.1080/00221686.2020.1729265},\n journal = {Journal of Hydraulic Research},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jia-kikumoto-constructionofurbanturbulentflowdatabasewithwaveletbasedcompressionastudywithlargeeddysimulationofflowanddispersioninblockarrayedbuildinggroupmodel-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Construction of urban turbulent flow database with wavelet-based compression: A study with large-eddy simulation of flow and dispersion in block-arrayed building group model.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jia,  H.;  and Kikumoto,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Wind Engineering and Industrial Aerodynamics</i>, 208: 104433. 1 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.jweia.2020.104433\"\n     onclick=\"log_download('jia-kikumoto-constructionofurbanturbulentflowdatabasewithwaveletbasedcompressionastudywithlargeeddysimulationofflowanddispersioninblockarrayedbuildinggroupmodel-2021', 'http://doi.org/10.1016/j.jweia.2020.104433', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jia-kikumoto-constructionofurbanturbulentflowdatabasewithwaveletbasedcompressionastudywithlargeeddysimulationofflowanddispersioninblockarrayedbuildinggroupmodel-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jia-kikumoto-constructionofurbanturbulentflowdatabasewithwaveletbasedcompressionastudywithlargeeddysimulationofflowanddispersioninblockarrayedbuildinggroupmodel-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Construction of urban turbulent flow database with wavelet-based compression: A study with large-eddy simulation of flow and dispersion in block-arrayed building group model},\n type = {article},\n year = {2021},\n keywords = {Computational fluid dynamics,Data compression,Dispersion simulation,Large-eddy simulation,Urban flow database,Wavelet transform},\n pages = {104433},\n volume = {208},\n month = {1},\n publisher = {Elsevier B.V.},\n day = {1},\n id = {e2b98148-30c1-35b0-a10e-b9b35cd10e46},\n created = {2021-04-09T15:23:07.512Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:07.512Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Urban Turbulent flow database, which includes accurately simulated velocity field with full spatial distribution and time-dependent dynamics, is beneficial for fast analysis of pollutant dispersion and comprehensive validation. However, the enormous data volume makes storage and sharing difficult. This research investigated the feasibility of constructing a small-sized database by compression. A wavelet-based compression method was selected because of its light calculation burden and independence of time series data. The database of the flow field in urban-like arrayed blocks was obtained by large-eddy simulation, and then the velocity and diffusion coefficient fields were compressed with different error controls to construct databases. The compression ability of the wavelet-based method was evaluated, and it was found that the maximum compression ratio is reached when most information in the wavelet coefficients is discarded. The effects of compression error on both the single snapshot and the time-series results were studied. The applicability of the compressed database was verified by the resimulation of passive scalar dispersion in the flow. According to results, the database with approximately 100-times compression is suitable for such applications as the visualization and dispersion simulation of passive scalars with sufficient accuracy.},\n bibtype = {article},\n author = {Jia, Hongyuan and Kikumoto, Hideki},\n doi = {10.1016/j.jweia.2020.104433},\n journal = {Journal of Wind Engineering and Industrial Aerodynamics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Urban Turbulent flow database, which includes accurately simulated velocity field with full spatial distribution and time-dependent dynamics, is beneficial for fast analysis of pollutant dispersion and comprehensive validation. However, the enormous data volume makes storage and sharing difficult. This research investigated the feasibility of constructing a small-sized database by compression. A wavelet-based compression method was selected because of its light calculation burden and independence of time series data. The database of the flow field in urban-like arrayed blocks was obtained by large-eddy simulation, and then the velocity and diffusion coefficient fields were compressed with different error controls to construct databases. The compression ability of the wavelet-based method was evaluated, and it was found that the maximum compression ratio is reached when most information in the wavelet coefficients is discarded. The effects of compression error on both the single snapshot and the time-series results were studied. The applicability of the compressed database was verified by the resimulation of passive scalar dispersion in the flow. According to results, the database with approximately 100-times compression is suitable for such applications as the visualization and dispersion simulation of passive scalars with sufficient accuracy.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5a1e3df4-a7be-35cb-1a7b-3136a38cfd59/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5a1e3df4-a7be-35cb-1a7b-3136a38cfd59/full_text.pdf.pdf', event);\">\n    Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fratantonio,  D.; Lai,  C., C., K.; Charonko,  J.;  and Prestridge,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 62(4): 84. 4 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5a1e3df4-a7be-35cb-1a7b-3136a38cfd59/full_text.pdf.pdf\"\n     onclick=\"log_download('fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5a1e3df4-a7be-35cb-1a7b-3136a38cfd59/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-021-03156-0\"\n     onclick=\"log_download('fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021', 'http://link.springer.com/10.1007/s00348-021-03156-0', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-021-03156-0\"\n     onclick=\"log_download('fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021', 'http://doi.org/10.1007/s00348-021-03156-0', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fratantonio-lai-charonko-prestridge-beyondtaylorshypothesisanovelvolumetricreconstructionofvelocityanddensityfieldsforvariabledensityandshearflows-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable-density and shear flows},\n type = {article},\n year = {2021},\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\n pages = {84},\n volume = {62},\n websites = {http://link.springer.com/10.1007/s00348-021-03156-0},\n month = {4},\n publisher = {Springer},\n day = {31},\n id = {96e37199-25a7-3e0b-849d-8fbb8637bf75},\n created = {2021-04-09T15:23:08.214Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:13.472Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor&#x27;s hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian-Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor&#x27;s hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier-Stokes equations compared to the mean flow convective method.},\n bibtype = {article},\n author = {Fratantonio, Dominique and Lai, Chris C. K. and Charonko, John and Prestridge, Kathy},\n doi = {10.1007/s00348-021-03156-0},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor's hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian-Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor's hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier-Stokes equations compared to the mean flow convective method.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021', 'https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta', event);\">\n    Vision-based correspondence using relaxation algorithms for particle tracking velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Benkovic,  T.; Krawczynski,  J.;  and Druault,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 32(2): 25303. 4 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta\"\n     onclick=\"log_download('benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021', 'https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Vision-based correspondence using relaxation algorithms for particle tracking velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/abb437\"\n     onclick=\"log_download('benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021', 'http://doi.org/10.1088/1361-6501/abb437', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('benkovic-krawczynski-druault-visionbasedcorrespondenceusingrelaxationalgorithmsforparticletrackingvelocimetry-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vision-based correspondence using relaxation algorithms for particle tracking velocimetry},\n type = {article},\n year = {2021},\n pages = {25303},\n volume = {32},\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/abb437,https://iopscience.iop.org/article/10.1088/1361-6501/abb437/meta},\n month = {4},\n publisher = {IOP Publishing},\n id = {750f71b5-9fd8-3a2b-96db-645511a456fb},\n created = {2021-04-09T15:25:03.224Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:03.224Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Benkovic, Théo and Krawczynski, Jean-François and Druault, Philippe},\n doi = {10.1088/1361-6501/abb437},\n journal = {Measurement Science and Technology},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/112ac63e-5f1c-1b03-61f7-534e4ae5b885/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/112ac63e-5f1c-1b03-61f7-534e4ae5b885/full_text.pdf.pdf', event);\">\n    A perspective on machine learning methods in turbulence modeling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Beck,  A.;  and Kurz,  M.\n</span>\n\n  \n\n</span>\n\n  <i>GAMM-Mitteilungen</i>, 44(1): e202100002. 3 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/112ac63e-5f1c-1b03-61f7-534e4ae5b885/full_text.pdf.pdf\"\n     onclick=\"log_download('beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/112ac63e-5f1c-1b03-61f7-534e4ae5b885/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"A perspective on machine learning methods in turbulence modeling [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002\"\n     onclick=\"log_download('beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021', 'https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A perspective on machine learning methods in turbulence modeling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/gamm.202100002\"\n     onclick=\"log_download('beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021', 'http://doi.org/10.1002/gamm.202100002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('beck-kurz-aperspectiveonmachinelearningmethodsinturbulencemodeling-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A perspective on machine learning methods in turbulence modeling},\n type = {article},\n year = {2021},\n keywords = {LES,RANS,closure models,machine learning,turbulence simulation},\n pages = {e202100002},\n volume = {44},\n websites = {https://onlinelibrary.wiley.com/doi/10.1002/gamm.202100002},\n month = {3},\n publisher = {John Wiley and Sons Inc},\n day = {4},\n id = {6e94090b-dae2-3ea5-ac66-dbb72308e871},\n created = {2021-04-13T18:26:48.366Z},\n accessed = {2021-04-13},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-13T18:26:49.437Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues but also on the advantages and promises of machine learning (ML) methods applied to parameter estimation, model identification, closure term reconstruction, and beyond, mostly from the perspective of large Eddy simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics, and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. In this study, we present a survey of the current data-driven model concepts and methods, highlight important developments, and put them into the context of the discussed challenges.},\n bibtype = {article},\n author = {Beck, Andrea and Kurz, Marius},\n doi = {10.1002/gamm.202100002},\n journal = {GAMM-Mitteilungen},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues but also on the advantages and promises of machine learning (ML) methods applied to parameter estimation, model identification, closure term reconstruction, and beyond, mostly from the perspective of large Eddy simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics, and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. In this study, we present a survey of the current data-driven model concepts and methods, highlight important developments, and put them into the context of the discussed challenges.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gross-gumhold-advancedrenderingoflinedatawithambientocclusionandtransparency-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Advanced Rendering of Line Data with Ambient Occlusion and Transparency.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gross,  D.;  and Gumhold,  S.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>, 27(2): 614-624. 2 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2020.3028954\"\n     onclick=\"log_download('gross-gumhold-advancedrenderingoflinedatawithambientocclusionandtransparency-2021', 'http://doi.org/10.1109/TVCG.2020.3028954', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gross-gumhold-advancedrenderingoflinedatawithambientocclusionandtransparency-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gross-gumhold-advancedrenderingoflinedatawithambientocclusionandtransparency-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Advanced Rendering of Line Data with Ambient Occlusion and Transparency},\n type = {article},\n year = {2021},\n keywords = {Scientific visualization,line rendering,ray-casting,transparency},\n pages = {614-624},\n volume = {27},\n month = {2},\n publisher = {IEEE Computer Society},\n day = {1},\n id = {5529d502-fd6d-310f-afa4-2deafd97a98c},\n created = {2021-04-13T18:57:54.824Z},\n accessed = {2021-04-13},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-13T18:57:54.824Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.},\n bibtype = {article},\n author = {Gross, David and Gumhold, Stefan},\n doi = {10.1109/TVCG.2020.3028954},\n journal = {IEEE Transactions on Visualization and Computer Graphics},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  3D Lines are a widespread rendering primitive for the visualization of data from research fields like fluid dynamics or fiber tractography. Global illumination effects and transparent rendering improve the perception of three-dimensional features and decrease occlusion within the data set, thus enabling better understanding of complex line data. We present an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. Our approach builds on GPU-based raycasting of rounded cones, which are geometric primitives similar to truncated cones, but with spherical endcaps. Object space ambient occlusion is provided by an efficient voxel cone tracing approach. Our core contribution is a new fragment visibility sorting strategy that allows for interactive visualization of line data sets with millions of line segments. We improve performance further by exploiting hierarchical opacity maps.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-krishna-luhar-hemati-modelbasedmultisensorfusionforreconstructingwallboundedturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Model-based multi-sensor fusion for reconstructing wall-bounded turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  M.; Krishna,  C., V.; Luhar,  M.;  and Hemati,  M., S.\n</span>\n\n  \n\n</span>\n\n  <i>Theoretical and Computational Fluid Dynamics</i>, 35(5): 683-707. 10 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00162-021-00586-8\"\n     onclick=\"log_download('wang-krishna-luhar-hemati-modelbasedmultisensorfusionforreconstructingwallboundedturbulence-2021', 'http://doi.org/10.1007/s00162-021-00586-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-krishna-luhar-hemati-modelbasedmultisensorfusionforreconstructingwallboundedturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-krishna-luhar-hemati-modelbasedmultisensorfusionforreconstructingwallboundedturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Model-based multi-sensor fusion for reconstructing wall-bounded turbulence},\n type = {article},\n year = {2021},\n pages = {683-707},\n volume = {35},\n month = {10},\n day = {22},\n id = {349c86f2-eb91-3217-a7db-d8f1c622711a},\n created = {2022-02-20T21:37:29.373Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-20T21:37:29.373Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Mengying and Krishna, C. Vamsi and Luhar, Mitul and Hemati, Maziar S.},\n doi = {10.1007/s00162-021-00586-8},\n journal = {Theoretical and Computational Fluid Dynamics},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pulido-dasilva-livescu-hamann-multiresolutionclassificationofturbulencefeaturesinimagedatathroughmachinelearning-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Multiresolution classification of turbulence features in image data through machine learning.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pulido,  J.; da Silva,  R., D.; Livescu,  D.;  and Hamann,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Computers & Fluids</i>, 214: 104770. 1 2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/J.COMPFLUID.2020.104770\"\n     onclick=\"log_download('pulido-dasilva-livescu-hamann-multiresolutionclassificationofturbulencefeaturesinimagedatathroughmachinelearning-2021', 'http://doi.org/10.1016/J.COMPFLUID.2020.104770', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pulido-dasilva-livescu-hamann-multiresolutionclassificationofturbulencefeaturesinimagedatathroughmachinelearning-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pulido-dasilva-livescu-hamann-multiresolutionclassificationofturbulencefeaturesinimagedatathroughmachinelearning-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multiresolution classification of turbulence features in image data through machine learning},\n type = {article},\n year = {2021},\n keywords = {Image processing,Machine learning,Turbulence,Vortex detection},\n pages = {104770},\n volume = {214},\n month = {1},\n publisher = {Pergamon},\n day = {15},\n id = {052413a3-fcdc-3dff-ab3b-f7d91f97b7aa},\n created = {2022-02-20T23:29:14.961Z},\n accessed = {2022-02-20},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-20T23:29:14.961Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. We present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.},\n bibtype = {article},\n author = {Pulido, Jesus and da Silva, Ricardo Dutra and Livescu, Daniel and Hamann, Bernd},\n doi = {10.1016/J.COMPFLUID.2020.104770},\n journal = {Computers &amp; Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. We present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1a0cafe7-d99c-4711-40ba-d076bbebebb9/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1a0cafe7-d99c-4711-40ba-d076bbebebb9/full_text.pdf.pdf', event);\">\n    Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  X.;  and Moreto,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Phys. Fluids</i>, 33: 101703.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1a0cafe7-d99c-4711-40ba-d076bbebebb9/full_text.pdf.pdf\"\n     onclick=\"log_download('liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1a0cafe7-d99c-4711-40ba-d076bbebebb9/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1063/5.0066332\"\n     onclick=\"log_download('liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021', 'https://doi.org/10.1063/5.0066332', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/5.0066332\"\n     onclick=\"log_download('liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021', 'http://doi.org/10.1063/5.0066332', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-moreto-pressurereconstructionofaplanarturbulentflowfieldwithinamultiplyconnecteddomainwitharbitraryboundaryshapes-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pressure reconstruction of a planar turbulent flow field within a multiply connected domain with arbitrary boundary shapes},\n type = {article},\n year = {2021},\n pages = {101703},\n volume = {33},\n websites = {https://doi.org/10.1063/5.0066332},\n id = {d887d298-1140-3521-b80b-f8178cac337a},\n created = {2022-02-20T23:33:36.678Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-20T23:33:37.243Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n bibtype = {article},\n author = {Liu, Xiaofeng and Moreto, Jose Roberto},\n doi = {10.1063/5.0066332},\n journal = {Phys. Fluids}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/7011c56a-830c-5e45-46ca-fda21cdc358d/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/7011c56a-830c-5e45-46ca-fda21cdc358d/full_text.pdf.pdf', event);\">\n    Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Clark,  P.; Leoni,  D.; Zaki,  T., A.; Karniadakis,  G.; Meneveau,  C.; Clark,  P.; Zaki,  T., A.; Karniadakis,  G.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>J. Fluid Mech</i>, 914: 6.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/7011c56a-830c-5e45-46ca-fda21cdc358d/full_text.pdf.pdf\"\n     onclick=\"log_download('clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/7011c56a-830c-5e45-46ca-fda21cdc358d/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1017/jfm.2020.977\"\n     onclick=\"log_download('clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021', 'https://doi.org/10.1017/jfm.2020.977', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.977\"\n     onclick=\"log_download('clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021', 'http://doi.org/10.1017/jfm.2020.977', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('clark-leoni-zaki-karniadakis-meneveau-clark-zaki-karniadakis-etal-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Two-point stress-strain-rate correlation structure and non-local eddy viscosity in turbulent flows},\n type = {article},\n year = {2021},\n keywords = {turbulence modelling,turbulence theory †},\n pages = {6},\n volume = {914},\n websites = {https://doi.org/10.1017/jfm.2020.977},\n id = {d17dc74f-091c-3ad3-9876-dbe551c5865f},\n created = {2022-02-20T23:35:02.757Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-20T23:35:03.347Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {By analysing the Karman-Howarth equation for filtered-velocity fields in turbulent flows, we show that the two-point correlation between the filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlation-based statistical a priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence, we show that local eddy-viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain-rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 &lt; α &lt; 1 (where α is the fractional gradient order) rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional-gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows. Hence, non-local operators thus exhibit interesting modelling capabilities and potential for large-eddy simulations although more developments are required, both on the theoretical and computational implementation fronts.},\n bibtype = {article},\n author = {Clark, Patricio and Leoni, Di and Zaki, Tamer A and Karniadakis, George and Meneveau, Charles and Clark, P and Zaki, T A and Karniadakis, G and Meneveau, C},\n doi = {10.1017/jfm.2020.977},\n journal = {J. Fluid Mech}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  By analysing the Karman-Howarth equation for filtered-velocity fields in turbulent flows, we show that the two-point correlation between the filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlation-based statistical a priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence, we show that local eddy-viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain-rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 (where α is the fractional gradient order) rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional-gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows. Hence, non-local operators thus exhibit interesting modelling capabilities and potential for large-eddy simulations although more developments are required, both on the theoretical and computational implementation fronts.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/214133d9-0f22-d399-0c4b-c05e371716f1/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/214133d9-0f22-d399-0c4b-c05e371716f1/full_text.pdf.pdf', event);\">\n    DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  J.; Chen,  J.; Zhuo,  X.; Moon,  A.;  and Woo Son,  S.\n</span>\n\n  \n\n</span>\n\n  <i>2021 IEEE International Conference on Cluster Computing (CLUSTER)</i>.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/214133d9-0f22-d399-0c4b-c05e371716f1/full_text.pdf.pdf\"\n     onclick=\"log_download('zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/214133d9-0f22-d399-0c4b-c05e371716f1/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/Cluster48925.2021.00056\"\n     onclick=\"log_download('zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021', 'http://doi.org/10.1109/Cluster48925.2021.00056', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-chen-zhuo-moon-wooson-dpzimprovinglossycompressionratiowithinformationretrievalonscientificdatadpzimprovinglossycompressionratiowithinformationretrievalonscientificdata-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data; DPZ: Improving Lossy Compression Ratio with Information Retrieval on Scientific Data},\n type = {article},\n year = {2021},\n keywords = {Lossy compression,PCA,information retrieval},\n id = {a1abcec3-2790-3c53-a0ab-83f79ddd347a},\n created = {2022-02-21T19:17:28.173Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:17:28.724Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and ZFP, show promising rate-distortion efficiency. However, as the data storage burden and need for feature-preserving compression continue to grow, relying on unitary or single-stage compression is becoming insufficient for obtaining desirable data reductions and feature preservation. This paper aims to improve the compression ratio by taking advantage of information retrieval (IR), a well-established topic but under-explored in lossy compression for scientific data. We propose our lossy compression technique, called DPZ, based on multi-stage feature extractions, a commonly employed step in IR. Unlike the prior works where the compression is either done by predicting or bit-plane encoding, this work focuses on preserving the key data content from each stage to the maximum extent, ultimately elevates the compression ratio. With the application of discrete cosine transform, principal component analysis, and quantization, DPZ obtains the dominant features with the least amount of bits possible. Specifically, a knee-point detection and an explained variance variation method are designed for finding optimal tradeoffs. DPZ also employs a sampling strategy to reduce computational overhead and estimate compressibility and parameters before compression. We evaluate the performance of DPZ using real-world scientific datasets. Experiments demonstrate that DPZ achieves superior compression ratios through multi-stage retrievals and outperforms SZ and ZFP at medium to high accuracy on most of the evaluated datasets.},\n bibtype = {article},\n author = {Zhang, Jialing and Chen, Jiaxi and Zhuo, Xiaoyan and Moon, Aekyeung and Woo Son, Seung},\n doi = {10.1109/Cluster48925.2021.00056},\n journal = {2021 IEEE International Conference on Cluster Computing (CLUSTER)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Lossy compression on scientific data is coming into prominence as the scientific workflow is hampered significantly by large amounts of data produced by high-performance computing (HPC) applications. State-of-the-art lossy compressors, such as SZ and ZFP, show promising rate-distortion efficiency. However, as the data storage burden and need for feature-preserving compression continue to grow, relying on unitary or single-stage compression is becoming insufficient for obtaining desirable data reductions and feature preservation. This paper aims to improve the compression ratio by taking advantage of information retrieval (IR), a well-established topic but under-explored in lossy compression for scientific data. We propose our lossy compression technique, called DPZ, based on multi-stage feature extractions, a commonly employed step in IR. Unlike the prior works where the compression is either done by predicting or bit-plane encoding, this work focuses on preserving the key data content from each stage to the maximum extent, ultimately elevates the compression ratio. With the application of discrete cosine transform, principal component analysis, and quantization, DPZ obtains the dominant features with the least amount of bits possible. Specifically, a knee-point detection and an explained variance variation method are designed for finding optimal tradeoffs. DPZ also employs a sampling strategy to reduce computational overhead and estimate compressibility and parameters before compression. We evaluate the performance of DPZ using real-world scientific datasets. Experiments demonstrate that DPZ achieves superior compression ratios through multi-stage retrievals and outperforms SZ and ZFP at medium to high accuracy on most of the evaluated datasets.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/644cdd8a-80b3-8aa5-7d1f-3e8ebe07d145/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/644cdd8a-80b3-8aa5-7d1f-3e8ebe07d145/full_text.pdf.pdf', event);\">\n    LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Bi,  X.; Fan,  Y.; Han,  Y.;  and Kuai,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT</i>, 70: 2021.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/644cdd8a-80b3-8aa5-7d1f-3e8ebe07d145/full_text.pdf.pdf\"\n     onclick=\"log_download('yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/644cdd8a-80b3-8aa5-7d1f-3e8ebe07d145/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://www.ieee.org/publications/rights/index.html\"\n     onclick=\"log_download('yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021', 'https://www.ieee.org/publications/rights/index.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TIM.2021.3082313\"\n     onclick=\"log_download('yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021', 'http://doi.org/10.1109/TIM.2021.3082313', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-bi-fan-han-kuai-lightpivnetaneffectiveconvolutionalneuralnetworkforparticleimagevelocimetry-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {LightPIVNet: An Effective Convolutional Neural Network for Particle Image Velocimetry},\n type = {article},\n year = {2021},\n pages = {2021},\n volume = {70},\n websites = {https://www.ieee.org/publications/rights/index.html},\n id = {a770ec53-7b70-3157-8e6a-cd62f806e33f},\n created = {2022-02-21T19:20:57.099Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:20:58.051Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en. Index Terms-Deep learning (DL), fluid motion estimation, lightweight, optical flow, particle image velocimetry (PIV).},\n bibtype = {article},\n author = {Yu, Changdong and Bi, Xiaojun and Fan, Yiwei and Han, Yang and Kuai, Yunfei},\n doi = {10.1109/TIM.2021.3082313},\n journal = {IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en. Index Terms-Deep learning (DL), fluid motion estimation, lightweight, optical flow, particle image velocimetry (PIV).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/78517cbb-77d3-9fbd-68e6-9cbc2117d271/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/78517cbb-77d3-9fbd-68e6-9cbc2117d271/full_text.pdf.pdf', event);\">\n    Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hayne,  L.; Clyne,  J.;  and Li,  S.\n</span>\n\n  \n\n</span>\n\n  .  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/78517cbb-77d3-9fbd-68e6-9cbc2117d271/full_text.pdf.pdf\"\n     onclick=\"log_download('hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/78517cbb-77d3-9fbd-68e6-9cbc2117d271/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/BigData52589.2021.9671627\"\n     onclick=\"log_download('hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021', 'http://doi.org/10.1109/BigData52589.2021.9671627', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hayne-clyne-li-usingneuralnetworksfortwodimensionalscientificdatacompressionusingneuralnetworksfortwodimensionalscientificdatacompression-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using Neural Networks for Two Dimensional Scientific Data Compression; Using Neural Networks for Two Dimensional Scientific Data Compression},\n type = {article},\n year = {2021},\n id = {89d9254b-bf2f-354a-8f06-5ec1df0284b5},\n created = {2022-02-21T19:20:57.493Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:20:58.433Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Continual advances in high-performance computing have enabled the development of higher resolution and more realistic simulations of a wide variety of scientific phenomena. As a result, many computational science communities are increasingly constrained by the massive volumes of data produced,for example, strict storage constraints often force reductions in the number of output variables, data output frequency, or simulation length. Accordingly, modelers across many scientific domains are beginning to adopt purpose-built scientific data compression techniques as an effective mitigation for these challenges. The origins of scientific data compression tools every so often lie in image and video compression. Recently, compression researchers have achieved state-of-the-art performance using neural networks for natural image compression, but this achievement has yet to be adapted to scientific data. This paper assesses the performance of an existing autoencoder neural network compression algorithm on two sets of two-dimensional floating-point scientific data. Compared to state-of-the-art scientific data compression algorithms SZ and ZFP, this out-of-the-box neural network achieves higher peak signal-to-noise ratios at low bit rates, and remains competitive in controlling maximum point-wise error. This preliminary assessment paves the way for future research into neural network compression on floating-point scientific data.},\n bibtype = {article},\n author = {Hayne, Lucas and Clyne, John and Li, Shaomeng},\n doi = {10.1109/BigData52589.2021.9671627}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Continual advances in high-performance computing have enabled the development of higher resolution and more realistic simulations of a wide variety of scientific phenomena. As a result, many computational science communities are increasingly constrained by the massive volumes of data produced,for example, strict storage constraints often force reductions in the number of output variables, data output frequency, or simulation length. Accordingly, modelers across many scientific domains are beginning to adopt purpose-built scientific data compression techniques as an effective mitigation for these challenges. The origins of scientific data compression tools every so often lie in image and video compression. Recently, compression researchers have achieved state-of-the-art performance using neural networks for natural image compression, but this achievement has yet to be adapted to scientific data. This paper assesses the performance of an existing autoencoder neural network compression algorithm on two sets of two-dimensional floating-point scientific data. Compared to state-of-the-art scientific data compression algorithms SZ and ZFP, this out-of-the-box neural network achieves higher peak signal-to-noise ratios at low bit rates, and remains competitive in controlling maximum point-wise error. This preliminary assessment paves the way for future research into neural network compression on floating-point scientific data.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1f70af45-fbec-2e1f-1b3c-1dc5fce958ad/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1f70af45-fbec-2e1f-1b3c-1dc5fce958ad/full_text.pdf.pdf', event);\">\n    Unsupervised deep learning for super-resolution reconstruction of turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kim,  H.; Kim,  J.; Won,  S.;  and Lee,  C.\n</span>\n\n  \n\n</span>\n\n  <i>J. Fluid Mech</i>, 910: 29.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1f70af45-fbec-2e1f-1b3c-1dc5fce958ad/full_text.pdf.pdf\"\n     onclick=\"log_download('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1f70af45-fbec-2e1f-1b3c-1dc5fce958ad/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Unsupervised deep learning for super-resolution reconstruction of turbulence [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1017/jfm.2020.1028\"\n     onclick=\"log_download('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021', 'https://doi.org/10.1017/jfm.2020.1028', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Unsupervised deep learning for super-resolution reconstruction of turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.1028\"\n     onclick=\"log_download('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021', 'http://doi.org/10.1017/jfm.2020.1028', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},\n type = {article},\n year = {2021},\n keywords = {turbulence simulation},\n pages = {29},\n volume = {910},\n websites = {https://doi.org/10.1017/jfm.2020.1028},\n id = {4720e5ff-e367-373c-8a45-62e9091085f7},\n created = {2022-02-21T19:25:34.158Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:25:34.724Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},\n bibtype = {article},\n author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},\n doi = {10.1017/jfm.2020.1028},\n journal = {J. Fluid Mech}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-fan-bi-han-kuai-deepparticleimagevelocimetrysupervisedlearningunderlightconditions-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Deep particle image velocimetry supervised learning under light conditions.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  C.; Fan,  Y.; Bi,  X.; Han,  Y.;  and Kuai,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Flow Measurement and Instrumentation</i>, 80: 102000.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-fan-bi-han-kuai-deepparticleimagevelocimetrysupervisedlearningunderlightconditions-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-fan-bi-han-kuai-deepparticleimagevelocimetrysupervisedlearningunderlightconditions-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deep particle image velocimetry supervised learning under light conditions},\n type = {article},\n year = {2021},\n pages = {102000},\n volume = {80},\n publisher = {Elsevier},\n id = {495815cf-b476-3500-8e87-c593e9700f09},\n created = {2022-02-21T19:26:56.482Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:26:56.482Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Yu, Chang-Dong and Fan, Yi-Wei and Bi, Xiao-Jun and Han, Yang and Kuai, Yun-Fei},\n journal = {Flow Measurement and Instrumentation}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"nandal-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Nandal,  T.; Tyagi,  P.;  and Singh,  R., K.\n</span>\n\n  \n\n</span>\n\n  In <i>ASME International Mechanical Engineering Congress and Exposition</i>, volume 85666, pages V010T10A062,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/nandal-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('nandal-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},\n type = {inproceedings},\n year = {2021},\n pages = {V010T10A062},\n volume = {85666},\n id = {96b2cc13-c310-36a9-8034-bb0f3480edba},\n created = {2022-02-21T19:26:56.874Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:26:56.874Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Nandal, Tanishk and Tyagi, Prince and Singh, Raj Kumar},\n booktitle = {ASME International Mechanical Engineering Congress and Exposition}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R e τ= 150, 400 and 1020.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ahmed,  U.; Apsley,  D.; Stallard,  T.; Stansby,  P.;  and Afgan,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydraulic Research</i>, 59(1): 36-50.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers R e τ= 150, 400 and 1020},\n type = {article},\n year = {2021},\n pages = {36-50},\n volume = {59},\n publisher = {Taylor &amp; Francis},\n id = {4b757602-02db-3a90-b756-e6de5d0be789},\n created = {2022-02-21T19:26:57.246Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:26:57.246Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},\n journal = {Journal of Hydraulic Research},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gao-lin-tu-zhu-wei-zhang-shao-arobustsinglepixelparticleimagevelocimetrybasedonfullyconvolutionalnetworkswithcrosscorrelationembedded-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A robust single-pixel particle image velocimetry based on fully convolutional networks with cross-correlation embedded.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gao,  Q.; Lin,  H.; Tu,  H.; Zhu,  H.; Wei,  R.; Zhang,  G.;  and Shao,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 33(12): 127125.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gao-lin-tu-zhu-wei-zhang-shao-arobustsinglepixelparticleimagevelocimetrybasedonfullyconvolutionalnetworkswithcrosscorrelationembedded-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gao-lin-tu-zhu-wei-zhang-shao-arobustsinglepixelparticleimagevelocimetrybasedonfullyconvolutionalnetworkswithcrosscorrelationembedded-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A robust single-pixel particle image velocimetry based on fully convolutional networks with cross-correlation embedded},\n type = {article},\n year = {2021},\n pages = {127125},\n volume = {33},\n publisher = {AIP Publishing LLC},\n id = {b209b52c-fbd0-334d-b45b-26f3ca4ae06a},\n created = {2022-02-21T19:28:32.885Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:28:32.885Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Gao, Qi and Lin, Hongtao and Tu, Han and Zhu, Haoran and Wei, Runjie and Zhang, Guoping and Shao, Xueming},\n journal = {Physics of Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-0083-27bea5fc2259/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-0083-27bea5fc2259/full_text.pdf.pdf', event);\">\n    A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  L.; Hu,  R.;  and Zheng,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Phys. Fluids</i>, 33: 45120.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-0083-27bea5fc2259/full_text.pdf.pdf\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-0083-27bea5fc2259/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1063/5.0046502\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://doi.org/10.1063/5.0046502', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/5.0046502\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'http://doi.org/10.1063/5.0046502', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},\n type = {article},\n year = {2021},\n pages = {45120},\n volume = {33},\n websites = {https://doi.org/10.1063/5.0046502},\n id = {e964db44-a8b8-3b7c-8083-764c8ca4795b},\n created = {2022-02-21T19:34:18.460Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:34:20.372Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ &lt; 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},\n bibtype = {article},\n author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},\n doi = {10.1063/5.0046502},\n journal = {Phys. Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-6c4a-85ec090c2385/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-6c4a-85ec090c2385/full_text.pdf.pdf', event);\">\n    Time-resolved particle image velocimetry algorithm based on deep learning.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Guo,  C.; Fan,  Y.; Yu,  C.; Han,  Y.;  and Bi,  X.\n</span>\n\n  \n\n</span>\n\n  .  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-6c4a-85ec090c2385/full_text.pdf.pdf\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-6c4a-85ec090c2385/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Time-resolved particle image velocimetry algorithm based on deep learning [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"http://www.ieee.org/publications_standards/publications/rights/index.html\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'http://www.ieee.org/publications_standards/publications/rights/index.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Time-resolved particle image velocimetry algorithm based on deep learning [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TIM.2022.3141750\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'http://doi.org/10.1109/TIM.2022.3141750', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Time-resolved particle image velocimetry algorithm based on deep learning},\n type = {article},\n year = {2021},\n keywords = {Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow},\n websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},\n id = {f2410f9e-f814-3ae7-86c6-4d2a103081f3},\n created = {2022-02-21T19:34:18.855Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:34:20.654Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.},\n bibtype = {article},\n author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},\n doi = {10.1109/TIM.2022.3141750}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3348720c-cf6d-7dbf-5811-e4196c1c24b1/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3348720c-cf6d-7dbf-5811-e4196c1c24b1/full_text.pdf.pdf', event);\">\n    DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liang,  J.; Cai,  S.; Xu,  C.; Chen,  T.;  and Chu,  J.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Instrumentation and Measurement</i>, PP.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3348720c-cf6d-7dbf-5811-e4196c1c24b1/full_text.pdf.pdf\"\n     onclick=\"log_download('liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/3348720c-cf6d-7dbf-5811-e4196c1c24b1/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"http://www.ieee.org/publications_standards/publications/rights/index.html\"\n     onclick=\"log_download('liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021', 'http://www.ieee.org/publications_standards/publications/rights/index.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TIM.2021.3120127\"\n     onclick=\"log_download('liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021', 'http://doi.org/10.1109/TIM.2021.3120127', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liang-cai-xu-chen-chu-deepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworksdeepptvparticletrackingvelocimetryforcomplexflowmotionviadeepneuralnetworks-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks; DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks},\n type = {article},\n year = {2021},\n keywords = {Particle tracking velocimetry,deep learning,deep neural networks,fluid motion estimation,point clouds},\n volume = {PP},\n websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},\n id = {62e473c0-ea0f-3ba2-bcd2-3c3aea1e9c09},\n created = {2022-02-21T19:34:19.232Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:34:20.931Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Particle tracking velocimetry (PTV) is a powerful technique for global and non-intrusive flow field measurement , which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called DeepPTV, for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles are aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multi-scale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely from large scale motion to small scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.},\n bibtype = {article},\n author = {Liang, Jiaming and Cai, Shengze and Xu, Chao and Chen, Tehuan and Chu, Jian},\n doi = {10.1109/TIM.2021.3120127},\n journal = {IEEE Transactions on Instrumentation and Measurement}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Particle tracking velocimetry (PTV) is a powerful technique for global and non-intrusive flow field measurement , which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called DeepPTV, for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles are aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multi-scale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely from large scale motion to small scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kanishk-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kanishk,  T., N.; Tyagi,  P.;  and Singh,  R., K.\n</span>\n\n  \n\n</span>\n\n  In <i>ASME 2021 International Mechanical Engineering Congress and Exposition</i>,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kanishk-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kanishk-tyagi-singh-generationandparameterizationofforcedisotropicturbulentflowusingautoencodersandgenerativeadversarialnetworks-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Generation and Parameterization of Forced Isotropic Turbulent Flow Using Autoencoders and Generative Adversarial Networks},\n type = {inproceedings},\n year = {2021},\n id = {9a25fc39-6427-38ee-a5c8-9504e01a0b0c},\n created = {2022-02-21T19:54:37.633Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:54:37.633Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Kanishk, Tanishk Nandal and Tyagi, Prince and Singh, Raj Kumar},\n booktitle = {ASME 2021 International Mechanical Engineering Congress and Exposition}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ahmed-pawar-san-rasheed-iliescu-noack-onclosuresforreducedordermodelsaspectrumoffirstprincipletomachinelearnedavenues-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  On closures for reduced order models—A spectrum of first-principle to machine-learned avenues.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ahmed,  S., E.; Pawar,  S.; San,  O.; Rasheed,  A.; Iliescu,  T.;  and Noack,  B., R.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 33(9): 91301.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ahmed-pawar-san-rasheed-iliescu-noack-onclosuresforreducedordermodelsaspectrumoffirstprincipletomachinelearnedavenues-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ahmed-pawar-san-rasheed-iliescu-noack-onclosuresforreducedordermodelsaspectrumoffirstprincipletomachinelearnedavenues-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On closures for reduced order models—A spectrum of first-principle to machine-learned avenues},\n type = {article},\n year = {2021},\n pages = {91301},\n volume = {33},\n publisher = {AIP Publishing LLC},\n id = {ce06d381-1a1c-374f-b451-90ac4b12aaf3},\n created = {2022-02-21T19:54:38.009Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:54:38.009Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ahmed, Shady E and Pawar, Suraj and San, Omer and Rasheed, Adil and Iliescu, Traian and Noack, Bernd R},\n journal = {Physics of Fluids},\n number = {9}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-2ff0-40655594abe5/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-2ff0-40655594abe5/full_text.pdf.pdf', event);\">\n    A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  L.; Hu,  R.;  and Zheng,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Phys. Fluids</i>, 33: 45120.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-2ff0-40655594abe5/full_text.pdf.pdf\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/421414d0-7f0e-1437-2ff0-40655594abe5/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1063/5.0046502\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'https://doi.org/10.1063/5.0046502', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/5.0046502\"\n     onclick=\"log_download('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021', 'http://doi.org/10.1063/5.0046502', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-hu-zheng-ascalingimprovedinnerouterdecompositionofnearwallturbulentmotionsarticlesyoumaybeinterestedinascalingimprovedinnerouterdecompositionofnearwallturbulentmotions-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A scaling improved inner-outer decomposition of near-wall turbulent motions ARTICLES YOU MAY BE INTERESTED IN A scaling improved inner-outer decomposition of near-wall turbulent motions},\n type = {article},\n year = {2021},\n pages = {45120},\n volume = {33},\n websites = {https://doi.org/10.1063/5.0046502},\n id = {4ff7eba0-ee54-370d-96b4-cfda2bbe256d},\n created = {2022-02-21T19:54:57.325Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:54:58.549Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ &lt; 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502},\n bibtype = {article},\n author = {Wang, Limin and Hu, Ruifeng and Zheng, Xiaojing},\n doi = {10.1063/5.0046502},\n journal = {Phys. Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Cite as: Phys. Fluids 33, 045120 (2021); https://doi. A near-wall predictive model for passive scalars using minimal flow unit Physics of Fluids 33, 045119 (2021); https://doi.org/10.1063/5.0047472 Near-wall flow structures and related surface quantities in wall-bounded turbulence Physics of Fluids 33, 065116 (2021); https://doi.org/10.1063/5.0051649 Off-wall boundary conditions for large-eddy simulation based on near-wall turbulence prediction Physics of Fluids 33, 045125 (2021); https://doi. ABSTRACT Near-wall turbulent velocities in turbulent channel flows are decomposed into small-scale and large-scale components at y þ < 100 by improving the predictive inner-outer model of Baars et al. [Phys. Rev. Fluids 1, 054406 (2016)], where y + is the viscous-normalized wall-normal height. The small-scale one is obtained by reducing the outer reference height (a parameter in the model) from the center of the logarithmic layer to y þ ¼ 100, which can fully remove outer influences. On the other hand, the large-scale one represents the near-wall footprints of outer energy-containing motions. We present plenty of evidence that demonstrates that the small-scale motions are Reynolds-number invariant with the viscous scaling, at friction Reynolds numbers between 1000 and 5200. At lower Reynolds numbers from 180 to 600, the small scales cannot be scaled by the viscous units, and the vortical structures are progressively strengthened as Reynolds number increases, which is proposed as a possible mechanism responsible for the anomalous scaling behavior. Finally, it is found that a small-scale part of the outer large-scale footprint can be well scaled by the viscous units. Published under license by AIP Publishing. https://doi.org/10.1063/5.0046502\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-077e-fcc01bb4ae3d/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-077e-fcc01bb4ae3d/full_text.pdf.pdf', event);\">\n    Time-resolved particle image velocimetry algorithm based on deep learning.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Guo,  C.; Fan,  Y.; Yu,  C.; Han,  Y.;  and Bi,  X.\n</span>\n\n  \n\n</span>\n\n  .  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-077e-fcc01bb4ae3d/full_text.pdf.pdf\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/1ea7caf6-e6dd-ab73-077e-fcc01bb4ae3d/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Time-resolved particle image velocimetry algorithm based on deep learning [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"http://www.ieee.org/publications_standards/publications/rights/index.html\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'http://www.ieee.org/publications_standards/publications/rights/index.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Time-resolved particle image velocimetry algorithm based on deep learning [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TIM.2022.3141750\"\n     onclick=\"log_download('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021', 'http://doi.org/10.1109/TIM.2022.3141750', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('guo-fan-yu-han-bi-timeresolvedparticleimagevelocimetryalgorithmbasedondeeplearning-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Time-resolved particle image velocimetry algorithm based on deep learning},\n type = {article},\n year = {2021},\n keywords = {Deep learning,Fluid motion estimation,Index Terms-Time-resolved PIV,Multi-frame velocity field,Optical Flow},\n websites = {http://www.ieee.org/publications_standards/publications/rights/index.html},\n id = {bfd59ac7-a0c6-37f1-8e98-fd473976cd16},\n created = {2022-02-21T19:54:58.115Z},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:54:58.921Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.},\n bibtype = {article},\n author = {Guo, Chunyu and Fan, Yiwei and Yu, Changdong and Han, Yang and Bi, Xiaojun},\n doi = {10.1109/TIM.2022.3141750}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Time-resolved particle image velocimetry (TR-PIV) is an advanced fluid mechanics experiment technology, which can simultaneously measure the velocity field from multi-frame images to analyze the evolution of fluid over time. Deep learning technology has made great progress in the field of PIV. However, as far as we know, no deep learning method has been adopted to calculate the velocity field of Time-Resolved PIV images (i.e. TR-PIV). In this paper, we propose a novel cascaded convolutional neural network called CascLiteFlowNet-R-en for TR-PIV estimation task. Furthermore, to train and optimize the model, we generated a challenge TR-PIV dataset of multi-frame velocity fields. The velocity field here changes according to the frames in order to simulate the real fluid scene. Finally, the proposed model has been verified on synthetic and experimental particle images. The results show that our proposed method achieves excellent performance, with competitive calculation accuracy and high calculation efficiency.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rafner-gruji-bach-brentzen-gervang-jia-leinweber-misztal-etal-geometryofturbulentdissipationandthenavierstokesregularityproblem-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Geometry of turbulent dissipation and the Navier–Stokes regularity problem.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rafner,  J.; Grujić,  Z.; Bach,  C.; Bærentzen,  J., A.; Gervang,  B.; Jia,  R.; Leinweber,  S.; Misztal,  M.;  and Sherson,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Scientific Reports</i>, 11(1): 1-9.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rafner-gruji-bach-brentzen-gervang-jia-leinweber-misztal-etal-geometryofturbulentdissipationandthenavierstokesregularityproblem-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rafner-gruji-bach-brentzen-gervang-jia-leinweber-misztal-etal-geometryofturbulentdissipationandthenavierstokesregularityproblem-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Geometry of turbulent dissipation and the Navier–Stokes regularity problem},\n type = {article},\n year = {2021},\n pages = {1-9},\n volume = {11},\n publisher = {Nature Publishing Group},\n id = {d4914d45-1f3b-3900-abd0-cebdf83c4fe8},\n created = {2022-02-21T19:59:25.810Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T19:59:25.810Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Rafner, Janet and Grujić, Zoran and Bach, Christian and Bærentzen, Jakob Andreas and Gervang, Bo and Jia, Ruo and Leinweber, Scott and Misztal, Marek and Sherson, Jacob},\n journal = {Scientific Reports},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xie-desilva-baidya-yang-hu-thirdorderstructurefunctioninthelogarithmiclayerofboundarylayerturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Third-order structure function in the logarithmic layer of boundary-layer turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xie,  J.; De Silva,  C.; Baidya,  R.; Yang,  X., I., A.;  and Hu,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 6(7): 74602.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xie-desilva-baidya-yang-hu-thirdorderstructurefunctioninthelogarithmiclayerofboundarylayerturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xie-desilva-baidya-yang-hu-thirdorderstructurefunctioninthelogarithmiclayerofboundarylayerturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Third-order structure function in the logarithmic layer of boundary-layer turbulence},\n type = {article},\n year = {2021},\n pages = {74602},\n volume = {6},\n publisher = {APS},\n id = {dc7713fc-fc69-3719-a107-f3e04a13d433},\n created = {2022-02-21T20:13:41.180Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:41.180Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Xie, Jin-Han and De Silva, Charitha and Baidya, Rio and Yang, Xiang I A and Hu, Ruifeng},\n journal = {Physical Review Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhou-he-yang-wallmodelbasedonneuralnetworksforlesofturbulentflowsoverperiodichills-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Wall model based on neural networks for LES of turbulent flows over periodic hills.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhou,  Z.; He,  G.;  and Yang,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 6(5): 54610.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhou-he-yang-wallmodelbasedonneuralnetworksforlesofturbulentflowsoverperiodichills-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhou-he-yang-wallmodelbasedonneuralnetworksforlesofturbulentflowsoverperiodichills-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Wall model based on neural networks for LES of turbulent flows over periodic hills},\n type = {article},\n year = {2021},\n pages = {54610},\n volume = {6},\n publisher = {APS},\n id = {287b1ea2-125d-3f4f-b076-194d70e30478},\n created = {2022-02-21T20:13:41.557Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:41.557Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Zhou, Zhideng and He, Guowei and Yang, Xiaolei},\n journal = {Physical Review Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lu-jiang-levine-berger-compressiveneuralrepresentationsofvolumetricscalarfields-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Compressive neural representations of volumetric scalar fields.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lu,  Y.; Jiang,  K.; Levine,  J., A.;  and Berger,  M.\n</span>\n\n  \n\n</span>\n\n  In <i>Computer Graphics Forum</i>, volume 40, pages 135-146,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lu-jiang-levine-berger-compressiveneuralrepresentationsofvolumetricscalarfields-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lu-jiang-levine-berger-compressiveneuralrepresentationsofvolumetricscalarfields-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Compressive neural representations of volumetric scalar fields},\n type = {inproceedings},\n year = {2021},\n pages = {135-146},\n volume = {40},\n issue = {3},\n id = {ab19791e-a418-34fb-9e02-0a8fc802642e},\n created = {2022-02-21T20:13:42.676Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:42.676Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Lu, Yuzhe and Jiang, Kairong and Levine, Joshua A and Berger, Matthew},\n booktitle = {Computer Graphics Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sharma-das-girimaji-localvortexlinetopologyandgeometryinturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Local vortex line topology and geometry in turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sharma,  B.; Das,  R.;  and Girimaji,  S., S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 924.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sharma-das-girimaji-localvortexlinetopologyandgeometryinturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sharma-das-girimaji-localvortexlinetopologyandgeometryinturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Local vortex line topology and geometry in turbulence},\n type = {article},\n year = {2021},\n volume = {924},\n publisher = {Cambridge University Press},\n id = {3be703da-cc17-3f0e-b821-de876b396c7f},\n created = {2022-02-21T20:13:43.052Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:43.052Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Sharma, Bajrang and Das, Rishita and Girimaji, Sharath S},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-wang-zheng-logarithmicenergyprofileofthestreamwisevelocityforwallattachededdiesalongthespanwisedirectioninturbulentboundarylayer-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Logarithmic energy profile of the streamwise velocity for wall-attached eddies along the spanwise direction in turbulent boundary layer.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  X.; Wang,  G.;  and Zheng,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 33(10): 105119.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-wang-zheng-logarithmicenergyprofileofthestreamwisevelocityforwallattachededdiesalongthespanwisedirectioninturbulentboundarylayer-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-wang-zheng-logarithmicenergyprofileofthestreamwisevelocityforwallattachededdiesalongthespanwisedirectioninturbulentboundarylayer-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Logarithmic energy profile of the streamwise velocity for wall-attached eddies along the spanwise direction in turbulent boundary layer},\n type = {article},\n year = {2021},\n pages = {105119},\n volume = {33},\n publisher = {AIP Publishing LLC},\n id = {87f6c645-a0df-37e0-873a-5c459a613874},\n created = {2022-02-21T20:13:43.794Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:43.794Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Li, Xuebo and Wang, Guohua and Zheng, Xiaojing},\n journal = {Physics of Fluids},\n number = {10}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jie,  Y.; Andersson,  H., I.;  and Zhao,  L.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Multiphase Flow</i>, 140: 103627.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jie-andersson-zhao-effectsofthequiescentcoreinturbulentchannelflowontransportandclusteringofinertialparticles-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Effects of the quiescent core in turbulent channel flow on transport and clustering of inertial particles},\n type = {article},\n year = {2021},\n pages = {103627},\n volume = {140},\n publisher = {Elsevier},\n id = {36f582f0-e23e-37be-a3ba-70fd98441b42},\n created = {2022-02-21T20:13:44.169Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:44.169Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Jie, Yucheng and Andersson, Helge I and Zhao, Lihao},\n journal = {International Journal of Multiphase Flow}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-zhong-tang-ontherelationshipsbetweendifferentvortexidentificationmethodsbasedonlocaltracecriterion-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  On the relationships between different vortex identification methods based on local trace criterion.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  Y.; Zhong,  W.;  and Tang,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 33(10): 105116.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-zhong-tang-ontherelationshipsbetweendifferentvortexidentificationmethodsbasedonlocaltracecriterion-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-zhong-tang-ontherelationshipsbetweendifferentvortexidentificationmethodsbasedonlocaltracecriterion-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On the relationships between different vortex identification methods based on local trace criterion},\n type = {article},\n year = {2021},\n pages = {105116},\n volume = {33},\n publisher = {AIP Publishing LLC},\n id = {7a36bf54-d4a7-3f45-b4df-34dcd2064a38},\n created = {2022-02-21T20:13:44.552Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:44.552Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Liu, Yangwei and Zhong, Weibo and Tang, Yumeng},\n journal = {Physics of Fluids},\n number = {10}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lagemann-klaas-schrder-unsupervisedrecurrentallpairsfieldtransformsforparticleimagevelocimetry-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Unsupervised Recurrent All-Pairs Field Transforms for Particle Image Velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lagemann,  C.; Klaas,  M.;  and Schröder,  W.\n</span>\n\n  \n\n</span>\n\n  In <i>14th International Symposium on Particle Image Velocimetry</i>, volume 1,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lagemann-klaas-schrder-unsupervisedrecurrentallpairsfieldtransformsforparticleimagevelocimetry-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lagemann-klaas-schrder-unsupervisedrecurrentallpairsfieldtransformsforparticleimagevelocimetry-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Unsupervised Recurrent All-Pairs Field Transforms for Particle Image Velocimetry},\n type = {inproceedings},\n year = {2021},\n volume = {1},\n issue = {1},\n id = {fe46489b-d407-3495-bf68-2f3aaeb644fc},\n created = {2022-02-21T20:13:44.942Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:44.942Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Lagemann, Christian and Klaas, Michael and Schröder, Wolfgang},\n booktitle = {14th International Symposium on Particle Image Velocimetry}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Optimal Clipping of the Gradient Model for Subgrid Stress Closure.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Prakash,  A.; Jansen,  K., E.;  and Evans,  J., A.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA Scitech 2021 Forum</i>, pages 1665,  2021. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prakash-jansen-evans-optimalclippingofthegradientmodelforsubgridstressclosure-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Optimal Clipping of the Gradient Model for Subgrid Stress Closure},\n type = {inproceedings},\n year = {2021},\n pages = {1665},\n id = {e775cf78-75dc-3f8e-803d-006c435a7aef},\n created = {2022-02-21T20:13:45.676Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:45.676Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Prakash, Aviral and Jansen, Kenneth E and Evans, John A},\n booktitle = {AIAA Scitech 2021 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"iacobello-ridolfi-scarsoglio-largetosmallscalefrequencymodulationanalysisinwallboundedturbulenceviavisibilitynetworks-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Large-to-small scale frequency modulation analysis in wall-bounded turbulence via visibility networks.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Iacobello,  G.; Ridolfi,  L.;  and Scarsoglio,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 918.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/iacobello-ridolfi-scarsoglio-largetosmallscalefrequencymodulationanalysisinwallboundedturbulenceviavisibilitynetworks-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('iacobello-ridolfi-scarsoglio-largetosmallscalefrequencymodulationanalysisinwallboundedturbulenceviavisibilitynetworks-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Large-to-small scale frequency modulation analysis in wall-bounded turbulence via visibility networks},\n type = {article},\n year = {2021},\n volume = {918},\n publisher = {Cambridge University Press},\n id = {af488c54-0bb2-3c6e-87d4-bad7625e67ee},\n created = {2022-02-21T20:13:46.039Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:46.039Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Iacobello, Giovanni and Ridolfi, Luca and Scarsoglio, Stefania},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-wang-heidrich-snapshotspacetimeholographic3dparticletrackingvelocimetry-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Snapshot space–time holographic 3D particle tracking velocimetry.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  N.; Wang,  C.;  and Heidrich,  W.\n</span>\n\n  \n\n</span>\n\n  <i>Laser & Photonics Reviews</i>, 15(8): 2100008.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-wang-heidrich-snapshotspacetimeholographic3dparticletrackingvelocimetry-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-wang-heidrich-snapshotspacetimeholographic3dparticletrackingvelocimetry-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Snapshot space–time holographic 3D particle tracking velocimetry},\n type = {article},\n year = {2021},\n pages = {2100008},\n volume = {15},\n publisher = {Wiley Online Library},\n id = {daa61412-44ba-390f-a39d-63865fdba06e},\n created = {2022-02-21T20:13:46.410Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:46.410Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chen, Ni and Wang, Congli and Heidrich, Wolfgang},\n journal = {Laser &amp; Photonics Reviews},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lemoine-particleaccelerationinstrongmhdturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Particle acceleration in strong MHD turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lemoine,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review D</i>, 104(6): 63020.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lemoine-particleaccelerationinstrongmhdturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lemoine-particleaccelerationinstrongmhdturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Particle acceleration in strong MHD turbulence},\n type = {article},\n year = {2021},\n pages = {63020},\n volume = {104},\n publisher = {APS},\n id = {8ca9953a-9c7a-3943-bd8c-f1368e925962},\n created = {2022-02-21T20:13:46.778Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:13:46.778Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lemoine, Martin},\n journal = {Physical Review D},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ruth-vernet-perrard-deike-theeffectofnonlineardragontherisevelocityofbubblesinturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  The effect of nonlinear drag on the rise velocity of bubbles in turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ruth,  D., J.; Vernet,  M.; Perrard,  S.;  and Deike,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 924.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ruth-vernet-perrard-deike-theeffectofnonlineardragontherisevelocityofbubblesinturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ruth-vernet-perrard-deike-theeffectofnonlineardragontherisevelocityofbubblesinturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The effect of nonlinear drag on the rise velocity of bubbles in turbulence},\n type = {article},\n year = {2021},\n volume = {924},\n publisher = {Cambridge University Press},\n id = {2ae19162-6dcd-3e5b-a7ba-b58fc6a4a692},\n created = {2022-02-21T20:31:00.540Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:00.540Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ruth, Daniel J and Vernet, Marlone and Perrard, Stéphane and Deike, Luc},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fu-houghton-dabiri-asinglecamera3dscanningvelocimetrysystemforquantifyingactiveparticleaggregations-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A single-camera, 3D scanning velocimetry system for quantifying active particle aggregations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fu,  M., K.; Houghton,  I., A.;  and Dabiri,  J., O.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 62(8): 1-17.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fu-houghton-dabiri-asinglecamera3dscanningvelocimetrysystemforquantifyingactiveparticleaggregations-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fu-houghton-dabiri-asinglecamera3dscanningvelocimetrysystemforquantifyingactiveparticleaggregations-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A single-camera, 3D scanning velocimetry system for quantifying active particle aggregations},\n type = {article},\n year = {2021},\n pages = {1-17},\n volume = {62},\n publisher = {Springer},\n id = {64d1825f-5fc9-38e8-91c0-7607d9ebc993},\n created = {2022-02-21T20:31:01.361Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:01.361Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fu, Matt K and Houghton, Isabel A and Dabiri, John O},\n journal = {Experiments in Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Learning dominant physical processes with data-driven balance models.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Callaham,  J., L.; Koch,  J., V.; Brunton,  B., W.; Kutz,  J., N.;  and Brunton,  S., L.\n</span>\n\n  \n\n</span>\n\n  <i>Nature communications</i>, 12(1): 1-10.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('callaham-koch-brunton-kutz-brunton-learningdominantphysicalprocesseswithdatadrivenbalancemodels-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Learning dominant physical processes with data-driven balance models},\n type = {article},\n year = {2021},\n pages = {1-10},\n volume = {12},\n publisher = {Nature Publishing Group},\n id = {e8a9a0e7-ed97-345c-9332-5554884a2bb5},\n created = {2022-02-21T20:31:01.747Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:01.747Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Callaham, Jared L and Koch, James V and Brunton, Bingni W and Kutz, J Nathan and Brunton, Steven L},\n journal = {Nature communications},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jin,  X.; Cai,  S.; Li,  H.;  and Karniadakis,  G., E.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Computational Physics</i>, 426: 109951.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jin-cai-li-karniadakis-nsfnetsnavierstokesflownetsphysicsinformedneuralnetworksfortheincompressiblenavierstokesequations-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations},\n type = {article},\n year = {2021},\n pages = {109951},\n volume = {426},\n publisher = {Elsevier},\n id = {1a580e64-7034-35c9-905f-6339b44340f0},\n created = {2022-02-21T20:31:02.131Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:02.131Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Jin, Xiaowei and Cai, Shengze and Li, Hui and Karniadakis, George Em},\n journal = {Journal of Computational Physics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2021\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  As a matter of tension: Kinetic energy spectra in MHD turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grete,  P.; O’Shea,  B., W.;  and Beckwith,  K.\n</span>\n\n  \n\n</span>\n\n  <i>The Astrophysical Journal</i>, 909(2): 148.  2021.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2021\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2021')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {As a matter of tension: Kinetic energy spectra in MHD turbulence},\n type = {article},\n year = {2021},\n pages = {148},\n volume = {909},\n publisher = {IOP Publishing},\n id = {cbc09b53-2b67-3f11-ad8a-ea0a40de1fc1},\n created = {2022-02-21T20:31:02.521Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2022-02-21T20:31:02.521Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Grete, Philipp and O’Shea, Brian W and Beckwith, Kris},\n journal = {The Astrophysical Journal},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2020\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2020')\"\n      onkeypress=\"toggleGroup('group_2020')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2020</span>\n      <span class=\"bibbase_group_count\">\n        \n        (42)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F', event);\">\n    Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Viggiano,  B.; Friedrich,  J.; Volk,  R.; Bourgoin,  M.; Cal,  R., B.;  and Chevillard,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 900.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F\"\n     onclick=\"log_download('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.495\"\n     onclick=\"log_download('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'http://doi.org/10.1017/jfm.2020.495', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>11 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes},\n type = {article},\n year = {2020},\n keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},\n volume = {900},\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/modelling-lagrangian-velocity-and-acceleration-in-turbulent-flows-as-infinitely-differentiable-stochastic-processes/6AC3199BBF404A5BBD38A2BC04913E6F},\n publisher = {Cambridge University Press},\n id = {8cc0f47e-27fc-38bb-a4af-8911bc26fe10},\n created = {2021-04-09T15:22:51.557Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:22:51.557Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic differential equation. In comparison with previously proposed stochastic models, the obtained process is infinitely differentiable at a given finite Reynolds number, and its second-order statistical properties converge to those of an Ornstein-Uhlenbeck process in the infinite Reynolds number limit. In this limit, it exhibits furthermore intermittent scaling properties, as they can be quantified using higher-order statistics. To achieve this, we begin with generalizing the two-layered embedded stochastic process of Sawford (Phys. Fluids A, vol. 3 (6), 1991, pp. 1577-1586) by considering an infinite number of layers. We then study, both theoretically and numerically, the convergence towards a smooth (i.e. infinitely differentiable) Gaussian process. To include intermittent corrections, we follow similar considerations as for the multifractal random walk of Bacry et al. (Phys. Rev. E, vol. 64, 2001, 026103). We derive in an exact manner the statistical properties of this process, and compare them with those estimated from Lagrangian trajectories extracted from numerically simulated turbulent flows. Key predictions of the multifractal formalism regarding the acceleration correlation function and high-order structure functions are also derived. Through these predictions, we understand phenomenologically peculiar behaviours of the fluctuations in the dissipative range, that are not reproduced by our stochastic process. The proposed theoretical method regarding the modelling of infinitely differentiability opens the route to the full stochastic modelling of velocity, including the peculiar action of viscosity on the very fine scales.},\n bibtype = {article},\n author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},\n doi = {10.1017/jfm.2020.495},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic differential equation. In comparison with previously proposed stochastic models, the obtained process is infinitely differentiable at a given finite Reynolds number, and its second-order statistical properties converge to those of an Ornstein-Uhlenbeck process in the infinite Reynolds number limit. In this limit, it exhibits furthermore intermittent scaling properties, as they can be quantified using higher-order statistics. To achieve this, we begin with generalizing the two-layered embedded stochastic process of Sawford (Phys. Fluids A, vol. 3 (6), 1991, pp. 1577-1586) by considering an infinite number of layers. We then study, both theoretically and numerically, the convergence towards a smooth (i.e. infinitely differentiable) Gaussian process. To include intermittent corrections, we follow similar considerations as for the multifractal random walk of Bacry et al. (Phys. Rev. E, vol. 64, 2001, 026103). We derive in an exact manner the statistical properties of this process, and compare them with those estimated from Lagrangian trajectories extracted from numerically simulated turbulent flows. Key predictions of the multifractal formalism regarding the acceleration correlation function and high-order structure functions are also derived. Through these predictions, we understand phenomenologically peculiar behaviours of the fluctuations in the dissipative range, that are not reproduced by our stochastic process. The proposed theoretical method regarding the modelling of infinitely differentiability opens the route to the full stochastic modelling of velocity, including the peculiar action of viscosity on the very fine scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Díaz,  J.; Marton,  F.;  and Gobbetti,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Graphics (Pergamon)</i>, 88: 45-56. 5 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.cag.2020.03.002\"\n     onclick=\"log_download('daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020', 'http://doi.org/10.1016/j.cag.2020.03.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>7 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},\n type = {article},\n year = {2020},\n keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},\n pages = {45-56},\n volume = {88},\n month = {5},\n publisher = {Elsevier Ltd},\n day = {1},\n id = {2163eeea-5277-3538-b932-9bca1745b1b6},\n created = {2021-04-09T15:22:57.667Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:22:57.667Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},\n bibtype = {article},\n author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},\n doi = {10.1016/j.cag.2020.03.002},\n journal = {Computers and Graphics (Pergamon)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/354e1d2d-d745-37f7-0d56-c9b7a49cd905/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/354e1d2d-d745-37f7-0d56-c9b7a49cd905/full_text.pdf.pdf', event);\">\n    ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kashinath,  K.;  and Marcus,  P.\n</span>\n\n  \n\n</span>\n\n  Technical Report 2 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/354e1d2d-d745-37f7-0d56-c9b7a49cd905/full_text.pdf.pdf\"\n     onclick=\"log_download('kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/354e1d2d-d745-37f7-0d56-c9b7a49cd905/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kashinath-marcus-enforcinghardphysicalconstraintsincnnsthroughdifferentiablepdelayer-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@techreport{\n title = {ENFORCING HARD PHYSICAL CONSTRAINTS IN CNNS THROUGH DIFFERENTIABLE PDE LAYER},\n type = {techreport},\n year = {2020},\n month = {2},\n day = {26},\n id = {11ddc1a2-9ba3-3585-8fff-4772389fff79},\n created = {2021-04-09T15:22:58.110Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:07.834Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions. Many systems in the physical sciences are governed by Partial Differential Equations (PDEs). Enforcing these as hard constraints, we show, are inefficient in conventional frameworks due to the high dimensionality of the generated fields. To this end, we propose the use of a novel differentiable spectral projection layer for neural networks that efficiently enforces spatial PDE constraints using spectral methods, yet is fully differentiable, allowing for its use as a layer within Convolutional Neural Networks (CNNs) during end-to-end training. We show that its computational cost is cheaper than a single convolution layer. We apply it to an important class of physical systems-incompressible turbulent flows, where the divergence-free PDE constraint is required. We train a 3D Conditional Generative Adversarial Network (CGAN) for turbulent flow superresolution efficiently, while guaranteeing the spatial PDE constraint of zero divergence. Furthermore, our empirical results show that the model produces realistic flow statistics when trained with hard constraints imposed via the proposed novel differentiable spectral projection layer, as compared to soft constrained and unconstrained counterparts.},\n bibtype = {techreport},\n author = {Kashinath, Karthik and Marcus, Philip}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions. Many systems in the physical sciences are governed by Partial Differential Equations (PDEs). Enforcing these as hard constraints, we show, are inefficient in conventional frameworks due to the high dimensionality of the generated fields. To this end, we propose the use of a novel differentiable spectral projection layer for neural networks that efficiently enforces spatial PDE constraints using spectral methods, yet is fully differentiable, allowing for its use as a layer within Convolutional Neural Networks (CNNs) during end-to-end training. We show that its computational cost is cheaper than a single convolution layer. We apply it to an important class of physical systems-incompressible turbulent flows, where the divergence-free PDE constraint is required. We train a 3D Conditional Generative Adversarial Network (CGAN) for turbulent flow superresolution efficiently, while guaranteeing the spatial PDE constraint of zero divergence. Furthermore, our empirical results show that the model produces realistic flow statistics when trained with hard constraints imposed via the proposed novel differentiable spectral projection layer, as compared to soft constrained and unconstrained counterparts.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"olshanskii-speeddirectiondescriptionofturbulentflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0f028845-ab84-e2a7-3c74-426d30dcddb5/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'olshanskii-speeddirectiondescriptionofturbulentflows-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0f028845-ab84-e2a7-3c74-426d30dcddb5/full_text.pdf.pdf', event);\">\n    Speed-direction description of turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Olshanskii,  M., A.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 32(11): 115128. 11 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0f028845-ab84-e2a7-3c74-426d30dcddb5/full_text.pdf.pdf\"\n     onclick=\"log_download('olshanskii-speeddirectiondescriptionofturbulentflows-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/0f028845-ab84-e2a7-3c74-426d30dcddb5/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Speed-direction description of turbulent flows [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/5.0031218\"\n     onclick=\"log_download('olshanskii-speeddirectiondescriptionofturbulentflows-2020', 'http://aip.scitation.org/doi/10.1063/5.0031218', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Speed-direction description of turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/5.0031218\"\n     onclick=\"log_download('olshanskii-speeddirectiondescriptionofturbulentflows-2020', 'http://doi.org/10.1063/5.0031218', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/olshanskii-speeddirectiondescriptionofturbulentflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('olshanskii-speeddirectiondescriptionofturbulentflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Speed-direction description of turbulent flows},\n type = {article},\n year = {2020},\n pages = {115128},\n volume = {32},\n websites = {http://aip.scitation.org/doi/10.1063/5.0031218},\n month = {11},\n publisher = {American Institute of Physics Inc.},\n day = {1},\n id = {61e5a178-e0bc-3b06-82b2-2ec7fe5c9107},\n created = {2021-04-09T15:22:58.545Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:08.486Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In this note, we introduce speed and direction variables to describe the motion of incompressible viscous fluid. Fluid velocity u is decomposed into u = ur, with u = |u| and r = u/|u|. We consider a directional split of the Navier-Stokes equations into a coupled system of equations for u and for r. The equation for u is particularly simple but solely maintains the energy balance of the system. Under the assumption of a weak correlation between fluctuations in speed and direction in a developed turbulent flow, we further illustrate the application of u-r variables to describe mean statistics of a shear turbulence. The standard (full) Reynolds stress tensor does not appear in a resulting equation for the mean flow profile.},\n bibtype = {article},\n author = {Olshanskii, Maxim A.},\n doi = {10.1063/5.0031218},\n journal = {Physics of Fluids},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this note, we introduce speed and direction variables to describe the motion of incompressible viscous fluid. Fluid velocity u is decomposed into u = ur, with u = |u| and r = u/|u|. We consider a directional split of the Navier-Stokes equations into a coupled system of equations for u and for r. The equation for u is particularly simple but solely maintains the energy balance of the system. Under the assumption of a weak correlation between fluctuations in speed and direction in a developed turbulent flow, we further illustrate the application of u-r variables to describe mean statistics of a shear turbulence. The standard (full) Reynolds stress tensor does not appear in a resulting equation for the mean flow profile.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ziaei-goudarzi-atakeonwakemodelingofturbinesbasedondeeplearning-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  A take on wake modeling of turbines based on deep learning.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ziaei,  D.;  and Goudarzi,  N.\n</span>\n\n  \n\n</span>\n\n  In <i>American Society of Mechanical Engineers, Power Division (Publication) POWER</i>, volume 2020-August, 10 2020. American Society of Mechanical Engineers (ASME)\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1115/POWER2020-16950\"\n     onclick=\"log_download('ziaei-goudarzi-atakeonwakemodelingofturbinesbasedondeeplearning-2020', 'http://doi.org/10.1115/POWER2020-16950', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ziaei-goudarzi-atakeonwakemodelingofturbinesbasedondeeplearning-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ziaei-goudarzi-atakeonwakemodelingofturbinesbasedondeeplearning-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {A take on wake modeling of turbines based on deep learning},\n type = {inproceedings},\n year = {2020},\n keywords = {CNN,Computational fluid dynamics,GAN,Offshore renewable energy systems,Reduced-order modeling,Turbulent flow field,Unsupervised learning},\n volume = {2020-August},\n month = {10},\n publisher = {American Society of Mechanical Engineers (ASME)},\n day = {13},\n id = {7aafb4af-eba4-32ce-a7dc-e2914e92ed36},\n created = {2021-04-09T15:22:59.016Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:22:59.016Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Analyzing real-world engineering problems such as wake modeling of wind/ocean current turbines are known to be complex and challenging. The multivariable nature of these problems requires either the implementation of computational analyses under certain simplifying assumptions or conducting experiments for a limited number of scenarios. Hence, there is always several fundamental features missed in understanding the key players in determining the complex turbulent velocity fields within the wake of turbines. It becomes more critical when studying the optimization of wind/ocean renewable farms with more than one turbine to determine the true power density or cost of energy. Machine learning (ML) algorithms suggest promising complementary solutions to the existing physics-based (e.g. wind farm wake modeling) techniques. Implementation of conventional ML algorithms that require long-term historical data is either not feasible in many real-case applications or very expensive and time-consuming. Moreover, there are often infinite features in dataset with complex relation between them. It makes the tasks of feature selection and model tuning more challenging. In this work, a cross-domain study of physics and ML models is performed to show the need of integration of these domains. The key achievement of this work is two-fold: first, suggesting a group of emerging generative models (e.g. Generative Adversarial Networks) in the wake modeling domain; second, reducing the computational cost by demanding either smaller or no simulation dataset.},\n bibtype = {inproceedings},\n author = {Ziaei, Dorsa and Goudarzi, Navid},\n doi = {10.1115/POWER2020-16950},\n booktitle = {American Society of Mechanical Engineers, Power Division (Publication) POWER}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Analyzing real-world engineering problems such as wake modeling of wind/ocean current turbines are known to be complex and challenging. The multivariable nature of these problems requires either the implementation of computational analyses under certain simplifying assumptions or conducting experiments for a limited number of scenarios. Hence, there is always several fundamental features missed in understanding the key players in determining the complex turbulent velocity fields within the wake of turbines. It becomes more critical when studying the optimization of wind/ocean renewable farms with more than one turbine to determine the true power density or cost of energy. Machine learning (ML) algorithms suggest promising complementary solutions to the existing physics-based (e.g. wind farm wake modeling) techniques. Implementation of conventional ML algorithms that require long-term historical data is either not feasible in many real-case applications or very expensive and time-consuming. Moreover, there are often infinite features in dataset with complex relation between them. It makes the tasks of feature selection and model tuning more challenging. In this work, a cross-domain study of physics and ML models is performed to show the need of integration of these domains. The key achievement of this work is two-fold: first, suggesting a group of emerging generative models (e.g. Generative Adversarial Networks) in the wake modeling domain; second, reducing the computational cost by demanding either smaller or no simulation dataset.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xiao-wu-laizet-duan-flowsoverperiodichillsofparameterizedgeometriesadatasetfordatadriventurbulencemodelingfromdirectsimulations-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xiao,  H.; Wu,  J., L.; Laizet,  S.;  and Duan,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Fluids</i>, 200: 104431. 3 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compfluid.2020.104431\"\n     onclick=\"log_download('xiao-wu-laizet-duan-flowsoverperiodichillsofparameterizedgeometriesadatasetfordatadriventurbulencemodelingfromdirectsimulations-2020', 'http://doi.org/10.1016/j.compfluid.2020.104431', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xiao-wu-laizet-duan-flowsoverperiodichillsofparameterizedgeometriesadatasetfordatadriventurbulencemodelingfromdirectsimulations-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xiao-wu-laizet-duan-flowsoverperiodichillsofparameterizedgeometriesadatasetfordatadriventurbulencemodelingfromdirectsimulations-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Flows over periodic hills of parameterized geometries: A dataset for data-driven turbulence modeling from direct simulations},\n type = {article},\n year = {2020},\n keywords = {Physics-informed machine learning,Separated flows,Turbulence modeling},\n pages = {104431},\n volume = {200},\n month = {3},\n publisher = {Elsevier Ltd},\n day = {30},\n id = {d382f22a-060d-3a0c-948f-2de090393e2d},\n created = {2021-04-09T15:22:59.647Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:22:59.647Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Computational fluid dynamics models based on Reynolds-averaged Navier–Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant for decades. With recent advances in machine learning, data-driven turbulence models have become attractive alternatives worth further explorations. However, a major obstacle in the development of data-driven turbulence models is the lack of training data. In this work, we survey currently available public turbulent flow databases and conclude that they are inadequate for developing and validating data-driven models. Rather, we need more benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space for this purpose. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations. We further demonstrate the use of such a dataset by training a machine learning model that predicts Reynolds stress anisotropy based on a set of mean flow features. We expect the generated dataset, along with its design methodology and the example application presented herein, will facilitate development and comparison of future data-driven turbulence models.},\n bibtype = {article},\n author = {Xiao, Heng and Wu, Jin Long and Laizet, Sylvain and Duan, Lian},\n doi = {10.1016/j.compfluid.2020.104431},\n journal = {Computers and Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Computational fluid dynamics models based on Reynolds-averaged Navier–Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant for decades. With recent advances in machine learning, data-driven turbulence models have become attractive alternatives worth further explorations. However, a major obstacle in the development of data-driven turbulence models is the lack of training data. In this work, we survey currently available public turbulent flow databases and conclude that they are inadequate for developing and validating data-driven models. Rather, we need more benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space for this purpose. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations. We further demonstrate the use of such a dataset by training a machine learning model that predicts Reynolds stress anisotropy based on a set of mean flow features. We expect the generated dataset, along with its design methodology and the example application presented herein, will facilitate development and comparison of future data-driven turbulence models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html', event);\">\n    Developing particle image velocimetry software based on a deep neural network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Majewski,  W.; Wei,  R.;  and Kumar,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Flow Visualization and Image Processing</i>, 27(4): 359-376.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"\n     onclick=\"log_download('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing particle image velocimetry software based on a deep neural network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1615/JFlowVisImageProc.2020033180\"\n     onclick=\"log_download('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://doi.org/10.1615/JFlowVisImageProc.2020033180', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>12 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing particle image velocimetry software based on a deep neural network},\n type = {article},\n year = {2020},\n keywords = {Deep neural networks,Estimation of fluid motion,Particle image velocimetry},\n pages = {359-376},\n volume = {27},\n websites = {http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},\n publisher = {Begell House Inc.},\n id = {855967e5-91dd-34db-92b6-6aa75f42ee99},\n created = {2021-04-09T15:23:00.253Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:00.253Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {As an experimental technique for fluid mechanics, particle image velocimetry (PIV) can extract global and quantitative velocity field from images. With the development of artificial intelligence, designing PIV method based on deep learning is quite promising and worth exploring. First, in this paper, the authors introduce the optical flow neural network based on one proposed in the computer vision community. Second, a data set including particle images and the ground truth fluid motion is generated to train the parameters of the networks. This leads to a deep neural network for PIV which can provide estimation of dense motion (down to maximum one vector for one pixel) with the high degree of efficiency. The featuring of particle image extracted by the neural network is also investigated in this paper. It is found that feature matching improves the accuracy of esti-mation. The proposed network model is firstly evaluated by a synthetic image sequence of turbulent flow. An experiment measuring the flow over an aerofoil is used to validate the practicability. The experimental results indicate that compared with the traditional cross correlation method, the proposed deep neural network has advantages in accuracy, spatial resolution, and efficiency.},\n bibtype = {article},\n author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},\n doi = {10.1615/JFlowVisImageProc.2020033180},\n journal = {Journal of Flow Visualization and Image Processing},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  As an experimental technique for fluid mechanics, particle image velocimetry (PIV) can extract global and quantitative velocity field from images. With the development of artificial intelligence, designing PIV method based on deep learning is quite promising and worth exploring. First, in this paper, the authors introduce the optical flow neural network based on one proposed in the computer vision community. Second, a data set including particle images and the ground truth fluid motion is generated to train the parameters of the networks. This leads to a deep neural network for PIV which can provide estimation of dense motion (down to maximum one vector for one pixel) with the high degree of efficiency. The featuring of particle image extracted by the neural network is also investigated in this paper. It is found that feature matching improves the accuracy of esti-mation. The proposed network model is firstly evaluated by a synthetic image sequence of turbulent flow. An experiment measuring the flow over an aerofoil is used to validate the practicability. The experimental results indicate that compared with the traditional cross correlation method, the proposed deep neural network has advantages in accuracy, spatial resolution, and efficiency.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF', event);\">\n    Dual channels of helicity cascade in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yan,  Z.; Li,  X.; Yu,  C.; Wang,  J.;  and Chen,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 894.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF\"\n     onclick=\"log_download('yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dual channels of helicity cascade in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.289\"\n     onclick=\"log_download('yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020', 'http://doi.org/10.1017/jfm.2020.289', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yan-li-yu-wang-chen-dualchannelsofhelicitycascadeinturbulentflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dual channels of helicity cascade in turbulent flows},\n type = {article},\n year = {2020},\n keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},\n volume = {894},\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/dual-channels-of-helicity-cascade-in-turbulent-flows/F44321DC4323869E99AD3CA7DA6BE1BF},\n publisher = {Cambridge University Press},\n id = {08eeb047-4cd5-346d-9698-456857823601},\n created = {2021-04-09T15:23:00.826Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:00.826Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulent flows. Through theoretical analyses, we find that there are two channels in the helicity cascade process, which differs dramatically from the traditional viewpoint. In this paper, we have conducted important research on the newly proposed dual-channel helicity cascade theory, including vortex dynamic processes, intermittent discrepancies, tensor geometries, etc. The first channel mainly originates from the vortex twisting process, and the second channel mainly originates from the vortex stretching process. Antisymmetric tensors are introduced to the derivations of dual-channel helicity cascade theory, and a complex rotation frame leads to a higher helicity transfer efficiency. By analysing data from direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other types of turbulent flows. The intermittency of the second channel is stronger than that of the first channel. In addition, we find a novel mechanism of hindered or even inverse energy cascades, which could be attributed to the second-channel helicity flux.},\n bibtype = {article},\n author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Wang, Jianchun and Chen, Shiyi},\n doi = {10.1017/jfm.2020.289},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulent flows. Through theoretical analyses, we find that there are two channels in the helicity cascade process, which differs dramatically from the traditional viewpoint. In this paper, we have conducted important research on the newly proposed dual-channel helicity cascade theory, including vortex dynamic processes, intermittent discrepancies, tensor geometries, etc. The first channel mainly originates from the vortex twisting process, and the second channel mainly originates from the vortex stretching process. Antisymmetric tensors are introduced to the derivations of dual-channel helicity cascade theory, and a complex rotation frame leads to a higher helicity transfer efficiency. By analysing data from direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other types of turbulent flows. The intermittency of the second channel is stronger than that of the first channel. In addition, we find a novel mechanism of hindered or even inverse energy cascades, which could be attributed to the second-channel helicity flux.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020', 'https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607', event);\">\n    Data compression for turbulence databases using spatiotemporal subsampling and local resimulation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  Z.; Zaki,  T., A.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 5(6): 064607. 6 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607\"\n     onclick=\"log_download('wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020', 'https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Data compression for turbulence databases using spatiotemporal subsampling and local resimulation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.5.064607\"\n     onclick=\"log_download('wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020', 'http://doi.org/10.1103/PhysRevFluids.5.064607', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-zaki-meneveau-datacompressionforturbulencedatabasesusingspatiotemporalsubsamplingandlocalresimulation-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Data compression for turbulence databases using spatiotemporal subsampling and local resimulation},\n type = {article},\n year = {2020},\n pages = {064607},\n volume = {5},\n websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.064607},\n month = {6},\n publisher = {American Physical Society},\n day = {1},\n id = {6ce865be-a713-3e73-83dc-be3fbb8bd04b},\n created = {2021-04-09T15:23:01.423Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:01.423Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.},\n bibtype = {article},\n author = {Wu, Zhao and Zaki, Tamer A. and Meneveau, Charles},\n doi = {10.1103/PhysRevFluids.5.064607},\n journal = {Physical Review Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5d5a4e3b-6739-43f7-3594-0abb38acecf1/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5d5a4e3b-6739-43f7-3594-0abb38acecf1/full_text.pdf.pdf', event);\">\n    Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ehlers,  F.; Schröder,  A.;  and Gesemann,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 31(9): 16. 9 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5d5a4e3b-6739-43f7-3594-0abb38acecf1/full_text.pdf.pdf\"\n     onclick=\"log_download('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/5d5a4e3b-6739-43f7-3594-0abb38acecf1/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1088/1361-6501/ab848d\"\n     onclick=\"log_download('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'https://doi.org/10.1088/1361-6501/ab848d', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab848d\"\n     onclick=\"log_download('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'http://doi.org/10.1088/1361-6501/ab848d', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>14 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},\n type = {article},\n year = {2020},\n pages = {16},\n volume = {31},\n websites = {https://doi.org/10.1088/1361-6501/ab848d},\n month = {9},\n publisher = {Institute of Physics Publishing},\n day = {1},\n id = {65d799a3-d02e-31c4-bf57-e23d965b9285},\n created = {2021-04-09T15:23:01.980Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:10.041Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method &#x27;Shake-the-Box&#x27; (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit&#x27;s core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},\n bibtype = {article},\n author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},\n doi = {10.1088/1361-6501/ab848d},\n journal = {Measurement Science and Technology},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020', 'https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta', event);\">\n    As a matter of tension - kinetic energy spectra in MHD turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grete,  P.; O’Shea,  B., W.;  and Beckwith,  K.\n</span>\n\n  \n\n</span>\n\n  9 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta\"\n     onclick=\"log_download('grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020', 'https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"As a matter of tension - kinetic energy spectra in MHD turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3847/1538-4357/abdd22\"\n     onclick=\"log_download('grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020', 'http://doi.org/10.3847/1538-4357/abdd22', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grete-oshea-beckwith-asamatteroftensionkineticenergyspectrainmhdturbulence-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {As a matter of tension - kinetic energy spectra in MHD turbulence},\n type = {misc},\n year = {2020},\n source = {arXiv},\n keywords = {MHD,Methods: numerical,Turbulence},\n pages = {148},\n volume = {909},\n issue = {2},\n websites = {https://iopscience.iop.org/article/10.3847/1538-4357/abdd22,https://iopscience.iop.org/article/10.3847/1538-4357/abdd22/meta},\n month = {9},\n publisher = {arXiv},\n day = {7},\n id = {46aa6f81-0116-3381-9a45-cb8ae1a65f65},\n created = {2021-04-09T15:23:04.161Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:04.161Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Magnetized turbulence is ubiquitous in many astrophysical and terrestrial systems but no complete, uncontested theory even in the simplest form, magnetohydrodynamics (MHD), exists. Many theories and phenomenologies focus on the joint (kinetic and magnetic) energy fluxes and spectra. We highlight the importance of treating kinetic and magnetic energies separately to shed light on MHD turbulence dynamics. We conduct an implicit large eddy simulation of subsonic, super-Alfvénic MHD turbulence and analyze the scale-wise energy transfer over time. Our key finding is that the kinetic energy spectrum develops a scaling of approximately k−4/3 in the stationary regime as the kinetic energy cascade is suppressed by magnetic tension. This motivates a reevaluation of existing MHD turbulence theories with respect to a more differentiated modeling of the energy fluxes.},\n bibtype = {misc},\n author = {Grete, Philipp and O’Shea, Brian W. and Beckwith, Kris},\n doi = {10.3847/1538-4357/abdd22}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Magnetized turbulence is ubiquitous in many astrophysical and terrestrial systems but no complete, uncontested theory even in the simplest form, magnetohydrodynamics (MHD), exists. Many theories and phenomenologies focus on the joint (kinetic and magnetic) energy fluxes and spectra. We highlight the importance of treating kinetic and magnetic energies separately to shed light on MHD turbulence dynamics. We conduct an implicit large eddy simulation of subsonic, super-Alfvénic MHD turbulence and analyze the scale-wise energy transfer over time. Our key finding is that the kinetic energy spectrum develops a scaling of approximately k−4/3 in the stationary regime as the kinetic energy cascade is suppressed by magnetic tension. This motivates a reevaluation of existing MHD turbulence theories with respect to a more differentiated modeling of the energy fluxes.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6', event);\">\n    Unsupervised deep learning for super-resolution reconstruction of turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kim,  H.; Kim,  J.; Won,  S.;  and Lee,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 910.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6\"\n     onclick=\"log_download('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Unsupervised deep learning for super-resolution reconstruction of turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.1028\"\n     onclick=\"log_download('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020', 'http://doi.org/10.1017/jfm.2020.1028', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kim-kim-won-lee-unsuperviseddeeplearningforsuperresolutionreconstructionofturbulence-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Unsupervised deep learning for super-resolution reconstruction of turbulence},\n type = {article},\n year = {2020},\n keywords = {turbulence simulation},\n volume = {910},\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/abs/unsupervised-deep-learning-for-superresolution-reconstruction-of-turbulence/CF82FEF56DD7C2711B1102209872E6D6},\n publisher = {Cambridge University Press},\n id = {27c4e2e7-9c31-38fb-a542-9c5db2bdcdeb},\n created = {2021-04-09T15:23:05.570Z},\n accessed = {2021-04-08},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:05.570Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.},\n bibtype = {article},\n author = {Kim, Hyojin and Kim, Junhyuk and Won, Sungjin and Lee, Changhoon},\n doi = {10.1017/jfm.2020.1028},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Recent attempts to use deep learning for super-resolution reconstruction of turbulent flows have used supervised learning, which requires paired data for training. This limitation hinders more practical applications of super-resolution reconstruction. Therefore, we present an unsupervised learning model that adopts a cycle-consistent generative adversarial network (CycleGAN) that can be trained with unpaired turbulence data for super-resolution reconstruction. Our model is validated using three examples: (i) recovering the original flow field from filtered data using direct numerical simulation (DNS) of homogeneous isotropic turbulence; (ii) reconstructing full-resolution fields using partially measured data from the DNS of turbulent channel flows; and (iii) generating a DNS-resolution flow field from large-eddy simulation (LES) data for turbulent channel flows. In examples (i) and (ii), for which paired data are available for supervised learning, our unsupervised model demonstrates qualitatively and quantitatively similar performance as that of the best supervised learning model. More importantly, in example (iii), where supervised learning is impossible, our model successfully reconstructs the high-resolution flow field of statistical DNS quality from the LES data. Furthermore, we find that the present model has almost universal applicability to all values of Reynolds numbers within the tested range. This demonstrates that unsupervised learning of turbulence data is indeed possible, opening a new door for the wide application of super-resolution reconstruction of turbulent fields.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/70c270b0-be18-a15d-13ce-fc26512cf651/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/70c270b0-be18-a15d-13ce-fc26512cf651/full_text.pdf.pdf', event);\">\n    Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Clark Di Leoni,  P.; Zaki,  T., A.; Karniadakis,  G.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  6 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/70c270b0-be18-a15d-13ce-fc26512cf651/full_text.pdf.pdf\"\n     onclick=\"log_download('clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/70c270b0-be18-a15d-13ce-fc26512cf651/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://doi.org/10.1017/jfm.2020.977\"\n     onclick=\"log_download('clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020', 'https://doi.org/10.1017/jfm.2020.977', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.977\"\n     onclick=\"log_download('clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020', 'http://doi.org/10.1017/jfm.2020.977', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('clarkdileoni-zaki-karniadakis-meneveau-twopointstressstrainratecorrelationstructureandnonlocaleddyviscosityinturbulentflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Two-point stress-strain rate correlation structure and non-local eddy viscosity in turbulent flows},\n type = {misc},\n year = {2020},\n source = {arXiv},\n keywords = {turbulence modelling,turbulence theory †},\n pages = {6},\n volume = {914},\n websites = {https://doi.org/10.1017/jfm.2020.977},\n month = {6},\n publisher = {arXiv},\n day = {3},\n id = {70465517-279e-3fdb-9989-01d5df030e63},\n created = {2021-04-09T15:23:06.069Z},\n accessed = {2021-04-08},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:11.909Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {By analyzing the Karman-Howarth equation for filtered velocity fields in turbulent flows, we show that the two-point correlation between filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlations-based statistical priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence we show that local eddy viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 &lt; α &lt; 1 rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows.},\n bibtype = {misc},\n author = {Clark Di Leoni, Patricio and Zaki, Tamer A. and Karniadakis, George and Meneveau, Charles},\n doi = {10.1017/jfm.2020.977}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  By analyzing the Karman-Howarth equation for filtered velocity fields in turbulent flows, we show that the two-point correlation between filtered strain-rate and subfilter stress tensors plays a central role in the evolution of filtered-velocity correlation functions. Two-point correlations-based statistical priori tests thus enable rigorous and physically meaningful studies of turbulence models. Using data from direct numerical simulations of isotropic and channel flow turbulence we show that local eddy viscosity models fail to exhibit the long tails observed in the real subfilter stress-strain rate correlation functions. Stronger non-local correlations may be achieved by defining the eddy-viscosity model based on fractional gradients of order 0 < α < 1 rather than the classical gradient corresponding to α = 1. Analyses of such correlation functions are presented for various orders of the fractional gradient operators. It is found that in isotropic turbulence fractional derivative order α ∼ 0.5 yields best results, while for channel flow α ∼ 0.2 yields better results for the correlations in the streamwise direction, even well into the core channel region. In the spanwise direction, channel flow results show significantly more local interactions. The overall results confirm strong non-locality in the interactions between subfilter stresses and resolved-scale fluid deformation rates, but with non-trivial directional dependencies in non-isotropic flows.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart1generaltheoryforviscousincompressiblefluids-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Stochastic Lagrangian dynamics of vorticity. Part 1. General theory for viscous, incompressible fluids.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eyink,  G., L.; Gupta,  A.;  and Zaki,  T., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 901. 10 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.491\"\n     onclick=\"log_download('eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart1generaltheoryforviscousincompressiblefluids-2020', 'http://doi.org/10.1017/jfm.2020.491', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart1generaltheoryforviscousincompressiblefluids-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart1generaltheoryforviscousincompressiblefluids-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Stochastic Lagrangian dynamics of vorticity. Part 1. General theory for viscous, incompressible fluids},\n type = {article},\n year = {2020},\n volume = {901},\n month = {10},\n day = {25},\n id = {31cff53d-f2e9-385b-bee6-263cf1d5df55},\n created = {2021-04-09T15:23:08.688Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:08.688Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Prior mathematical work of Constantin &amp; Iyer (Commun. Pure Appl. Maths, vol. 61, 2008, pp. 330–345; Ann. Appl. Probab., vol. 21, 2011, pp. 1466–1492) has shown that incompressible Navier–Stokes solutions possess infinitely many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the invariants of Cauchy (Sciences mathématiques et physique, vol. I, 1815, pp. 33–73) for smooth Euler solutions. We reformulate this theory for the case of wall-bounded flows by appealing to the Kuz&#x27;min (Phys. Lett. A, vol. 96, 1983, pp. 88–90)–Oseledets (Russ. Math. Surv., vol. 44, 1989, p. 210) representation of Navier–Stokes dynamics, in terms of the vortex-momentum density associated to a continuous distribution of infinitesimal vortex rings. The Constantin–Iyer theory provides an exact representation for vorticity at any interior point as an average over stochastic vorticity contributions transported from the wall. We point out relations of this Lagrangian formulation with the Eulerian theory of Lighthill (Boundary layer theory. In Laminar Boundary Layers (ed. L. Rosenhead), 1963, pp. 46–113)–Morton (Geophys. Astrophys. Fluid Dyn., vol. 28, 1984, pp. 277–308) for vorticity generation at solid walls, and also with a statistical result of Taylor (Proc. R. Soc. Lond. A, vol. 135, 1932, pp. 685–702)–Huggins (J. Low Temp. Phys., vol. 96, 1994, pp. 317–346), which connects dissipative drag with organized cross-stream motion of vorticity and which is closely analogous to the ‘Josephson–Anderson relation’ for quantum superfluids. We elaborate a Monte Carlo numerical Lagrangian scheme to calculate the stochastic Cauchy invariants and their statistics, given the Eulerian space–time velocity field. The method is validated using an online database of a turbulent channel-flow simulation (Graham et al., J. Turbul., vol. 17, 2016, pp. 181–215), where conservation of the mean Cauchy invariant is verified for two selected buffer-layer events corresponding to an ‘ejection’ and a ‘sweep’. The variances of the stochastic Cauchy invariants grow exponentially backward in time, however, revealing Lagrangian chaos of the stochastic trajectories undergoing both fluid advection and viscous diffusion.},\n bibtype = {article},\n author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},\n doi = {10.1017/jfm.2020.491},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Prior mathematical work of Constantin & Iyer (Commun. Pure Appl. Maths, vol. 61, 2008, pp. 330–345; Ann. Appl. Probab., vol. 21, 2011, pp. 1466–1492) has shown that incompressible Navier–Stokes solutions possess infinitely many stochastic Lagrangian conservation laws for vorticity, backward in time, which generalize the invariants of Cauchy (Sciences mathématiques et physique, vol. I, 1815, pp. 33–73) for smooth Euler solutions. We reformulate this theory for the case of wall-bounded flows by appealing to the Kuz'min (Phys. Lett. A, vol. 96, 1983, pp. 88–90)–Oseledets (Russ. Math. Surv., vol. 44, 1989, p. 210) representation of Navier–Stokes dynamics, in terms of the vortex-momentum density associated to a continuous distribution of infinitesimal vortex rings. The Constantin–Iyer theory provides an exact representation for vorticity at any interior point as an average over stochastic vorticity contributions transported from the wall. We point out relations of this Lagrangian formulation with the Eulerian theory of Lighthill (Boundary layer theory. In Laminar Boundary Layers (ed. L. Rosenhead), 1963, pp. 46–113)–Morton (Geophys. Astrophys. Fluid Dyn., vol. 28, 1984, pp. 277–308) for vorticity generation at solid walls, and also with a statistical result of Taylor (Proc. R. Soc. Lond. A, vol. 135, 1932, pp. 685–702)–Huggins (J. Low Temp. Phys., vol. 96, 1994, pp. 317–346), which connects dissipative drag with organized cross-stream motion of vorticity and which is closely analogous to the ‘Josephson–Anderson relation’ for quantum superfluids. We elaborate a Monte Carlo numerical Lagrangian scheme to calculate the stochastic Cauchy invariants and their statistics, given the Eulerian space–time velocity field. The method is validated using an online database of a turbulent channel-flow simulation (Graham et al., J. Turbul., vol. 17, 2016, pp. 181–215), where conservation of the mean Cauchy invariant is verified for two selected buffer-layer events corresponding to an ‘ejection’ and a ‘sweep’. The variances of the stochastic Cauchy invariants grow exponentially backward in time, however, revealing Lagrangian chaos of the stochastic trajectories undergoing both fluid advection and viscous diffusion.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart2applicationtonearwallchannelflowturbulence-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Stochastic Lagrangian dynamics of vorticity. Part 2. Application to near-wall channel-flow turbulence.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eyink,  G., L.; Gupta,  A.;  and Zaki,  T., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 901. 10 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.492\"\n     onclick=\"log_download('eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart2applicationtonearwallchannelflowturbulence-2020', 'http://doi.org/10.1017/jfm.2020.492', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart2applicationtonearwallchannelflowturbulence-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eyink-gupta-zaki-stochasticlagrangiandynamicsofvorticitypart2applicationtonearwallchannelflowturbulence-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Stochastic Lagrangian dynamics of vorticity. Part 2. Application to near-wall channel-flow turbulence},\n type = {article},\n year = {2020},\n volume = {901},\n month = {10},\n day = {25},\n id = {f4a750c4-3dce-3e29-b0ae-ae027506a6da},\n created = {2021-04-09T15:23:09.180Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:09.180Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {We use an online database of a turbulent channel-flow simulation at 𝑅𝑒𝜏=1000 (Graham et al. J. Turbul., vol. 17, issue 2, 2016, pp. 181–215) to determine the origin of vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (J. Fluid Mech., vol. 633, 2009, pp.17–60), we identify typical ‘ejection’ and ‘sweep’ events in the buffer layer by local minima/maxima of the wall stress. In contrast to their conjecture, however, we find that vortex lifting from the wall is not a discrete event requiring ∼ 1 viscous time and ∼ 10 wall units, but is instead a distributed process over a space–time region at least 1∼2 orders of magnitude larger in extent. To reach this conclusion, we exploit a rigorous mathematical theory of vorticity dynamics for Navier–Stokes solutions, in terms of stochastic Lagrangian flows and stochastic Cauchy invariants, conserved on average backward in time. This theory yields exact expressions for vorticity inside the flow domain in terms of vorticity at the wall, as transported by viscous diffusion and by nonlinear advection, stretching and rotation. We show that Lagrangian chaos observed in the buffer layer can be reconciled with saturated vorticity magnitude by ‘virtual reconnection’: although the Eulerian vorticity field in the viscous sublayer has a single sign of spanwise component, opposite signs of Lagrangian vorticity evolve by rotation and cancel by viscous destruction. Our analysis reveals many unifying features of classical fluids and quantum superfluids. We argue that ‘bundles’ of quantized vortices in superfluid turbulence will also exhibit stochastic Lagrangian dynamics and satisfy stochastic conservation laws resulting from particle relabelling symmetry.},\n bibtype = {article},\n author = {Eyink, Gregory L. and Gupta, Akshat and Zaki, Tamer A.},\n doi = {10.1017/jfm.2020.492},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We use an online database of a turbulent channel-flow simulation at 𝑅𝑒𝜏=1000 (Graham et al. J. Turbul., vol. 17, issue 2, 2016, pp. 181–215) to determine the origin of vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (J. Fluid Mech., vol. 633, 2009, pp.17–60), we identify typical ‘ejection’ and ‘sweep’ events in the buffer layer by local minima/maxima of the wall stress. In contrast to their conjecture, however, we find that vortex lifting from the wall is not a discrete event requiring ∼ 1 viscous time and ∼ 10 wall units, but is instead a distributed process over a space–time region at least 1∼2 orders of magnitude larger in extent. To reach this conclusion, we exploit a rigorous mathematical theory of vorticity dynamics for Navier–Stokes solutions, in terms of stochastic Lagrangian flows and stochastic Cauchy invariants, conserved on average backward in time. This theory yields exact expressions for vorticity inside the flow domain in terms of vorticity at the wall, as transported by viscous diffusion and by nonlinear advection, stretching and rotation. We show that Lagrangian chaos observed in the buffer layer can be reconciled with saturated vorticity magnitude by ‘virtual reconnection’: although the Eulerian vorticity field in the viscous sublayer has a single sign of spanwise component, opposite signs of Lagrangian vorticity evolve by rotation and cancel by viscous destruction. Our analysis reveals many unifying features of classical fluids and quantum superfluids. We argue that ‘bundles’ of quantized vortices in superfluid turbulence will also exhibit stochastic Lagrangian dynamics and satisfy stochastic conservation laws resulting from particle relabelling symmetry.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020', 'https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604', event);\">\n    Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Krishna,  C., V.; Wang,  M.; Hemati,  M., S.;  and Luhar,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 5(5): 54604. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604\"\n     onclick=\"log_download('krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020', 'https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.5.054604\"\n     onclick=\"log_download('krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020', 'http://doi.org/10.1103/PhysRevFluids.5.054604', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('krishna-wang-hemati-luhar-reconstructingthetimeevolutionofwallboundedturbulentflowsfromnontimeresolvedpivmeasurements-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements},\n type = {article},\n year = {2020},\n pages = {54604},\n volume = {5},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.054604},\n month = {4},\n publisher = {American Physical Society},\n id = {f211ca87-c1f5-30ae-b860-b03aca46a225},\n created = {2021-04-09T15:24:46.917Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:46.917Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Krishna, C Vamsi and Wang, Mengying and Hemati, Maziar S and Luhar, Mitul},\n doi = {10.1103/PhysRevFluids.5.054604},\n journal = {Physical Review Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020', 'http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117', event);\">\n    High-Reynolds-number fractal signature of nascent turbulence during transition.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  Z.; Zaki,  T., A.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Proceedings of the National Academy of Sciences</i>, 117(7): 3461-3468. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117\"\n     onclick=\"log_download('wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020', 'http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"High-Reynolds-number fractal signature of nascent turbulence during transition [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1073/pnas.1916636117\"\n     onclick=\"log_download('wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020', 'http://doi.org/10.1073/pnas.1916636117', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-zaki-meneveau-highreynoldsnumberfractalsignatureofnascentturbulenceduringtransition-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {High-Reynolds-number fractal signature of nascent turbulence during transition},\n type = {article},\n year = {2020},\n keywords = {Fractal dimension,Transitional boundary layer,Turbulent spots},\n pages = {3461-3468},\n volume = {117},\n websites = {http://www.pnas.org/lookup/doi/10.1073/pnas.1916636117},\n month = {4},\n publisher = {National Academy of Sciences},\n id = {961c0616-69f2-3de4-b644-445021490b1f},\n created = {2021-04-09T15:24:47.453Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:47.453Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension D ≈ 7 / 3 , where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume–area fractal scaling exponent. Measurements show a dimension of D = 2.36 ± 0.03 over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.},\n bibtype = {article},\n author = {Wu, Zhao and Zaki, Tamer A and Meneveau, Charles},\n doi = {10.1073/pnas.1916636117},\n journal = {Proceedings of the National Academy of Sciences},\n number = {7}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension D ≈ 7 / 3 , where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume–area fractal scaling exponent. Measurements show a dimension of D = 2.36 ± 0.03 over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020', 'https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603', event);\">\n    Geometric constraints on energy transfer in the turbulent cascade.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ballouz,  J., G.;  and Ouellette,  N., T.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 5(3): 34603. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603\"\n     onclick=\"log_download('ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020', 'https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Geometric constraints on energy transfer in the turbulent cascade [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.5.034603\"\n     onclick=\"log_download('ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020', 'http://doi.org/10.1103/PhysRevFluids.5.034603', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ballouz-ouellette-geometricconstraintsonenergytransferintheturbulentcascade-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Geometric constraints on energy transfer in the turbulent cascade},\n type = {article},\n year = {2020},\n pages = {34603},\n volume = {5},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.5.034603},\n month = {4},\n publisher = {American Physical Society},\n id = {a82e659f-7268-3e32-b8f7-441f609d4224},\n created = {2021-04-09T15:24:48.171Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:48.171Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The energy cascade is the most significant feature that separates turbulence from other unsteady flows, and results from the behavior of the nonlinear term in the Navier-Stokes equations. The mathematical form of this term, however, places constraints on exactly how it can act. Here we consider the action of the nonlinear term in physical space rather than in Fourier space, where the energy transfer between scales can be interpreted as a mechanical process where some scales do work on others. This formulation reveals the fundamental role played by geometry, as work can only be done when the eigenframes of the turbulent stress and strain rate are appropriately aligned. By comparing a direct numerical simulation of the Navier-Stokes equations, an ensemble of random solenoidal vector fields, and a random sampling of uniform eigenframe alignments, we show that this geometric alignment plays a much stronger role in determining the flux between scales than do the magnitudes of the stress and strain rate. We also show that when the alignment is effectively two dimensional, even when embedded in a three-dimensional flow, the energy flux is typically inverse, suggesting that the inverse cascade in two-dimensional turbulence may have a kinematic origin. Our results point to some potentially fruitful directions for turbulence modeling.},\n bibtype = {article},\n author = {Ballouz, Joseph G and Ouellette, Nicholas T},\n doi = {10.1103/PhysRevFluids.5.034603},\n journal = {Physical Review Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The energy cascade is the most significant feature that separates turbulence from other unsteady flows, and results from the behavior of the nonlinear term in the Navier-Stokes equations. The mathematical form of this term, however, places constraints on exactly how it can act. Here we consider the action of the nonlinear term in physical space rather than in Fourier space, where the energy transfer between scales can be interpreted as a mechanical process where some scales do work on others. This formulation reveals the fundamental role played by geometry, as work can only be done when the eigenframes of the turbulent stress and strain rate are appropriately aligned. By comparing a direct numerical simulation of the Navier-Stokes equations, an ensemble of random solenoidal vector fields, and a random sampling of uniform eigenframe alignments, we show that this geometric alignment plays a much stronger role in determining the flux between scales than do the magnitudes of the stress and strain rate. We also show that when the alignment is effectively two dimensional, even when embedded in a three-dimensional flow, the energy flux is typically inverse, suggesting that the inverse cascade in two-dimensional turbulence may have a kinematic origin. Our results point to some potentially fruitful directions for turbulence modeling.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2859-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020', 'http://link.springer.com/10.1007/s00348-019-2859-2', event);\">\n    Double-frame tomographic PTV at high seeding densities.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Cornic,  P.; Leclaire,  B.; Champagnat,  F.; Besnerais,  G., L.; Cheminet,  A.; Illoul,  C.;  and Losfeld,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 61(2): 23. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2859-2\"\n     onclick=\"log_download('cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020', 'http://link.springer.com/10.1007/s00348-019-2859-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Double-frame tomographic PTV at high seeding densities [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2859-2\"\n     onclick=\"log_download('cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020', 'http://doi.org/10.1007/s00348-019-2859-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('cornic-leclaire-champagnat-besnerais-cheminet-illoul-losfeld-doubleframetomographicptvathighseedingdensities-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Double-frame tomographic PTV at high seeding densities},\n type = {article},\n year = {2020},\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\n pages = {23},\n volume = {61},\n websites = {http://link.springer.com/10.1007/s00348-019-2859-2},\n month = {4},\n publisher = {Springer},\n id = {f97dbeff-e7dd-31f8-8835-6edc9b4add50},\n created = {2021-04-09T15:24:52.904Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:52.904Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {A novel method performing 3D PTV from double-frame multi-camera images is introduced. Particle velocities are estimated by following three steps: First, separate particle reconstructions with a sparsity based algorithm are performed on a fine grid. Second, they are expanded on a coarser grid on which 3D correlation is performed, yielding a predictor displacement field that allows to efficiently match particles at the two time instants. As these particles are still located on a voxel grid, the third, final step achieves particle position refinement to their actual subvoxel position by a global optimization process, also accounting for their intensities. As it strongly leverages on principles from tomographic reconstruction, the technique is termed Double-Frame Tomo-PTV (DF-TPTV). Standard synthetic tests on a complex turbulent flow show that the method achieves high particle and vector detection efficiency, up to seeding densities of around 0.08 particles per pixel (ppp). On these tests, it also shows a higher robustness to noise and lower root-mean-square errors on velocity estimation than similar state-of-the-art methods. Results from an experimental campaign on a transitional round air jet at Reynolds number 4600 are also presented. Average seeding density varies in time from 0.06 to 0.03 ppp during the considered run, with different densities and signal-to-noise ratios being observed with time in the jet and ambient air regions, supplied by two different seeding systems. The strong polydisperse nature of the seeding, as well as the coexistence of two spatial zones of significantly different particle densities and signal-to-noise ratios, are observed to be the most influential sources of limitation for DF-TPTV performance. However, the method still successfully reconstructs a large amount of particles, and, associated with an outlier rejection scheme based on temporal statistics, truthfully reconstructs the instantaneous jet dynamics. Further quantitative performance assessment is then provided by introducing statistics performed by bin averaging, upon assuming statistical axisymmetry of the jet. Mean and fluctuating axial velocity components in the jet near-field are compared with reference results obtained from planar PIV at higher seeding density, with an interrogation window of size comparable to that of the bins. Results are found to be in excellent agreement with one another, confirming the high performance of DF-TPTV to yield reliable volumetric vector fields at seeding densities usually considered for tomographic PIV processing.},\n bibtype = {article},\n author = {Cornic, Philippe and Leclaire, Benjamin and Champagnat, Frédéric and Besnerais, Guy Le and Cheminet, Adam and Illoul, Cédric and Losfeld, Gilles},\n doi = {10.1007/s00348-019-2859-2},\n journal = {Experiments in Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A novel method performing 3D PTV from double-frame multi-camera images is introduced. Particle velocities are estimated by following three steps: First, separate particle reconstructions with a sparsity based algorithm are performed on a fine grid. Second, they are expanded on a coarser grid on which 3D correlation is performed, yielding a predictor displacement field that allows to efficiently match particles at the two time instants. As these particles are still located on a voxel grid, the third, final step achieves particle position refinement to their actual subvoxel position by a global optimization process, also accounting for their intensities. As it strongly leverages on principles from tomographic reconstruction, the technique is termed Double-Frame Tomo-PTV (DF-TPTV). Standard synthetic tests on a complex turbulent flow show that the method achieves high particle and vector detection efficiency, up to seeding densities of around 0.08 particles per pixel (ppp). On these tests, it also shows a higher robustness to noise and lower root-mean-square errors on velocity estimation than similar state-of-the-art methods. Results from an experimental campaign on a transitional round air jet at Reynolds number 4600 are also presented. Average seeding density varies in time from 0.06 to 0.03 ppp during the considered run, with different densities and signal-to-noise ratios being observed with time in the jet and ambient air regions, supplied by two different seeding systems. The strong polydisperse nature of the seeding, as well as the coexistence of two spatial zones of significantly different particle densities and signal-to-noise ratios, are observed to be the most influential sources of limitation for DF-TPTV performance. However, the method still successfully reconstructs a large amount of particles, and, associated with an outlier rejection scheme based on temporal statistics, truthfully reconstructs the instantaneous jet dynamics. Further quantitative performance assessment is then provided by introducing statistics performed by bin averaging, upon assuming statistical axisymmetry of the jet. Mean and fluctuating axial velocity components in the jet near-field are compared with reference results obtained from planar PIV at higher seeding density, with an interrogation window of size comparable to that of the bins. Results are found to be in excellent agreement with one another, confirming the high performance of DF-TPTV to yield reliable volumetric vector fields at seeding densities usually considered for tomographic PIV processing.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020', 'https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article', event);\">\n    Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Aslangil,  D.; Livescu,  D.;  and Banerjee,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 895: A12. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article\"\n     onclick=\"log_download('aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020', 'https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.268\"\n     onclick=\"log_download('aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020', 'http://doi.org/10.1017/jfm.2020.268', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('aslangil-livescu-banerjee-effectsofatwoodandreynoldsnumbersontheevolutionofbuoyancydrivenhomogeneousvariabledensityturbulence-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence},\n type = {article},\n year = {2020},\n keywords = {buoyancy-driven instability,homogeneous turbulence,turbulent mixing},\n pages = {A12},\n volume = {895},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112020002682/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {e07b1214-d2e2-3f30-b087-fa980a509277},\n created = {2021-04-09T15:24:53.393Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:53.393Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Aslangil, Denis and Livescu, Daniel and Banerjee, Arindam},\n doi = {10.1017/jfm.2020.268},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html', event);\">\n    Developing particle image velocimetry software based on a deep neural network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Majewski,  W.; Wei,  R.;  and Kumar,  V.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Flow Visualization and Image Processing</i>, 27(4): 359-376.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html\"\n     onclick=\"log_download('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Developing particle image velocimetry software based on a deep neural network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1615/JFlowVisImageProc.2020033180\"\n     onclick=\"log_download('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020', 'http://doi.org/10.1615/JFlowVisImageProc.2020033180', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>12 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('majewski-wei-kumar-developingparticleimagevelocimetrysoftwarebasedonadeepneuralnetwork-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Developing particle image velocimetry software based on a deep neural network},\n type = {article},\n year = {2020},\n keywords = {deep neural networks,fluid motion estimation,particle image velocimetry},\n pages = {359-376},\n volume = {27},\n websites = {http://dl.begellhouse.com/journals/52b74bd3689ab10b,forthcoming,33180.html,http://www.dl.begellhouse.com/journals/52b74bd3689ab10b,478f33b4434d88c8,4879b5ce22f635ce.html},\n publisher = {Begell House},\n id = {06f51761-ca9e-36a5-9636-b609c6c8f2c7},\n created = {2021-04-09T15:24:54.071Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:54.071Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Majewski, Wojciech and Wei, Runjie and Kumar, Vivek},\n doi = {10.1615/JFlowVisImageProc.2020033180},\n journal = {Journal of Flow Visualization and Image Processing},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285', event);\">\n    Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Díaz,  J.; Marton,  F.;  and Gobbetti,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Computers & Graphics</i>, 88: 45-56. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285\"\n     onclick=\"log_download('daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.cag.2020.03.002\"\n     onclick=\"log_download('daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020', 'http://doi.org/10.1016/j.cag.2020.03.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>7 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('daz-marton-gobbetti-interactivespatiotemporalexplorationofmassivetimevaryingrectilinearscalarvolumesbasedonavariablebitratesparserepresentationoverlearneddictionaries-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Interactive spatio-temporal exploration of massive time-Varying rectilinear scalar volumes based on a variable bit-rate sparse representation over learned dictionaries},\n type = {article},\n year = {2020},\n keywords = {Compression,Direct volume rendering,Learned dictionary,Sparse coding,Time-varying data},\n pages = {45-56},\n volume = {88},\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0097849320300285},\n month = {4},\n publisher = {Elsevier Ltd},\n id = {363377e2-48c9-3547-a8c4-1cf8706456c9},\n created = {2021-04-09T15:24:54.552Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:54.552Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.},\n bibtype = {article},\n author = {Díaz, Jose and Marton, Fabio and Gobbetti, Enrico},\n doi = {10.1016/j.cag.2020.03.002},\n journal = {Computers &amp; Graphics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We introduce a novel approach for supporting fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms. To do this, we decompose each frame into an octree of overlapping bricks. Each brick is further subdivided into smaller non-overlapping blocks compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a learned data-dependent dictionary. An efficient tolerance-driven learning and approximation process, capable of computing the tolerance required to achieve a given frame size, exploits coresets and an incremental dictionary refinement strategy to cope with datasets made of thousands of multi-gigavoxel frames. The compressed representation of each frame is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access, view-frustum and transfer-function culling, and transient and local decompression interleaved with ray-casting. Our variable-rate codec provides high-quality approximations at very low bit-rates, while offering real-time decoding performance. Thus, the bandwidth provided by current commodity PCs proves sufficient to fully stream and render a working set of one gigavoxel per frame without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5128379\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020', 'http://aip.scitation.org/doi/10.1063/1.5128379', event);\">\n    A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Samiee,  M.; Akhavan-Safaei,  A.;  and Zayernouri,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 32(5): 55102. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5128379\"\n     onclick=\"log_download('samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020', 'http://aip.scitation.org/doi/10.1063/1.5128379', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5128379\"\n     onclick=\"log_download('samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020', 'http://doi.org/10.1063/1.5128379', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>10 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('samiee-akhavansafaei-zayernouri-afractionalsubgridscalemodelforturbulentflowstheoreticalformulationandaprioristudy-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study},\n type = {article},\n year = {2020},\n pages = {55102},\n volume = {32},\n websites = {http://aip.scitation.org/doi/10.1063/1.5128379},\n month = {4},\n publisher = {AIP Publishing LLCAIP Publishing},\n id = {8c44d1e5-9a8d-3934-8a8e-5c4f91bf7721},\n created = {2021-04-09T15:24:55.310Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:55.310Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian ...},\n bibtype = {article},\n author = {Samiee, Mehdi and Akhavan-Safaei, Ali and Zayernouri, Mohsen},\n doi = {10.1063/1.5128379},\n journal = {Physics of Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Coherent structures/motions in turbulence inherently give rise to intermittent signals with sharp peaks, heavy-skirt, and skewed distributions of velocity increments, highlighting the non-Gaussian ...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020', 'https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article', event);\">\n    Wall-attached and wall-detached eddies in wall-bounded turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hu,  R.; Yang,  X., I., A.;  and Zheng,  X.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 885: A30. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article\"\n     onclick=\"log_download('hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020', 'https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Wall-attached and wall-detached eddies in wall-bounded turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2019.980\"\n     onclick=\"log_download('hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020', 'http://doi.org/10.1017/jfm.2019.980', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hu-yang-zheng-wallattachedandwalldetachededdiesinwallboundedturbulentflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Wall-attached and wall-detached eddies in wall-bounded turbulent flows},\n type = {article},\n year = {2020},\n keywords = {boundary layer structure,turbulence theory,turbulent boundary layers},\n pages = {A30},\n volume = {885},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019009807/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {3bd35814-20d4-35a0-a335-1615f7927ae3},\n created = {2021-04-09T15:24:55.789Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:55.789Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Hu, Ruifeng and Yang, Xiang I A and Zheng, Xiaojing},\n doi = {10.1017/jfm.2019.980},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2875-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020', 'http://link.springer.com/10.1007/s00348-019-2875-2', event);\">\n    Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tan,  S.; Salibindla,  A.; Masuk,  A., U., M.;  and Ni,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 61(2): 47. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2875-2\"\n     onclick=\"log_download('tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020', 'http://link.springer.com/10.1007/s00348-019-2875-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2875-2\"\n     onclick=\"log_download('tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020', 'http://doi.org/10.1007/s00348-019-2875-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tan-salibindla-masuk-ni-introducingopenlptnewmethodofremovingghostparticlesandhighconcentrationparticleshadowtracking-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Introducing OpenLPT: new method of removing ghost particles and high-concentration particle shadow tracking},\n type = {article},\n year = {2020},\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\n pages = {47},\n volume = {61},\n websites = {http://link.springer.com/10.1007/s00348-019-2875-2},\n month = {4},\n publisher = {Springer},\n id = {a329aa66-d78d-3813-af6b-87dfe61107eb},\n created = {2021-04-09T15:24:56.527Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:56.527Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We developed an open-source Lagrangian particle tracking (OpenLPT) based on the Shake-the-Box (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) method. The source code of OpenLPT is available on GitHub repository (@JHU-NI-LAB). The code features a new method that removes the majority of ghost particles at a high particle image density. The resulting percentage of ghost particles drops from 110% to 26% for image density at 0.125 ppp—nearly 84% of ghost particles are removed. Extensive tests of OpenLPT using synthetic data sets show that the code produces tracks with accuracy and processing time similar to the previously-reported values. In addition, OpenLPT has been parallelized to run on high-performance computing clusters to drastically increase its processing speed. To examine the code’s capability of tracking shadows of small tracers for backlit experiments, the blurred-particle effect was also included on synthetic images and OpenLPT was tested to process these noisy images. The results show that OpenLPT can also track shadows of a high-concentration of particles reliably in 3D. Based on the test, the optimal depth of field (DoF) and particle concentration for future experiments using Lagrangian shadow tracking are provided. For example, DoF controlled by the aperture should be set at around half of the size of the view area. At this DoF, most particles in the interrogation volume can be tracked, whereas particles outside the interrogation volume become too dim to affect results. 40 experimental data sets for a wide range of particle concentrations were also used for evaluating the code, and the results show a nice agreement with the synthetic tests.},\n bibtype = {article},\n author = {Tan, Shiyong and Salibindla, Ashwanth and Masuk, Ashik Ullah Mohammad and Ni, Rui},\n doi = {10.1007/s00348-019-2875-2},\n journal = {Experiments in Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We developed an open-source Lagrangian particle tracking (OpenLPT) based on the Shake-the-Box (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) method. The source code of OpenLPT is available on GitHub repository (@JHU-NI-LAB). The code features a new method that removes the majority of ghost particles at a high particle image density. The resulting percentage of ghost particles drops from 110% to 26% for image density at 0.125 ppp—nearly 84% of ghost particles are removed. Extensive tests of OpenLPT using synthetic data sets show that the code produces tracks with accuracy and processing time similar to the previously-reported values. In addition, OpenLPT has been parallelized to run on high-performance computing clusters to drastically increase its processing speed. To examine the code’s capability of tracking shadows of small tracers for backlit experiments, the blurred-particle effect was also included on synthetic images and OpenLPT was tested to process these noisy images. The results show that OpenLPT can also track shadows of a high-concentration of particles reliably in 3D. Based on the test, the optimal depth of field (DoF) and particle concentration for future experiments using Lagrangian shadow tracking are provided. For example, DoF controlled by the aperture should be set at around half of the size of the view area. At this DoF, most particles in the interrogation volume can be tracked, whereas particles outside the interrogation volume become too dim to affect results. 40 experimental data sets for a wide range of particle concentrations were also used for evaluating the code, and the results show a nice agreement with the synthetic tests.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5139028\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020', 'http://aip.scitation.org/doi/10.1063/1.5139028', event);\">\n    The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  Z.;  and Zhao,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 32(1): 13302. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5139028\"\n     onclick=\"log_download('wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020', 'http://aip.scitation.org/doi/10.1063/1.5139028', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5139028\"\n     onclick=\"log_download('wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020', 'http://doi.org/10.1063/1.5139028', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-zhao-theparticlestressindilutesuspensionsofinertialessspheroidsinturbulentchannelflow-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The particle stress in dilute suspensions of inertialess spheroids in turbulent channel flow},\n type = {article},\n year = {2020},\n pages = {13302},\n volume = {32},\n websites = {http://aip.scitation.org/doi/10.1063/1.5139028},\n month = {4},\n publisher = {American Institute of Physics Inc.},\n id = {39347325-914b-3dc5-abf4-3bffa7a604d6},\n created = {2021-04-09T15:24:57.014Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:57.014Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Particle stress is known to play a vital role in turbulence modulation. However, the earlier studies on particle stress were mostly confined to the cases of spherical and elongated particles. In the present study, we investigated the stress generated in dilute suspensions of inertialess spheroids with various shapes in wall-bounded turbulence. We performed direct numerical simulations of turbulent particle-laden channel flows utilizing a one-way coupled Eulerian-Lagrangian approach. The stress in the suspension of oblate spheroids was examined in detail and compared with prolate spheroid cases for the first time. The results show that particle stress is strongly dependent on particle shape and the stress of the oblate spheroid is qualitatively different from the case of prolate particles. However, we found that the fluctuating spanwise shear stress of flat oblate spheroids, which makes a significant contribution to turbulence dissipation, is in the same order of magnitude of the term generated by elongated prolate spheroids at a constant volume fraction. We also examined the effect of the Reynolds number on the particle stress in channel flows at Reτ = 180 and 1000. The results reveal a negligible influence on the mean stresses, but the fluctuating stresses are significantly Reynolds number dependent. In the buffer layer, we observed the correlations between the particle stress of spheroids and the fluctuating velocity of the fluid in the streamwise direction, which could be attributed to the different orientation of spheroids and fluid strain rate in low- and high-speed streaks of near-wall turbulence.},\n bibtype = {article},\n author = {Wang, Ze and Zhao, Lihao},\n doi = {10.1063/1.5139028},\n journal = {Physics of Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Particle stress is known to play a vital role in turbulence modulation. However, the earlier studies on particle stress were mostly confined to the cases of spherical and elongated particles. In the present study, we investigated the stress generated in dilute suspensions of inertialess spheroids with various shapes in wall-bounded turbulence. We performed direct numerical simulations of turbulent particle-laden channel flows utilizing a one-way coupled Eulerian-Lagrangian approach. The stress in the suspension of oblate spheroids was examined in detail and compared with prolate spheroid cases for the first time. The results show that particle stress is strongly dependent on particle shape and the stress of the oblate spheroid is qualitatively different from the case of prolate particles. However, we found that the fluctuating spanwise shear stress of flat oblate spheroids, which makes a significant contribution to turbulence dissipation, is in the same order of magnitude of the term generated by elongated prolate spheroids at a constant volume fraction. We also examined the effect of the Reynolds number on the particle stress in channel flows at Reτ = 180 and 1000. The results reveal a negligible influence on the mean stresses, but the fluctuating stresses are significantly Reynolds number dependent. In the buffer layer, we observed the correlations between the particle stress of spheroids and the fluctuating velocity of the fluid in the streamwise direction, which could be attributed to the different orientation of spheroids and fluid strain rate in low- and high-speed streaks of near-wall turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916', event);\">\n    Pressure power spectrum in high-Reynolds number wall-bounded flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xu,  H., H., A.; Towne,  A.; Yang,  X., I., A.;  and Marusic,  I.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Heat and Fluid Flow</i>, 84: 108620. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916\"\n     onclick=\"log_download('xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020', 'https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Pressure power spectrum in high-Reynolds number wall-bounded flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ijheatfluidflow.2020.108620\"\n     onclick=\"log_download('xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020', 'http://doi.org/10.1016/j.ijheatfluidflow.2020.108620', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xu-towne-yang-marusic-pressurepowerspectruminhighreynoldsnumberwallboundedflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pressure power spectrum in high-Reynolds number wall-bounded flows},\n type = {article},\n year = {2020},\n pages = {108620},\n volume = {84},\n websites = {https://linkinghub.elsevier.com/retrieve/pii/S0142727X20300916},\n month = {4},\n publisher = {Elsevier},\n id = {b85f5b6f-a0aa-376a-ad98-fc145ff5b768},\n created = {2021-04-09T15:24:57.575Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:57.575Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Xu, Haosen H A and Towne, Aaron and Yang, Xiang I A and Marusic, Ivan},\n doi = {10.1016/j.ijheatfluidflow.2020.108620},\n journal = {International Journal of Heat and Fluid Flow}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/9007507/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020', 'https://ieeexplore.ieee.org/document/9007507/', event);\">\n    A Comparison of Rendering Techniques for 3D Line Sets with Transparency.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kern,  M.; Neuhauser,  C.; Maack,  T.; Han,  M.; Usher,  W.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>,1. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/9007507/\"\n     onclick=\"log_download('kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020', 'https://ieeexplore.ieee.org/document/9007507/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Comparison of Rendering Techniques for 3D Line Sets with Transparency [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2020.2975795\"\n     onclick=\"log_download('kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020', 'http://doi.org/10.1109/TVCG.2020.2975795', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kern-neuhauser-maack-han-usher-westermann-acomparisonofrenderingtechniquesfor3dlinesetswithtransparency-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Comparison of Rendering Techniques for 3D Line Sets with Transparency},\n type = {article},\n year = {2020},\n pages = {1},\n websites = {https://ieeexplore.ieee.org/document/9007507/},\n month = {4},\n publisher = {Institute of Electrical and Electronics Engineers (IEEE)},\n id = {77692821-f40f-3cb9-9904-265929f62c49},\n created = {2021-04-09T15:24:58.040Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:58.040Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visualizing trajectories of tracer particles in flow fields. Transparency is then used to fade out lines deemed unimportant, based on, for instance, geometric properties or attributes defined along them. Since accurate blending of transparent lines requires rendering the lines in back-to-front or front-to-back order, enforcing this order for 3D line sets with tens or even hundreds of thousands of elements becomes challenging. In this paper, we study CPU and GPU rendering techniques for large transparent 3D line sets. We compare accurate and approximate techniques using optimized implementations and a number of benchmark data sets. We discuss the effects of data size and transparency on quality, performance and memory consumption. Based on our study, we propose two improvements to per-pixel fragment lists and multi-layer alpha blending. The first improves the rendering speed via an improved GPU sorting operation, and the second improves rendering quality via a transparency-based bucketing.},\n bibtype = {article},\n author = {Kern, Michael and Neuhauser, Christoph and Maack, Torben and Han, Mengjiao and Usher, Will and Westermann, Ruediger},\n doi = {10.1109/TVCG.2020.2975795},\n journal = {IEEE Transactions on Visualization and Computer Graphics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visualizing trajectories of tracer particles in flow fields. Transparency is then used to fade out lines deemed unimportant, based on, for instance, geometric properties or attributes defined along them. Since accurate blending of transparent lines requires rendering the lines in back-to-front or front-to-back order, enforcing this order for 3D line sets with tens or even hundreds of thousands of elements becomes challenging. In this paper, we study CPU and GPU rendering techniques for large transparent 3D line sets. We compare accurate and approximate techniques using optimized implementations and a number of benchmark data sets. We discuss the effects of data size and transparency on quality, performance and memory consumption. Based on our study, we propose two improvements to per-pixel fragment lists and multi-layer alpha blending. The first improves the rendering speed via an improved GPU sorting operation, and the second improves rendering quality via a transparency-based bucketing.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020', 'https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265', event);\">\n    Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ahmed,  U.; Apsley,  D.; Stallard,  T.; Stansby,  P.;  and Afgan,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Hydraulic Research</i>,1-15. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265\"\n     onclick=\"log_download('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020', 'https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020 [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/00221686.2020.1729265\"\n     onclick=\"log_download('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020', 'http://doi.org/10.1080/00221686.2020.1729265', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ahmed-apsley-stallard-stansby-afgan-turbulentlengthscalesandbudgetsofreynoldsstresstransportforopenchannelflowsfrictionreynoldsnumbersre150400and1020-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Turbulent length scales and budgets of Reynolds stress-transport for open-channel flows; friction Reynolds numbers (R e τ ) = 150, 400 and 1020},\n type = {article},\n year = {2020},\n keywords = {Anisotropy,budgets,open-channel flow,tidal stream turbines,turbulence length scales,turbulence spectra},\n pages = {1-15},\n websites = {https://www.tandfonline.com/doi/full/10.1080/00221686.2020.1729265},\n month = {4},\n publisher = {Taylor and Francis Ltd.},\n id = {5fb83e3f-627a-3eb4-98b2-e71bbadefb97},\n created = {2021-04-09T15:24:58.541Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:58.541Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.},\n bibtype = {article},\n author = {Ahmed, Umair and Apsley, David and Stallard, Timothy and Stansby, Peter and Afgan, Imran},\n doi = {10.1080/00221686.2020.1729265},\n journal = {Journal of Hydraulic Research}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Turbulence in open channel flows is ubiquitous to hydro-environmental applications and has recently increased in importance with the deployment of tidal stream turbines, as turbulence impacts both the turbine performance and the blade fatigue life. Tidal turbine analysis requires fully developed turbulence characteristics at the inlet of numerical simulations where generally the length scale information is limited. In this study, fully resolved large eddy simulations (LES) with flat beds were undertaken using an open source code at friction Reynolds numbers ((Formula presented.)) of 150, 400 and 1020. It was found that the effects of the free surface on turbulence length scales were felt in approximately the uppermost 10% of the channel only, although the influence on Reynolds stresses extended further downwards. Furthermore, the cross-correlation length scales of both streamwise and spanwise velocities were found to be significantly affected by the free surface where turbulent eddies were flattened to the two-component limit.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d', event);\">\n    Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ehlers,  F.; Schröder,  A.;  and Gesemann,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 31(9): 94013. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d\"\n     onclick=\"log_download('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab848d\"\n     onclick=\"log_download('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020', 'http://doi.org/10.1088/1361-6501/ab848d', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>14 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ehlers-schrder-gesemann-enforcingtemporalconsistencyinphysicallyconstrainedflowfieldreconstructionwithflowfitbyuseofvirtualtracerparticles-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles},\n type = {article},\n year = {2020},\n pages = {94013},\n volume = {31},\n websites = {https://doi.org/10.1088/1361-6501/ab848d,https://iopscience.iop.org/article/10.1088/1361-6501/ab848d},\n month = {4},\n publisher = {Institute of Physics Publishing},\n id = {48519ba0-b237-3437-bb93-5ee1105659c9},\n created = {2021-04-09T15:24:59.283Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:59.283Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method &#x27;Shake-the-Box&#x27; (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit&#x27;s core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.},\n bibtype = {article},\n author = {Ehlers, Frithjof and Schröder, Andreas and Gesemann, Sebastian},\n doi = {10.1088/1361-6501/ab848d},\n journal = {Measurement Science and Technology},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method 'Shake-the-Box' (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit's core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta', event);\">\n    Adaptive ensemble PTV.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Raiola,  M.; Lopez-Nuñez,  E.; Cafiero,  G.;  and Discetti,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 31(8): 85301. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta\"\n     onclick=\"log_download('raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Adaptive ensemble PTV [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab82bf\"\n     onclick=\"log_download('raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020', 'http://doi.org/10.1088/1361-6501/ab82bf', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('raiola-lopeznuez-cafiero-discetti-adaptiveensembleptv-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Adaptive ensemble PTV},\n type = {article},\n year = {2020},\n keywords = {PIV,PTV,spatial resolution,turbulent flow statistics},\n pages = {85301},\n volume = {31},\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf,https://iopscience.iop.org/article/10.1088/1361-6501/ab82bf/meta},\n month = {4},\n publisher = {Institute of Physics Publishing},\n id = {40b7bc2d-a36e-33e4-8f93-3ef9a1935879},\n created = {2021-04-09T15:24:59.778Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:59.778Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out.},\n bibtype = {article},\n author = {Raiola, Marco and Lopez-Nuñez, Elena and Cafiero, Gioacchino and Discetti, Stefano},\n doi = {10.1088/1361-6501/ab82bf},\n journal = {Measurement Science and Technology},\n number = {8}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020', 'https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116', event);\">\n    A Priori Sub-grid Modelling Using Artificial Neural Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Prat,  A.; Sautory,  T.;  and Navarro-Martinez,  S.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Computational Fluid Dynamics</i>, 34(6): 397-417. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116\"\n     onclick=\"log_download('prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020', 'https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Priori Sub-grid Modelling Using Artificial Neural Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/10618562.2020.1789116\"\n     onclick=\"log_download('prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020', 'http://doi.org/10.1080/10618562.2020.1789116', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('prat-sautory-navarromartinez-apriorisubgridmodellingusingartificialneuralnetworks-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Priori Sub-grid Modelling Using Artificial Neural Networks},\n type = {article},\n year = {2020},\n keywords = {ANN,LES,turbulence},\n pages = {397-417},\n volume = {34},\n websites = {https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1789116},\n month = {4},\n publisher = {Taylor and Francis Ltd.},\n id = {d7410cf0-8ad5-3cc3-afea-2ec408731071},\n created = {2021-04-09T15:25:00.319Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:00.319Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation of Homogeneous Isotropic Turbulence at different Reynolds numbers. The results show that the correlation coefficients are superior to other sub-grid models, using a similar set of input variables. As the ANN model extrapolates to larger Reynolds, the correlation coefficient decreases. However, it remains higher than other sub-grid approaches, and suggest that the combined LES-ANN methodology can potentially be used as a sub-grid model at realistic Reynolds numbers. Models derived from Homogeneous Isotropic Turbulence can also be used in different simple flows and provide relatively good agreement.},\n bibtype = {article},\n author = {Prat, Alvaro and Sautory, Theophile and Navarro-Martinez, S},\n doi = {10.1080/10618562.2020.1789116},\n journal = {International Journal of Computational Fluid Dynamics},\n number = {6}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation of Homogeneous Isotropic Turbulence at different Reynolds numbers. The results show that the correlation coefficients are superior to other sub-grid models, using a similar set of input variables. As the ANN model extrapolates to larger Reynolds, the correlation coefficient decreases. However, it remains higher than other sub-grid approaches, and suggest that the combined LES-ANN methodology can potentially be used as a sub-grid model at realistic Reynolds numbers. Models derived from Homogeneous Isotropic Turbulence can also be used in different simple flows and provide relatively good agreement.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020', 'https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401', event);\">\n    Robust principal component analysis for modal decomposition of corrupt fluid flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Scherl,  I.; Strom,  B.; Shang,  J., K.; Williams,  O.; Polagye,  B., L.;  and Brunton,  S., L.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 5(5): 54401. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401\"\n     onclick=\"log_download('scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020', 'https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Robust principal component analysis for modal decomposition of corrupt fluid flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.5.054401\"\n     onclick=\"log_download('scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020', 'http://doi.org/10.1103/PhysRevFluids.5.054401', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisformodaldecompositionofcorruptfluidflows-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Robust principal component analysis for modal decomposition of corrupt fluid flows},\n type = {article},\n year = {2020},\n keywords = {doi:10.1103/PhysRevFluids.5.054401 url:https://doi},\n pages = {54401},\n volume = {5},\n websites = {https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.5.054401,https://link.aps.org/doi/10.1103/PhysRevFluids.5.054401},\n month = {4},\n publisher = {American Physical Society},\n id = {0d4e9077-a45a-3e73-b1bf-865c5c74c7c8},\n created = {2021-04-09T15:25:00.870Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:00.870Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Modal analysis techniques are used to identify patterns and develop reduced-order models in a variety of fluid applications. However, experimentally acquired flow fields may be corrupted with incorrect and missing entries, which may degrade modal decomposition. Here we use robust principal component analysis (RPCA) to improve the quality of flow-field data by leveraging global coherent structures to identify and replace spurious data points. RPCA is a robust variant of principal component analysis, also known as proper orthogonal decomposition in fluids, that decomposes a data matrix into the sum of a low-rank matrix containing coherent structures and a sparse matrix of outliers and corrupt entries. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. The performance is particularly striking when flow fields are analyzed using dynamic mode decomposition, which is sensitive to noise and outliers.},\n bibtype = {article},\n author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L},\n doi = {10.1103/PhysRevFluids.5.054401},\n journal = {Physical Review Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Modal analysis techniques are used to identify patterns and develop reduced-order models in a variety of fluid applications. However, experimentally acquired flow fields may be corrupted with incorrect and missing entries, which may degrade modal decomposition. Here we use robust principal component analysis (RPCA) to improve the quality of flow-field data by leveraging global coherent structures to identify and replace spurious data points. RPCA is a robust variant of principal component analysis, also known as proper orthogonal decomposition in fluids, that decomposes a data matrix into the sum of a low-rank matrix containing coherent structures and a sparse matrix of outliers and corrupt entries. We apply RPCA filtering to a range of fluid simulations and experiments of varying complexities and assess the accuracy of low-rank structure recovery. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificial outliers, alongside similar particle image velocimetry (PIV) measurements at Reynolds number 413. Next, we apply RPCA filtering to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are preserved in the low-rank matrix. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA filtering extracts dominant coherent structures and identifies and fills in incorrect or missing measurements. The performance is particularly striking when flow fields are analyzed using dynamic mode decomposition, which is sensitive to noise and outliers.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020', 'https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta', event);\">\n    Nanoflare Theory and Stochastic Reconnection.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jafari,  A.; Vishniac,  E., T.;  and Xu,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Research Notes of the AAS</i>, 4(6): 89. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta\"\n     onclick=\"log_download('jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020', 'https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Nanoflare Theory and Stochastic Reconnection [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3847/2515-5172/ab9e02\"\n     onclick=\"log_download('jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020', 'http://doi.org/10.3847/2515-5172/ab9e02', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jafari-vishniac-xu-nanoflaretheoryandstochasticreconnection-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Nanoflare Theory and Stochastic Reconnection},\n type = {article},\n year = {2020},\n pages = {89},\n volume = {4},\n websites = {https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02,https://iopscience.iop.org/article/10.3847/2515-5172/ab9e02/meta},\n month = {4},\n publisher = {American Astronomical Society},\n id = {e476ace8-2be9-37fa-8534-8643d2ebfb1b},\n created = {2021-04-09T15:25:01.361Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:01.361Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Jafari, Amir and Vishniac, Ethan T and Xu, Siyao},\n doi = {10.3847/2515-5172/ab9e02},\n journal = {Research Notes of the AAS},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020', 'https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060', event);\">\n    A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Myhre,  N.; Prazenica,  R., J.; Balas,  M.;  and Gnanamanickam,  E., P.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA AVIATION 2020 FORUM</i>, 4 2020. American Institute of Aeronautics and Astronautics\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060\"\n     onclick=\"log_download('myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020', 'https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2020-3060\"\n     onclick=\"log_download('myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020', 'http://doi.org/10.2514/6.2020-3060', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('myhre-prazenica-balas-gnanamanickam-amodelreductionmethodusingresolventmodestopreserveforcingsensitivity-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {A Model Reduction Method Using Resolvent Modes to Preserve Forcing Sensitivity},\n type = {inproceedings},\n year = {2020},\n websites = {https://arc.aiaa.org/doi/abs/10.2514/6.2020-3060,https://arc.aiaa.org/doi/10.2514/6.2020-3060},\n month = {4},\n publisher = {American Institute of Aeronautics and Astronautics},\n id = {2178269a-95b7-37d7-9746-7dadf37353f3},\n created = {2021-04-09T15:25:02.054Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:02.054Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Myhre, Nicodemus and Prazenica, Richard J and Balas, Mark and Gnanamanickam, Ebenezer P},\n doi = {10.2514/6.2020-3060},\n booktitle = {AIAA AVIATION 2020 FORUM}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article', event);\">\n    Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Viggiano,  B.; Friedrich,  J.; Volk,  R.; Bourgoin,  M.; Cal,  R., B.;  and Chevillard,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 900: A27. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article\"\n     onclick=\"log_download('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2020.495\"\n     onclick=\"log_download('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020', 'http://doi.org/10.1017/jfm.2020.495', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>11 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('viggiano-friedrich-volk-bourgoin-cal-chevillard-modellinglagrangianvelocityandaccelerationinturbulentflowsasinfinitelydifferentiablestochasticprocesses-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes},\n type = {article},\n year = {2020},\n keywords = {homogeneous turbulence,isotropic turbulence,turbulence theory},\n pages = {A27},\n volume = {900},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112020004954/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {a9e970dd-84ff-353a-9f37-6fb053ef372c},\n created = {2021-04-09T15:25:02.534Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:02.534Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Viggiano, Bianca and Friedrich, Jan and Volk, Romain and Bourgoin, Mickael and Cal, Raúl Bayoán and Chevillard, Laurent},\n doi = {10.1017/jfm.2020.495},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-020-03061-y\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020', 'http://link.springer.com/10.1007/s00348-020-03061-y', event);\">\n    Dense particle tracking using a learned predictive model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mallery,  K.; Shao,  S.;  and Hong,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 61(10): 223. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-020-03061-y\"\n     onclick=\"log_download('mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020', 'http://link.springer.com/10.1007/s00348-020-03061-y', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dense particle tracking using a learned predictive model [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-020-03061-y\"\n     onclick=\"log_download('mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020', 'http://doi.org/10.1007/s00348-020-03061-y', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mallery-shao-hong-denseparticletrackingusingalearnedpredictivemodel-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dense particle tracking using a learned predictive model},\n type = {article},\n year = {2020},\n keywords = {Engineering Fluid Dynamics,Engineering Thermodynamics,Fluid,Heat and Mass Transfer,and Aerodynamics},\n pages = {223},\n volume = {61},\n websites = {http://link.springer.com/10.1007/s00348-020-03061-y},\n month = {4},\n publisher = {Springer},\n id = {fa0bf048-fc79-3234-9569-946909b0b385},\n created = {2021-04-09T15:25:03.814Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:03.814Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle&#x27;s velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases-turbulent channel flow, flow through a T-junction, and swimming microorganisms-demonstrate the broad applicability of the proposed method to different fields with unique challenges. Graphic abstract 1 Introduction},\n bibtype = {article},\n author = {Mallery, Kevin and Shao, Siyao and Hong, Jiarong},\n doi = {10.1007/s00348-020-03061-y},\n journal = {Experiments in Fluids},\n number = {10}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The velocity resolution for particle tracking velocimetry is limited by the ability to link multiple instances of the same particle captured over time to form trajectories. This becomes increasingly difficult as the particle speed and concentration increase. To address these concerns, we propose a data-driven approach to generate a learned predictive model capable of accurately estimating future particle behavior. The model uses the long short-term memory (LSTM) recurrent neural network architecture to predict a particle's velocity from its past positions. The model achieves increased linking performance with a negligible increase in the computational cost. Historical trajectories demonstrating the range of expected behaviors for a given application are used to train the model and can be collected using either of two methods. Manual filtering and selection can be used to select exemplary trajectories produced by an incomplete or inadequate method. Supplemental experiments with reduced tracer concentration can also produce training data. Both methods are demonstrated through experimental validation. The ability of the learned predictor to accurately link particles at tracer concentrations and flow speeds where traditional methods fail is demonstrated using two simulated flow cases. Three experimental cases are presented to demonstrate the performance of the proposed method under challenging conditions. Each case tracks the 3D positions of particles captured using microscopic digital inline holography although the approach is generalizable and can be applied to data obtained with other 2D and 3D PTV techniques. The selected cases-turbulent channel flow, flow through a T-junction, and swimming microorganisms-demonstrate the broad applicability of the proposed method to different fields with unique challenges. Graphic abstract 1 Introduction\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://xlink.rsc.org/?DOI=C9SM02492A\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020', 'http://xlink.rsc.org/?DOI=C9SM02492A', event);\">\n    Spectral energy analysis of bulk three-dimensional active nematic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Krajnik,  Ž.; Kos,  Ž.;  and Ravnik,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Soft Matter</i>, 16(39): 9059-9068.  2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://xlink.rsc.org/?DOI=C9SM02492A\"\n     onclick=\"log_download('krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020', 'http://xlink.rsc.org/?DOI=C9SM02492A', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Spectral energy analysis of bulk three-dimensional active nematic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1039/C9SM02492A\"\n     onclick=\"log_download('krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020', 'http://doi.org/10.1039/C9SM02492A', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('krajnik-kos-ravnik-spectralenergyanalysisofbulkthreedimensionalactivenematicturbulence-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Spectral energy analysis of bulk three-dimensional active nematic turbulence},\n type = {article},\n year = {2020},\n pages = {9059-9068},\n volume = {16},\n websites = {http://xlink.rsc.org/?DOI=C9SM02492A},\n publisher = {Royal Society of Chemistry (RSC)},\n id = {2dcd947a-1b83-353a-a5c2-c938a56fe531},\n created = {2021-04-09T15:25:04.756Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:04.756Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Energy spectrum analysis of 3D active nematic turbulence is perfomed and combined with geometrical analysis of ordering and flow fields.},\n bibtype = {article},\n author = {Krajnik, Žiga and Kos, Žiga and Ravnik, Miha},\n doi = {10.1039/C9SM02492A},\n journal = {Soft Matter},\n number = {39}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Energy spectrum analysis of 3D active nematic turbulence is perfomed and combined with geometrical analysis of ordering and flow fields.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020', 'https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097', event);\">\n    Shallow neural networks for fluid flow reconstruction with limited sensors.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Erichson,  N., B.; Mathelin,  L.; Yao,  Z.; Brunton,  S., L.; Mahoney,  M., W.;  and Kutz,  J., N.\n</span>\n\n  \n\n</span>\n\n  <i>Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences</i>, 476(2238): 20200097. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097\"\n     onclick=\"log_download('erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020', 'https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Shallow neural networks for fluid flow reconstruction with limited sensors [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1098/rspa.2020.0097\"\n     onclick=\"log_download('erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020', 'http://doi.org/10.1098/rspa.2020.0097', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('erichson-mathelin-yao-brunton-mahoney-kutz-shallowneuralnetworksforfluidflowreconstructionwithlimitedsensors-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Shallow neural networks for fluid flow reconstruction with limited sensors},\n type = {article},\n year = {2020},\n keywords = {flow field estimation,fluid dynamics,machine learning,neural networks,sensors},\n pages = {20200097},\n volume = {476},\n websites = {https://royalsocietypublishing.org/doi/10.1098/rspa.2020.0097},\n month = {4},\n publisher = {The Royal Society},\n id = {0bae8a3f-c6d6-3a4c-a627-b21c29e1dee7},\n created = {2021-04-09T15:25:05.426Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:05.426Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {&lt;p&gt;In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.&lt;/p&gt;},\n bibtype = {article},\n author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan},\n doi = {10.1098/rspa.2020.0097},\n journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences},\n number = {2238}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  <p>In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.</p>\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta', event);\">\n    Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  X.;  and Moreto,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 31(5): 55301. 4 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta\"\n     onclick=\"log_download('liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab6c28\"\n     onclick=\"log_download('liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020', 'http://doi.org/10.1088/1361-6501/ab6c28', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-moreto-errorpropagationfromthepivbasedpressuregradienttotheintegratedpressurebytheomnidirectionalintegrationmethod-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Error propagation from the PIV-based pressure gradient to the integrated pressure by the omnidirectional integration method},\n type = {article},\n year = {2020},\n keywords = {Poisson equation,boundary condition,error-embedded data,pressure,pressure gradient,pressure reconstruction},\n pages = {55301},\n volume = {31},\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28,https://iopscience.iop.org/article/10.1088/1361-6501/ab6c28/meta},\n month = {4},\n publisher = {Institute of Physics Publishing},\n id = {7dfa7c22-5ab5-345b-bbd0-3f7dd6656c75},\n created = {2021-04-09T15:25:06.098Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:25:06.098Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper reports a theoretical analysis and the corresponding numerical and experimental validation results of the error propagation characteristics of the omnidirectional integration method used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omnidirectional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise embedded in the measured pressure gradient. Accurate determination of the boundary pressure values is the first step in ensuring the accuracy of the reconstructed pressure. The boundary pressure error consists of two parts, with one part decreasing exponentially in magnitude and eventually vanishing, and the other remaining as a constant with small magnitude through iteration. These results are verified by using a direct numerical simulation database of isotropic turbulence flow superimposed with noise at various noise levels and spatial distribution schemes to simulate noise embedded data. The nondimensionalized average error of the reconstructed pressure based on 1000 statistically independent pressure gradient field realizations with a 40% added noise level is 0.854 ± 0.406 for the pressure Poisson equation with Neumann boundary condition, 0.154 ± 0.015 for the circular virtual boundary omnidirectional integration and 0.149 ± 0.015 for the rotating parallel ray omnidirectional integration. If the converged boundary pressure values obtained by the rotating parallel ray are used as Dirichlet boundary conditions, the average pressure error by Poisson is reduced to 0.151 ± 0.015. Of the different variations of the omnidirectional methods, the parallel ray method shows the best performance and therefore is the method of choice. Comparisons of the performance of these pressure reconstruction methods using an experimentally obtained turbulent shear layer flow over an open cavity are in agreement with the conclusions obtained with the DNS simulation data. With the noise added DNS data, limitations regarding the pressure reconstruction methods in determining pressure fluctuation statistics are also identified and quantified.},\n bibtype = {article},\n author = {Liu, Xiaofeng and Moreto, Jose Roberto},\n doi = {10.1088/1361-6501/ab6c28},\n journal = {Measurement Science and Technology},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper reports a theoretical analysis and the corresponding numerical and experimental validation results of the error propagation characteristics of the omnidirectional integration method used for pressure reconstruction from the PIV measured pressure gradient. The analysis shows that the omnidirectional integration provides an effective mechanism in reducing the sensitivity of the reconstructed pressure to the random noise embedded in the measured pressure gradient. Accurate determination of the boundary pressure values is the first step in ensuring the accuracy of the reconstructed pressure. The boundary pressure error consists of two parts, with one part decreasing exponentially in magnitude and eventually vanishing, and the other remaining as a constant with small magnitude through iteration. These results are verified by using a direct numerical simulation database of isotropic turbulence flow superimposed with noise at various noise levels and spatial distribution schemes to simulate noise embedded data. The nondimensionalized average error of the reconstructed pressure based on 1000 statistically independent pressure gradient field realizations with a 40% added noise level is 0.854 ± 0.406 for the pressure Poisson equation with Neumann boundary condition, 0.154 ± 0.015 for the circular virtual boundary omnidirectional integration and 0.149 ± 0.015 for the rotating parallel ray omnidirectional integration. If the converged boundary pressure values obtained by the rotating parallel ray are used as Dirichlet boundary conditions, the average pressure error by Poisson is reduced to 0.151 ± 0.015. Of the different variations of the omnidirectional methods, the parallel ray method shows the best performance and therefore is the method of choice. Comparisons of the performance of these pressure reconstruction methods using an experimentally obtained turbulent shear layer flow over an open cavity are in agreement with the conclusions obtained with the DNS simulation data. With the noise added DNS data, limitations regarding the pressure reconstruction methods in determining pressure fluctuation statistics are also identified and quantified.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/2a19625b-99c7-da31-5c26-8287f273bf25/full_text.pdf.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/2a19625b-99c7-da31-5c26-8287f273bf25/full_text.pdf.pdf', event);\">\n    Learning Similarity Metrics for Numerical Simulations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kohl,  G.; Um,  K.;  and Thuerey,  N.\n</span>\n\n  \n\n</span>\n\n  Technical Report 11 2020.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/2a19625b-99c7-da31-5c26-8287f273bf25/full_text.pdf.pdf\"\n     onclick=\"log_download('kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020', 'https://bibbase.org/service/mendeley/75799766-8e2d-3c98-81f9-e3efa41233d0/file/2a19625b-99c7-da31-5c26-8287f273bf25/full_text.pdf.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Learning Similarity Metrics for Numerical Simulations [pdf]\"\n       title=\"Paper\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Paper</span></a>\n  &nbsp;\n  \n  <a href=\"https://github.com/tum-pbs/LSIM.\"\n     onclick=\"log_download('kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020', 'https://github.com/tum-pbs/LSIM.', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Learning Similarity Metrics for Numerical Simulations [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kohl-um-thuerey-learningsimilaritymetricsfornumericalsimulations-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@techreport{\n title = {Learning Similarity Metrics for Numerical Simulations},\n type = {techreport},\n year = {2020},\n keywords = {CNNs,PDEs,metric learning,numerical simulation,perceptual evaluation,physics simulation},\n pages = {5349-5360},\n websites = {https://github.com/tum-pbs/LSIM.},\n month = {11},\n publisher = {PMLR},\n day = {21},\n id = {5b1c7a6a-a307-3046-be8c-474af85470ca},\n created = {2021-04-13T18:41:19.893Z},\n accessed = {2021-04-13},\n file_attached = {true},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-13T18:41:20.784Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of nu­ merical simulation sources. We focus on scalar time-dependent 2D data that commonly arises from motion and transport-based partial differen­ tial equations (PDEs). Our method employs a Siamese network architecture that is motivated by the mathematical properties of a metric. We leverage a controllable data generation setup with PDE solvers to create increasingly different out­ puts from a reference simulation in a controlled environment. A central component of our learned metric is a specialized loss function that intro­ duces knowledge about the correlation between single data samples into the training process. To demonstrate that the proposed approach outper­ forms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the dif­ ferent methods on a large range of test data. Addi­ tionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.},\n bibtype = {techreport},\n author = {Kohl, Georg and Um, Kiwon and Thuerey, Nils}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of nu­ merical simulation sources. We focus on scalar time-dependent 2D data that commonly arises from motion and transport-based partial differen­ tial equations (PDEs). Our method employs a Siamese network architecture that is motivated by the mathematical properties of a metric. We leverage a controllable data generation setup with PDE solvers to create increasingly different out­ puts from a reference simulation in a controlled environment. A central component of our learned metric is a specialized loss function that intro­ duces knowledge about the correlation between single data samples into the training process. To demonstrate that the proposed approach outper­ forms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the dif­ ferent methods on a large range of test data. Addi­ tionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tunkiel-wiktorski-sui-drillingdatasetexplorationprocessingandinterpretationusingvolvefielddata-2020\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  Drilling dataset exploration, processing and interpretation using volve field data.\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tunkiel,  A., T.; Wiktorski,  T.;  and Sui,  D.\n</span>\n\n  \n\n</span>\n\n  In <i>Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE</i>, volume 11, 12 2020. American Society of Mechanical Engineers (ASME)\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n\n  \n  <a href=\"http://doi.org/10.1115/OMAE2020-18151\"\n     onclick=\"log_download('tunkiel-wiktorski-sui-drillingdatasetexplorationprocessingandinterpretationusingvolvefielddata-2020', 'http://doi.org/10.1115/OMAE2020-18151', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tunkiel-wiktorski-sui-drillingdatasetexplorationprocessingandinterpretationusingvolvefielddata-2020\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tunkiel-wiktorski-sui-drillingdatasetexplorationprocessingandinterpretationusingvolvefielddata-2020')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Drilling dataset exploration, processing and interpretation using volve field data},\n type = {inproceedings},\n year = {2020},\n keywords = {Catalysts,Drilling,Gages},\n volume = {11},\n month = {12},\n publisher = {American Society of Mechanical Engineers (ASME)},\n day = {18},\n id = {d0725421-9955-38ea-af18-eb63688a8a6f},\n created = {2021-04-13T18:50:47.936Z},\n accessed = {2021-04-13},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-13T18:50:47.936Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {In 2018 Equinor made an unprecedented step for an energy company and made a multi-terabyte dataset from Volve field open. However, there is a long way from downloading data to executing meaningful analysis. With no way of quickly evaluating the data due to its size and unfamiliar file formats the use of Volve data was so far limited. This paper presents our exploratory work related to the real-time drilling part of the dataset. We provide description of common obstacles and approaches for overcoming them. We also describe specific contents of the dataset for others to gauge the potential for case studies. We hope that this will lower the bar for Volve field data accessibility, promote research, and become a catalyst for other data science projects.},\n bibtype = {inproceedings},\n author = {Tunkiel, Andrzej T. and Wiktorski, Tomasz and Sui, Dan},\n doi = {10.1115/OMAE2020-18151},\n booktitle = {Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In 2018 Equinor made an unprecedented step for an energy company and made a multi-terabyte dataset from Volve field open. However, there is a long way from downloading data to executing meaningful analysis. With no way of quickly evaluating the data due to its size and unfamiliar file formats the use of Volve data was so far limited. This paper presents our exploratory work related to the real-time drilling part of the dataset. We provide description of common obstacles and approaches for overcoming them. We also describe specific contents of the dataset for others to gauge the potential for case studies. We hope that this will lower the bar for Volve field data accessibility, promote research, and become a catalyst for other data science projects.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2019\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2019')\"\n      onkeypress=\"toggleGroup('group_2019')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2019</span>\n      <span class=\"bibbase_group_count\">\n        \n        (44)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1902.09929\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019', 'http://arxiv.org/abs/1902.09929', event);\">\n    Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mukherjee,  S.; Safdari,  A.; Shardt,  O.; Kenjeres,  S.;  and den Akker,  H., E., A., V.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1902.09929\"\n     onclick=\"log_download('mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019', 'http://arxiv.org/abs/1902.09929', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mukherjee-safdari-shardt-kenjeres-denakker-dropletturbulenceinteractionsandquasiequilibriumdynamicsinturbulentemulsions-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Droplet-turbulence interactions and quasi-equilibrium dynamics in turbulent emulsions},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1902.09929},\n month = {4},\n id = {281385a6-8a49-3483-95e5-d151e1a57bd5},\n created = {2021-04-09T15:23:10.129Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:10.129Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We perform direct numerical simulations (DNSs) of emulsions in homogeneous, isotropic turbulence using a pseudopotential lattice-Boltzmann (PP-LB) method. Improving on previous literature by minimizing droplet dissolution and spurious currents, we show that the PP-LB technique is capable of long, stable simulations in certain parameter regions. Varying the dispersed phase volume fraction φ, we demonstrate that droplet breakup extracts kinetic energy from the larger scales while injecting energy into the smaller scales, increasingly with higher φ, with the Hinze scale dividing the two effects. Droplet size (d) distribution was found to follow the d^-10/3 scaling (Deane &amp; Stokes 2002). We show the need to maintain a separation of the turbulence forcing scale and domain size to prevent the formation of large connected regions of the dispersed phase. For the first time, we show that turbulent emulsions evolve into a quasi-equilibrium cycle of alternating coalescence and breakup dominated processes. Studying the system in its state-space comprising kinetic energy E_k, enstrophy ω^2 and the droplet number density N_d, we find that their dynamics resemble limit-cycles with a time delay. Extreme values in the evolution of E_k manifest in the evolution of ω^2 and N_d with a delay of ~0.3T and ~0.9T respectively (with T the large eddy timescale). Lastly, we also show that flow topology of turbulence in an emulsion is significantly more different than single-phase turbulence than previously thought. In particular, vortex compression and axial straining mechanisms become dominant in the droplet phase, a consequence of the elastic behaviour of droplet interfaces.},\n bibtype = {article},\n author = {Mukherjee, Siddhartha and Safdari, Arman and Shardt, Orest and Kenjeres, Sasa and den Akker, Harry E A Van}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We perform direct numerical simulations (DNSs) of emulsions in homogeneous, isotropic turbulence using a pseudopotential lattice-Boltzmann (PP-LB) method. Improving on previous literature by minimizing droplet dissolution and spurious currents, we show that the PP-LB technique is capable of long, stable simulations in certain parameter regions. Varying the dispersed phase volume fraction φ, we demonstrate that droplet breakup extracts kinetic energy from the larger scales while injecting energy into the smaller scales, increasingly with higher φ, with the Hinze scale dividing the two effects. Droplet size (d) distribution was found to follow the d^-10/3 scaling (Deane & Stokes 2002). We show the need to maintain a separation of the turbulence forcing scale and domain size to prevent the formation of large connected regions of the dispersed phase. For the first time, we show that turbulent emulsions evolve into a quasi-equilibrium cycle of alternating coalescence and breakup dominated processes. Studying the system in its state-space comprising kinetic energy E_k, enstrophy ω^2 and the droplet number density N_d, we find that their dynamics resemble limit-cycles with a time delay. Extreme values in the evolution of E_k manifest in the evolution of ω^2 and N_d with a delay of ~0.3T and ~0.9T respectively (with T the large eddy timescale). Lastly, we also show that flow topology of turbulence in an emulsion is significantly more different than single-phase turbulence than previously thought. In particular, vortex compression and axial straining mechanisms become dominant in the droplet phase, a consequence of the elastic behaviour of droplet interfaces.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101', event);\">\n    Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ge,  M.; Yang,  X., I., A.;  and Marusic,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 4(3): 34101. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101\"\n     onclick=\"log_download('ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.4.034101\"\n     onclick=\"log_download('ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019', 'http://doi.org/10.1103/PhysRevFluids.4.034101', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ge-yang-marusic-velocityprobabilitydistributionscalinginwallboundedflowsathighreynoldsnumbers-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Velocity probability distribution scaling in wall-bounded flows at high Reynolds numbers},\n type = {article},\n year = {2019},\n pages = {34101},\n volume = {4},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034101},\n month = {4},\n publisher = {American Physical Society},\n id = {cdf950fb-cf1c-354d-b297-b77c65b772e1},\n created = {2021-04-09T15:23:11.553Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:11.553Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ge, M.-W. and Yang, Xiang I A and Marusic, Ivan},\n doi = {10.1103/PhysRevFluids.4.034101},\n journal = {Physical Review Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article', event);\">\n    A uniform momentum zone–vortical fissure model of the turbulent boundary layer.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bautista,  J., C., C.; Ebadi,  A.; White,  C., M.; Chini,  G., P.;  and Klewicki,  J., C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 858: 609-633. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article\"\n     onclick=\"log_download('bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A uniform momentum zone–vortical fissure model of the turbulent boundary layer [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.769\"\n     onclick=\"log_download('bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019', 'http://doi.org/10.1017/jfm.2018.769', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bautista-ebadi-white-chini-klewicki-auniformmomentumzonevorticalfissuremodeloftheturbulentboundarylayer-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A uniform momentum zone–vortical fissure model of the turbulent boundary layer},\n type = {article},\n year = {2019},\n keywords = {boundary layer structure,turbulence modelling,turbulent boundary layers},\n pages = {609-633},\n volume = {858},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018007693/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {ee6df86a-88f6-3f40-8c15-a9446fb35c8a},\n created = {2021-04-09T15:23:19.246Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:19.246Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Recent studies reveal that at large friction Reynolds number [STIX]x1D6FF^+ the inertially dominated region of the turbulent boundary layer is composed of large-scale zones of nearly uniform momentum segregated by narrow fissures of concentrated vorticity. Experiments show that, when scaled by the boundary-layer thickness, the fissure thickness is O(1/[STIX]x1D6FF^+) , while the dimensional jump in streamwise velocity across each fissure scales in proportion to the friction velocity u_[STIX]x1D70F . A simple model that exploits these essential elements of the turbulent boundary-layer structure at large [STIX]x1D6FF^+ is developed. First, a master wall-normal profile of streamwise velocity is constructed by placing a discrete number of fissures across the boundary layer. The number of fissures and their wall-normal locations follow scalings informed by analysis of the mean momentum equation. The fissures are then randomly displaced in the wall-normal direction, exchanging momentum as they move, to create an instantaneous velocity profile. This process is repeated to generate ensembles of streamwise velocity profiles from which statistical moments are computed. The modelled statistical profiles are shown to agree remarkably well with those acquired from direct numerical simulations of turbulent channel flow at large [STIX]x1D6FF^+ . In particular, the model robustly reproduces the empirically observed sub-Gaussian behaviour for the skewness and kurtosis profiles over a large range of input parameters.},\n bibtype = {article},\n author = {Bautista, Juan Carlos Cuevas and Ebadi, Alireza and White, Christopher M and Chini, Gregory P and Klewicki, Joseph C},\n doi = {10.1017/jfm.2018.769},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Recent studies reveal that at large friction Reynolds number [STIX]x1D6FF^+ the inertially dominated region of the turbulent boundary layer is composed of large-scale zones of nearly uniform momentum segregated by narrow fissures of concentrated vorticity. Experiments show that, when scaled by the boundary-layer thickness, the fissure thickness is O(1/[STIX]x1D6FF^+) , while the dimensional jump in streamwise velocity across each fissure scales in proportion to the friction velocity u_[STIX]x1D70F . A simple model that exploits these essential elements of the turbulent boundary-layer structure at large [STIX]x1D6FF^+ is developed. First, a master wall-normal profile of streamwise velocity is constructed by placing a discrete number of fissures across the boundary layer. The number of fissures and their wall-normal locations follow scalings informed by analysis of the mean momentum equation. The fissures are then randomly displaced in the wall-normal direction, exchanging momentum as they move, to create an instantaneous velocity profile. This process is repeated to generate ensembles of streamwise velocity profiles from which statistical moments are computed. The modelled statistical profiles are shown to agree remarkably well with those acquired from direct numerical simulations of turbulent channel flow at large [STIX]x1D6FF^+ . In particular, the model robustly reproduces the empirically observed sub-Gaussian behaviour for the skewness and kurtosis profiles over a large range of input parameters.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2700-y\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019', 'http://link.springer.com/10.1007/s00348-019-2700-y', event);\">\n    GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  J.; Zhang,  C.;  and Katz,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 60(4): 58. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2700-y\"\n     onclick=\"log_download('wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019', 'http://link.springer.com/10.1007/s00348-019-2700-y', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2700-y\"\n     onclick=\"log_download('wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019', 'http://doi.org/10.1007/s00348-019-2700-y', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-zhang-katz-gpubasedparallellineomnidirectionalintegrationofmeasuredpressuregradientfieldtoobtainthe3dpressuredistribution-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {GPU-based, parallel-line, omni-directional integration of measured pressure gradient field to obtain the 3D pressure distribution},\n type = {article},\n year = {2019},\n pages = {58},\n volume = {60},\n websites = {http://link.springer.com/10.1007/s00348-019-2700-y},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {d7556610-b073-3556-97e4-8438c2bb3eb2},\n created = {2021-04-09T15:23:26.564Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:26.564Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Jin and Zhang, Cao and Katz, Joseph},\n doi = {10.1007/s00348-019-2700-y},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019', 'http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c', event);\">\n    A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Clark,  A.; Machicoane,  N.;  and Aliseda,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 30(4): 45302. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c\"\n     onclick=\"log_download('clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019', 'http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab0786\"\n     onclick=\"log_download('clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019', 'http://doi.org/10.1088/1361-6501/ab0786', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('clark-machicoane-aliseda-aquantitativestudyoftrackinitializationofthefourframebestestimatealgorithmforthreedimensionallagrangianparticletracking-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A quantitative study of track initialization of the four-frame best estimate algorithm for three-dimensional Lagrangian particle tracking},\n type = {article},\n year = {2019},\n pages = {45302},\n volume = {30},\n websites = {http://stacks.iop.org/0957-0233/30/i=4/a=045302?key=crossref.80b8e9e8b96b372c441184f4d517257c},\n month = {4},\n publisher = {IOP Publishing},\n id = {6f742a18-ef05-39f4-8e72-5916fb799b83},\n created = {2021-04-09T15:23:33.577Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:33.577Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Clark, A and Machicoane, N and Aliseda, A},\n doi = {10.1088/1361-6501/ab0786},\n journal = {Measurement Science and Technology},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1902.07358\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019', 'http://arxiv.org/abs/1902.07358', event);\">\n    Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Erichson,  N., B.; Mathelin,  L.; Yao,  Z.; Brunton,  S., L.; Mahoney,  M., W.;  and Kutz,  J., N.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1902.07358\"\n     onclick=\"log_download('erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019', 'http://arxiv.org/abs/1902.07358', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('erichson-mathelin-yao-brunton-mahoney-kutz-shallowlearningforfluidflowreconstructionwithlimitedsensorsandlimiteddata-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1902.07358},\n month = {4},\n id = {bf1067d7-1a27-31e0-9024-7edb31cc4c99},\n created = {2021-04-09T15:23:35.428Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:35.428Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance with traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.},\n bibtype = {article},\n author = {Erichson, N Benjamin and Mathelin, Lionel and Yao, Zhewei and Brunton, Steven L and Mahoney, Michael W and Kutz, J Nathan}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance with traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article', event);\">\n    Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pujara,  N.; Voth,  G., A.;  and Variano,  E., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 860: 465-486. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article\"\n     onclick=\"log_download('pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.866\"\n     onclick=\"log_download('pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019', 'http://doi.org/10.1017/jfm.2018.866', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pujara-voth-variano-scaledependentalignmenttumblingandstretchingofslenderrodsinisotropicturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Scale-dependent alignment, tumbling and stretching of slender rods in isotropic turbulence},\n type = {article},\n year = {2019},\n keywords = {intermittency,isotropic turbulence,particle/fluid flows},\n pages = {465-486},\n volume = {860},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018008662/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {0aeeba05-23f0-32cf-918a-2aeba6c223e8},\n created = {2021-04-09T15:23:36.064Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:36.064Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We examine the dynamics of slender, rigid rods in direct numerical simulation of isotropic turbulence. The focus is on the statistics of three quantities and how they vary as rod length increases from the dissipation range to the inertial range. These quantities are (i) the steady-state rod alignment with respect to the perceived velocity gradients in the surrounding flow, (ii) the rate of rod reorientation (tumbling) and (iii) the rate at which the rod end points move apart (stretching). Under the approximations of slender-body theory, the rod inertia is neglected and rods are modelled as passive particles in the flow that do not affect the fluid velocity field. We find that the average rod alignment changes qualitatively as rod length increases from the dissipation range to the inertial range. While rods in the dissipation range align most strongly with fluid vorticity, rods in the inertial range align most strongly with the most extensional eigenvector of the perceived strain-rate tensor. For rods in the inertial range, we find that the variance of rod stretching and the variance of rod tumbling both scale as l^-4/3 , where l is the rod length. However, when rod dynamics are compared to two-point fluid velocity statistics (structure functions), we see non-monotonic behaviour in the variance of rod tumbling due to the influence of small-scale fluid motions. Additionally, we find that the skewness of rod stretching does not show scale invariance in the inertial range, in contrast to the skewness of longitudinal fluid velocity increments as predicted by Kolmogorov’s 4/5 law. Finally, we examine the power-law scaling exponents of higher-order moments of rod tumbling and rod stretching for rods with lengths in the inertial range and find that they show anomalous scaling. We compare these scaling exponents to predictions from Kolmogorov’s refined similarity hypotheses.},\n bibtype = {article},\n author = {Pujara, Nimish and Voth, Greg A and Variano, Evan A},\n doi = {10.1017/jfm.2018.866},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We examine the dynamics of slender, rigid rods in direct numerical simulation of isotropic turbulence. The focus is on the statistics of three quantities and how they vary as rod length increases from the dissipation range to the inertial range. These quantities are (i) the steady-state rod alignment with respect to the perceived velocity gradients in the surrounding flow, (ii) the rate of rod reorientation (tumbling) and (iii) the rate at which the rod end points move apart (stretching). Under the approximations of slender-body theory, the rod inertia is neglected and rods are modelled as passive particles in the flow that do not affect the fluid velocity field. We find that the average rod alignment changes qualitatively as rod length increases from the dissipation range to the inertial range. While rods in the dissipation range align most strongly with fluid vorticity, rods in the inertial range align most strongly with the most extensional eigenvector of the perceived strain-rate tensor. For rods in the inertial range, we find that the variance of rod stretching and the variance of rod tumbling both scale as l^-4/3 , where l is the rod length. However, when rod dynamics are compared to two-point fluid velocity statistics (structure functions), we see non-monotonic behaviour in the variance of rod tumbling due to the influence of small-scale fluid motions. Additionally, we find that the skewness of rod stretching does not show scale invariance in the inertial range, in contrast to the skewness of longitudinal fluid velocity increments as predicted by Kolmogorov’s 4/5 law. Finally, we examine the power-law scaling exponents of higher-order moments of rod tumbling and rod stretching for rods with lengths in the inertial range and find that they show anomalous scaling. We compare these scaling exponents to predictions from Kolmogorov’s refined similarity hypotheses.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019', 'http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/', event);\">\n    TTHRESH: Tensor Compression for Multidimensional Visual Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ballester-Ripoll,  R.; Lindstrom,  P.;  and Pajarola,  R.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>,1. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/\"\n     onclick=\"log_download('ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019', 'http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"TTHRESH: Tensor Compression for Multidimensional Visual Data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2019.2904063\"\n     onclick=\"log_download('ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019', 'http://doi.org/10.1109/TVCG.2019.2904063', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ballesterripoll-lindstrom-pajarola-tthreshtensorcompressionformultidimensionalvisualdata-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {TTHRESH: Tensor Compression for Multidimensional Visual Data},\n type = {article},\n year = {2019},\n pages = {1},\n websites = {http://arxiv.org/abs/1806.05952,https://ieeexplore.ieee.org/document/8663447/},\n month = {4},\n id = {42be9489-0a16-33a0-83cb-d7f6a51e32f6},\n created = {2021-04-09T15:23:37.189Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:37.189Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression algorithm for N-dimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to 3 and more dimensions, together with adaptive quantization, run-length and arithmetic coding to store the HOSVD transform coefficients&#x27; relative positions as sorted by their absolute magnitude. Our scheme degrades the data particularly smoothly and outperforms other state-of-the-art volume compressors at low-to-medium bit rates, as required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include extremely fine bit rate selection granularity, bounded resulting l^2 error, and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct subsampled or filtered-resampled versions of all (or selected parts) of the data set.},\n bibtype = {article},\n author = {Ballester-Ripoll, Rafael and Lindstrom, Peter and Pajarola, Renato},\n doi = {10.1109/TVCG.2019.2904063},\n journal = {IEEE Transactions on Visualization and Computer Graphics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression algorithm for N-dimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to 3 and more dimensions, together with adaptive quantization, run-length and arithmetic coding to store the HOSVD transform coefficients' relative positions as sorted by their absolute magnitude. Our scheme degrades the data particularly smoothly and outperforms other state-of-the-art volume compressors at low-to-medium bit rates, as required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include extremely fine bit rate selection granularity, bounded resulting l^2 error, and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct subsampled or filtered-resampled versions of all (or selected parts) of the data set.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"dubrulle-beyondkolmogorovcascades-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dubrulle-beyondkolmogorovcascades-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article', event);\">\n    Beyond Kolmogorov cascades.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Dubrulle,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 867: P1. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article\"\n     onclick=\"log_download('dubrulle-beyondkolmogorovcascades-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Beyond Kolmogorov cascades [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2019.98\"\n     onclick=\"log_download('dubrulle-beyondkolmogorovcascades-2019', 'http://doi.org/10.1017/jfm.2019.98', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dubrulle-beyondkolmogorovcascades-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dubrulle-beyondkolmogorovcascades-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Beyond Kolmogorov cascades},\n type = {article},\n year = {2019},\n keywords = {intermittency,turbulence theory},\n pages = {P1},\n volume = {867},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019000983/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {1012b117-456b-32d9-b1ba-3795e219b594},\n created = {2021-04-09T15:23:38.322Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:38.322Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The large-scale structure of many turbulent flows encountered in practical situations such as aeronautics, industry, meteorology is nowadays successfully computed using the Kolmogorov–Kármán–Howarth energy cascade picture. This theory appears increasingly inaccurate when going down the energy cascade that terminates through intermittent spots of energy dissipation, at variance with the assumed homogeneity. This is problematic for the modelling of all processes that depend on small scales of turbulence, such as combustion instabilities or droplet atomization in industrial burners or cloud formation. This paper explores a paradigm shift where the homogeneity hypothesis is replaced by the assumption that turbulence contains singularities, as suggested by Onsager. This paradigm leads to a weak formulation of the Kolmogorov–Kármán–Howarth–Monin equation (WKHE) that allows taking into account explicitly the presence of singularities and their impact on the energy transfer and dissipation. It provides a local in scale, space and time description of energy transfers and dissipation, valid for any inhomogeneous, anisotropic flow, under any type of boundary conditions. The goal of this article is to discuss WKHE as a tool to get a new description of energy cascades and dissipation that goes beyond Kolmogorov and allows the description of small-scale intermittency. It puts the problem of intermittency and dissipation in turbulence into a modern framework, compatible with recent mathematical advances on the proof of Onsager’s conjecture.},\n bibtype = {article},\n author = {Dubrulle, Bérengère},\n doi = {10.1017/jfm.2019.98},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The large-scale structure of many turbulent flows encountered in practical situations such as aeronautics, industry, meteorology is nowadays successfully computed using the Kolmogorov–Kármán–Howarth energy cascade picture. This theory appears increasingly inaccurate when going down the energy cascade that terminates through intermittent spots of energy dissipation, at variance with the assumed homogeneity. This is problematic for the modelling of all processes that depend on small scales of turbulence, such as combustion instabilities or droplet atomization in industrial burners or cloud formation. This paper explores a paradigm shift where the homogeneity hypothesis is replaced by the assumption that turbulence contains singularities, as suggested by Onsager. This paradigm leads to a weak formulation of the Kolmogorov–Kármán–Howarth–Monin equation (WKHE) that allows taking into account explicitly the presence of singularities and their impact on the energy transfer and dissipation. It provides a local in scale, space and time description of energy transfers and dissipation, valid for any inhomogeneous, anisotropic flow, under any type of boundary conditions. The goal of this article is to discuss WKHE as a tool to get a new description of energy cascades and dissipation that goes beyond Kolmogorov and allows the description of small-scale intermittency. It puts the problem of intermittency and dissipation in turbulence into a modern framework, compatible with recent mathematical advances on the proof of Onsager’s conjecture.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.osti.gov/servlets/purl/1493479/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019', 'http://www.osti.gov/servlets/purl/1493479/', event);\">\n    Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lawson,  M., J.; Melvin,  J.; Ananthan,  S.; Gruchalla,  K., M.; Rood,  J., S.;  and Sprague,  M., A.\n</span>\n\n  \n\n</span>\n\n  4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.osti.gov/servlets/purl/1493479/\"\n     onclick=\"log_download('lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019', 'http://www.osti.gov/servlets/purl/1493479/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2172/1493479\"\n     onclick=\"log_download('lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019', 'http://doi.org/10.2172/1493479', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lawson-melvin-ananthan-gruchalla-rood-sprague-bladeresolvedsingleturbinesimulationsunderatmosphericflow-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow},\n type = {misc},\n year = {2019},\n keywords = {analysis,computational fluid dynamics,reference turbine,simulations,wind energy},\n websites = {http://www.osti.gov/servlets/purl/1493479/},\n month = {4},\n institution = {National Renewable Energy Laboratory (NREL)},\n id = {70cedc58-3373-3d60-afe1-61d2bbed6131},\n created = {2021-04-09T15:23:38.930Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:38.930Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {report},\n private_publication = {false},\n bibtype = {misc},\n author = {Lawson, Michael J and Melvin, Jeremy and Ananthan, Shreyas and Gruchalla, Kenny M and Rood, Jonathan S and Sprague, Michael A},\n doi = {10.2172/1493479}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tsinober-intermittencyandstructuresofandinturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-99531-1_9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tsinober-intermittencyandstructuresofandinturbulence-2019', 'http://link.springer.com/10.1007/978-3-319-99531-1_9', event);\">\n    Intermittency and Structure(s) of and/in Turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tsinober,  A.\n</span>\n\n  \n\n</span>\n\n   2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-99531-1_9\"\n     onclick=\"log_download('tsinober-intermittencyandstructuresofandinturbulence-2019', 'http://link.springer.com/10.1007/978-3-319-99531-1_9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Intermittency and Structure(s) of and/in Turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-319-99531-1_9\"\n     onclick=\"log_download('tsinober-intermittencyandstructuresofandinturbulence-2019', 'http://doi.org/10.1007/978-3-319-99531-1_9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tsinober-intermittencyandstructuresofandinturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tsinober-intermittencyandstructuresofandinturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Intermittency and Structure(s) of and/in Turbulence},\n type = {misc},\n year = {2019},\n source = {The Essence of Turbulence as a Physical Phenomenon},\n pages = {157-190},\n websites = {http://link.springer.com/10.1007/978-3-319-99531-1_9},\n publisher = {Springer International Publishing},\n id = {e83f4ea7-2729-3756-b100-dc5719f9e27d},\n created = {2021-04-09T15:23:46.181Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:46.181Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {book_section},\n private_publication = {false},\n bibtype = {misc},\n author = {Tsinober, Arkady},\n doi = {10.1007/978-3-319-99531-1_9}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1906.03075\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019', 'http://arxiv.org/abs/1906.03075', event);\">\n    Using deformable particles for single particle measurements of velocity gradient tensors.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Hejazi,  B.; Krellenstein,  M.;  and Voth,  G., A.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1906.03075\"\n     onclick=\"log_download('hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019', 'http://arxiv.org/abs/1906.03075', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Using deformable particles for single particle measurements of velocity gradient tensors [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('hejazi-krellenstein-voth-usingdeformableparticlesforsingleparticlemeasurementsofvelocitygradienttensors-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Using deformable particles for single particle measurements of velocity gradient tensors},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1906.03075},\n month = {4},\n id = {2d3fb34f-e041-36e5-9b65-9804e1cba455},\n created = {2021-04-09T15:23:46.671Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:46.671Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We measure the deformation of particles made of several slender arms in a two-dimensional (2D) linear shear and a three-dimensional (3D) turbulent flow. We show how these measurements of arm deformations along with the rotation rate of the particle allow us to extract the velocity gradient tensor of the flow. The particles used in the experiments have three symmetric arms in a plane (triads) and are fabricated using 3D printing of a flexible polymeric material. Deformation measurements of a particle free to rotate about a fixed axis in a 2D simple shear flow are used to validate our model relating particle deformations to the fluid strain. We then examine deformable particles in a 3D turbulent flow created by a jet array in a vertical water tunnel. Particle orientations and deformations are measured with high precision using four high speed cameras and have an uncertainty on the order of 10^-4 radians. Measured deformations in 3D turbulence are small and only slightly larger than our orientation measurement uncertainty. Simulation results for triads in turbulence show deformations similar to the experimental observations. Deformable particles offer a promising method for measuring the full local velocity gradient tensor from measurements of a single particle where traditionally a high concentration of tracer particles would be required.},\n bibtype = {article},\n author = {Hejazi, Bardia and Krellenstein, Michael and Voth, Greg A}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We measure the deformation of particles made of several slender arms in a two-dimensional (2D) linear shear and a three-dimensional (3D) turbulent flow. We show how these measurements of arm deformations along with the rotation rate of the particle allow us to extract the velocity gradient tensor of the flow. The particles used in the experiments have three symmetric arms in a plane (triads) and are fabricated using 3D printing of a flexible polymeric material. Deformation measurements of a particle free to rotate about a fixed axis in a 2D simple shear flow are used to validate our model relating particle deformations to the fluid strain. We then examine deformable particles in a 3D turbulent flow created by a jet array in a vertical water tunnel. Particle orientations and deformations are measured with high precision using four high speed cameras and have an uncertainty on the order of 10^-4 radians. Measured deformations in 3D turbulence are small and only slightly larger than our orientation measurement uncertainty. Simulation results for triads in turbulence show deformations similar to the experimental observations. Deformable particles offer a promising method for measuring the full local velocity gradient tensor from measurements of a single particle where traditionally a high concentration of tracer particles would be required.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8356687/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019', 'https://ieeexplore.ieee.org/document/8356687/', event);\">\n    A Voxel-Based Rendering Pipeline for Large 3D Line Sets.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kanzler,  M.; Rautenhaus,  M.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>, 25(7): 2378-2391. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8356687/\"\n     onclick=\"log_download('kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019', 'https://ieeexplore.ieee.org/document/8356687/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Voxel-Based Rendering Pipeline for Large 3D Line Sets [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2018.2834372\"\n     onclick=\"log_download('kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019', 'http://doi.org/10.1109/TVCG.2018.2834372', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kanzler-rautenhaus-westermann-avoxelbasedrenderingpipelineforlarge3dlinesets-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Voxel-Based Rendering Pipeline for Large 3D Line Sets},\n type = {article},\n year = {2019},\n keywords = {Ray-casting,global illumination,large 3D line sets,transparency},\n pages = {2378-2391},\n volume = {25},\n websites = {https://ieeexplore.ieee.org/document/8356687/},\n month = {4},\n id = {f26f0e03-62ab-3fb6-a185-654bd2768cf8},\n created = {2021-04-09T15:23:47.931Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:47.931Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We present a voxel-based rendering pipeline for large 3D line sets that employs GPU ray-casting to achieve scalable rendering including transparency and global illumination effects that cannot be achieved with GPU rasterization. Even for opaque lines we demonstrate superior rendering performance compared to GPU rasterization of lines, and when transparency is used we can interactively render large amounts of lines that are infeasible to be rendered via rasterization. To achieve this, we propose a direction-preserving encoding of lines into a regular voxel grid, along with the quantization of directions using face-to-face connectivity in this grid. On the regular grid structure, parallel GPU ray-casting is used to determine visible fragments in correct visibility order. To enable interactive rendering of global illumination effects like low-frequency shadows and ambient occlusions, illumination simulation is performed during ray-casting on a level-of-detail (LoD) line representation that considers the number of lines and their lengths per voxel. In this way we can render effects which are very difficult to render via GPU rasterization. A detailed performance and quality evaluation compares our approach to rasterization-based rendering of lines.},\n bibtype = {article},\n author = {Kanzler, Mathias and Rautenhaus, Marc and Westermann, Rudiger},\n doi = {10.1109/TVCG.2018.2834372},\n journal = {IEEE Transactions on Visualization and Computer Graphics},\n number = {7}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We present a voxel-based rendering pipeline for large 3D line sets that employs GPU ray-casting to achieve scalable rendering including transparency and global illumination effects that cannot be achieved with GPU rasterization. Even for opaque lines we demonstrate superior rendering performance compared to GPU rasterization of lines, and when transparency is used we can interactively render large amounts of lines that are infeasible to be rendered via rasterization. To achieve this, we propose a direction-preserving encoding of lines into a regular voxel grid, along with the quantization of directions using face-to-face connectivity in this grid. On the regular grid structure, parallel GPU ray-casting is used to determine visible fragments in correct visibility order. To enable interactive rendering of global illumination effects like low-frequency shadows and ambient occlusions, illumination simulation is performed during ray-casting on a level-of-detail (LoD) line representation that considers the number of lines and their lengths per voxel. In this way we can render effects which are very difficult to render via GPU rasterization. A detailed performance and quality evaluation compares our approach to rasterization-based rendering of lines.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8817345/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019', 'https://ieeexplore.ieee.org/document/8817345/', event);\">\n    Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Baghaie,  A.\n</span>\n\n  \n\n</span>\n\n  In <i>2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT)</i>, pages 1-6, 4 2019. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8817345/\"\n     onclick=\"log_download('baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019', 'https://ieeexplore.ieee.org/document/8817345/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/LISAT.2019.8817345\"\n     onclick=\"log_download('baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019', 'http://doi.org/10.1109/LISAT.2019.8817345', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('baghaie-robustprincipalcomponentanalysisforbackgroundestimationofparticleimagevelocimetrydata-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Robust Principal Component Analysis for Background Estimation of Particle Image Velocimetry Data},\n type = {inproceedings},\n year = {2019},\n pages = {1-6},\n websites = {https://ieeexplore.ieee.org/document/8817345/},\n month = {4},\n publisher = {IEEE},\n id = {4a0ae990-a42f-3d6c-bb0e-654d5daa9608},\n created = {2021-04-09T15:23:48.365Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:48.365Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Baghaie, Ahmadreza},\n doi = {10.1109/LISAT.2019.8817345},\n booktitle = {2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT)}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019', 'https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671', event);\">\n    A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Marton,  F.; Agus,  M.;  and Gobbetti,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Computer Graphics Forum</i>, 38(3): 53-66. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671\"\n     onclick=\"log_download('marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019', 'https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1111/cgf.13671\"\n     onclick=\"log_download('marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019', 'http://doi.org/10.1111/cgf.13671', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>11 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('marton-agus-gobbetti-aframeworkforgpuacceleratedexplorationofmassivetimevaryingrectilinearscalarvolumes-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A framework for GPU‐accelerated exploration of massive time‐varying rectilinear scalar volumes},\n type = {article},\n year = {2019},\n keywords = {CCS Concepts,Graphics systems and interfaces,• Computing methodologies → Computer graphics,• Human‐centered computing → Scientific visualizat},\n pages = {53-66},\n volume = {38},\n websites = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13671},\n month = {4},\n publisher = {John Wiley &amp; Sons, Ltd (10.1111)},\n id = {4b5cd8db-6947-3ac8-b9dd-7f6ed694dab5},\n created = {2021-04-09T15:23:51.035Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:51.035Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Marton, Fabio and Agus, Marco and Gobbetti, Enrico},\n doi = {10.1111/cgf.13671},\n journal = {Computer Graphics Forum},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.99.053202\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019', 'https://link.aps.org/doi/10.1103/PhysRevE.99.053202', event);\">\n    Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kuzzay,  D.; Alexandrova,  O.;  and Matteini,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 99(5): 53202. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.99.053202\"\n     onclick=\"log_download('kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019', 'https://link.aps.org/doi/10.1103/PhysRevE.99.053202', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.99.053202\"\n     onclick=\"log_download('kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019', 'http://doi.org/10.1103/PhysRevE.99.053202', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kuzzay-alexandrova-matteini-localapproachtothestudyofenergytransfersinincompressiblemagnetohydrodynamicturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Local approach to the study of energy transfers in incompressible magnetohydrodynamic turbulence},\n type = {article},\n year = {2019},\n pages = {53202},\n volume = {99},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.99.053202},\n month = {4},\n publisher = {American Physical Society},\n id = {f3da8baa-5c3d-344e-87ea-28d5bbeac4a0},\n created = {2021-04-09T15:24:00.465Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:00.465Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Kuzzay, Denis and Alexandrova, Olga and Matteini, Lorenzo},\n doi = {10.1103/PhysRevE.99.053202},\n journal = {Physical Review E},\n number = {5}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1907.03634\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019', 'http://arxiv.org/abs/1907.03634', event);\">\n    Dual channels of helicity cascade in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yan,  Z.; Li,  X.; Yu,  C.;  and Chen,  S.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1907.03634\"\n     onclick=\"log_download('yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019', 'http://arxiv.org/abs/1907.03634', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dual channels of helicity cascade in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yan-li-yu-chen-dualchannelsofhelicitycascadeinturbulentflows-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dual channels of helicity cascade in turbulent flows},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1907.03634},\n month = {4},\n id = {f1f0d347-1a37-3f18-bb4c-677bb59ee33c},\n created = {2021-04-09T15:24:01.743Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:01.743Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.},\n bibtype = {article},\n author = {Yan, Zheng and Li, Xinliang and Yu, Changping and Chen, Shiyi}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Helicity, as one of only two inviscid invariants in three-dimensional turbulence, plays an important role in the generation and evolution of turbulence. From the traditional viewpoint, there exists only one channel of helicity cascade similar to that of kinetic energy cascade. Through theoretical analysis, we find that there are two channels in helicity cascade process. The first channel mainly originates from vortex twisting process, and the second channel mainly originates from vortex stretching process. By analysing the data of direct numerical simulations of typical turbulent flows, we find that these two channels behave differently. The ensemble averages of helicity flux in different channels are equal in homogeneous and isotropic turbulence, while they are different in other type of turbulent flows. The second channel is more intermittent and acts more like a scalar, especially on small scales. Besides, we find a novel mechanism of hindered even inverse energy cascade, which could be attributed to the second-channel helicity flux with large amplitude.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602', event);\">\n    Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sosa-Correa,  W.; Pereira,  R., M.; Macêdo,  A., M., S.; Raposo,  E., P.; Salazar,  D., S., P.;  and Vasconcelos,  G., L.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 4(6): 64602. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602\"\n     onclick=\"log_download('sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.4.064602\"\n     onclick=\"log_download('sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019', 'http://doi.org/10.1103/PhysRevFluids.4.064602', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sosacorrea-pereira-macdo-raposo-salazar-vasconcelos-emergenceofskewednongaussiandistributionsofvelocityincrementsinisotropicturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Emergence of skewed non-Gaussian distributions of velocity increments in isotropic turbulence},\n type = {article},\n year = {2019},\n pages = {64602},\n volume = {4},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.064602},\n month = {4},\n publisher = {American Physical Society},\n id = {021f32d8-a291-3056-a16b-dc980553a5b4},\n created = {2021-04-09T15:24:02.532Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:02.532Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Sosa-Correa, W and Pereira, R M and Macêdo, A M S and Raposo, E P and Salazar, D S P and Vasconcelos, G L},\n doi = {10.1103/PhysRevFluids.4.064602},\n journal = {Physical Review Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://journals.sagepub.com/doi/10.1177/0040517519846078\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019', 'http://journals.sagepub.com/doi/10.1177/0040517519846078', event);\">\n    Velocity and pressure visualization of three-dimensional flow in porous textiles.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lee,  J.; Yang,  B.; Cho,  J.;  and Song,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Textile Research Journal</i>, 89(23-24): 5041-5052. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://journals.sagepub.com/doi/10.1177/0040517519846078\"\n     onclick=\"log_download('lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019', 'http://journals.sagepub.com/doi/10.1177/0040517519846078', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Velocity and pressure visualization of three-dimensional flow in porous textiles [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1177/0040517519846078\"\n     onclick=\"log_download('lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019', 'http://doi.org/10.1177/0040517519846078', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lee-yang-cho-song-velocityandpressurevisualizationofthreedimensionalflowinporoustextiles-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Velocity and pressure visualization of three-dimensional flow in porous textiles},\n type = {article},\n year = {2019},\n keywords = {and systems engineering,flow visualization,magnetic resonance velocimetry,management of systems,materials,measurement,pressure visualization,product,product design,structure-properties},\n pages = {5041-5052},\n volume = {89},\n websites = {http://journals.sagepub.com/doi/10.1177/0040517519846078},\n month = {4},\n publisher = {SAGE PublicationsSage UK: London, England},\n id = {6aaefaff-4247-3be7-b4e8-2ed4fff906f5},\n created = {2021-04-09T15:24:03.314Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:03.314Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Advances in flow visualization techniques based on optics, such as lasers and digital cameras, have contributed considerably to the development of various flow models. However, the uses of optical techniques for flow visualization in porous media are limited owing to the complexity or opaqueness of the medium. This study demonstrates the utilization of magnetic resonance velocimetry to visualize a flow field in a textile material. By using phase-contrast magnetic resonance imaging, a three-dimensional, three-component velocity vector field was obtained for induced flow through a cut-pile carpet owing to the suction of a vacuum cleaner nozzle. As a result, we were able to experimentally identify the flow-dominant region in the carpet. Specifically, velocity vector plots and flow streamlines facilitated the identification of the flow paths, and indicated that the flow was strongest beneath the narrow walls of the vacuum nozzle. In addition, the pressure field in the carpet was estimated by an omni-directional integral method based on the utilization of the visualized velocity field, which showed where the pressure loss was maximized.},\n bibtype = {article},\n author = {Lee, Jeesoo and Yang, Byungkuen and Cho, Jee-Hyun and Song, Simon},\n doi = {10.1177/0040517519846078},\n journal = {Textile Research Journal},\n number = {23-24}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Advances in flow visualization techniques based on optics, such as lasers and digital cameras, have contributed considerably to the development of various flow models. However, the uses of optical techniques for flow visualization in porous media are limited owing to the complexity or opaqueness of the medium. This study demonstrates the utilization of magnetic resonance velocimetry to visualize a flow field in a textile material. By using phase-contrast magnetic resonance imaging, a three-dimensional, three-component velocity vector field was obtained for induced flow through a cut-pile carpet owing to the suction of a vacuum cleaner nozzle. As a result, we were able to experimentally identify the flow-dominant region in the carpet. Specifically, velocity vector plots and flow streamlines facilitated the identification of the flow paths, and indicated that the flow was strongest beneath the narrow walls of the vacuum nozzle. In addition, the pressure field in the carpet was estimated by an omni-directional integral method based on the utilization of the visualized velocity field, which showed where the pressure loss was maximized.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2717-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019', 'http://link.springer.com/10.1007/s00348-019-2717-2', event);\">\n    Dense motion estimation of particle images via a convolutional neural network.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Cai,  S.; Zhou,  S.; Xu,  C.;  and Gao,  Q.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 60(4): 73. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2717-2\"\n     onclick=\"log_download('cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019', 'http://link.springer.com/10.1007/s00348-019-2717-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dense motion estimation of particle images via a convolutional neural network [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2717-2\"\n     onclick=\"log_download('cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019', 'http://doi.org/10.1007/s00348-019-2717-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('cai-zhou-xu-gao-densemotionestimationofparticleimagesviaaconvolutionalneuralnetwork-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dense motion estimation of particle images via a convolutional neural network},\n type = {article},\n year = {2019},\n pages = {73},\n volume = {60},\n websites = {http://link.springer.com/10.1007/s00348-019-2717-2},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {e0ac0c33-5c62-3be2-976c-160d3a74533a},\n created = {2021-04-09T15:24:07.101Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:07.101Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Cai, Shengze and Zhou, Shichao and Xu, Chao and Gao, Qi},\n doi = {10.1007/s00348-019-2717-2},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5089883\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019', 'http://aip.scitation.org/doi/10.1063/1.5089883', event);\">\n    On the inherent bias of swirling strength in defining vortical structure.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bernard,  P., S.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 31(3): 35107. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5089883\"\n     onclick=\"log_download('bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019', 'http://aip.scitation.org/doi/10.1063/1.5089883', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On the inherent bias of swirling strength in defining vortical structure [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5089883\"\n     onclick=\"log_download('bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019', 'http://doi.org/10.1063/1.5089883', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bernard-ontheinherentbiasofswirlingstrengthindefiningvorticalstructure-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On the inherent bias of swirling strength in defining vortical structure},\n type = {article},\n year = {2019},\n pages = {35107},\n volume = {31},\n websites = {http://aip.scitation.org/doi/10.1063/1.5089883},\n month = {4},\n publisher = {AIP Publishing LLC},\n id = {1bcc598a-709e-3005-a0d9-7596e55ee9b5},\n created = {2021-04-09T15:24:12.031Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:12.031Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The traditional practice of using rotational motion as the principal attribute of coherent vortical structures in the buffer region of near-wall turbulent flow is shown to create a biased accountin...},\n bibtype = {article},\n author = {Bernard, Peter S},\n doi = {10.1063/1.5089883},\n journal = {Physics of Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The traditional practice of using rotational motion as the principal attribute of coherent vortical structures in the buffer region of near-wall turbulent flow is shown to create a biased accountin...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019', 'https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource', event);\">\n    Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Dallas,  C.; Wu,  M.; Chou,  V.; Liberzon,  A.;  and Sullivan,  P., E.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluids Engineering</i>, 141(11). 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource\"\n     onclick=\"log_download('dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019', 'https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1115/1.4043422\"\n     onclick=\"log_download('dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019', 'http://doi.org/10.1115/1.4043422', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dallas-wu-chou-liberzon-sullivan-graphicalprocessingunitacceleratedopensourceparticleimagevelocimetrysoftwareforhighperformancecomputingsystems-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Graphical Processing Unit-Accelerated Open-Source Particle Image Velocimetry Software for High Performance Computing Systems},\n type = {article},\n year = {2019},\n keywords = {Algorithms,Computer software,Graphics processing units,Particulate matter},\n volume = {141},\n websites = {https://asmedigitalcollection.asme.org/fluidsengineering/article/doi/10.1115/1.4043422/726873/Graphical-Processing-UnitAccelerated-OpenSource},\n month = {4},\n publisher = {American Society of Mechanical Engineers Digital Collection},\n id = {cc217224-e312-3428-96b2-ee61491e548c},\n created = {2021-04-09T15:24:14.978Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:14.978Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Particle image velocimetry (PIV) data processing time can constrain data set size and limit the types of statistical analyses performed. General purpose graphics processing unit (GPGPU) computing can accelerate PIV data processing allowing for larger datasets and accompanying higher order statistical analyses. However, this has not been widespread likely due to limited accessibility to the GPU-PIV hardware and software. Most GPU-PIV software is platform dependent and proprietary, which restricts the computing systems that can be used and makes the details of the algorithm unknown. This work highlights the development of an open-source, cross-platform, GPU-accelerated, PIV algorithm. Validation of the algorithm is done using both synthetic and experimental images. The algorithm was found to accurately resolve the time-averaged flow, instantaneous velocity fluctuations, and vortices. All data processing was done on a GPU supercomputing cluster and notably outperformed the central processing unit version of the software by a factor of 175. The algorithm is freely available and included in the OpenPIV distribution.},\n bibtype = {article},\n author = {Dallas, Cameron and Wu, Maria and Chou, Vincent and Liberzon, Alex and Sullivan, Pierre E},\n doi = {10.1115/1.4043422},\n journal = {Journal of Fluids Engineering},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Particle image velocimetry (PIV) data processing time can constrain data set size and limit the types of statistical analyses performed. General purpose graphics processing unit (GPGPU) computing can accelerate PIV data processing allowing for larger datasets and accompanying higher order statistical analyses. However, this has not been widespread likely due to limited accessibility to the GPU-PIV hardware and software. Most GPU-PIV software is platform dependent and proprietary, which restricts the computing systems that can be used and makes the details of the algorithm unknown. This work highlights the development of an open-source, cross-platform, GPU-accelerated, PIV algorithm. Validation of the algorithm is done using both synthetic and experimental images. The algorithm was found to accurately resolve the time-averaged flow, instantaneous velocity fluctuations, and vortices. All data processing was done on a GPU supercomputing cluster and notably outperformed the central processing unit version of the software by a factor of 175. The algorithm is freely available and included in the OpenPIV distribution.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019', 'https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X', event);\">\n    Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shen,  H.; Wu,  Y.; Zhou,  M.; Zhang,  H.;  and Yue,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Chinese Journal of Chemical Engineering</i>. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X\"\n     onclick=\"log_download('shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019', 'https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.cjche.2019.05.007\"\n     onclick=\"log_download('shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019', 'http://doi.org/10.1016/j.cjche.2019.05.007', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shen-wu-zhou-zhang-yue-stochasticmodelingofsubgridscaleeffectsonparticlemotioninforcedisotropicturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Stochastic modeling of subgrid-scale effects on particle motion in forced isotropic turbulence},\n type = {article},\n year = {2019},\n websites = {https://www.sciencedirect.com/science/article/pii/S100495411930357X,https://linkinghub.elsevier.com/retrieve/pii/S100495411930357X},\n month = {4},\n publisher = {Elsevier},\n id = {b6773a3d-bb0f-3392-b88a-44c5aaaa5583},\n created = {2021-04-09T15:24:15.979Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:15.979Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The subgrid-scale effects on particle motion were investigated in forced isotropic turbulence by DNS and prior-LES methods. In the DNS field, the importance of Kolmogorov scaling to preferential accumulation was validated by comparing the radial distribution functions under various particle Stokes numbers. The prior-LES fields were generated by filtering the DNS data. The subgrid-scale Stokes number (StSGS) is a useful tool for determining the effects of subgrid-scale eddies on particle motion. The subgrid-scale eddies tend to accumulate particles with StSGS &lt; 1 and disperse particles with 1 &lt; StSGS &lt; 10. For particles with StSGS ≫ 1, the effects of subgrid-scale eddies on particle motion can be neglected. In order to restore the subgrid-scale effects, the Langevin-type stochastic model with optimized parameters was adopted in this study. This model is effective for the particles with StSGS &gt; 1 while has an adverse impact on the particles with StSGS &lt; 1. The results show that the Langevin-type stochastic model tends to smooth the particle distribution in the isotropic turbulence.},\n bibtype = {article},\n author = {Shen, Haoshu and Wu, Yuxin and Zhou, Minmin and Zhang, Hai and Yue, Guangxi},\n doi = {10.1016/j.cjche.2019.05.007},\n journal = {Chinese Journal of Chemical Engineering}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The subgrid-scale effects on particle motion were investigated in forced isotropic turbulence by DNS and prior-LES methods. In the DNS field, the importance of Kolmogorov scaling to preferential accumulation was validated by comparing the radial distribution functions under various particle Stokes numbers. The prior-LES fields were generated by filtering the DNS data. The subgrid-scale Stokes number (StSGS) is a useful tool for determining the effects of subgrid-scale eddies on particle motion. The subgrid-scale eddies tend to accumulate particles with StSGS < 1 and disperse particles with 1 < StSGS < 10. For particles with StSGS ≫ 1, the effects of subgrid-scale eddies on particle motion can be neglected. In order to restore the subgrid-scale effects, the Langevin-type stochastic model with optimized parameters was adopted in this study. This model is effective for the particles with StSGS > 1 while has an adverse impact on the particles with StSGS < 1. The results show that the Langevin-type stochastic model tends to smooth the particle distribution in the isotropic turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8', event);\">\n    PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rajendran,  L., K.; Bane,  S., P., M.;  and Vlachos,  P., P.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 30(8): 85302. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8\"\n     onclick=\"log_download('rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019', 'https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/1361-6501/ab1ca8\"\n     onclick=\"log_download('rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019', 'http://doi.org/10.1088/1361-6501/ab1ca8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rajendran-bane-vlachos-pivbossyntheticimagegenerationinvariabledensityenvironmentsforerroranalysisandexperimentdesign-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {PIV/BOS synthetic image generation in variable density environments for error analysis and experiment design},\n type = {article},\n year = {2019},\n pages = {85302},\n volume = {30},\n websites = {https://iopscience.iop.org/article/10.1088/1361-6501/ab1ca8},\n month = {4},\n publisher = {IOP Publishing},\n id = {694f4e21-cf49-34b6-a913-a707e0253073},\n created = {2021-04-09T15:24:16.417Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:16.417Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P},\n doi = {10.1088/1361-6501/ab1ca8},\n journal = {Measurement Science and Technology},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kshitij-accurateandefficientautonomicclosureforturbulentflows-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://search.proquest.com/docview/2226592272?pq-origsite=gscholar\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kshitij-accurateandefficientautonomicclosureforturbulentflows-2019', 'https://search.proquest.com/docview/2226592272?pq-origsite=gscholar', event);\">\n    Accurate and Efficient Autonomic Closure for Turbulent Flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kshitij,  A.\n</span>\n\n  \n\n</span>\n\n   2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://search.proquest.com/docview/2226592272?pq-origsite=gscholar\"\n     onclick=\"log_download('kshitij-accurateandefficientautonomicclosureforturbulentflows-2019', 'https://search.proquest.com/docview/2226592272?pq-origsite=gscholar', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Accurate and Efficient Autonomic Closure for Turbulent Flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kshitij-accurateandefficientautonomicclosureforturbulentflows-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kshitij-accurateandefficientautonomicclosureforturbulentflows-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Accurate and Efficient Autonomic Closure for Turbulent Flows},\n type = {misc},\n year = {2019},\n websites = {https://search.proquest.com/docview/2226592272?pq-origsite=gscholar},\n institution = {ARIZONA STATE UNIVERSITY},\n id = {30a18ab6-0157-38f8-9532-b74068f5a841},\n created = {2021-04-09T15:24:17.608Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:17.608Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {thesis},\n private_publication = {false},\n bibtype = {misc},\n author = {Kshitij, Abhinav}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2768-4\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019', 'http://link.springer.com/10.1007/s00348-019-2768-4', event);\">\n    Singular value decomposition of noisy data: noise filtering.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Epps,  B., P.;  and Krivitzky,  E., M.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 60(8): 126. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2768-4\"\n     onclick=\"log_download('epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019', 'http://link.springer.com/10.1007/s00348-019-2768-4', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Singular value decomposition of noisy data: noise filtering [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2768-4\"\n     onclick=\"log_download('epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019', 'http://doi.org/10.1007/s00348-019-2768-4', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('epps-krivitzky-singularvaluedecompositionofnoisydatanoisefiltering-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Singular value decomposition of noisy data: noise filtering},\n type = {article},\n year = {2019},\n pages = {126},\n volume = {60},\n websites = {http://link.springer.com/10.1007/s00348-019-2768-4},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {4b1ae409-ef40-393c-94fd-d0ed9c3d2f1d},\n created = {2021-04-09T15:24:18.163Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:18.163Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Epps, Brenden P and Krivitzky, Eric M},\n doi = {10.1007/s00348-019-2768-4},\n journal = {Experiments in Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019', 'https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069', event);\">\n    Regularized inverse holographic volume reconstruction for 3D particle tracking.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mallery,  K.;  and Hong,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Optics Express</i>, 27(13): 18069. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069\"\n     onclick=\"log_download('mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019', 'https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Regularized inverse holographic volume reconstruction for 3D particle tracking [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1364/OE.27.018069\"\n     onclick=\"log_download('mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019', 'http://doi.org/10.1364/OE.27.018069', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mallery-hong-regularizedinverseholographicvolumereconstructionfor3dparticletracking-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Regularized inverse holographic volume reconstruction for 3D particle tracking},\n type = {article},\n year = {2019},\n keywords = {Compressive holography,High speed photography,Image metrics,Image processing,Image quality,Phase retrieval},\n pages = {18069},\n volume = {27},\n websites = {https://www.osapublishing.org/abstract.cfm?URI=oe-27-13-18069},\n month = {4},\n publisher = {Optical Society of America},\n id = {77ebf8f3-d916-351b-8ed0-2df7438d554d},\n created = {2021-04-09T15:24:19.672Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:19.672Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.},\n bibtype = {article},\n author = {Mallery, Kevin and Hong, Jiarong},\n doi = {10.1364/OE.27.018069},\n journal = {Optics Express},\n number = {13}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization to perform full volumetric reconstructions of particle fields. By exploiting data sparsity in the solution and utilizing GPU processing, we dramatically reduce the computational cost usually associated with inverse reconstruction approaches. We demonstrate the accuracy of the proposed method using synthetic and experimental holograms. Finally, we present two practical applications (high concentration microorganism swimming and microfiber rotation) to extend the capabilities of DIH beyond what was possible using prior methods.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://ieeexplore.ieee.org/document/8440063/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019', 'https://ieeexplore.ieee.org/document/8440063/', event);\">\n    A Declarative Grammar of Flexible Volume Visualization Pipelines.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shih,  M.; Rozhon,  C.;  and Ma,  K.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>, 25(1): 1050-1059. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://ieeexplore.ieee.org/document/8440063/\"\n     onclick=\"log_download('shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019', 'https://ieeexplore.ieee.org/document/8440063/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Declarative Grammar of Flexible Volume Visualization Pipelines [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2018.2864841\"\n     onclick=\"log_download('shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019', 'http://doi.org/10.1109/TVCG.2018.2864841', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shih-rozhon-ma-adeclarativegrammarofflexiblevolumevisualizationpipelines-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Declarative Grammar of Flexible Volume Visualization Pipelines},\n type = {article},\n year = {2019},\n pages = {1050-1059},\n volume = {25},\n websites = {https://ieeexplore.ieee.org/document/8440063/},\n month = {4},\n id = {d2fa3e23-d58f-3188-801f-b9802e93fb62},\n created = {2021-04-09T15:24:20.241Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:20.241Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Shih, Min and Rozhon, Charles and Ma, Kwan-Liu},\n doi = {10.1109/TVCG.2018.2864841},\n journal = {IEEE Transactions on Visualization and Computer Graphics},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article', event);\">\n    On the Reynolds number dependence of velocity-gradient structure and dynamics.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Das,  R.;  and Girimaji,  S., S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 861: 163-179. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article\"\n     onclick=\"log_download('das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019', 'https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On the Reynolds number dependence of velocity-gradient structure and dynamics [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.924\"\n     onclick=\"log_download('das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019', 'http://doi.org/10.1017/jfm.2018.924', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('das-girimaji-onthereynoldsnumberdependenceofvelocitygradientstructureanddynamics-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On the Reynolds number dependence of velocity-gradient structure and dynamics},\n type = {article},\n year = {2019},\n keywords = {intermittency,isotropic turbulence,turbulent flows},\n pages = {163-179},\n volume = {861},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018009242/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {ae410480-9dcc-3981-b2c4-c727efa02cc1},\n created = {2021-04-09T15:24:21.799Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:21.799Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We seek to examine the changes in velocity-gradient structure (local streamline topology) and related dynamics as a function of Reynolds number ( Re_[STIX]x1D706 ). The analysis factorizes the velocity gradient ( [STIX]x1D608_ij ) into the magnitude ( A^2 ) and normalized-gradient tensor ( [STIX]x1D623_ij [STIX]x1D608_ij/A^2 ). The focus is on bounded [STIX]x1D623_ij as (i) it describes small-scale structure and local streamline topology, and (ii) its dynamics is shown to determine magnitude evolution. Using direct numerical simulation (DNS) data, the moments and probability distributions of [STIX]x1D623_ij and its scalar invariants are shown to attain Re_[STIX]x1D706 independence. The critical values beyond which each feature attains Re_[STIX]x1D706 independence are established. We proceed to characterize the Re_[STIX]x1D706 dependence of [STIX]x1D623_ij -conditioned statistics of key non-local pressure and viscous processes. Overall, the analysis provides further insight into velocity-gradient dynamics and offers an alternative framework for investigating intermittency, multifractal behaviour and for developing closure models.},\n bibtype = {article},\n author = {Das, Rishita and Girimaji, Sharath S},\n doi = {10.1017/jfm.2018.924},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We seek to examine the changes in velocity-gradient structure (local streamline topology) and related dynamics as a function of Reynolds number ( Re_[STIX]x1D706 ). The analysis factorizes the velocity gradient ( [STIX]x1D608_ij ) into the magnitude ( A^2 ) and normalized-gradient tensor ( [STIX]x1D623_ij [STIX]x1D608_ij/A^2 ). The focus is on bounded [STIX]x1D623_ij as (i) it describes small-scale structure and local streamline topology, and (ii) its dynamics is shown to determine magnitude evolution. Using direct numerical simulation (DNS) data, the moments and probability distributions of [STIX]x1D623_ij and its scalar invariants are shown to attain Re_[STIX]x1D706 independence. The critical values beyond which each feature attains Re_[STIX]x1D706 independence are established. We proceed to characterize the Re_[STIX]x1D706 dependence of [STIX]x1D623_ij -conditioned statistics of key non-local pressure and viscous processes. Overall, the analysis provides further insight into velocity-gradient dynamics and offers an alternative framework for investigating intermittency, multifractal behaviour and for developing closure models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1905.02657\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019', 'http://arxiv.org/abs/1905.02657', event);\">\n    Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bappy,  M.; Carrica,  P., M.;  and Buscaglia,  G., C.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1905.02657\"\n     onclick=\"log_download('bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019', 'http://arxiv.org/abs/1905.02657', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bappy-carrica-buscaglia-lagrangianstatisticsofpressurefluctuationeventsinhomogeneousisotropicturbulence-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Lagrangian statistics of pressure fluctuation events in homogeneous isotropic turbulence},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1905.02657},\n month = {4},\n id = {280c93e9-f450-3915-b1f9-260517c43d49},\n created = {2021-04-09T15:24:22.355Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:22.355Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Homogeneous and isotropic turbulent fields obtained from two DNS databases (with Re_λ equal to 150 and 418) were seeded with point particles that moved with the local fluid velocity to obtain Lagrangian pressure histories. Motivated by cavitation inception modeling, the statistics of events in which such particles undergo low-pressure fluctuations were computed, parameterized by the amplitude of the fluctuations and by their duration. The main results are the average frequencies of these events and the probabilistic distribution of their duration, which are of predictive value. A connection is also established between these average frequencies and the pressure probability density function, thus justifying experimental methods proposed in the literature. Further analyses of the data show that the occurrence of very-low-pressure events is highly intermittent and is associated with worm-like vortical structures of length comparable to the integral scale of the flow.},\n bibtype = {article},\n author = {Bappy, Mehedi and Carrica, Pablo M and Buscaglia, Gustavo C}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Homogeneous and isotropic turbulent fields obtained from two DNS databases (with Re_λ equal to 150 and 418) were seeded with point particles that moved with the local fluid velocity to obtain Lagrangian pressure histories. Motivated by cavitation inception modeling, the statistics of events in which such particles undergo low-pressure fluctuations were computed, parameterized by the amplitude of the fluctuations and by their duration. The main results are the average frequencies of these events and the probabilistic distribution of their duration, which are of predictive value. A connection is also established between these average frequencies and the pressure probability density function, thus justifying experimental methods proposed in the literature. Further analyses of the data show that the occurrence of very-low-pressure events is highly intermittent and is associated with worm-like vortical structures of length comparable to the integral scale of the flow.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-22196-6_12\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019', 'http://link.springer.com/10.1007/978-3-030-22196-6_12', event);\">\n    Identifying the Wall Signature of Large-Scale Motions with Extended POD.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Güemes,  A.; Vaquero,  A.; Flores,  O.; Discetti,  S.;  and Ianiro,  A.\n</span>\n\n  \n\n</span>\n\n  In Örlü,  R.; Talamelli,  A.; Peinke,  J.;  and Oberlack,  M., editor(s), <i>8th iTi Conference on Turbulence</i>, pages 75-80, 4 2019. Springer, Cham\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-030-22196-6_12\"\n     onclick=\"log_download('gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019', 'http://link.springer.com/10.1007/978-3-030-22196-6_12', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Identifying the Wall Signature of Large-Scale Motions with Extended POD [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-22196-6_12\"\n     onclick=\"log_download('gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019', 'http://doi.org/10.1007/978-3-030-22196-6_12', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>7 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gemes-vaquero-flores-discetti-ianiro-identifyingthewallsignatureoflargescalemotionswithextendedpod-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Identifying the Wall Signature of Large-Scale Motions with Extended POD},\n type = {inproceedings},\n year = {2019},\n pages = {75-80},\n websites = {http://link.springer.com/10.1007/978-3-030-22196-6_12},\n month = {4},\n publisher = {Springer, Cham},\n id = {d61dbfb7-bdc7-3a6d-be6f-dd3b8a1f6f86},\n created = {2021-04-09T15:24:22.820Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:22.820Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Güemes, A and Vaquero, A and Flores, O and Discetti, S and Ianiro, A},\n editor = {Örlü, R and Talamelli, A and Peinke, J and Oberlack, M},\n doi = {10.1007/978-3-030-22196-6_12},\n booktitle = {8th iTi Conference on Turbulence}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1905.07062\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019', 'http://arxiv.org/abs/1905.07062', event);\">\n    Robust Principal Component Analysis for Particle Image Velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Scherl,  I.; Strom,  B.; Shang,  J., K.; Williams,  O.; Polagye,  B., L.;  and Brunton,  S., L.\n</span>\n\n  \n\n</span>\n\n  . 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1905.07062\"\n     onclick=\"log_download('scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019', 'http://arxiv.org/abs/1905.07062', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Robust Principal Component Analysis for Particle Image Velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('scherl-strom-shang-williams-polagye-brunton-robustprincipalcomponentanalysisforparticleimagevelocimetry-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Robust Principal Component Analysis for Particle Image Velocimetry},\n type = {article},\n year = {2019},\n websites = {http://arxiv.org/abs/1905.07062},\n month = {4},\n id = {b2b8c1c5-c3df-3831-acee-24a087c7762f},\n created = {2021-04-09T15:24:23.533Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:23.533Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Particle image velocimetry (PIV) is an experimental technique used to measure fluid flow fields. However, PIV fields often have spurious and missing velocity vectors that degrade subsequent analyses. Standard post-processing involves the identification and replacement of outliers based on local information. We present a method to identify and fill in erroneous or missing PIV vectors using global information via robust principal component analysis (RPCA), a statistical technique developed for outlier rejection. RPCA decomposes a data matrix into a low-rank matrix containing coherent structures and a sparse matrix of outliers. We explore RPCA on a range of fluid simulations and experiments of varying complexity. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificially added outliers, alongside similar PIV measurements at Reynolds number 413. Next, we apply RPCA to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are maintained and the turbulent kinetic energy spectrum remains largely intact. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA extracts dominant fluid coherent structures and identifies and fills in corruption and outliers, with minimal degradation of small scale structures.},\n bibtype = {article},\n author = {Scherl, Isabel and Strom, Benjamin and Shang, Jessica K and Williams, Owen and Polagye, Brian L and Brunton, Steven L}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Particle image velocimetry (PIV) is an experimental technique used to measure fluid flow fields. However, PIV fields often have spurious and missing velocity vectors that degrade subsequent analyses. Standard post-processing involves the identification and replacement of outliers based on local information. We present a method to identify and fill in erroneous or missing PIV vectors using global information via robust principal component analysis (RPCA), a statistical technique developed for outlier rejection. RPCA decomposes a data matrix into a low-rank matrix containing coherent structures and a sparse matrix of outliers. We explore RPCA on a range of fluid simulations and experiments of varying complexity. First, we analyze direct numerical simulations of flow past a circular cylinder at Reynolds number 100 with artificially added outliers, alongside similar PIV measurements at Reynolds number 413. Next, we apply RPCA to a turbulent channel flow simulation from the Johns Hopkins Turbulence database, demonstrating that dominant coherent structures are maintained and the turbulent kinetic energy spectrum remains largely intact. Finally, we investigate PIV measurements behind a two-bladed cross-flow turbine that exhibits both broadband and coherent phenomena. In all cases, we find that RPCA extracts dominant fluid coherent structures and identifies and fills in corruption and outliers, with minimal degradation of small scale structures.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://epubs.siam.org/doi/10.1137/18M1208885\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019', 'https://epubs.siam.org/doi/10.1137/18M1208885', event);\">\n    Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ainsworth,  M.; Tugluk,  O.; Whitney,  B.;  and Klasky,  S.\n</span>\n\n  \n\n</span>\n\n  <i>SIAM Journal on Scientific Computing</i>, 41(4): A2146-A2171. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://epubs.siam.org/doi/10.1137/18M1208885\"\n     onclick=\"log_download('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019', 'https://epubs.siam.org/doi/10.1137/18M1208885', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1137/18M1208885\"\n     onclick=\"log_download('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019', 'http://doi.org/10.1137/18M1208885', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdataquantitativecontrolofaccuracyinderivedquantities-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities},\n type = {article},\n year = {2019},\n keywords = {68P30,94A24,big data,data compression,data reduction},\n pages = {A2146-A2171},\n volume = {41},\n websites = {https://epubs.siam.org/doi/10.1137/18M1208885},\n month = {4},\n publisher = {Society for Industrial and Applied Mathematics},\n id = {c4627576-776b-3e42-afb9-47c6f4432697},\n created = {2021-04-09T15:24:28.816Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:28.816Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may ...},\n bibtype = {article},\n author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},\n doi = {10.1137/18M1208885},\n journal = {SIAM Journal on Scientific Computing},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may ...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://arc.aiaa.org/doi/10.2514/6.2019-0269\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019', 'https://arc.aiaa.org/doi/10.2514/6.2019-0269', event);\">\n    High Spatial Resolution 3D Fluid Velocimetry by Tomographic Particle Flow Velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kumashiro,  K.; Steinberg,  A., M.;  and Yano,  M.\n</span>\n\n  \n\n</span>\n\n  In <i>AIAA Scitech 2019 Forum</i>, 4 2019. American Institute of Aeronautics and Astronautics\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://arc.aiaa.org/doi/10.2514/6.2019-0269\"\n     onclick=\"log_download('kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019', 'https://arc.aiaa.org/doi/10.2514/6.2019-0269', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"High Spatial Resolution 3D Fluid Velocimetry by Tomographic Particle Flow Velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2019-0269\"\n     onclick=\"log_download('kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019', 'http://doi.org/10.2514/6.2019-0269', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kumashiro-steinberg-yano-highspatialresolution3dfluidvelocimetrybytomographicparticleflowvelocimetry-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {High Spatial Resolution 3D Fluid Velocimetry by Tomographic Particle Flow Velocimetry},\n type = {inproceedings},\n year = {2019},\n websites = {https://arc.aiaa.org/doi/10.2514/6.2019-0269},\n month = {4},\n publisher = {American Institute of Aeronautics and Astronautics},\n id = {7092cfa0-40fc-3f5a-9dc4-623b16b65db8},\n created = {2021-04-09T15:24:29.312Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:29.312Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Kumashiro, Keishi and Steinberg, Adam M and Yano, Masayuki},\n doi = {10.2514/6.2019-0269},\n booktitle = {AIAA Scitech 2019 Forum}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019', 'https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573', event);\">\n    Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chen,  G., G.;  and Glimm,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Physica D: Nonlinear Phenomena</i>,132138. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573\"\n     onclick=\"log_download('chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019', 'https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3 [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.physd.2019.06.004\"\n     onclick=\"log_download('chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019', 'http://doi.org/10.1016/j.physd.2019.06.004', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chen-glimm-kolmogorovtypetheoryofcompressibleturbulenceandinviscidlimitofthenavierstokesequationsinr3-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Kolmogorov-type theory of compressible turbulence and inviscid limit of the Navier-Stokes equations in R3},\n type = {article},\n year = {2019},\n pages = {132138},\n websites = {https://www.sciencedirect.com/science/article/pii/S0167278918304573,https://linkinghub.elsevier.com/retrieve/pii/S0167278918304573},\n month = {4},\n publisher = {North-Holland},\n id = {b9e7ee8b-2fc2-36aa-9dba-abcc4c501d46},\n created = {2021-04-09T15:24:32.670Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:32.670Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We are concerned with the inviscid limit of the Navier–Stokes equations to the Euler equations for compressible fluids in R3. Motivated by the Kolmogorov hypothesis (1941) for incompressible flow, we introduce a Kolmogorov-type hypothesis for barotropic flows, in which the density and the sonic speed normally vary significantly. We then observe that the compressible Kolmogorov-type hypothesis implies the uniform boundedness of some fractional derivatives of the weighted velocity and sonic speed in the space variables in L2, which is independent of the viscosity coefficient μ&gt;0. It is shown that this key observation yields the equicontinuity in both space and time of the density in Lγ and the momentum in L2, as well as the uniform bound of the density in Lq1 and the velocity in Lq2 for some fixed q1&gt;γ and q2&gt;2, independent of μ&gt;0, where γ&gt;1 is the adiabatic exponent. These results lead to the strong convergence of solutions of the Navier–Stokes equations to a solution of the Euler equations for barotropic fluids in R3. Not only do we offer a framework for mathematical existence theories, but also we offer a framework for the interpretation of numerical solutions through the identification of a function space in which convergence should take place, with the bounds that are independent of μ&gt;0, that is in the high Reynolds number limit.},\n bibtype = {article},\n author = {Chen, Gui-Qiang G and Glimm, James},\n doi = {10.1016/j.physd.2019.06.004},\n journal = {Physica D: Nonlinear Phenomena}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We are concerned with the inviscid limit of the Navier–Stokes equations to the Euler equations for compressible fluids in R3. Motivated by the Kolmogorov hypothesis (1941) for incompressible flow, we introduce a Kolmogorov-type hypothesis for barotropic flows, in which the density and the sonic speed normally vary significantly. We then observe that the compressible Kolmogorov-type hypothesis implies the uniform boundedness of some fractional derivatives of the weighted velocity and sonic speed in the space variables in L2, which is independent of the viscosity coefficient μ>0. It is shown that this key observation yields the equicontinuity in both space and time of the density in Lγ and the momentum in L2, as well as the uniform bound of the density in Lq1 and the velocity in Lq2 for some fixed q1>γ and q2>2, independent of μ>0, where γ>1 is the adiabatic exponent. These results lead to the strong convergence of solutions of the Navier–Stokes equations to a solution of the Euler equations for barotropic fluids in R3. Not only do we offer a framework for mathematical existence theories, but also we offer a framework for the interpretation of numerical solutions through the identification of a function space in which convergence should take place, with the bounds that are independent of μ>0, that is in the high Reynolds number limit.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2777-3\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019', 'http://link.springer.com/10.1007/s00348-019-2777-3', event);\">\n    A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kozul,  M.; Koothur,  V.; Worth,  N., A.;  and Dawson,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 60(8): 137. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2777-3\"\n     onclick=\"log_download('kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019', 'http://link.springer.com/10.1007/s00348-019-2777-3', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2777-3\"\n     onclick=\"log_download('kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019', 'http://doi.org/10.1007/s00348-019-2777-3', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kozul-koothur-worth-dawson-ascanningparticletrackingvelocimetrytechniqueforhighreynoldsnumberturbulentflows-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows},\n type = {article},\n year = {2019},\n pages = {137},\n volume = {60},\n websites = {http://link.springer.com/10.1007/s00348-019-2777-3},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {1c8096ee-c7d7-33c2-a56c-6a2f7ef84968},\n created = {2021-04-09T15:24:36.419Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:36.419Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Kozul, Melissa and Koothur, Vipin and Worth, Nicholas A and Dawson, James R},\n doi = {10.1007/s00348-019-2777-3},\n journal = {Experiments in Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2678-5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019', 'http://link.springer.com/10.1007/s00348-019-2678-5', event);\">\n    Pressure from 2D snapshot PIV.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  der Kindere,  J., W., V.; Laskari,  A.; Ganapathisubramani,  B.;  and de Kat,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 60(2): 32. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-019-2678-5\"\n     onclick=\"log_download('derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019', 'http://link.springer.com/10.1007/s00348-019-2678-5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Pressure from 2D snapshot PIV [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-019-2678-5\"\n     onclick=\"log_download('derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019', 'http://doi.org/10.1007/s00348-019-2678-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('derkindere-laskari-ganapathisubramani-dekat-pressurefrom2dsnapshotpiv-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pressure from 2D snapshot PIV},\n type = {article},\n year = {2019},\n pages = {32},\n volume = {60},\n websites = {http://link.springer.com/10.1007/s00348-019-2678-5},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {ba00cf84-a72d-3998-a269-642fe5c25cf6},\n created = {2021-04-09T15:24:36.935Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:36.935Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {der Kindere, J W Van and Laskari, A and Ganapathisubramani, B and de Kat, R},\n doi = {10.1007/s00348-019-2678-5},\n journal = {Experiments in Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019', 'https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532', event);\">\n    On Visualizing Continuous Turbulence Scales.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  X.; Mishra,  M.; Skote,  M.;  and Fu,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Computer Graphics Forum</i>, 38(1): 300-315. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532\"\n     onclick=\"log_download('liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019', 'https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On Visualizing Continuous Turbulence Scales [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1111/cgf.13532\"\n     onclick=\"log_download('liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019', 'http://doi.org/10.1111/cgf.13532', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-mishra-skote-fu-onvisualizingcontinuousturbulencescales-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On Visualizing Continuous Turbulence Scales},\n type = {article},\n year = {2019},\n keywords = {Human‐centered computing∼Scientific visualization,flow visualization,scientific visualization,visualization,volume visualization},\n pages = {300-315},\n volume = {38},\n websites = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13532},\n month = {4},\n publisher = {John Wiley &amp; Sons, Ltd (10.1111)},\n id = {e60aa66b-61a5-3dc9-a8a9-4d541b501276},\n created = {2021-04-09T15:24:43.766Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:43.766Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Liu, Xiaopei and Mishra, Maneesh and Skote, Martin and Fu, Chi‐Wing},\n doi = {10.1111/cgf.13532},\n journal = {Computer Graphics Forum},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902', event);\">\n    Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  Z.; Lee,  J.; Meneveau,  C.;  and Zaki,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 4(2): 23902. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902\"\n     onclick=\"log_download('wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.4.023902\"\n     onclick=\"log_download('wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019', 'http://doi.org/10.1103/PhysRevFluids.4.023902', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-lee-meneveau-zaki-applicationofaselforganizingmaptoidentifytheturbulentboundarylayerinterfaceinatransitionalflow-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow},\n type = {article},\n year = {2019},\n pages = {23902},\n volume = {4},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.023902},\n month = {4},\n publisher = {American Physical Society},\n id = {ec287cd3-c0fe-353a-a570-e6ae60c03bac},\n created = {2021-04-09T15:24:48.752Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:48.752Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Existing methods to identify the interfaces separating different regions in turbulent flows, such as turbulent/nonturbulent interfaces, typically rely on subjectively chosen thresholds, often including visual verification that the resulting surface meaningfully separates the different regions. Since machine learning tools are known to help automate such classification tasks, we here propose to use an unsupervised self-organizing map (SOM) machine learning algorithm as an automatic classifier. We use it to separate a boundary layer undergoing bypass transition into two distinct spatial regions, the turbulent boundary layer (TBL) and non-TBL regions, the latter including the laminar portion prior to transition and the outer flow which possibly contains weak free-stream turbulence. Both regions are separated by the turbulent boundary layer interface (TBLI). The data used in this study are from a direct numerical simulation and are available on an open database system. In our analysis of one snapshot in time, every spatial point is characterized by a 16-dimensional vector containing the magnitudes of the components of total and fluctuating velocity, magnitudes of the velocity gradient tensor elements, and the streamwise and wall-normal coordinates, all normalized by their global standard deviation. In an unsupervised fashion, the SOM classifier separates the points into TBL and non-TBL regions, thus identifying the TBLI without the need for user-specified thresholds. Remarkably, it avoids including vortical streaky structures that exist in the laminar portion prior to transition as well as the weak free-stream turbulence in the turbulent boundary layer region. The approach is compared quantitatively with existing methods to determine the TBLI (vorticity magnitude, cross-stream velocity fluctuation). Also, the SOM classifier is cast as a linear hyperplane that separates the two clusters of data points, and the method is tested by finding the TBLI of other snapshots in the transitional boundary layer data set, as well as in a fully turbulent boundary layer with similar levels of free-stream turbulence. Variants in which the approach failed are also summarized.},\n bibtype = {article},\n author = {Wu, Zhao and Lee, Jin and Meneveau, Charles and Zaki, Tamer},\n doi = {10.1103/PhysRevFluids.4.023902},\n journal = {Physical Review Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Existing methods to identify the interfaces separating different regions in turbulent flows, such as turbulent/nonturbulent interfaces, typically rely on subjectively chosen thresholds, often including visual verification that the resulting surface meaningfully separates the different regions. Since machine learning tools are known to help automate such classification tasks, we here propose to use an unsupervised self-organizing map (SOM) machine learning algorithm as an automatic classifier. We use it to separate a boundary layer undergoing bypass transition into two distinct spatial regions, the turbulent boundary layer (TBL) and non-TBL regions, the latter including the laminar portion prior to transition and the outer flow which possibly contains weak free-stream turbulence. Both regions are separated by the turbulent boundary layer interface (TBLI). The data used in this study are from a direct numerical simulation and are available on an open database system. In our analysis of one snapshot in time, every spatial point is characterized by a 16-dimensional vector containing the magnitudes of the components of total and fluctuating velocity, magnitudes of the velocity gradient tensor elements, and the streamwise and wall-normal coordinates, all normalized by their global standard deviation. In an unsupervised fashion, the SOM classifier separates the points into TBL and non-TBL regions, thus identifying the TBLI without the need for user-specified thresholds. Remarkably, it avoids including vortical streaky structures that exist in the laminar portion prior to transition as well as the weak free-stream turbulence in the turbulent boundary layer region. The approach is compared quantitatively with existing methods to determine the TBLI (vorticity magnitude, cross-stream velocity fluctuation). Also, the SOM classifier is cast as a linear hyperplane that separates the two clusters of data points, and the method is tested by finding the TBLI of other snapshots in the transitional boundary layer data set, as well as in a fully turbulent boundary layer with similar levels of free-stream turbulence. Variants in which the approach failed are also summarized.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747', event);\">\n    Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jie,  Y.; Xu,  C.; Dawson,  J., R.; Andersson,  H., I.;  and Zhao,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Turbulence</i>, 20(7): 424-438. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747\"\n     onclick=\"log_download('jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/14685248.2019.1664747\"\n     onclick=\"log_download('jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019', 'http://doi.org/10.1080/14685248.2019.1664747', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jie-xu-dawson-andersson-zhao-influenceofthequiescentcoreontracerspheroidalparticledynamicsinturbulentchannelflow-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Influence of the quiescent core on tracer spheroidal particle dynamics in turbulent channel flow},\n type = {article},\n year = {2019},\n keywords = {Turbulent channel flow,quiescent core,spheroidal inertialess particles},\n pages = {424-438},\n volume = {20},\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2019.1664747},\n month = {4},\n publisher = {Taylor and Francis Ltd.},\n id = {bde9b67c-cc56-3e5a-ba15-32edb1794316},\n created = {2021-04-09T15:24:49.272Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:49.272Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Numerical studies into the dynamics of non-spherical particles in turbulent channel flow have, until now, been mostly confined to low Reynolds numbers. In this paper, we investigate the dynamics of tracer non-spherical particles in a channel flow at (Formula presented.) for the first time. Tracer spheroidal particles suspended in a turbulent channel flow are computed by means of direct numerical simulation coupled with a Lagrangian point-particle approach. We examine the rotational dynamics and alignment of tracer spheroids of different aspect ratio in both the near-wall region and, in particular, the quiescent core which is not observed at lower Reynolds numbers. In the near-wall region, the effect of Reynolds number on preferential alignment is negligible with particle rotation exhibiting a weak dependence for all aspect ratios investigated. However, the particle rotation is strongly damped in the quiescent core demonstrating that the motion of tracer spheroids becomes quiescent. The striking difference in spheroids&#x27; rotational dynamics observed inside and outside of the quiescent core is correlated with the local Kolmogorov time scale in the core and outside of it.},\n bibtype = {article},\n author = {Jie, Yucheng and Xu, Chunxiao and Dawson, James R and Andersson, Helge I and Zhao, Lihao},\n doi = {10.1080/14685248.2019.1664747},\n journal = {Journal of Turbulence},\n number = {7}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Numerical studies into the dynamics of non-spherical particles in turbulent channel flow have, until now, been mostly confined to low Reynolds numbers. In this paper, we investigate the dynamics of tracer non-spherical particles in a channel flow at (Formula presented.) for the first time. Tracer spheroidal particles suspended in a turbulent channel flow are computed by means of direct numerical simulation coupled with a Lagrangian point-particle approach. We examine the rotational dynamics and alignment of tracer spheroids of different aspect ratio in both the near-wall region and, in particular, the quiescent core which is not observed at lower Reynolds numbers. In the near-wall region, the effect of Reynolds number on preferential alignment is negligible with particle rotation exhibiting a weak dependence for all aspect ratios investigated. However, the particle rotation is strongly damped in the quiescent core demonstrating that the motion of tracer spheroids becomes quiescent. The striking difference in spheroids' rotational dynamics observed inside and outside of the quiescent core is correlated with the local Kolmogorov time scale in the core and outside of it.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5128053\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019', 'http://aip.scitation.org/doi/10.1063/1.5128053', event);\">\n    Sensing the turbulent large-scale motions with their wall signature.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Güemes,  A.; Discetti,  S.;  and Ianiro,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 31(12): 125112. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5128053\"\n     onclick=\"log_download('gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019', 'http://aip.scitation.org/doi/10.1063/1.5128053', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Sensing the turbulent large-scale motions with their wall signature [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5128053\"\n     onclick=\"log_download('gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019', 'http://doi.org/10.1063/1.5128053', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gemes-discetti-ianiro-sensingtheturbulentlargescalemotionswiththeirwallsignature-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Sensing the turbulent large-scale motions with their wall signature},\n type = {article},\n year = {2019},\n pages = {125112},\n volume = {31},\n websites = {http://aip.scitation.org/doi/10.1063/1.5128053},\n month = {4},\n publisher = {American Institute of Physics Inc.},\n id = {34785306-ab75-301c-9fe7-4a8b56499b9d},\n created = {2021-04-09T15:24:50.032Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:50.032Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.},\n bibtype = {article},\n author = {Güemes, A and Discetti, S and Ianiro, A},\n doi = {10.1063/1.5128053},\n journal = {Physics of Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article', event);\">\n    Mean dynamics and transition to turbulence in oscillatory channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ebadi,  A.; White,  C., M.; Pond,  I.;  and Dubief,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 880: 864-889. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article\"\n     onclick=\"log_download('ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Mean dynamics and transition to turbulence in oscillatory channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2019.706\"\n     onclick=\"log_download('ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019', 'http://doi.org/10.1017/jfm.2019.706', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ebadi-white-pond-dubief-meandynamicsandtransitiontoturbulenceinoscillatorychannelflow-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Mean dynamics and transition to turbulence in oscillatory channel flow},\n type = {article},\n year = {2019},\n keywords = {boundary layer structure,transition to turbulence,turbulent boundary layers},\n pages = {864-889},\n volume = {880},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019007067/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {2b9bc248-7bec-3add-aaf3-c815e69e4177},\n created = {2021-04-09T15:24:50.517Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:50.517Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The mean dynamics in oscillatory channel flow is examined to investigate the dynamical mechanisms underlying the transition to turbulence in oscillatory wall-bounded flow. The analyses employ direct numerical simulation data acquired at three Stokes Reynolds numbers: Re_s=648 , 801 and 1009, where the lower Re_s flow is transitional over the entire cycle and the two higher Re_s flows exhibit flow characteristics similar to steady turbulent wall-bounded flow during part of the cycle. The flow evolution over a half-period of oscillation for all three Re_s is as follows: near-wall streamwise velocity streaks develop during the early accelerating portion of the cycle; then at some later point in the cycle that depends on Re_s , the near-wall streaks breakdown (demarking the onset of the nonlinear development stage), and the near-wall Reynolds stress grows explosively; the Reynolds stress remains elevated for part of the cycle before diminishing (yet remaining finite) during the late decelerating portion of the cycle. This process is then repeated indefinitely. The present findings demonstrate that transition to turbulence occurs when the nonlinear development stage begins during the accelerating portion of the cycle. This crucially leads to the diminishing importance of the centreline momentum source, the emergence of a locally accelerating/decelerating internal layer centred about the edge of the Stokes layer and the wall-normal rearrangement of the mean forces prior to the start of the decelerating portion of the cycle. The rearrangement of mean forces culminates in a four layer structure in the mean balance of forces. This is significant on a number of accounts since empirical and theoretical evidence suggests that the formation of a four layer structure is an important characteristic of a self-similar hierarchal structure that underlies logarithmic dependence of the mean velocity profile in steady turbulent wall-bounded flows (Klewicki et al. , J. Fluid Mech. , vol. 638, 2009, pp. 73–93). When the nonlinear development stage begins during the decelerating portion of the cycle (i.e. at Re_s=648 ), a four layer structure is not observed in the mean balance of forces and the flow remains weakly transitional over the entire cycle.},\n bibtype = {article},\n author = {Ebadi, Alireza and White, Christopher M and Pond, Ian and Dubief, Yves},\n doi = {10.1017/jfm.2019.706},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The mean dynamics in oscillatory channel flow is examined to investigate the dynamical mechanisms underlying the transition to turbulence in oscillatory wall-bounded flow. The analyses employ direct numerical simulation data acquired at three Stokes Reynolds numbers: Re_s=648 , 801 and 1009, where the lower Re_s flow is transitional over the entire cycle and the two higher Re_s flows exhibit flow characteristics similar to steady turbulent wall-bounded flow during part of the cycle. The flow evolution over a half-period of oscillation for all three Re_s is as follows: near-wall streamwise velocity streaks develop during the early accelerating portion of the cycle; then at some later point in the cycle that depends on Re_s , the near-wall streaks breakdown (demarking the onset of the nonlinear development stage), and the near-wall Reynolds stress grows explosively; the Reynolds stress remains elevated for part of the cycle before diminishing (yet remaining finite) during the late decelerating portion of the cycle. This process is then repeated indefinitely. The present findings demonstrate that transition to turbulence occurs when the nonlinear development stage begins during the accelerating portion of the cycle. This crucially leads to the diminishing importance of the centreline momentum source, the emergence of a locally accelerating/decelerating internal layer centred about the edge of the Stokes layer and the wall-normal rearrangement of the mean forces prior to the start of the decelerating portion of the cycle. The rearrangement of mean forces culminates in a four layer structure in the mean balance of forces. This is significant on a number of accounts since empirical and theoretical evidence suggests that the formation of a four layer structure is an important characteristic of a self-similar hierarchal structure that underlies logarithmic dependence of the mean velocity profile in steady turbulent wall-bounded flows (Klewicki et al. , J. Fluid Mech. , vol. 638, 2009, pp. 73–93). When the nonlinear development stage begins during the decelerating portion of the cycle (i.e. at Re_s=648 ), a four layer structure is not observed in the mean balance of forces and the flow remains weakly transitional over the entire cycle.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article', event);\">\n    Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keylock,  C., J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 881: 283-312. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article\"\n     onclick=\"log_download('keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019', 'https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2019.779\"\n     onclick=\"log_download('keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019', 'http://doi.org/10.1017/jfm.2019.779', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keylock-turbulenceattheleeboundmaximallynonnormalvortexfilamentsandthedecayofalocaldissipationrate-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Turbulence at the Lee bound: maximally non-normal vortex filaments and the decay of a local dissipation rate},\n type = {article},\n year = {2019},\n keywords = {isotropic turbulence,turbulence theory,vortex dynamics},\n pages = {283-312},\n volume = {881},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112019007791/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {0acc8cd3-af07-36ae-9efd-4e068111d3af},\n created = {2021-04-09T15:24:50.978Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:50.978Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper uses a tight mathematical bound on the degree of the non-normality of the turbulent velocity gradient tensor to classify flow behaviour within vortical regions (where the eigenvalues of the tensor contain a conjugate pair). Structures attaining this bound are preferentially generated where enstrophy exceeds total strain and there is a positive balance between strain production and enstrophy production. Lagrangian analysis of homogeneous, isotropic turbulence shows that attainment of this bound is associated with relatively short durations and an upper limit to the spatial extent of the flow structures that is similar to the Taylor scale. An analysis of the dynamically relevant terms using a recently developed formulation (Keylock, J. Fluid Mech. , vol. 848, 2018, pp. 876–904), highlights the controls on this dynamics. In particular, in high enstrophy regions it is shown that the bound is attained when normal strain decreases rather than when non-normality increases. The near absence of normal total strain results in a source of intermittency in the dynamics of dissipation that is hidden in standard analyses. It is shown that of the two terms that contribute to the non-normal production dynamics, it is the one that is typically smallest in magnitude that is of greatest importance within these  =1 filaments. The typical distance between filament centroids is just less than a Taylor scale, implying a connection to the manner in which flow topology at the Taylor scale explains dissipation at smaller scales.},\n bibtype = {article},\n author = {Keylock, Christopher J},\n doi = {10.1017/jfm.2019.779},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper uses a tight mathematical bound on the degree of the non-normality of the turbulent velocity gradient tensor to classify flow behaviour within vortical regions (where the eigenvalues of the tensor contain a conjugate pair). Structures attaining this bound are preferentially generated where enstrophy exceeds total strain and there is a positive balance between strain production and enstrophy production. Lagrangian analysis of homogeneous, isotropic turbulence shows that attainment of this bound is associated with relatively short durations and an upper limit to the spatial extent of the flow structures that is similar to the Taylor scale. An analysis of the dynamically relevant terms using a recently developed formulation (Keylock, J. Fluid Mech. , vol. 848, 2018, pp. 876–904), highlights the controls on this dynamics. In particular, in high enstrophy regions it is shown that the bound is attained when normal strain decreases rather than when non-normality increases. The near absence of normal total strain results in a source of intermittency in the dynamics of dissipation that is hidden in standard analyses. It is shown that of the two terms that contribute to the non-normal production dynamics, it is the one that is typically smallest in magnitude that is of greatest importance within these  =1 filaments. The typical distance between filament centroids is just less than a Taylor scale, implying a connection to the manner in which flow topology at the Taylor scale explains dissipation at smaller scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602', event);\">\n    Predictive large-eddy-simulation wall modeling via physics-informed neural networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yang,  X., I., A.; Zafar,  S.; Wang,  J.;  and Xiao,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 4(3): 34602. 4 2019.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602\"\n     onclick=\"log_download('yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019', 'https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Predictive large-eddy-simulation wall modeling via physics-informed neural networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.4.034602\"\n     onclick=\"log_download('yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019', 'http://doi.org/10.1103/PhysRevFluids.4.034602', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yang-zafar-wang-xiao-predictivelargeeddysimulationwallmodelingviaphysicsinformedneuralnetworks-2019')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predictive large-eddy-simulation wall modeling via physics-informed neural networks},\n type = {article},\n year = {2019},\n pages = {34602},\n volume = {4},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.4.034602},\n month = {4},\n publisher = {American Physical Society},\n id = {3981fbac-dbaf-3646-acef-d3d887d228e4},\n created = {2021-04-09T15:24:52.317Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:52.317Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {While data-based approaches were found to be useful for subgrid scale (SGS) modeling in Reynolds-averaged Navier-Stokes (RANS) simulations, there have not been many attempts at using machine learning techniques for wall modeling in large-eddy simulations (LESs). Large-eddy simulation differs from RANS simulation in many aspects. For one thing, LES is scale resolving. For another, LES is in and of itself a high-fidelity tool. Because data sets of higher fidelity are in general not frequently accessible or available, this poses additional challenges to data-based modeling in LES. Further, SGS modeling usually needs flow information at only large scales, in contrast with wall modeling, which needs to account for both near-wall small scales and large scales above the wall. In this work we discuss how the above-noted challenges may be addressed when taking a data-based approach for wall modeling. We also show the necessity of incorporating physical insights in model inputs, i.e., using inputs that are inspired by the vertically integrated thin-boundary-layer equations and the eddy population density scalings. We show that the inclusion of the above physics-based considerations would enhance extrapolation capabilities of a neural network to flow conditions that are not within the train data. Being cheap to evaluate and using only channel flow data at Reτ=1000, the trained networks are found to capture the law of the wall at arbitrary Reynolds numbers and outperform the conventional equilibrium model in a nonequilibrium flow.},\n bibtype = {article},\n author = {Yang, X I A and Zafar, S and Wang, J.-X. and Xiao, H},\n doi = {10.1103/PhysRevFluids.4.034602},\n journal = {Physical Review Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  While data-based approaches were found to be useful for subgrid scale (SGS) modeling in Reynolds-averaged Navier-Stokes (RANS) simulations, there have not been many attempts at using machine learning techniques for wall modeling in large-eddy simulations (LESs). Large-eddy simulation differs from RANS simulation in many aspects. For one thing, LES is scale resolving. For another, LES is in and of itself a high-fidelity tool. Because data sets of higher fidelity are in general not frequently accessible or available, this poses additional challenges to data-based modeling in LES. Further, SGS modeling usually needs flow information at only large scales, in contrast with wall modeling, which needs to account for both near-wall small scales and large scales above the wall. In this work we discuss how the above-noted challenges may be addressed when taking a data-based approach for wall modeling. We also show the necessity of incorporating physical insights in model inputs, i.e., using inputs that are inspired by the vertically integrated thin-boundary-layer equations and the eddy population density scalings. We show that the inclusion of the above physics-based considerations would enhance extrapolation capabilities of a neural network to flow conditions that are not within the train data. Being cheap to evaluate and using only channel flow data at Reτ=1000, the trained networks are found to capture the law of the wall at arbitrary Reynolds numbers and outperform the conventional equilibrium model in a nonequilibrium flow.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2018\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2018')\"\n      onkeypress=\"toggleGroup('group_2018')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2018</span>\n      <span class=\"bibbase_group_count\">\n        \n        (40)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018', 'http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262', event);\">\n    Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  McCracken,  M.\n</span>\n\n  \n\n</span>\n\n  . 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262\"\n     onclick=\"log_download('mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018', 'http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1145/3219104.3229262\"\n     onclick=\"log_download('mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018', 'http://doi.org/10.1145/3219104.3229262', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mccracken-artificialneuralnetworksinfluiddynamicsanovelapproachtothenavierstokesequations-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations},\n type = {article},\n year = {2018},\n websites = {http://arxiv.org/abs/1808.06604,http://dx.doi.org/10.1145/3219104.3229262},\n month = {4},\n id = {b3715914-ba21-3486-84e7-5f2b72759a86},\n created = {2021-04-09T15:23:09.679Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:09.679Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynolds number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a sixty-seven percent accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.},\n bibtype = {article},\n author = {McCracken, Megan},\n doi = {10.1145/3219104.3229262}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynolds number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a sixty-seven percent accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-68852-7_9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018', 'http://link.springer.com/10.1007/978-3-319-68852-7_9', event);\">\n    Techniques for 3D-PIV.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Raffel,  M.; Willert,  C., E.; Scarano,  F.; Kähler,  C., J.; Wereley,  S., T.;  and Kompenhans,  J.\n</span>\n\n  \n\n</span>\n\n   2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-68852-7_9\"\n     onclick=\"log_download('raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018', 'http://link.springer.com/10.1007/978-3-319-68852-7_9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Techniques for 3D-PIV [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-319-68852-7_9\"\n     onclick=\"log_download('raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018', 'http://doi.org/10.1007/978-3-319-68852-7_9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('raffel-willert-scarano-khler-wereley-kompenhans-techniquesfor3dpiv-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Techniques for 3D-PIV},\n type = {misc},\n year = {2018},\n source = {Particle Image Velocimetry},\n pages = {309-365},\n websites = {http://link.springer.com/10.1007/978-3-319-68852-7_9},\n publisher = {Springer International Publishing},\n id = {8ee722fd-7e42-38e2-a51f-5d6d07406d7e},\n created = {2021-04-09T15:23:10.924Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:10.924Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {book_section},\n private_publication = {false},\n bibtype = {misc},\n author = {Raffel, Markus and Willert, Christian E and Scarano, Fulvio and Kähler, Christian J and Wereley, Steven T and Kompenhans, Jürgen},\n doi = {10.1007/978-3-319-68852-7_9}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://repositorio.ufpe.br/handle/123456789/31035\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018', 'https://repositorio.ufpe.br/handle/123456789/31035', event);\">\n    Hierarchical models for financial markets and turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Correa,  W., O., S.\n</span>\n\n  \n\n</span>\n\n  4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://repositorio.ufpe.br/handle/123456789/31035\"\n     onclick=\"log_download('correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018', 'https://repositorio.ufpe.br/handle/123456789/31035', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Hierarchical models for financial markets and turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('correa-hierarchicalmodelsforfinancialmarketsandturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Hierarchical models for financial markets and turbulence},\n type = {misc},\n year = {2018},\n websites = {https://repositorio.ufpe.br/handle/123456789/31035},\n month = {4},\n publisher = {Universidade Federal de Pernambuco},\n id = {8417a4a2-5d9f-349f-ad47-0263483f4ee4},\n created = {2021-04-09T15:23:14.900Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:14.900Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {thesis},\n private_publication = {false},\n abstract = {CAPES},\n bibtype = {misc},\n author = {Correa, William Oswaldo Sosa}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  CAPES\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.research-collection.ethz.ch/handle/20.500.11850/279200\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018', 'https://www.research-collection.ethz.ch/handle/20.500.11850/279200', event);\">\n    Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Huhn,  F.; Schröder,  A.; Schanz,  D.; Gesemann,  S.;  and Manovski,  P.\n</span>\n\n  \n\n</span>\n\n  In Rösgen,  T., editor(s), <i>18th International Symposium on Flow Visualization (ISFV18)</i>, 4 2018. ETH Zurich\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.research-collection.ethz.ch/handle/20.500.11850/279200\"\n     onclick=\"log_download('huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018', 'https://www.research-collection.ethz.ch/handle/20.500.11850/279200', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.3929/ETHZ-B-000279200\"\n     onclick=\"log_download('huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018', 'http://doi.org/10.3929/ETHZ-B-000279200', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('huhn-schrder-schanz-gesemann-manovski-estimationoftimeresolved3dpressurefieldsinanimpingingjetflowfromdenselagrangianparticletracking-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Estimation of time-resolved 3D pressure fields in an impinging jet flow from dense Lagrangian particle tracking},\n type = {inproceedings},\n year = {2018},\n websites = {https://www.research-collection.ethz.ch/handle/20.500.11850/279200},\n month = {4},\n publisher = {ETH Zurich},\n id = {a51771b0-62fb-346c-bdc2-bb3045c1a60b},\n created = {2021-04-09T15:23:17.163Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:17.163Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Huhn, F and Schröder, Andreas and Schanz, D and Gesemann, S and Manovski, P},\n editor = {Rösgen, Thomas},\n doi = {10.3929/ETHZ-B-000279200},\n booktitle = {18th International Symposium on Flow Visualization (ISFV18)}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://doi.wiley.com/10.1002/fld.4405\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018', 'http://doi.wiley.com/10.1002/fld.4405', event);\">\n    Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Obeidat,  A.;  and Bordas,  S., P., A.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal for Numerical Methods in Fluids</i>, 86(1): 1-19. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://doi.wiley.com/10.1002/fld.4405\"\n     onclick=\"log_download('obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018', 'http://doi.wiley.com/10.1002/fld.4405', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/fld.4405\"\n     onclick=\"log_download('obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018', 'http://doi.org/10.1002/fld.4405', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('obeidat-bordas-threedimensionalremeshedsmoothedparticlehydrodynamicsforthesimulationofisotropicturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Three-dimensional remeshed smoothed particle hydrodynamics for the simulation of isotropic turbulence},\n type = {article},\n year = {2018},\n keywords = {remesh smoothed particle hydrodynamics,three-dimensional isotropic decaying turbulence,turbulent flow},\n pages = {1-19},\n volume = {86},\n websites = {http://doi.wiley.com/10.1002/fld.4405},\n month = {4},\n publisher = {Wiley-Blackwell},\n id = {51235906-1632-379f-8de3-6d3c18134f8b},\n created = {2021-04-09T15:23:24.693Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:24.693Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Copyright © 2017 John Wiley &amp; Sons, Ltd. We present a remeshed particle-mesh method for the simulation of three-dimensional compressible turbulent flow. The method is related to the meshfree smoothed particle hydrodynamics method, but the present method introduces a mesh for efficient calculation of the pressure gradient, and laminar and turbulent diffusion. In addition, the mesh is used to remesh (reorganise uniformly) the particles to ensure a regular particle distribution and convergence of the method. The accuracy of the presented methodology is tested for a number of benchmark problems involving two- and three-dimensional Taylor-Green flow, thin double shear layer, and three-dimensional isotropic turbulence. Two models were implemented, direct numerical simulations, and Smagorinsky model. Taking advantage of the Lagrangian advection, and the finite difference efficiency, the method is capable of providing quality simulations while maintaining its robustness and versatility.},\n bibtype = {article},\n author = {Obeidat, Anas and Bordas, Stéphane P A},\n doi = {10.1002/fld.4405},\n journal = {International Journal for Numerical Methods in Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Copyright © 2017 John Wiley & Sons, Ltd. We present a remeshed particle-mesh method for the simulation of three-dimensional compressible turbulent flow. The method is related to the meshfree smoothed particle hydrodynamics method, but the present method introduces a mesh for efficient calculation of the pressure gradient, and laminar and turbulent diffusion. In addition, the mesh is used to remesh (reorganise uniformly) the particles to ensure a regular particle distribution and convergence of the method. The accuracy of the presented methodology is tested for a number of benchmark problems involving two- and three-dimensional Taylor-Green flow, thin double shear layer, and three-dimensional isotropic turbulence. Two models were implemented, direct numerical simulations, and Smagorinsky model. Taking advantage of the Lagrangian advection, and the finite difference efficiency, the method is capable of providing quality simulations while maintaining its robustness and versatility.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article', event);\">\n    Dependence of small-scale energetics on large scales in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Howland,  M., F.;  and Yang,  X., I., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 852: 641-662. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article\"\n     onclick=\"log_download('howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dependence of small-scale energetics on large scales in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.554\"\n     onclick=\"log_download('howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018', 'http://doi.org/10.1017/jfm.2018.554', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('howland-yang-dependenceofsmallscaleenergeticsonlargescalesinturbulentflows-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dependence of small-scale energetics on large scales in turbulent flows},\n type = {article},\n year = {2018},\n keywords = {turbulence modelling,turbulence theory,turbulent boundary layers},\n pages = {641-662},\n volume = {852},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018005542/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {20a15fd0-0e26-3049-909b-f48f7d0eab96},\n created = {2021-04-09T15:23:30.767Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:30.767Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In a turbulent flow, small- and large-scale fluid motions are coupled. In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. The evidence suggests that the existence of nonlinear interscale interactions in the form of amplitude modulation does not rely on the presence of a non-penetrating boundary, but on the presence of a range of viscosity-dominated scales and a range of inertial-dominated scales.},\n bibtype = {article},\n author = {Howland, M F and Yang, X I A},\n doi = {10.1017/jfm.2018.554},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In a turbulent flow, small- and large-scale fluid motions are coupled. In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. The evidence suggests that the existence of nonlinear interscale interactions in the form of amplitude modulation does not rely on the presence of a non-penetrating boundary, but on the presence of a range of viscosity-dominated scales and a range of inertial-dominated scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616', event);\">\n    Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ranjan,  R.;  and Menon,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Turbulence</i>, 19(4): 334-364. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616\"\n     onclick=\"log_download('ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/14685248.2018.1438616\"\n     onclick=\"log_download('ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018', 'http://doi.org/10.1080/14685248.2018.1438616', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ranjan-menon-vorticitybackscatterandcountergradienttransportpredictionsusingtwolevelsimulationofturbulentflows-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows},\n type = {article},\n year = {2018},\n keywords = {Two-level simulation,backscatter,large eddy simulation,turbulent transport,vorticity},\n pages = {334-364},\n volume = {19},\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1438616},\n month = {4},\n publisher = {Taylor &amp; Francis},\n id = {b6889d9f-7732-377a-8249-5a2127ff4b74},\n created = {2021-04-09T15:23:31.280Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:31.280Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {ABSTRACTThe two-level simulation (TLS) method evolves both the large-and the small-scale fields in a two-scale approach and has shown good predictive capabilities in both isotropic and wall-bounded...},\n bibtype = {article},\n author = {Ranjan, R and Menon, S},\n doi = {10.1080/14685248.2018.1438616},\n journal = {Journal of Turbulence},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  ABSTRACTThe two-level simulation (TLS) method evolves both the large-and the small-scale fields in a two-scale approach and has shown good predictive capabilities in both isotropic and wall-bounded...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://arc.aiaa.org/doi/10.2514/6.2018-0594\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018', 'https://arc.aiaa.org/doi/10.2514/6.2018-0594', event);\">\n    Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Doronina,  O.; Christopher,  J.; Towery,  C., A., Z.; Hamlington,  P.;  and Dahm,  W., J., A.\n</span>\n\n  \n\n</span>\n\n  In <i>2018 AIAA Aerospace Sciences Meeting</i>, 4 2018. American Institute of Aeronautics and Astronautics\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://arc.aiaa.org/doi/10.2514/6.2018-0594\"\n     onclick=\"log_download('doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018', 'https://arc.aiaa.org/doi/10.2514/6.2018-0594', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2018-0594\"\n     onclick=\"log_download('doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018', 'http://doi.org/10.2514/6.2018-0594', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('doronina-christopher-towery-hamlington-dahm-autonomicclosureforturbulentflowsusingapproximatebayesiancomputation-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Autonomic Closure for Turbulent Flows Using Approximate Bayesian Computation},\n type = {inproceedings},\n year = {2018},\n websites = {https://arc.aiaa.org/doi/10.2514/6.2018-0594},\n month = {4},\n publisher = {American Institute of Aeronautics and Astronautics},\n id = {c66ecc3c-d9e9-3b91-acdb-d8a24046714d},\n created = {2021-04-09T15:23:32.376Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:32.376Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Doronina, Olga and Christopher, Jason and Towery, Colin A Z and Hamlington, Peter and Dahm, Werner J A},\n doi = {10.2514/6.2018-0594},\n booktitle = {2018 AIAA Aerospace Sciences Meeting}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-wang-he-thespanwisespectrainwallboundedturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10409-017-0731-2\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-wang-he-thespanwisespectrainwallboundedturbulence-2018', 'http://link.springer.com/10.1007/s10409-017-0731-2', event);\">\n    The spanwise spectra in wall-bounded turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  H.; Wang,  S.;  and He,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Acta Mechanica Sinica</i>, 34(3): 452-461. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10409-017-0731-2\"\n     onclick=\"log_download('wang-wang-he-thespanwisespectrainwallboundedturbulence-2018', 'http://link.springer.com/10.1007/s10409-017-0731-2', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The spanwise spectra in wall-bounded turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10409-017-0731-2\"\n     onclick=\"log_download('wang-wang-he-thespanwisespectrainwallboundedturbulence-2018', 'http://doi.org/10.1007/s10409-017-0731-2', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-wang-he-thespanwisespectrainwallboundedturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-wang-he-thespanwisespectrainwallboundedturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The spanwise spectra in wall-bounded turbulence},\n type = {article},\n year = {2018},\n keywords = {Inner/outer peak,Scale separation,Streamwise/spanwise spectra,Wall-bounded turbulence},\n pages = {452-461},\n volume = {34},\n websites = {http://link.springer.com/10.1007/s10409-017-0731-2},\n month = {4},\n publisher = {The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences},\n id = {bb01c65f-b97c-3004-b791-211a96563468},\n created = {2021-04-09T15:23:37.690Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:37.690Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Hong-Ping and Wang, Shi-Zhao and He, Guo-Wei},\n doi = {10.1007/s10409-017-0731-2},\n journal = {Acta Mechanica Sinica},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018', 'https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941', event);\">\n    Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Discetti,  S.; Raiola,  M.;  and Ianiro,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 93: 119-130. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941\"\n     onclick=\"log_download('discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018', 'https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.expthermflusci.2017.12.011\"\n     onclick=\"log_download('discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018', 'http://doi.org/10.1016/j.expthermflusci.2017.12.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('discetti-raiola-ianiro-estimationoftimeresolvedturbulentfieldsthroughcorrelationofnontimeresolvedfieldmeasurementsandtimeresolvedpointmeasurements-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Estimation of time-resolved turbulent fields through correlation of non-time-resolved field measurements and time-resolved point measurements},\n type = {article},\n year = {2018},\n keywords = {Dynamic estimation,Linear stochastic estimation,PIV,Proper orthogonal decomposition},\n pages = {119-130},\n volume = {93},\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177717303941,https://linkinghub.elsevier.com/retrieve/pii/S0894177717303941},\n month = {4},\n publisher = {Elsevier},\n id = {cdac6288-8a17-349d-91de-b4fe36f68248},\n created = {2021-04-09T15:23:40.778Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:40.778Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {A method for the estimation of time-resolved turbulent fields from the combination of non-time-resolved field measurements and time-resolved point measurements is proposed. The approach poses its fundaments on a stochastic estimation based on the Proper Orthogonal Decomposition (POD) of the field measurements and of the time-resolved point measurements. The correlation between the temporal modes of the field measurements and the temporal modes of the point measurements at synchronized instants is evaluated; this correlation is extended to the “out-of-sample” time instants for the field measurements, i.e. those in which field data are not available. In the “out-of-sample” instants, POD modes time coefficients are estimated and the flow fields are reconstructed. The proposed method extends the work by Hosseini et al. (Experiments in fluids, 56, 2015) by proposing a truncation criterion which allows removing the uncorrelated part of the signal from the reconstruction of the flow fields. The truncation is fundamental in case of turbulent flow fields, in which a great wealth of scales is involved, thus reducing the correlation between the probe signal and the field measurements. The threshold selection is based on the random distribution of the uncorrelated signal. Additionally, the selection of the probe time-span to perform the POD analysis on the probe signal is discussed. The method is validated with a synthetic test case and an experimental one. A Direct Numerical Simulation database of a channel flow is selected since its spectral richness is expected to represent a significant challenge for this method. This dataset allows isolating the effects of correlation between field measurements and point measurements, removing issues connected to noise contamination or to the finite spatial resolution which would inevitably affect experimental data. The experimental test case is the wake-flow behind a high-angle-of-attack airfoil with a relatively small number of samples, affected by significant noise. The quality of the dynamic estimation is found to be affected by the noise contamination of the data and by the poor convergence of the POD modes, which add on the effect of the probe location, i.e. on the correlation between probe events and flow features. The squared correlation coefficient between reconstructed data and in-sample data is proposed as an assessment of the flow fields estimation quality. The use of the squared correlation coefficient directly on in-sample data is allowed by the truncation itself.},\n bibtype = {article},\n author = {Discetti, Stefano and Raiola, Marco and Ianiro, Andrea},\n doi = {10.1016/j.expthermflusci.2017.12.011},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A method for the estimation of time-resolved turbulent fields from the combination of non-time-resolved field measurements and time-resolved point measurements is proposed. The approach poses its fundaments on a stochastic estimation based on the Proper Orthogonal Decomposition (POD) of the field measurements and of the time-resolved point measurements. The correlation between the temporal modes of the field measurements and the temporal modes of the point measurements at synchronized instants is evaluated; this correlation is extended to the “out-of-sample” time instants for the field measurements, i.e. those in which field data are not available. In the “out-of-sample” instants, POD modes time coefficients are estimated and the flow fields are reconstructed. The proposed method extends the work by Hosseini et al. (Experiments in fluids, 56, 2015) by proposing a truncation criterion which allows removing the uncorrelated part of the signal from the reconstruction of the flow fields. The truncation is fundamental in case of turbulent flow fields, in which a great wealth of scales is involved, thus reducing the correlation between the probe signal and the field measurements. The threshold selection is based on the random distribution of the uncorrelated signal. Additionally, the selection of the probe time-span to perform the POD analysis on the probe signal is discussed. The method is validated with a synthetic test case and an experimental one. A Direct Numerical Simulation database of a channel flow is selected since its spectral richness is expected to represent a significant challenge for this method. This dataset allows isolating the effects of correlation between field measurements and point measurements, removing issues connected to noise contamination or to the finite spatial resolution which would inevitably affect experimental data. The experimental test case is the wake-flow behind a high-angle-of-attack airfoil with a relatively small number of samples, affected by significant noise. The quality of the dynamic estimation is found to be affected by the noise contamination of the data and by the poor convergence of the POD modes, which add on the effect of the probe location, i.e. on the correlation between probe events and flow features. The squared correlation coefficient between reconstructed data and in-sample data is proposed as an assessment of the flow fields estimation quality. The use of the squared correlation coefficient directly on in-sample data is allowed by the truncation itself.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018', 'http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22', event);\">\n    3D Fluid Flow Estimation with Integrated Particle Reconstruction.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lasinger,  K.; Vogel,  C.; Pock,  T.;  and Schindler,  K.\n</span>\n\n  \n\n</span>\n\n  In <i>40th German Conference on Pattern Recognition, GCPR 2018</i>, pages 315-332, 4 2018. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22\"\n     onclick=\"log_download('lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018', 'http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"3D Fluid Flow Estimation with Integrated Particle Reconstruction [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-030-12939-2_22\"\n     onclick=\"log_download('lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018', 'http://doi.org/10.1007/978-3-030-12939-2_22', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lasinger-vogel-pock-schindler-3dfluidflowestimationwithintegratedparticlereconstruction-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {3D Fluid Flow Estimation with Integrated Particle Reconstruction},\n type = {inproceedings},\n year = {2018},\n pages = {315-332},\n websites = {http://arxiv.org/abs/1804.03037,http://link.springer.com/10.1007/978-3-030-12939-2_22},\n month = {4},\n id = {494766c9-e3b7-399f-9215-806df54ff32a},\n created = {2021-04-09T15:23:41.951Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:41.951Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps: first, a per-frame reconstruction of the particles, usually in the form of soft occupancy likelihoods in a voxel representation; followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model explicitly reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-resolution input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over a recent baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of state-of-the-art tracking-based methods that require much longer sequences.},\n bibtype = {inproceedings},\n author = {Lasinger, Katrin and Vogel, Christoph and Pock, Thomas and Schindler, Konrad},\n doi = {10.1007/978-3-030-12939-2_22},\n booktitle = {40th German Conference on Pattern Recognition, GCPR 2018}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps: first, a per-frame reconstruction of the particles, usually in the form of soft occupancy likelihoods in a voxel representation; followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model explicitly reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-resolution input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over a recent baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of state-of-the-art tracking-based methods that require much longer sequences.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018', 'https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918', event);\">\n    Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  J., Z.; Fang,  L.; Shao,  L.;  and Lu,  L., P.\n</span>\n\n  \n\n</span>\n\n  <i>Physics Letters A</i>, 382(25): 1665-1671. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918\"\n     onclick=\"log_download('wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018', 'https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.physleta.2018.04.021\"\n     onclick=\"log_download('wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018', 'http://doi.org/10.1016/j.physleta.2018.04.021', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-fang-shao-lu-theoriesandapplicationsofsecondordercorrelationoflongitudinalvelocityincrementsatthreepointsinisotropicturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Theories and applications of second-order correlation of longitudinal velocity increments at three points in isotropic turbulence},\n type = {article},\n year = {2018},\n pages = {1665-1671},\n volume = {382},\n websites = {https://www.sciencedirect.com/science/article/pii/S0375960118303918,https://linkinghub.elsevier.com/retrieve/pii/S0375960118303918},\n month = {4},\n publisher = {North-Holland},\n id = {f51f7ca2-fc3f-3dcb-9662-759d1235c5ba},\n created = {2021-04-09T15:23:42.918Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:42.918Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In order to introduce new physics to traditional two-point correlations, we define the second-order correlation of longitudinal velocity increments at three points and obtain the analytical expressions in isotropic turbulence. By introducing the Kolmogorov 4/5 law, this three-point correlation explicitly contains velocity second- and third-order moments, which correspond to energy and energy transfer respectively. The combination of them then shows additional information of non-equilibrium turbulence by comparing to two-point correlations. Moreover, this three-point correlation shows the underlying inconsistency between numerical interpolation and three-point scaling law in numerical calculations, and inspires a preliminary model to correct this problem in isotropic turbulence.},\n bibtype = {article},\n author = {Wu, J Z and Fang, L and Shao, L and Lu, L P},\n doi = {10.1016/j.physleta.2018.04.021},\n journal = {Physics Letters A},\n number = {25}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In order to introduce new physics to traditional two-point correlations, we define the second-order correlation of longitudinal velocity increments at three points and obtain the analytical expressions in isotropic turbulence. By introducing the Kolmogorov 4/5 law, this three-point correlation explicitly contains velocity second- and third-order moments, which correspond to energy and energy transfer respectively. The combination of them then shows additional information of non-equilibrium turbulence by comparing to two-point correlations. Moreover, this three-point correlation shows the underlying inconsistency between numerical interpolation and three-point scaling law in numerical calculations, and inspires a preliminary model to correct this problem in isotropic turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055', event);\">\n    Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kopyev,  A., V.;  and Zybin,  K., P.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Turbulence</i>, 19(9): 717-730. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055\"\n     onclick=\"log_download('kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/14685248.2018.1511055\"\n     onclick=\"log_download('kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018', 'http://doi.org/10.1080/14685248.2018.1511055', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kopyev-zybin-exactresultformixedtripletwopointcorrelationsofvelocityandvelocitygradientsinisotropicturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Exact result for mixed triple two-point correlations of velocity and velocity gradients in isotropic turbulence},\n type = {article},\n year = {2018},\n keywords = {Isotropic turbulence,correlators,four-fifths law,incompressibility},\n pages = {717-730},\n volume = {19},\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1511055},\n month = {4},\n publisher = {Taylor &amp; Francis},\n id = {ea64be6e-fa7d-30d9-97b6-f2a6881023cd},\n created = {2021-04-09T15:23:43.536Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:43.536Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {ABSTRACTOn the grounds of Kolmogorov&#x27;s 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are deriv...},\n bibtype = {article},\n author = {Kopyev, A V and Zybin, K P},\n doi = {10.1080/14685248.2018.1511055},\n journal = {Journal of Turbulence},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  ABSTRACTOn the grounds of Kolmogorov's 4/5 law analytical relations for triple two-point correlations of velocity and velocity gradients in homogeneous isotropic incompressible turbulence are deriv...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ballouz-ouellette-tensorgeometryintheturbulentcascade-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ballouz-ouellette-tensorgeometryintheturbulentcascade-2018', 'https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article', event);\">\n    Tensor geometry in the turbulent cascade.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ballouz,  J., G.;  and Ouellette,  N., T.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 835: 1048-1064. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article\"\n     onclick=\"log_download('ballouz-ouellette-tensorgeometryintheturbulentcascade-2018', 'https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Tensor geometry in the turbulent cascade [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2017.802\"\n     onclick=\"log_download('ballouz-ouellette-tensorgeometryintheturbulentcascade-2018', 'http://doi.org/10.1017/jfm.2017.802', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ballouz-ouellette-tensorgeometryintheturbulentcascade-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>9 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ballouz-ouellette-tensorgeometryintheturbulentcascade-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Tensor geometry in the turbulent cascade},\n type = {article},\n year = {2018},\n keywords = {turbulence theory,turbulent flows},\n pages = {1048-1064},\n volume = {835},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017008023/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {10073d10-c167-3626-bd0c-6712d69b8083},\n created = {2021-04-09T15:23:44.057Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:44.057Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The defining characteristic of highly turbulent flows is the net directed transport of energy from the injection scales to the dissipation scales. This cascade is typically described in Fourier space, obscuring its connection to the mechanics of the flow. Here, we recast the energy cascade in mechanical terms, noting that for some scales to transfer energy to others, they must do mechanical work on them. This work can be expressed as the inner product of a turbulent stress and a rate of strain. But, as with all inner products, the relative alignment of these two tensors matters, and determines how strong the energy transfer will be. We show that this tensor alignment behaves very differently in two and three dimensions; in particular, the tensor eigenvalues affect the inner product in very different ways. By comparing the observed energy flux to the maximum possible if the tensors were in perfect alignment, we define an efficiency for the energy cascade. Using data from a direct numerical simulation of isotropic turbulence, we show that this efficiency is perhaps surprisingly low, with an average value of approximately 25 % in the inertial range, although it is spatially heterogeneous. Our results have implications for how the stress and strain-rate magnitudes influence the flux of energy between scales, and may help to explain why the energy cascades in two and three dimensions are different.},\n bibtype = {article},\n author = {Ballouz, Joseph G and Ouellette, Nicholas T},\n doi = {10.1017/jfm.2017.802},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The defining characteristic of highly turbulent flows is the net directed transport of energy from the injection scales to the dissipation scales. This cascade is typically described in Fourier space, obscuring its connection to the mechanics of the flow. Here, we recast the energy cascade in mechanical terms, noting that for some scales to transfer energy to others, they must do mechanical work on them. This work can be expressed as the inner product of a turbulent stress and a rate of strain. But, as with all inner products, the relative alignment of these two tensors matters, and determines how strong the energy transfer will be. We show that this tensor alignment behaves very differently in two and three dimensions; in particular, the tensor eigenvalues affect the inner product in very different ways. By comparing the observed energy flux to the maximum possible if the tensors were in perfect alignment, we define an efficiency for the energy cascade. Using data from a direct numerical simulation of isotropic turbulence, we show that this efficiency is perhaps surprisingly low, with an average value of approximately 25 % in the inertial range, although it is spatially heterogeneous. Our results have implications for how the stress and strain-rate magnitudes influence the flux of energy between scales, and may help to explain why the energy cascades in two and three dimensions are different.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5055752\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018', 'http://aip.scitation.org/doi/10.1063/1.5055752', event);\">\n    Modeling three-dimensional scalar mixing with forced one-dimensional turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Giddey,  V.; Meyer,  D., W.;  and Jenny,  P.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 30(12): 125103. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5055752\"\n     onclick=\"log_download('giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018', 'http://aip.scitation.org/doi/10.1063/1.5055752', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Modeling three-dimensional scalar mixing with forced one-dimensional turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5055752\"\n     onclick=\"log_download('giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018', 'http://doi.org/10.1063/1.5055752', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('giddey-meyer-jenny-modelingthreedimensionalscalarmixingwithforcedonedimensionalturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Modeling three-dimensional scalar mixing with forced one-dimensional turbulence},\n type = {article},\n year = {2018},\n keywords = {flow simulation,numerical analysis,turbulence},\n pages = {125103},\n volume = {30},\n websites = {http://aip.scitation.org/doi/10.1063/1.5055752},\n month = {4},\n publisher = {AIP Publishing LLC},\n id = {10740e25-ecd9-3e7a-99bf-da8defaee44c},\n created = {2021-04-09T15:23:47.440Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:47.440Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We study the capability of the One-Dimensional-Turbulence (ODT) model to simulate the turbulent transport and mixing of multiple passive scalars in homogeneous isotropic stationary turbulence. To t...},\n bibtype = {article},\n author = {Giddey, Valentin and Meyer, Daniel W and Jenny, Patrick},\n doi = {10.1063/1.5055752},\n journal = {Physics of Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We study the capability of the One-Dimensional-Turbulence (ODT) model to simulate the turbulent transport and mixing of multiple passive scalars in homogeneous isotropic stationary turbulence. To t...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018', 'http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X', event);\">\n    Visibility graph analysis of wall turbulence time-series.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Iacobello,  G.; Scarsoglio,  S.;  and Ridolfi,  L.\n</span>\n\n  \n\n</span>\n\n  <i>Physics Letters A</i>, 382(1): 1-11. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X\"\n     onclick=\"log_download('iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018', 'http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Visibility graph analysis of wall turbulence time-series [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.physleta.2017.10.027\"\n     onclick=\"log_download('iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018', 'http://doi.org/10.1016/j.physleta.2017.10.027', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('iacobello-scarsoglio-ridolfi-visibilitygraphanalysisofwallturbulencetimeseries-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Visibility graph analysis of wall turbulence time-series},\n type = {article},\n year = {2018},\n keywords = {Complex networks,Direct numerical simulations,Time-series analysis,Turbulent channel flows,Visibility graph},\n pages = {1-11},\n volume = {382},\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S037596011731023X,https://www.sciencedirect.com/science/article/pii/S037596011731023X,https://linkinghub.elsevier.com/retrieve/pii/S037596011731023X},\n month = {4},\n publisher = {North-Holland},\n id = {117a628a-3309-3870-811a-5f4e5b726b7e},\n created = {2021-04-09T15:23:49.217Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:49.217Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.},\n bibtype = {article},\n author = {Iacobello, Giovanni and Scarsoglio, Stefania and Ridolfi, Luca},\n doi = {10.1016/j.physleta.2017.10.027},\n journal = {Physics Letters A},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article', event);\">\n    Tracer particle dispersion around elementary flow patterns.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Goudar,  M., V.;  and Elsinga,  G., E.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 843: 872-897. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article\"\n     onclick=\"log_download('goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Tracer particle dispersion around elementary flow patterns [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.146\"\n     onclick=\"log_download('goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018', 'http://doi.org/10.1017/jfm.2018.146', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>5 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('goudar-elsinga-tracerparticledispersionaroundelementaryflowpatterns-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Tracer particle dispersion around elementary flow patterns},\n type = {article},\n year = {2018},\n keywords = {topological fluid dynamics,turbulence theory,turbulent mixing},\n pages = {872-897},\n volume = {843},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018001465/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {20461682-0462-316b-935f-97d5994ffecc},\n created = {2021-04-09T15:23:50.515Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:50.515Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The motion of tracer particles is kinematically simulated around three elementary flow patterns; a Burgers vortex, a shear-layer structure with coincident vortices and a node-saddle topology. These patterns are representative for their broader class of coherent structures in turbulence. Therefore, examining the dispersion in these elementary structures can improve the general understanding of turbulent dispersion at short time scales. The shear-layer structure and the node-saddle topology exhibit similar pair dispersion statistics compared to the actual turbulent flow for times up to 3-10[STIX]x1D70F_[STIX]x1D702 , where, [STIX]x1D70F_[STIX]x1D702 is the Kolmogorov time scale. However, oscillations are observed for the pair dispersion in the Burgers vortex. Furthermore, all three structures exhibit Batchelor’s scaling. Richardson’s scaling was observed for initial particle pair separations r_0 4[STIX]x1D702 for the shear-layer topology and the node-saddle topology and was related to the formation of the particle sheets. Moreover, the material line orientation statistics for the shear-layer and node-saddle topology are similar to the actual turbulent flow statistics, up to at least 4[STIX]x1D70F_[STIX]x1D702 . However, only the shear-layer structure can explain the non-perpendicular preferential alignment between the material lines and the direction of the most compressive strain, as observed in actual turbulence. This behaviour is due to shear-layer vorticity, which rotates the particle sheet generated by straining motions and causes the particles to spread in the direction of compressive strain also. The material line statistics in the Burgers vortex clearly differ, due to the presence of two compressive principal straining directions as opposed to two stretching directions in the shear-layer structure and the node-saddle topology. The tetrad dispersion statistics for the shear-layer structure qualitatively capture the behaviour of the shape parameters as observed in actual turbulence. In particular, it shows the initial development towards planar shapes followed by a return to more volumetric tetrads at approximately 10[STIX]x1D70F_[STIX]x1D702 , which is associated with the particles approaching the vortices inside the shear layer. However, a large deviation is observed in such behaviour in the node-saddle topology and the Burgers vortex. It is concluded that the results for the Burgers vortex deviated the most from actual turbulence and the node-saddle topology dispersion exhibits some similarities, but does not capture the geometrical features associated with material lines and tetrad dispersion. Finally, the dispersion around the shear-layer structure shows many quantitative (until 2– 4[STIX]x1D70F_[STIX]x1D702 ) and qualitative (until 20[STIX]x1D70F_[STIX]x1D702 ) similarities to the actual turbulence.},\n bibtype = {article},\n author = {Goudar, Manu V and Elsinga, Gerrit E},\n doi = {10.1017/jfm.2018.146},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The motion of tracer particles is kinematically simulated around three elementary flow patterns; a Burgers vortex, a shear-layer structure with coincident vortices and a node-saddle topology. These patterns are representative for their broader class of coherent structures in turbulence. Therefore, examining the dispersion in these elementary structures can improve the general understanding of turbulent dispersion at short time scales. The shear-layer structure and the node-saddle topology exhibit similar pair dispersion statistics compared to the actual turbulent flow for times up to 3-10[STIX]x1D70F_[STIX]x1D702 , where, [STIX]x1D70F_[STIX]x1D702 is the Kolmogorov time scale. However, oscillations are observed for the pair dispersion in the Burgers vortex. Furthermore, all three structures exhibit Batchelor’s scaling. Richardson’s scaling was observed for initial particle pair separations r_0 4[STIX]x1D702 for the shear-layer topology and the node-saddle topology and was related to the formation of the particle sheets. Moreover, the material line orientation statistics for the shear-layer and node-saddle topology are similar to the actual turbulent flow statistics, up to at least 4[STIX]x1D70F_[STIX]x1D702 . However, only the shear-layer structure can explain the non-perpendicular preferential alignment between the material lines and the direction of the most compressive strain, as observed in actual turbulence. This behaviour is due to shear-layer vorticity, which rotates the particle sheet generated by straining motions and causes the particles to spread in the direction of compressive strain also. The material line statistics in the Burgers vortex clearly differ, due to the presence of two compressive principal straining directions as opposed to two stretching directions in the shear-layer structure and the node-saddle topology. The tetrad dispersion statistics for the shear-layer structure qualitatively capture the behaviour of the shape parameters as observed in actual turbulence. In particular, it shows the initial development towards planar shapes followed by a return to more volumetric tetrads at approximately 10[STIX]x1D70F_[STIX]x1D702 , which is associated with the particles approaching the vortices inside the shear layer. However, a large deviation is observed in such behaviour in the node-saddle topology and the Burgers vortex. It is concluded that the results for the Burgers vortex deviated the most from actual turbulence and the node-saddle topology dispersion exhibits some similarities, but does not capture the geometrical features associated with material lines and tetrad dispersion. Finally, the dispersion around the shear-layer structure shows many quantitative (until 2– 4[STIX]x1D70F_[STIX]x1D702 ) and qualitative (until 20[STIX]x1D70F_[STIX]x1D702 ) similarities to the actual turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1804.09269\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018', 'http://arxiv.org/abs/1804.09269', event);\">\n    A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mohan,  A., T.;  and Gaitonde,  D., V.\n</span>\n\n  \n\n</span>\n\n  . 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1804.09269\"\n     onclick=\"log_download('mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018', 'http://arxiv.org/abs/1804.09269', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mohan-gaitonde-adeeplearningbasedapproachtoreducedordermodelingforturbulentflowcontrolusinglstmneuralnetworks-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks},\n type = {article},\n year = {2018},\n websites = {http://arxiv.org/abs/1804.09269},\n month = {4},\n id = {3506f98e-a070-3139-824c-288b57b0e8d1},\n created = {2021-04-09T15:23:51.617Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:51.617Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Reduced Order Modeling (ROM) for engineering applications has been a major research focus in the past few decades due to the unprecedented physical insight into turbulence offered by high-fidelity CFD. The primary goal of a ROM is to model the key physics/features of a flow-field without computing the full Navier-Stokes (NS) equations. This is accomplished by projecting the high-dimensional dynamics to a low-dimensional subspace, typically utilizing dimensionality reduction techniques like Proper Orthogonal Decomposition (POD), coupled with Galerkin projection. In this work, we demonstrate a deep learning based approach to build a ROM using the POD basis of canonical DNS datasets, for turbulent flow control applications. We find that a type of Recurrent Neural Network, the Long Short Term Memory (LSTM) which has been primarily utilized for problems like speech modeling and language translation, shows attractive potential in modeling temporal dynamics of turbulence. Additionally, we introduce the Hurst Exponent as a tool to study LSTM behavior for non-stationary data, and uncover useful characteristics that may aid ROM development for a variety of applications.},\n bibtype = {article},\n author = {Mohan, Arvind T and Gaitonde, Datta V}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Reduced Order Modeling (ROM) for engineering applications has been a major research focus in the past few decades due to the unprecedented physical insight into turbulence offered by high-fidelity CFD. The primary goal of a ROM is to model the key physics/features of a flow-field without computing the full Navier-Stokes (NS) equations. This is accomplished by projecting the high-dimensional dynamics to a low-dimensional subspace, typically utilizing dimensionality reduction techniques like Proper Orthogonal Decomposition (POD), coupled with Galerkin projection. In this work, we demonstrate a deep learning based approach to build a ROM using the POD basis of canonical DNS datasets, for turbulent flow control applications. We find that a type of Recurrent Neural Network, the Long Short Term Memory (LSTM) which has been primarily utilized for problems like speech modeling and language translation, shows attractive potential in modeling temporal dynamics of turbulence. Additionally, we introduce the Hurst Exponent as a tool to study LSTM behavior for non-stationary data, and uncover useful characteristics that may aid ROM development for a variety of applications.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article', event);\">\n    Estimating large-scale structures in wall turbulence using linear models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Illingworth,  S., J.; Monty,  J., P.;  and Marusic,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 842: 146-162. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article\"\n     onclick=\"log_download('illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Estimating large-scale structures in wall turbulence using linear models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.129\"\n     onclick=\"log_download('illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018', 'http://doi.org/10.1017/jfm.2018.129', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>4 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('illingworth-monty-marusic-estimatinglargescalestructuresinwallturbulenceusinglinearmodels-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Estimating large-scale structures in wall turbulence using linear models},\n type = {article},\n year = {2018},\n keywords = {turbulence control,turbulence modelling,turbulent flows},\n pages = {146-162},\n volume = {842},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018001295/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {3e4a0e2c-0224-3e99-bc54-88aeb5f4790c},\n created = {2021-04-09T15:23:54.716Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:54.716Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of Re_[STIX]x1D70F=1000 . The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon &amp;amp; Sharma ( J. Fluid Mech. , vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.},\n bibtype = {article},\n author = {Illingworth, Simon J and Monty, Jason P and Marusic, Ivan},\n doi = {10.1017/jfm.2018.129},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of Re_[STIX]x1D70F=1000 . The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon &amp; Sharma ( J. Fluid Mech. , vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301', event);\">\n    Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fouxon,  I.; Schmidt,  L.; Ditlevsen,  P.; van Reeuwijk,  M.;  and Holzner,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 3(6): 64301. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301\"\n     onclick=\"log_download('fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.3.064301\"\n     onclick=\"log_download('fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018', 'http://doi.org/10.1103/PhysRevFluids.3.064301', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fouxon-schmidt-ditlevsen-vanreeuwijk-holzner-inhomogeneousgrowthoffluctuationsofconcentrationofinertialparticlesinchannelturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Inhomogeneous growth of fluctuations of concentration of inertial particles in channel turbulence},\n type = {article},\n year = {2018},\n keywords = {doi:10.1103/PhysRevFluids.3.064301 url:https://doi},\n pages = {64301},\n volume = {3},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.064301},\n month = {4},\n publisher = {American Physical Society},\n id = {6ee00bf4-b546-3cfe-8cb4-4d8cec83ae01},\n created = {2021-04-09T15:23:57.403Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:57.403Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Fouxon, Itzhak and Schmidt, Lukas and Ditlevsen, Peter and van Reeuwijk, Maarten and Holzner, Markus},\n doi = {10.1103/PhysRevFluids.3.064301},\n journal = {Physical Review Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1810.07785\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018', 'http://arxiv.org/abs/1810.07785', event);\">\n    From Deep to Physics-Informed Learning of Turbulence: Diagnostics.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  King,  R.; Hennigh,  O.; Mohan,  A.;  and Chertkov,  M.\n</span>\n\n  \n\n</span>\n\n  . 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1810.07785\"\n     onclick=\"log_download('king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018', 'http://arxiv.org/abs/1810.07785', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"From Deep to Physics-Informed Learning of Turbulence: Diagnostics [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('king-hennigh-mohan-chertkov-fromdeeptophysicsinformedlearningofturbulencediagnostics-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {From Deep to Physics-Informed Learning of Turbulence: Diagnostics},\n type = {article},\n year = {2018},\n websites = {http://arxiv.org/abs/1810.07785},\n month = {4},\n id = {c2ce5c72-f100-31b5-9cac-81b8dc4415c7},\n created = {2021-04-09T15:23:59.239Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:59.239Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of turbulence. Even the bare DL solutions, which do not take into account any physics of turbulence explicitly, are impressively good overall when it comes to qualitative description of important features of turbulence. However, the early tests have also uncovered some caveats of the DL approaches. We observe that the static DL scheme, implementing Convolutional GAN and trained on spatial snapshots of turbulence, fails to reproduce intermittency of turbulent fluctuations at small scales and details of the turbulence geometry at large scales. We show that the dynamic NN schemes, namely LAT-NET and Compressed Convolutional LSTM, trained on a temporal sequence of turbulence snapshots are capable to correct for the caveats of the static NN. We suggest a path forward towards improving reproducibility of the large-scale geometry of turbulence with NN.},\n bibtype = {article},\n author = {King, Ryan and Hennigh, Oliver and Mohan, Arvind and Chertkov, Michael}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of turbulence. Even the bare DL solutions, which do not take into account any physics of turbulence explicitly, are impressively good overall when it comes to qualitative description of important features of turbulence. However, the early tests have also uncovered some caveats of the DL approaches. We observe that the static DL scheme, implementing Convolutional GAN and trained on spatial snapshots of turbulence, fails to reproduce intermittency of turbulent fluctuations at small scales and details of the turbulence geometry at large scales. We show that the dynamic NN schemes, namely LAT-NET and Compressed Convolutional LSTM, trained on a temporal sequence of turbulence snapshots are capable to correct for the caveats of the static NN. We suggest a path forward towards improving reproducibility of the large-scale geometry of turbulence with NN.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00791-018-00303-9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018', 'http://link.springer.com/10.1007/s00791-018-00303-9', event);\">\n    Multilevel techniques for compression and reduction of scientific data—the univariate case.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ainsworth,  M.; Tugluk,  O.; Whitney,  B.;  and Klasky,  S.\n</span>\n\n  \n\n</span>\n\n  <i>Computing and Visualization in Science</i>, 19(5-6): 65-76. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00791-018-00303-9\"\n     onclick=\"log_download('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018', 'http://link.springer.com/10.1007/s00791-018-00303-9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multilevel techniques for compression and reduction of scientific data—the univariate case [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00791-018-00303-9\"\n     onclick=\"log_download('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018', 'http://doi.org/10.1007/s00791-018-00303-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ainsworth-tugluk-whitney-klasky-multileveltechniquesforcompressionandreductionofscientificdatatheunivariatecase-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multilevel techniques for compression and reduction of scientific data—the univariate case},\n type = {article},\n year = {2018},\n pages = {65-76},\n volume = {19},\n websites = {http://link.springer.com/10.1007/s00791-018-00303-9},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {b18efc62-6fe3-3e73-b604-803dc1772fcf},\n created = {2021-04-09T15:24:04.997Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:04.997Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Ainsworth, Mark and Tugluk, Ozan and Whitney, Ben and Klasky, Scott},\n doi = {10.1007/s00791-018-00303-9},\n journal = {Computing and Visualization in Science},\n number = {5-6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610', event);\">\n    Extracting the spectrum of a flow by spatial filtering.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sadek,  M.;  and Aluie,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 3(12): 124610. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610\"\n     onclick=\"log_download('sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Extracting the spectrum of a flow by spatial filtering [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.3.124610\"\n     onclick=\"log_download('sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018', 'http://doi.org/10.1103/PhysRevFluids.3.124610', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sadek-aluie-extractingthespectrumofaflowbyspatialfiltering-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Extracting the spectrum of a flow by spatial filtering},\n type = {article},\n year = {2018},\n pages = {124610},\n volume = {3},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.124610},\n month = {4},\n publisher = {American Physical Society},\n id = {6af5bb72-a429-33a8-9102-fa8f60b255d8},\n created = {2021-04-09T15:24:06.594Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:06.594Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Sadek, Mahmoud and Aluie, Hussein},\n doi = {10.1103/PhysRevFluids.3.124610},\n journal = {Physical Review Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1812.10870\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018', 'http://arxiv.org/abs/1812.10870', event);\">\n    Dot-Tracking Methodology for Background Oriented Schlieren (BOS).\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rajendran,  L., K.; Bane,  S., P., M.;  and Vlachos,  P., P.\n</span>\n\n  \n\n</span>\n\n  . 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1812.10870\"\n     onclick=\"log_download('rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018', 'http://arxiv.org/abs/1812.10870', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Dot-Tracking Methodology for Background Oriented Schlieren (BOS) [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>4 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rajendran-bane-vlachos-dottrackingmethodologyforbackgroundorientedschlierenbos-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Dot-Tracking Methodology for Background Oriented Schlieren (BOS)},\n type = {article},\n year = {2018},\n websites = {http://arxiv.org/abs/1812.10870},\n month = {4},\n id = {55e1a8fa-d58c-383c-91dc-41eb42ac2471},\n created = {2021-04-09T15:24:11.040Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:11.040Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a &quot;correlation correction&quot;, whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in th exit plane of a converging-diverging nozzle.},\n bibtype = {article},\n author = {Rajendran, Lalit K and Bane, Sally P M and Vlachos, Pavlos P}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We propose a dot-tracking methodology for processing Background Oriented Schlieren (BOS) images. The method significantly improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32x32 pix.) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a \"correlation correction\", whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy driven turbulence rendered using ray tracing simulations, and experimental images of flow in th exit plane of a converging-diverging nozzle.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kanzler-westermann-interactivevisualexplorationoflineclusters-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://dl.acm.org/citation.cfm?id=3307680\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kanzler-westermann-interactivevisualexplorationoflineclusters-2018', 'https://dl.acm.org/citation.cfm?id=3307680', event);\">\n    Interactive visual exploration of line clusters.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kanzler,  M.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  In Beck,  F.; Dachsbacher,  C.;  and Sadlo,  F., editor(s), <i>EG VMV '18 Proceedings of the Conference on Vision, Modeling, and Visualization</i>, pages 155-163,  2018. Eurographics Association\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://dl.acm.org/citation.cfm?id=3307680\"\n     onclick=\"log_download('kanzler-westermann-interactivevisualexplorationoflineclusters-2018', 'https://dl.acm.org/citation.cfm?id=3307680', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Interactive visual exploration of line clusters [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2312/VMV.20181265\"\n     onclick=\"log_download('kanzler-westermann-interactivevisualexplorationoflineclusters-2018', 'http://doi.org/10.2312/VMV.20181265', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kanzler-westermann-interactivevisualexplorationoflineclusters-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kanzler-westermann-interactivevisualexplorationoflineclusters-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Interactive visual exploration of line clusters},\n type = {inproceedings},\n year = {2018},\n pages = {155-163},\n websites = {https://dl.acm.org/citation.cfm?id=3307680},\n publisher = {Eurographics Association},\n id = {3af76be2-f576-3cff-afa8-adcecb7e50bb},\n created = {2021-04-09T15:24:13.073Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:13.073Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n bibtype = {inproceedings},\n author = {Kanzler, Mathias and Westermann, Rüdiger},\n editor = {Beck, Fabian and Dachsbacher, Carsten and Sadlo, Filip},\n doi = {10.2312/VMV.20181265},\n booktitle = {EG VMV &#x27;18 Proceedings of the Conference on Vision, Modeling, and Visualization}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995', event);\">\n    Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Elsas,  J., H.; Szalay,  A., S.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Turbulence</i>, 19(4): 297-321. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995\"\n     onclick=\"log_download('elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018', 'https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/14685248.2018.1424995\"\n     onclick=\"log_download('elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018', 'http://doi.org/10.1080/14685248.2018.1424995', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('elsas-szalay-meneveau-geometryandscalinglawsofexcursionandisosetsofenstrophyanddissipationinisotropicturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence},\n type = {article},\n year = {2018},\n keywords = {Isotropic turbulence,chaos and fractals,direct numerical simulation},\n pages = {297-321},\n volume = {19},\n websites = {https://www.tandfonline.com/doi/full/10.1080/14685248.2018.1424995},\n month = {4},\n publisher = {Taylor &amp; Francis},\n id = {32a620b0-6e74-3b93-806b-efbd3195b9c1},\n created = {2021-04-09T15:24:15.454Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:15.454Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Motivated by interest in the geometry of high intensity events of turbulent flows, we examine spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analyzed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation, and velocity gradient invariants Q and R and their joint spatial distibutions, using data from a direct numerical simulation of isotropic turbulence at  Re_λ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus a geometric characterization in terms of these sets&#x27; correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behavior. Nevertheless the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on the multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow. We show that sets defined by joint conditions on strain and enstrophy, and on Q and R, also display power law scaling of correlation functions, providing further characterization of the complex spatial structure of these intersection sets.},\n bibtype = {article},\n author = {Elsas, José Hugo and Szalay, Alexander S and Meneveau, Charles},\n doi = {10.1080/14685248.2018.1424995},\n journal = {Journal of Turbulence},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Motivated by interest in the geometry of high intensity events of turbulent flows, we examine spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analyzed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation, and velocity gradient invariants Q and R and their joint spatial distibutions, using data from a direct numerical simulation of isotropic turbulence at  Re_λ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus a geometric characterization in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behavior. Nevertheless the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on the multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow. We show that sets defined by joint conditions on strain and enstrophy, and on Q and R, also display power law scaling of correlation functions, providing further characterization of the complex spatial structure of these intersection sets.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018', 'https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article', event);\">\n    Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  P., L.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 837: 80-114. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article\"\n     onclick=\"log_download('johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018', 'https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2017.838\"\n     onclick=\"log_download('johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018', 'http://doi.org/10.1017/jfm.2017.838', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-meneveau-predictingviscousrangevelocitygradientdynamicsinlargeeddysimulationsofturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence},\n type = {article},\n year = {2018},\n keywords = {turbulence modelling,turbulence simulation,turbulent flows},\n pages = {80-114},\n volume = {837},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017008382/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {7ec7ca23-80fc-34ff-a1d2-9fbfa4fdf7c8},\n created = {2021-04-09T15:24:25.619Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:25.619Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The detailed dynamics of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modelling challenge, because many micro-physical processes such as deformation of aggregates, drops, bubbles and polymers dynamics depend strongly on the velocity gradient tensor, which is dominated by the turbulence structure in the viscous range. In this paper, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with coarse-grained fluid simulations to recover small-scale physics without resorting to direct numerical simulations (DNS). The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modelling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out and results are again compared to DNS results. Results illustrate the ability of the proposed model to predict the influence of small-scale turbulence on droplet micro-physics in the context of LES.},\n bibtype = {article},\n author = {Johnson, Perry L and Meneveau, Charles},\n doi = {10.1017/jfm.2017.838},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The detailed dynamics of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modelling challenge, because many micro-physical processes such as deformation of aggregates, drops, bubbles and polymers dynamics depend strongly on the velocity gradient tensor, which is dominated by the turbulence structure in the viscous range. In this paper, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with coarse-grained fluid simulations to recover small-scale physics without resorting to direct numerical simulations (DNS). The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modelling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out and results are again compared to DNS results. Results illustrate the ability of the proposed model to predict the influence of small-scale turbulence on droplet micro-physics in the context of LES.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018', 'http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061', event);\">\n    Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Antonialli,  L., A.; Silveira-Neto,  A.; Mecânica,  F., D., E.; Uberlândia,  U., F., D.;  and Gerais,  M.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Applied Mathematics and Physics</i>, 06(04): 677-692. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061\"\n     onclick=\"log_download('antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018', 'http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.4236/jamp.2018.64061\"\n     onclick=\"log_download('antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018', 'http://doi.org/10.4236/jamp.2018.64061', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('antonialli-silveiraneto-mecnica-uberlndia-gerais-theoreticalstudyoffullydevelopedturbulentflowinachannelusingprandtlsmixinglengthmodel-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Theoretical Study of Fully Developed Turbulent Flow in a Channel, Using Prandtl’s Mixing Length Model},\n type = {article},\n year = {2018},\n keywords = {Channel,Mixing Length,Pipe,Turbulent Flow},\n pages = {677-692},\n volume = {06},\n websites = {http://www.scirp.org/journal/doi.aspx?DOI=10.4236/jamp.2018.64061},\n month = {4},\n publisher = {Scientific Research Publishing},\n id = {15314fa1-afcd-3437-82f0-3af0189ff9a2},\n created = {2021-04-09T15:24:26.097Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:26.097Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This research used the common decomposition of the velocity and pressure in an average part and a fluctuating part, for high Reynolds number, of the Navier-Stokes equation, which leads to the classic problem of turbulent closure. The Prandtl’s mixing length model, based on the Boussinesq hypothesis and traditionally used for free shear flows, was chosen and adapted for internal flows to solve the closure problem. For channel flows, Johann Nikuradse proposed a model for the Prandtl mixing length. In the present paper, which has an academic character, the authors made a return to the model of the mixing length of Prandtl and the model of Nikuradse, to solve turbulent flows inside a plane channel. It was possible to develop an ordinary differential model for the velocity in the direction of the flow whose solution occurs computationally in a simple but extremely accurate way when compared with Direct Numerical Simulation databases. For the viscous stress on the wall, it was possible to determine the exact mathematical solution of the ordinary differential equation. It is a model of great academic value and even to be used as reference for verification of computational codes destined to the solution of complete numerical and computational models.},\n bibtype = {article},\n author = {Antonialli, Luigi A and Silveira-Neto, Aristeu and Mecânica, Faculdade De Engenharia and Uberlândia, Universidade Federal De and Gerais, Minas},\n doi = {10.4236/jamp.2018.64061},\n journal = {Journal of Applied Mathematics and Physics},\n number = {04}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This research used the common decomposition of the velocity and pressure in an average part and a fluctuating part, for high Reynolds number, of the Navier-Stokes equation, which leads to the classic problem of turbulent closure. The Prandtl’s mixing length model, based on the Boussinesq hypothesis and traditionally used for free shear flows, was chosen and adapted for internal flows to solve the closure problem. For channel flows, Johann Nikuradse proposed a model for the Prandtl mixing length. In the present paper, which has an academic character, the authors made a return to the model of the mixing length of Prandtl and the model of Nikuradse, to solve turbulent flows inside a plane channel. It was possible to develop an ordinary differential model for the velocity in the direction of the flow whose solution occurs computationally in a simple but extremely accurate way when compared with Direct Numerical Simulation databases. For the viscous stress on the wall, it was possible to determine the exact mathematical solution of the ordinary differential equation. It is a model of great academic value and even to be used as reference for verification of computational codes destined to the solution of complete numerical and computational models.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article', event);\">\n    Fluid particle dynamics and the non-local origin of the Reynolds shear stress.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bernard,  P., S.;  and Erinin,  M., A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 847: 520-551. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article\"\n     onclick=\"log_download('bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018', 'https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Fluid particle dynamics and the non-local origin of the Reynolds shear stress [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2018.333\"\n     onclick=\"log_download('bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018', 'http://doi.org/10.1017/jfm.2018.333', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bernard-erinin-fluidparticledynamicsandthenonlocaloriginofthereynoldsshearstress-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Fluid particle dynamics and the non-local origin of the Reynolds shear stress},\n type = {article},\n year = {2018},\n keywords = {turbulence modelling,turbulence theory,turbulent flows},\n pages = {520-551},\n volume = {847},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112018003336/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {42c6b162-4fe6-3fc0-897e-a0b8228970c7},\n created = {2021-04-09T15:24:27.317Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:27.317Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The causative factors leading to the Reynolds shear stress distribution in turbulent channel flow are analysed via a backward particle path analysis. It is found that the classical displacement transport mechanism, by which changes in the mean velocity field over a mixing time correlate with the wall-normal velocity, is the dominant source of Reynolds shear stress. Approximately 20 % of channel flow at any given time contains fluid motions that contribute to displacement transport. Much rarer events provide a small but non-negligible contribution to the Reynolds shear stress due to fluid particle accelerations and long-lived correlations deriving from structural features of the near-wall flow. The Reynolds shear stress in channel flow is shown to be a non-local phenomenon that is not conducive to description via a local model and particularly one depending directly on the local mean velocity gradient.},\n bibtype = {article},\n author = {Bernard, Peter S and Erinin, Martin A},\n doi = {10.1017/jfm.2018.333},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The causative factors leading to the Reynolds shear stress distribution in turbulent channel flow are analysed via a backward particle path analysis. It is found that the classical displacement transport mechanism, by which changes in the mean velocity field over a mixing time correlate with the wall-normal velocity, is the dominant source of Reynolds shear stress. Approximately 20 % of channel flow at any given time contains fluid motions that contribute to displacement transport. Much rarer events provide a small but non-negligible contribution to the Reynolds shear stress due to fluid particle accelerations and long-lived correlations deriving from structural features of the near-wall flow. The Reynolds shear stress in channel flow is shown to be a non-local phenomenon that is not conducive to description via a local model and particularly one depending directly on the local mean velocity gradient.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018', 'https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435', event);\">\n    Hypothesis Testing For Nonlinear Phenomena In The Geosciences Using Synthetic, Surrogate Data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keylock,  C., J.\n</span>\n\n  \n\n</span>\n\n  <i>Earth and Space Science</i>, 6(1): 2018EA000435. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435\"\n     onclick=\"log_download('keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018', 'https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Hypothesis Testing For Nonlinear Phenomena In The Geosciences Using Synthetic, Surrogate Data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2018EA000435\"\n     onclick=\"log_download('keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018', 'http://doi.org/10.1029/2018EA000435', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keylock-hypothesistestingfornonlinearphenomenainthegeosciencesusingsyntheticsurrogatedata-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Hypothesis Testing For Nonlinear Phenomena In The Geosciences Using Synthetic, Surrogate Data},\n type = {article},\n year = {2018},\n keywords = {Fourier transform,chaos,gradual reconstruction,nonlinearity,surrogate data,wavelets},\n pages = {2018EA000435},\n volume = {6},\n websites = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018EA000435},\n month = {4},\n publisher = {John Wiley &amp; Sons, Ltd},\n id = {e44a6f1f-eb36-366b-aae3-126fdaaf70f8},\n created = {2021-04-09T15:24:29.792Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:29.792Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Keylock, C J},\n doi = {10.1029/2018EA000435},\n journal = {Earth and Space Science},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shih-highendvolumevisualization-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://search.proquest.com/docview/2133012476\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shih-highendvolumevisualization-2018', 'https://search.proquest.com/docview/2133012476', event);\">\n    High-End Volume Visualization.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shih,  M.\n</span>\n\n  \n\n</span>\n\n   2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://search.proquest.com/docview/2133012476\"\n     onclick=\"log_download('shih-highendvolumevisualization-2018', 'https://search.proquest.com/docview/2133012476', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"High-End Volume Visualization [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shih-highendvolumevisualization-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shih-highendvolumevisualization-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {High-End Volume Visualization},\n type = {misc},\n year = {2018},\n pages = {135},\n websites = {https://search.proquest.com/docview/2133012476},\n institution = {University of California, Davis},\n id = {e72c3b4c-0dd6-3e15-87f9-c049e8ff0df1},\n created = {2021-04-09T15:24:31.948Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:31.948Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {thesis},\n private_publication = {false},\n bibtype = {misc},\n author = {Shih, Min}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5004710\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018', 'http://aip.scitation.org/doi/10.1063/1.5004710', event);\">\n    Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Martínez-Tossas,  L., A.; Churchfield,  M., J.; Yilmaz,  A., E.; Sarlak,  H.; Johnson,  P., L.; Sørensen,  J., N.; Meyers,  J.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Renewable and Sustainable Energy</i>, 10(3): 33301. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.5004710\"\n     onclick=\"log_download('martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018', 'http://aip.scitation.org/doi/10.1063/1.5004710', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.5004710\"\n     onclick=\"log_download('martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018', 'http://doi.org/10.1063/1.5004710', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('martneztossas-churchfield-yilmaz-sarlak-johnson-srensen-meyers-meneveau-comparisonoffourlargeeddysimulationresearchcodesandeffectsofmodelcoefficientandinflowturbulenceinactuatorlinebasedwindturbinemodeling-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling},\n type = {article},\n year = {2018},\n pages = {33301},\n volume = {10},\n websites = {http://aip.scitation.org/doi/10.1063/1.5004710},\n month = {4},\n publisher = {AIP Publishing LLC},\n id = {6cce001b-5f00-397b-b895-e112dad1bbb1},\n created = {2021-04-09T15:24:33.156Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:33.156Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Large-eddy simulation (LES) of a wind turbine under uniform inflow is performed using an actuator line model (ALM). Predictions from four LES research codes from the wind energy community are compa...},\n bibtype = {article},\n author = {Martínez-Tossas, Luis A and Churchfield, Matthew J and Yilmaz, Ali Emre and Sarlak, Hamid and Johnson, Perry L and Sørensen, Jens N and Meyers, Johan and Meneveau, Charles},\n doi = {10.1063/1.5004710},\n journal = {Journal of Renewable and Sustainable Energy},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Large-eddy simulation (LES) of a wind turbine under uniform inflow is performed using an actuator line model (ALM). Predictions from four LES research codes from the wind energy community are compa...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10546-018-0335-9\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018', 'http://link.springer.com/10.1007/s10546-018-0335-9', event);\">\n    Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  van Hooft,  J., A.; Popinet,  S.; van Heerwaarden,  C., C.; van der Linden,  S., J., A., A.; de Roode,  S., R.;  and van de Wiel,  B., J., H., H.\n</span>\n\n  \n\n</span>\n\n  <i>Boundary-Layer Meteorology</i>, 167(3): 421-443. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10546-018-0335-9\"\n     onclick=\"log_download('vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018', 'http://link.springer.com/10.1007/s10546-018-0335-9', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10546-018-0335-9\"\n     onclick=\"log_download('vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018', 'http://doi.org/10.1007/s10546-018-0335-9', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('vanhooft-popinet-vanheerwaarden-vanderlinden-deroode-vandewiel-towardsadaptivegridsforatmosphericboundarylayersimulations-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Towards Adaptive Grids for Atmospheric Boundary-Layer Simulations},\n type = {article},\n year = {2018},\n keywords = {Adaptive mesh refinement,Atmospheric boundary layer,Direct numerical simulations,Large-eddy simulations,Turbulence},\n pages = {421-443},\n volume = {167},\n websites = {http://link.springer.com/10.1007/s10546-018-0335-9},\n month = {4},\n publisher = {Springer Netherlands},\n id = {4bc7706d-0fde-3429-a0b5-d729ea5cdb3f},\n created = {2021-04-09T15:24:35.225Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:35.225Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© 2018 The Author(s) We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.},\n bibtype = {article},\n author = {van Hooft, J Antoon and Popinet, Stéphane and van Heerwaarden, Chiel C and van der Linden, Steven J A A and de Roode, Stephan R and van de Wiel, Bas J H H},\n doi = {10.1007/s10546-018-0335-9},\n journal = {Boundary-Layer Meteorology},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2018 The Author(s) We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018', 'https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923', event);\">\n    Spurious noise in direct noise computation with a finite volume method for automotive applications.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Dawi,  A., H.;  and Akkermans,  R., A., D.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Heat and Fluid Flow</i>, 72: 243-256. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923\"\n     onclick=\"log_download('dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018', 'https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Spurious noise in direct noise computation with a finite volume method for automotive applications [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.ijheatfluidflow.2018.06.008\"\n     onclick=\"log_download('dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018', 'http://doi.org/10.1016/j.ijheatfluidflow.2018.06.008', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>8 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('dawi-akkermans-spuriousnoiseindirectnoisecomputationwithafinitevolumemethodforautomotiveapplications-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Spurious noise in direct noise computation with a finite volume method for automotive applications},\n type = {article},\n year = {2018},\n pages = {243-256},\n volume = {72},\n websites = {https://www.sciencedirect.com/science/article/pii/S0142727X18302923,https://linkinghub.elsevier.com/retrieve/pii/S0142727X18302923},\n month = {4},\n publisher = {Elsevier},\n id = {e3f14195-dd58-3ff8-9dcc-5636fa237eeb},\n created = {2021-04-09T15:24:38.065Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:38.065Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The present paper represents a study on spurious noise generated in direct noise computation using finite volume methods. Different sources of spurious noise are examined as well as the mechanism of their generation. This investigation involves two test cases. The first one consists of a turbulence box convected by a uniform flow field. This case serves to identify spurious noise sources and qualitatively evaluate their relevance. The second test case involves a single side mirror mounted on a flat plate, which serves to quantify the level of spurious noise produced and its relevance compared to physical sound generated by the flow past the mirror. Both test cases are calculated using a compressible flow solver for low Mach-number flows utilised with an IDDES approach for turbulence modelling. A new acoustic damping model which damps out acoustic waves without affecting hydrodynamic turbulent fluctuations has been implemented. Furthermore, special emphasis on refinement interfaces is given. Since no measurements are available, the results of the direct noise computation are compared to the results of a method based on Kirchhoff integral.},\n bibtype = {article},\n author = {Dawi, Ali H and Akkermans, Rinie A D},\n doi = {10.1016/j.ijheatfluidflow.2018.06.008},\n journal = {International Journal of Heat and Fluid Flow}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The present paper represents a study on spurious noise generated in direct noise computation using finite volume methods. Different sources of spurious noise are examined as well as the mechanism of their generation. This investigation involves two test cases. The first one consists of a turbulence box convected by a uniform flow field. This case serves to identify spurious noise sources and qualitatively evaluate their relevance. The second test case involves a single side mirror mounted on a flat plate, which serves to quantify the level of spurious noise produced and its relevance compared to physical sound generated by the flow past the mirror. Both test cases are calculated using a compressible flow solver for low Mach-number flows utilised with an IDDES approach for turbulence modelling. A new acoustic damping model which damps out acoustic waves without affecting hydrodynamic turbulent fluctuations has been implemented. Furthermore, special emphasis on refinement interfaces is given. Since no measurements are available, the results of the direct noise computation are compared to the results of a method based on Kirchhoff integral.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604', event);\">\n    Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Danish,  M.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 3(4): 44604. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604\"\n     onclick=\"log_download('danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.3.044604\"\n     onclick=\"log_download('danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018', 'http://doi.org/10.1103/PhysRevFluids.3.044604', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('danish-meneveau-multiscaleanalysisoftheinvariantsofthevelocitygradienttensorinisotropicturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multiscale analysis of the invariants of the velocity gradient tensor in isotropic turbulence},\n type = {article},\n year = {2018},\n pages = {44604},\n volume = {3},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.044604},\n month = {4},\n publisher = {American Physical Society},\n id = {ebeac5a4-3763-3b93-bf27-ee587aebb8e5},\n created = {2021-04-09T15:24:40.168Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:40.168Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Danish, Mohammad and Meneveau, Charles},\n doi = {10.1103/PhysRevFluids.3.044604},\n journal = {Physical Review Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018', 'https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703', event);\">\n    Building a scientific workflow framework to enable real-time machine learning and visualization.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  F.;  and Song,  F.\n</span>\n\n  \n\n</span>\n\n  <i>Concurrency and Computation: Practice and Experience</i>, 31(16): e4703. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703\"\n     onclick=\"log_download('li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018', 'https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Building a scientific workflow framework to enable real-time machine learning and visualization [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/cpe.4703\"\n     onclick=\"log_download('li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018', 'http://doi.org/10.1002/cpe.4703', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-song-buildingascientificworkflowframeworktoenablerealtimemachinelearningandvisualization-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Building a scientific workflow framework to enable real-time machine learning and visualization},\n type = {article},\n year = {2018},\n keywords = {DataSpaces,computational fluid dynamics,high performance computing,machine learning,real‐time online data analytics,scientific workflows},\n pages = {e4703},\n volume = {31},\n websites = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4703,http://doi.wiley.com/10.1002/cpe.4703},\n month = {4},\n publisher = {Wiley-Blackwell},\n id = {643d3582-6581-3ebb-b923-a79c94872b63},\n created = {2021-04-09T15:24:42.504Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:42.504Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Li, Feng and Song, Fengguang},\n doi = {10.1002/cpe.4703},\n journal = {Concurrency and Computation: Practice and Experience},\n number = {16}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.120.244502\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018', 'https://link.aps.org/doi/10.1103/PhysRevLett.120.244502', event);\">\n    Generalization of Turbulent Pair Dispersion to Large Initial Separations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Shnapp,  R.;  and Liberzon,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 120(24): 244502. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.120.244502\"\n     onclick=\"log_download('shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018', 'https://link.aps.org/doi/10.1103/PhysRevLett.120.244502', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Generalization of Turbulent Pair Dispersion to Large Initial Separations [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevLett.120.244502\"\n     onclick=\"log_download('shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018', 'http://doi.org/10.1103/PhysRevLett.120.244502', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('shnapp-liberzon-generalizationofturbulentpairdispersiontolargeinitialseparations-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Generalization of Turbulent Pair Dispersion to Large Initial Separations},\n type = {article},\n year = {2018},\n pages = {244502},\n volume = {120},\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.120.244502},\n month = {4},\n publisher = {American Physical Society},\n id = {19f0e616-4624-396b-90a8-7e7edd4ffb39},\n created = {2021-04-09T15:24:43.155Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:43.155Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Shnapp, Ron and Liberzon, Alex},\n doi = {10.1103/PhysRevLett.120.244502},\n journal = {Physical Review Letters},\n number = {24}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.98.033116\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevE.98.033116', event);\">\n    Renormalization of viscosity in wavelet-based model of turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Altaisky,  M., V.; Hnatich,  M.;  and Kaputkina,  N., E.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 98(3): 33116. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.98.033116\"\n     onclick=\"log_download('altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018', 'https://link.aps.org/doi/10.1103/PhysRevE.98.033116', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Renormalization of viscosity in wavelet-based model of turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.98.033116\"\n     onclick=\"log_download('altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018', 'http://doi.org/10.1103/PhysRevE.98.033116', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('altaisky-hnatich-kaputkina-renormalizationofviscosityinwaveletbasedmodelofturbulence-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Renormalization of viscosity in wavelet-based model of turbulence},\n type = {article},\n year = {2018},\n pages = {33116},\n volume = {98},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.98.033116},\n month = {4},\n publisher = {American Physical Society},\n id = {c93ca499-6722-3c06-8166-73943def56c5},\n created = {2021-04-09T15:24:44.383Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:44.383Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Altaisky, M V and Hnatich, M and Kaputkina, N E},\n doi = {10.1103/PhysRevE.98.033116},\n journal = {Physical Review E},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602', event);\">\n    Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Debue,  P.; Kuzzay,  D.; Saw,  E.; Daviaud,  F.; Dubrulle,  B.; Canet,  L.; Rossetto,  V.;  and Wschebor,  N.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 3(2): 24602. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602\"\n     onclick=\"log_download('debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018', 'https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.3.024602\"\n     onclick=\"log_download('debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018', 'http://doi.org/10.1103/PhysRevFluids.3.024602', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('debue-kuzzay-saw-daviaud-dubrulle-canet-rossetto-wschebor-experimentaltestofthecrossoverbetweentheinertialandthedissipativerangeinaturbulentswirlingflow-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Experimental test of the crossover between the inertial and the dissipative range in a turbulent swirling flow},\n type = {article},\n year = {2018},\n pages = {24602},\n volume = {3},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.3.024602},\n month = {4},\n publisher = {American Physical Society},\n id = {4d7dc155-2758-3e9a-b31c-49fcd1d57167},\n created = {2021-04-09T15:24:45.029Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:45.029Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The kinetic energy spectrum of high-Reynolds turbulent swirling flows is experimentally studied. This spectrum, obtained from direct measurements in space, exhibits nearly two decades of Kolmogorov k −5/3 decay in the inertial range of scales. Beyond this regime, in the dissipative range of scales, a crossover to a stretched exponential decay on scale k 2/3 is observed, in full agreement with a recent theoretical prediction based on nonperturbative renormalization group theory.},\n bibtype = {article},\n author = {Debue, Paul and Kuzzay, Denis and Saw, Ewe-Wei and Daviaud, François and Dubrulle, Bérengère and Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás},\n doi = {10.1103/PhysRevFluids.3.024602},\n journal = {Physical Review Fluids},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The kinetic energy spectrum of high-Reynolds turbulent swirling flows is experimentally studied. This spectrum, obtained from direct measurements in space, exhibits nearly two decades of Kolmogorov k −5/3 decay in the inertial range of scales. Beyond this regime, in the dissipative range of scales, a crossover to a stretched exponential decay on scale k 2/3 is observed, in full agreement with a recent theoretical prediction based on nonperturbative renormalization group theory.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0743731518303927\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018', 'https://www.sciencedirect.com/science/article/pii/S0743731518303927', event);\">\n    Remote visual analysis of large turbulence databases at multiple scales.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pulido,  J.; Livescu,  D.; Kanov,  K.; Burns,  R.; Canada,  C.; Ahrens,  J.;  and Hamann,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Parallel and Distributed Computing</i>, 120: 115-126. 4 2018.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0743731518303927\"\n     onclick=\"log_download('pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018', 'https://www.sciencedirect.com/science/article/pii/S0743731518303927', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Remote visual analysis of large turbulence databases at multiple scales [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/J.JPDC.2018.05.011\"\n     onclick=\"log_download('pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018', 'http://doi.org/10.1016/J.JPDC.2018.05.011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>9 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pulido-livescu-kanov-burns-canada-ahrens-hamann-remotevisualanalysisoflargeturbulencedatabasesatmultiplescales-2018')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Remote visual analysis of large turbulence databases at multiple scales},\n type = {article},\n year = {2018},\n pages = {115-126},\n volume = {120},\n websites = {https://www.sciencedirect.com/science/article/pii/S0743731518303927},\n month = {4},\n publisher = {Academic Press},\n id = {35837047-3f06-3d53-b882-ecb1c35bd473},\n created = {2021-04-09T15:24:46.266Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:46.266Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. We present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. The database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.},\n bibtype = {article},\n author = {Pulido, Jesus and Livescu, Daniel and Kanov, Kalin and Burns, Randal and Canada, Curtis and Ahrens, James and Hamann, Bernd},\n doi = {10.1016/J.JPDC.2018.05.011},\n journal = {Journal of Parallel and Distributed Computing}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. We present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. The database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2017\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2017')\"\n      onkeypress=\"toggleGroup('group_2017')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2017</span>\n      <span class=\"bibbase_group_count\">\n        \n        (15)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://ieeexplore.ieee.org/document/8237542/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017', 'http://ieeexplore.ieee.org/document/8237542/', event);\">\n    Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lasinger,  K.; Vogel,  C.;  and Schindler,  K.\n</span>\n\n  \n\n</span>\n\n  In <i>2017 IEEE International Conference on Computer Vision (ICCV)</i>, pages 2584-2592, 4 2017. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://ieeexplore.ieee.org/document/8237542/\"\n     onclick=\"log_download('lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017', 'http://ieeexplore.ieee.org/document/8237542/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/ICCV.2017.280\"\n     onclick=\"log_download('lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017', 'http://doi.org/10.1109/ICCV.2017.280', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lasinger-vogel-schindler-volumetricflowestimationforincompressiblefluidsusingthestationarystokesequations-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations},\n type = {inproceedings},\n year = {2017},\n pages = {2584-2592},\n websites = {http://ieeexplore.ieee.org/document/8237542/},\n month = {4},\n publisher = {IEEE},\n id = {3f68124b-812f-3e04-a39c-7163dc10e60e},\n created = {2021-04-09T15:23:12.026Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:12.026Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {In experimental fluid dynamics, the flow in a volume of fluid is observed by injecting high-contrast tracer particles and tracking them in multi-view video. Fluid dynamics re-searchers have developed variants of space-carving to re-construct the 3D particle distribution at a given time-step, and then use relatively simple local matching to recover the motion over time. On the contrary, estimating the opti-cal flow between two consecutive images is a long-standing standard problem in computer vision, but only little work exists about volumetric 3D flow. Here, we propose a varia-tional method for 3D fluid flow estimation from multi-view data. We start from a 3D version of the standard varia-tional flow model, and investigate different regularization schemes that ensure divergence-free flow fields, to account for the physics of incompressible fluids. Moreover, we pro-pose a semi-dense formulation, to cope with the computa-tional demands of large volumetric datasets. Flow is esti-mated and regularized at a lower spatial resolution, while the data term is evaluated at full resolution to preserve the discriminative power and geometric precision of the local particle distribution. Extensive experiments reveal that a simple sum of squared differences (SSD) is the most suit-able data term for our application. For regularization, an energy whose Euler-Lagrange equations correspond to the stationary Stokes equations leads to the best results. This strictly enforces a divergence-free flow and additionally pe-nalizes the squared gradient of the flow.},\n bibtype = {inproceedings},\n author = {Lasinger, Katrin and Vogel, Christoph and Schindler, Konrad},\n doi = {10.1109/ICCV.2017.280},\n booktitle = {2017 IEEE International Conference on Computer Vision (ICCV)}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In experimental fluid dynamics, the flow in a volume of fluid is observed by injecting high-contrast tracer particles and tracking them in multi-view video. Fluid dynamics re-searchers have developed variants of space-carving to re-construct the 3D particle distribution at a given time-step, and then use relatively simple local matching to recover the motion over time. On the contrary, estimating the opti-cal flow between two consecutive images is a long-standing standard problem in computer vision, but only little work exists about volumetric 3D flow. Here, we propose a varia-tional method for 3D fluid flow estimation from multi-view data. We start from a 3D version of the standard varia-tional flow model, and investigate different regularization schemes that ensure divergence-free flow fields, to account for the physics of incompressible fluids. Moreover, we pro-pose a semi-dense formulation, to cope with the computa-tional demands of large volumetric datasets. Flow is esti-mated and regularized at a lower spatial resolution, while the data term is evaluated at full resolution to preserve the discriminative power and geometric precision of the local particle distribution. Extensive experiments reveal that a simple sum of squared differences (SSD) is the most suit-able data term for our application. For regularization, an energy whose Euler-Lagrange equations correspond to the stationary Stokes equations leads to the best results. This strictly enforces a divergence-free flow and additionally pe-nalizes the squared gradient of the flow.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0045793017302852\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017', 'https://www.sciencedirect.com/science/article/pii/S0045793017302852', event);\">\n    Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Tunstall,  R.; Laurence,  D.; Prosser,  R.;  and Skillen,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Fluids</i>, 157: 73-83. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0045793017302852\"\n     onclick=\"log_download('tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017', 'https://www.sciencedirect.com/science/article/pii/S0045793017302852', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compfluid.2017.08.002\"\n     onclick=\"log_download('tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017', 'http://doi.org/10.1016/j.compfluid.2017.08.002', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('tunstall-laurence-prosser-skillen-towardsageneraliseddualmeshhybridlesransframeworkwithimprovedconsistency-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Towards a generalised dual-mesh hybrid LES/RANS framework with improved consistency},\n type = {article},\n year = {2017},\n keywords = {Hybrid LES/RANS,OpenFOAM,Turbulence modelling,Wall-bounded flows},\n pages = {73-83},\n volume = {157},\n websites = {https://www.sciencedirect.com/science/article/pii/S0045793017302852},\n month = {4},\n publisher = {Pergamon},\n id = {8dde42f9-59e0-384e-8274-2b5e9502d15e},\n created = {2021-04-09T15:23:12.565Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:12.565Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper presents a combined RANS and LES methodology, which automates the dual-mesh hybrid LES/RANS approach and circumvents the need for wall-functions. Unlike RANS, wall-resolved LES is still unaffordable for studying high Reynolds number complex flows in industry and requires much user expertise when turbulence features are unknown a priori. The present approach avoids these issues by concurrently solving the LES and unsteady RANS equations on separate meshes, which are adapted to each model and are overlapping over the entire domain. The RANS solution guides the LES where its mesh is too coarse, and vice-versa where the LES is well-resolved. The driver- and driven-simulation locally swap roles automatically, depending on which one is deemed more reliable by a blending function. Consistency between the RANS solution and a temporal average of the LES solution is enforced by drift terms, whose strength depend on relaxation times-scales that are provided by the RANS model. Predictions for fully-developed channel flows and the flow through periodic hills are shown to be in excellent agreement with reference data. The LES grids are deliberately too coarse for wall-resolved LES, while the independent RANS mesh uses high aspect-ratio cells to economically resolve the near-wall layer.},\n bibtype = {article},\n author = {Tunstall, R and Laurence, D and Prosser, R and Skillen, A},\n doi = {10.1016/j.compfluid.2017.08.002},\n journal = {Computers and Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper presents a combined RANS and LES methodology, which automates the dual-mesh hybrid LES/RANS approach and circumvents the need for wall-functions. Unlike RANS, wall-resolved LES is still unaffordable for studying high Reynolds number complex flows in industry and requires much user expertise when turbulence features are unknown a priori. The present approach avoids these issues by concurrently solving the LES and unsteady RANS equations on separate meshes, which are adapted to each model and are overlapping over the entire domain. The RANS solution guides the LES where its mesh is too coarse, and vice-versa where the LES is well-resolved. The driver- and driven-simulation locally swap roles automatically, depending on which one is deemed more reliable by a blending function. Consistency between the RANS solution and a temporal average of the LES solution is enforced by drift terms, whose strength depend on relaxation times-scales that are provided by the RANS model. Predictions for fully-developed channel flows and the flow through periodic hills are shown to be in excellent agreement with reference data. The LES grids are deliberately too coarse for wall-resolved LES, while the independent RANS mesh uses high aspect-ratio cells to economically resolve the near-wall layer.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://ieeexplore.ieee.org/document/8231852/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017', 'http://ieeexplore.ieee.org/document/8231852/', event);\">\n    In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Leaf,  N.; Miller,  B.;  and Ma,  K., L.\n</span>\n\n  \n\n</span>\n\n  In <i>2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017</i>, volume 2017-Decem, pages 64-73, 4 2017. IEEE\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://ieeexplore.ieee.org/document/8231852/\"\n     onclick=\"log_download('leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017', 'http://ieeexplore.ieee.org/document/8231852/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/LDAV.2017.8231852\"\n     onclick=\"log_download('leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017', 'http://doi.org/10.1109/LDAV.2017.8231852', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('leaf-miller-ma-insituvideoencodingoffloatingpointvolumedatausingspecialpurposehardwareforaposteriorirenderingandanalysis-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {In situ video encoding of floating-point volume data using special-purpose hardware for a posteriori rendering and analysis},\n type = {inproceedings},\n year = {2017},\n keywords = {Floating-point compression,GPU video encoding,Volume compression},\n pages = {64-73},\n volume = {2017-Decem},\n websites = {http://ieeexplore.ieee.org/document/8231852/},\n month = {4},\n publisher = {IEEE},\n id = {ae2fd0e8-eb3b-34bb-ae02-c84319d53fb9},\n created = {2021-04-09T15:23:18.258Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:18.258Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.},\n bibtype = {inproceedings},\n author = {Leaf, Nick and Miller, Bob and Ma, Kwan Liu},\n doi = {10.1109/LDAV.2017.8231852},\n booktitle = {2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017', 'https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article', event);\">\n    Deformation of a compliant wall in a turbulent channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Zhang,  C.; Wang,  J.; Blake,  W.;  and Katz,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 823: 345-390. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article\"\n     onclick=\"log_download('zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017', 'https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Deformation of a compliant wall in a turbulent channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2017.299\"\n     onclick=\"log_download('zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017', 'http://doi.org/10.1017/jfm.2017.299', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('zhang-wang-blake-katz-deformationofacompliantwallinaturbulentchannelflow-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Deformation of a compliant wall in a turbulent channel flow},\n type = {article},\n year = {2017},\n keywords = {Turbulent boundary Layers,Turbulent flows},\n pages = {345-390},\n volume = {823},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017002993/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {b7254578-dcde-3f36-a742-ff0536faf242},\n created = {2021-04-09T15:23:34.928Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:34.928Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Interaction of a compliant wall with a turbulent channel flow is investigated experimentally by simultaneously measuring the time-resolved, three-dimensional (3D) flow field and the two-dimensional (2D) surface deformation. The optical set-up integrates tomographic particle image velocimetry to measure the flow with Mach–Zehnder interferometry to map the deformation. The Reynolds number is Re_[STIX]x1D70F=2300 , and the Young’s modulus of the wall is 0.93 MPa, resulting in a ratio of shear speed to the centreline velocity ( U_0 ) of 6.8. The wavenumber–frequency spectra of deformation show the surface motions consist of a non-advected low-frequency component and advected modes, some travelling downstream at approximately U_0 and others at ~0.72U_0 . The r.m.s. values of the advected and non-advected modes are 0.04~[STIX]x03BCm (0.004[STIX]x1D6FF_[STIX]x1D708) and 0.2~[STIX]x03BCm ( 0.02[STIX]x1D6FF_[STIX]x1D708 ), respectively, much smaller than the wall unit ( [STIX]x1D6FF_[STIX]x1D708 ), hence they do not affect the flow. Trends in the wall dynamics are elucidated by correlating the deformation with flow variables, including the 3D pressure distribution calculated by spatially integrating the material acceleration. Predictions by the Chase [ J. Acoust. Soc. Am. , vol. 89 (6), pp. 2589–2596] linear model are also calculated and compared to the measured trends. The spatial deformation–pressure correlations peak at y/h 0.12 ( h is half channel height), the elevation of Reynolds shear stress maximum in the log-layer. Streamwise lagging of the deformation behind the pressure is caused in part by phase lag of the pressure with decreasing distance from the wall, and in part by material damping. Positive deformations (bumps) caused by negative pressure fluctuations are preferentially associated with ejections involving spanwise vortices located downstream and quasi-streamwise vortices with spanwise offset. Results of conditional correlations are consistent with the presence of hairpin-like structures. The negative deformations (dimples) are preferentially associated with positive pressure fluctuations at the transition between an upstream sweep to a downstream ejection.},\n bibtype = {article},\n author = {Zhang, Cao and Wang, Jin and Blake, William and Katz, Joseph},\n doi = {10.1017/jfm.2017.299},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Interaction of a compliant wall with a turbulent channel flow is investigated experimentally by simultaneously measuring the time-resolved, three-dimensional (3D) flow field and the two-dimensional (2D) surface deformation. The optical set-up integrates tomographic particle image velocimetry to measure the flow with Mach–Zehnder interferometry to map the deformation. The Reynolds number is Re_[STIX]x1D70F=2300 , and the Young’s modulus of the wall is 0.93 MPa, resulting in a ratio of shear speed to the centreline velocity ( U_0 ) of 6.8. The wavenumber–frequency spectra of deformation show the surface motions consist of a non-advected low-frequency component and advected modes, some travelling downstream at approximately U_0 and others at ~0.72U_0 . The r.m.s. values of the advected and non-advected modes are 0.04~[STIX]x03BCm (0.004[STIX]x1D6FF_[STIX]x1D708) and 0.2~[STIX]x03BCm ( 0.02[STIX]x1D6FF_[STIX]x1D708 ), respectively, much smaller than the wall unit ( [STIX]x1D6FF_[STIX]x1D708 ), hence they do not affect the flow. Trends in the wall dynamics are elucidated by correlating the deformation with flow variables, including the 3D pressure distribution calculated by spatially integrating the material acceleration. Predictions by the Chase [ J. Acoust. Soc. Am. , vol. 89 (6), pp. 2589–2596] linear model are also calculated and compared to the measured trends. The spatial deformation–pressure correlations peak at y/h 0.12 ( h is half channel height), the elevation of Reynolds shear stress maximum in the log-layer. Streamwise lagging of the deformation behind the pressure is caused in part by phase lag of the pressure with decreasing distance from the wall, and in part by material damping. Positive deformations (bumps) caused by negative pressure fluctuations are preferentially associated with ejections involving spanwise vortices located downstream and quasi-streamwise vortices with spanwise offset. Results of conditional correlations are consistent with the presence of hairpin-like structures. The negative deformations (dimples) are preferentially associated with positive pressure fluctuations at the transition between an upstream sweep to a downstream ejection.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017', 'https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605', event);\">\n    Analysis of geometrical and statistical features of Lagrangian stretching in turbulent channel flow using a database task-parallel particle tracking algorithm.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  P., L.; Hamilton,  S., S.; Burns,  R.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 2(1): 14605. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605\"\n     onclick=\"log_download('johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017', 'https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Analysis of geometrical and statistical features of Lagrangian stretching in turbulent channel flow using a database task-parallel particle tracking algorithm [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.2.014605\"\n     onclick=\"log_download('johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017', 'http://doi.org/10.1103/PhysRevFluids.2.014605', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-hamilton-burns-meneveau-analysisofgeometricalandstatisticalfeaturesoflagrangianstretchinginturbulentchannelflowusingadatabasetaskparallelparticletrackingalgorithm-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Analysis of geometrical and statistical features of Lagrangian stretching in turbulent channel flow using a database task-parallel particle tracking algorithm},\n type = {article},\n year = {2017},\n pages = {14605},\n volume = {2},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.014605},\n month = {4},\n publisher = {American Physical Society},\n id = {e74b8566-4274-3b1a-a739-79796c7ef4f6},\n created = {2021-04-09T15:23:39.680Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:39.680Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Johnson, Perry L and Hamilton, Stephen S and Burns, Randal and Meneveau, Charles},\n doi = {10.1103/PhysRevFluids.2.014605},\n journal = {Physical Review Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-017-2307-0\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017', 'http://link.springer.com/10.1007/s00348-017-2307-0', event);\">\n    Weighted divergence correction scheme and its fast implementation.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  C., Y.; Gao,  Q.; Wei,  R., J.; Li,  T.;  and Wang,  J., J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 58(5): 44. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-017-2307-0\"\n     onclick=\"log_download('wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017', 'http://link.springer.com/10.1007/s00348-017-2307-0', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Weighted divergence correction scheme and its fast implementation [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-017-2307-0\"\n     onclick=\"log_download('wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017', 'http://doi.org/10.1007/s00348-017-2307-0', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-gao-wei-li-wang-weighteddivergencecorrectionschemeanditsfastimplementation-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Weighted divergence correction scheme and its fast implementation},\n type = {article},\n year = {2017},\n pages = {44},\n volume = {58},\n websites = {http://link.springer.com/10.1007/s00348-017-2307-0},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {0192ceee-aab1-3e66-936d-56c4d9b81025},\n created = {2021-04-09T15:23:54.184Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:54.184Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.},\n bibtype = {article},\n author = {Wang, Cheng Yue and Gao, Qi and Wei, Run Jie and Li, Tian and Wang, Jin Jun},\n doi = {10.1007/s00348-017-2307-0},\n journal = {Experiments in Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://doi.wiley.com/10.1002/fld.4272\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017', 'http://doi.wiley.com/10.1002/fld.4272', event);\">\n    Uncertainty quantification in LES of channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Safta,  C.; Blaylock,  M.; Templeton,  J.; Domino,  S.; Sargsyan,  K.;  and Najm,  H.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal for Numerical Methods in Fluids</i>, 83(4): 376-401. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://doi.wiley.com/10.1002/fld.4272\"\n     onclick=\"log_download('safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017', 'http://doi.wiley.com/10.1002/fld.4272', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Uncertainty quantification in LES of channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1002/fld.4272\"\n     onclick=\"log_download('safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017', 'http://doi.org/10.1002/fld.4272', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('safta-blaylock-templeton-domino-sargsyan-najm-uncertaintyquantificationinlesofchannelflow-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Uncertainty quantification in LES of channel flow},\n type = {article},\n year = {2017},\n keywords = {Bayesian framework,Rosenblatt transformation,calibration,large eddy simulation,model error,polynomial chaos},\n pages = {376-401},\n volume = {83},\n websites = {http://doi.wiley.com/10.1002/fld.4272},\n month = {4},\n id = {0e749df6-9a68-34cb-a517-ccc9d4a029c0},\n created = {2021-04-09T15:23:58.644Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:58.644Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Dis- crepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.},\n bibtype = {article},\n author = {Safta, Cosmin and Blaylock, Myra and Templeton, Jeremy and Domino, Stefan and Sargsyan, Khachik and Najm, Habib},\n doi = {10.1002/fld.4272},\n journal = {International Journal for Numerical Methods in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Dis- crepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.95.023107\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017', 'https://link.aps.org/doi/10.1103/PhysRevE.95.023107', event);\">\n    Spatiotemporal velocity-velocity correlation function in fully developed turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Canet,  L.; Rossetto,  V.; Wschebor,  N.;  and Balarac,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 95(2): 23107. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.95.023107\"\n     onclick=\"log_download('canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017', 'https://link.aps.org/doi/10.1103/PhysRevE.95.023107', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Spatiotemporal velocity-velocity correlation function in fully developed turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.95.023107\"\n     onclick=\"log_download('canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017', 'http://doi.org/10.1103/PhysRevE.95.023107', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('canet-rossetto-wschebor-balarac-spatiotemporalvelocityvelocitycorrelationfunctioninfullydevelopedturbulence-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Spatiotemporal velocity-velocity correlation function in fully developed turbulence},\n type = {article},\n year = {2017},\n pages = {23107},\n volume = {95},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.95.023107},\n month = {4},\n id = {154cc137-ce6e-3f00-84dd-862eaefbfbb8},\n created = {2021-04-09T15:24:06.109Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:06.109Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Turbulence is an ubiquitous phenomenon in natural and industrial flows. Since the celebrated work of Kolmogorov in 1941, understanding the statistical properties of fully developed turbulence has remained a major quest. In particular, deriving the properties of turbulent flows from a mesoscopic description, that is from Navier-Stokes equation, has eluded most theoretical attempts. Here, we provide a theoretical prediction for the  space and time dependent velocity-velocity correlation function of homogeneous and isotropic turbulence from the field theory associated to Navier-Stokes equation with stochastic forcing. This prediction is the analytical fixed-point solution of Non-Perturbative Renormalisation Group flow equations, which are exact in a certain large wave-number limit. This solution is compared to two-point two-times correlation functions computed in direct numerical simulations. We obtain a remarkable agreement both in the inertial and in the dissipative ranges.},\n bibtype = {article},\n author = {Canet, Léonie and Rossetto, Vincent and Wschebor, Nicolás and Balarac, Guillaume},\n doi = {10.1103/PhysRevE.95.023107},\n journal = {Physical Review E},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Turbulence is an ubiquitous phenomenon in natural and industrial flows. Since the celebrated work of Kolmogorov in 1941, understanding the statistical properties of fully developed turbulence has remained a major quest. In particular, deriving the properties of turbulent flows from a mesoscopic description, that is from Navier-Stokes equation, has eluded most theoretical attempts. Here, we provide a theoretical prediction for the  space and time dependent velocity-velocity correlation function of homogeneous and isotropic turbulence from the field theory associated to Navier-Stokes equation with stochastic forcing. This prediction is the analytical fixed-point solution of Non-Perturbative Renormalisation Group flow equations, which are exact in a certain large wave-number limit. This solution is compared to two-point two-times correlation functions computed in direct numerical simulations. We obtain a remarkable agreement both in the inertial and in the dissipative ranges.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017', 'http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602', event);\">\n    Structure of the velocity gradient tensor in turbulent shear flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pumir,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 2(7): 74602. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602\"\n     onclick=\"log_download('pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017', 'http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Structure of the velocity gradient tensor in turbulent shear flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.2.074602\"\n     onclick=\"log_download('pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017', 'http://doi.org/10.1103/PhysRevFluids.2.074602', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pumir-structureofthevelocitygradienttensorinturbulentshearflows-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Structure of the velocity gradient tensor in turbulent shear flows},\n type = {article},\n year = {2017},\n pages = {74602},\n volume = {2},\n websites = {http://link.aps.org/doi/10.1103/PhysRevFluids.2.074602},\n month = {4},\n publisher = {American Physical Society},\n id = {03d44fe9-4542-3cf6-90b0-3277cd950651},\n created = {2021-04-09T15:24:20.716Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:20.716Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The expected universality of small-scale properties of turbulent flows implies isotropic properties of the velocity gradient tensor in the very large Reynolds number limit. Using direct numerical simulations, we determine the tensors formed by n = 2 and 3 velocity gradients at a single point in turbulent homogeneous shear flows, and in the log-layer of a turbulent channel flow, and we characterize the departure of these tensors from the corresponding isotropic prediction. Specifically, we separate the even components of the tensors, invariant under reflexion with respect to all axes, from the odd ones, which identically vanish in the absence of shear. Our results indicate that the largest deviation from isotropy comes from the odd component of the third velocity gradient correlation function, especially from the third moment of the derivative along the normal direction of the streamwise velocity component. At the Reynolds numbers considered (R_lambda ~ 140), we observe that these second and third order correlation functions are significantly larger in turbulent channel flows than in homogeneous shear flow. Overall, our work demonstrates that a mean shear leads to relatively simple structure of the velocity gradient tensor. How isotropy is restored in the very large Reynolds limit remains to be understood.},\n bibtype = {article},\n author = {Pumir, Alain},\n doi = {10.1103/PhysRevFluids.2.074602},\n journal = {Physical Review Fluids},\n number = {7}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The expected universality of small-scale properties of turbulent flows implies isotropic properties of the velocity gradient tensor in the very large Reynolds number limit. Using direct numerical simulations, we determine the tensors formed by n = 2 and 3 velocity gradients at a single point in turbulent homogeneous shear flows, and in the log-layer of a turbulent channel flow, and we characterize the departure of these tensors from the corresponding isotropic prediction. Specifically, we separate the even components of the tensors, invariant under reflexion with respect to all axes, from the odd ones, which identically vanish in the absence of shear. Our results indicate that the largest deviation from isotropy comes from the odd component of the third velocity gradient correlation function, especially from the third moment of the derivative along the normal direction of the streamwise velocity component. At the Reynolds numbers considered (R_lambda ~ 140), we observe that these second and third order correlation functions are significantly larger in turbulent channel flows than in homogeneous shear flow. Overall, our work demonstrates that a mean shear leads to relatively simple structure of the velocity gradient tensor. How isotropy is restored in the very large Reynolds limit remains to be understood.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017', 'https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607', event);\">\n    Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keylock,  C., J.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Fluids</i>, 2(8): 84607. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607\"\n     onclick=\"log_download('keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017', 'https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevFluids.2.084607\"\n     onclick=\"log_download('keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017', 'http://doi.org/10.1103/PhysRevFluids.2.084607', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keylock-syntheticvelocitygradienttensorsandtheidentificationofstatisticallysignificantaspectsofthestructureofturbulence-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence},\n type = {article},\n year = {2017},\n pages = {84607},\n volume = {2},\n websites = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.084607},\n month = {4},\n id = {07452386-7dbf-3811-a8de-be917350f3f1},\n created = {2021-04-09T15:24:24.548Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:24.548Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Keylock, Christopher J},\n doi = {10.1103/PhysRevFluids.2.084607},\n journal = {Physical Review Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arxiv.org/abs/1702.01438\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017', 'http://arxiv.org/abs/1702.01438', event);\">\n    Inhomogeneous preferential concentration of inertial particles in turbulent channel flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schmidt,  L.; Fouxon,  I.; Ditlevsen,  P.;  and Holzner,  M.\n</span>\n\n  \n\n</span>\n\n  . 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arxiv.org/abs/1702.01438\"\n     onclick=\"log_download('schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017', 'http://arxiv.org/abs/1702.01438', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Inhomogeneous preferential concentration of inertial particles in turbulent channel flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schmidt-fouxon-ditlevsen-holzner-inhomogeneouspreferentialconcentrationofinertialparticlesinturbulentchannelflow-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Inhomogeneous preferential concentration of inertial particles in turbulent channel flow},\n type = {article},\n year = {2017},\n websites = {http://arxiv.org/abs/1702.01438},\n month = {4},\n id = {969b0689-e176-3ccf-97c1-524f2b1d503b},\n created = {2021-04-09T15:24:25.148Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:25.148Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Turbophoresis leading to preferential concentration of inertial particles in regions of low turbulent diffusivity is a unique feature of inhomogeneous turbulent flows, such as free shear flows or wall-bounded flows. In this work, the theory for clustering of weakly inertial particles in homogeneous turbulence is extended to the inhomogeneous case of a turbulent channel flow. The inhomogeneity contributes to the cluster formation in addition to clustering in homogeneous turbulence. A space-dependent rate for the creation of inhomogeneous particle concentration is derived in terms of local statistics of turbulence. We provide the formula for the pair-correlation function of concentration that factorizes in product of time and space-dependent average concentrations and time-independent factor of clustering that obeys a power-law in the distance between the points. This power-law characterizes inhomogeneous multifractality of the particle distribution. A unique demonstration and quantification of the combined effects of turbophoresis and fractal clustering in a direct numerical simulation of particle motion in a turbulent channel flow is performed according to the presented theory. The strongest contribution to clustering coming from the inhomogeneity of the flow occurs in the transitional region between viscous sublayer and the buffer layer. Further the ratio of homogeneous and inhomogeneous term depends on the wall distance. The inhomogeneous terms may significantly increase the preferential concentration of inertial particles, thus the overall degree of clustering in inhomogeneous turbulence is potentially stronger compared to particles with the same inertia in purely homogeneous turbulence.},\n bibtype = {article},\n author = {Schmidt, Lukas and Fouxon, Itzhak and Ditlevsen, Peter and Holzner, Markus}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Turbophoresis leading to preferential concentration of inertial particles in regions of low turbulent diffusivity is a unique feature of inhomogeneous turbulent flows, such as free shear flows or wall-bounded flows. In this work, the theory for clustering of weakly inertial particles in homogeneous turbulence is extended to the inhomogeneous case of a turbulent channel flow. The inhomogeneity contributes to the cluster formation in addition to clustering in homogeneous turbulence. A space-dependent rate for the creation of inhomogeneous particle concentration is derived in terms of local statistics of turbulence. We provide the formula for the pair-correlation function of concentration that factorizes in product of time and space-dependent average concentrations and time-independent factor of clustering that obeys a power-law in the distance between the points. This power-law characterizes inhomogeneous multifractality of the particle distribution. A unique demonstration and quantification of the combined effects of turbophoresis and fractal clustering in a direct numerical simulation of particle motion in a turbulent channel flow is performed according to the presented theory. The strongest contribution to clustering coming from the inhomogeneity of the flow occurs in the transitional region between viscous sublayer and the buffer layer. Further the ratio of homogeneous and inhomogeneous term depends on the wall distance. The inhomogeneous terms may significantly increase the preferential concentration of inertial particles, thus the overall degree of clustering in inhomogeneous turbulence is potentially stronger compared to particles with the same inertia in purely homogeneous turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177716302266\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017', 'https://www.sciencedirect.com/science/article/pii/S0894177716302266', event);\">\n    POD-based background removal for particle image velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mendez,  M., A.; Raiola,  M.; Masullo,  A.; Discetti,  S.; Ianiro,  A.; Theunissen,  R.;  and Buchlin,  J., M.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 80: 181-192. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177716302266\"\n     onclick=\"log_download('mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017', 'https://www.sciencedirect.com/science/article/pii/S0894177716302266', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"POD-based background removal for particle image velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.expthermflusci.2016.08.021\"\n     onclick=\"log_download('mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017', 'http://doi.org/10.1016/j.expthermflusci.2016.08.021', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>4 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mendez-raiola-masullo-discetti-ianiro-theunissen-buchlin-podbasedbackgroundremovalforparticleimagevelocimetry-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {POD-based background removal for particle image velocimetry},\n type = {article},\n year = {2017},\n keywords = {PIV image pre-processing,POD decomposition of video sequences,Reduced Order Modeling (ROM)},\n pages = {181-192},\n volume = {80},\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177716302266},\n month = {4},\n publisher = {Elsevier},\n id = {ae00564d-5c14-3b61-bdab-99f9cbbc9812},\n created = {2021-04-09T15:24:27.798Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:27.798Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.},\n bibtype = {article},\n author = {Mendez, M A and Raiola, M and Masullo, A and Discetti, S and Ianiro, A and Theunissen, R and Buchlin, J M},\n doi = {10.1016/j.expthermflusci.2016.08.021},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-017-2395-x\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017', 'http://link.springer.com/10.1007/s00348-017-2395-x', event);\">\n    Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lian,  H.; Soulopoulos,  N.;  and Hardalupas,  Y.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 58(9): 118. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-017-2395-x\"\n     onclick=\"log_download('lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017', 'http://link.springer.com/10.1007/s00348-017-2395-x', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-017-2395-x\"\n     onclick=\"log_download('lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017', 'http://doi.org/10.1007/s00348-017-2395-x', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lian-soulopoulos-hardalupas-evaluationofthetopologicalcharacteristicsoftheturbulentflowinaboxofturbulencethrough2dtimeresolvedparticleimagevelocimetry-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Evaluation of the topological characteristics of the turbulent flow in a ‘box of turbulence’ through 2D time-resolved particle image velocimetry},\n type = {article},\n year = {2017},\n pages = {118},\n volume = {58},\n websites = {http://link.springer.com/10.1007/s00348-017-2395-x},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {fb414d52-e7c1-3c6d-96c0-a6059b9dcc40},\n created = {2021-04-09T15:24:34.718Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:34.718Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© 2017, The Author(s). The experimental evaluation of the topological characteristics of the turbulent flow in a ‘box’ of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.},\n bibtype = {article},\n author = {Lian, Huan and Soulopoulos, Nikolaos and Hardalupas, Yannis},\n doi = {10.1007/s00348-017-2395-x},\n journal = {Experiments in Fluids},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2017, The Author(s). The experimental evaluation of the topological characteristics of the turbulent flow in a ‘box’ of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016007199\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017', 'http://www.journals.cambridge.org/abstract_S0022112016007199', event);\">\n    Nonlinear effects in buoyancy-driven variable-density turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Rao,  P.; Caulfield,  C., P.;  and Gibbon,  J., D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 810: 362-377. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016007199\"\n     onclick=\"log_download('rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017', 'http://www.journals.cambridge.org/abstract_S0022112016007199', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Nonlinear effects in buoyancy-driven variable-density turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2016.719\"\n     onclick=\"log_download('rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017', 'http://doi.org/10.1017/jfm.2016.719', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('rao-caulfield-gibbon-nonlineareffectsinbuoyancydrivenvariabledensityturbulence-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Nonlinear effects in buoyancy-driven variable-density turbulence},\n type = {article},\n year = {2017},\n keywords = {Navier–Stokes equations,buoyancy-driven instability,mathematical foundations},\n pages = {362-377},\n volume = {810},\n websites = {http://www.journals.cambridge.org/abstract_S0022112016007199},\n month = {4},\n publisher = {Cambridge University Press},\n id = {d4f5f478-aada-3f5f-87d3-74e0200b074e},\n created = {2021-04-09T15:24:40.792Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:40.792Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We consider the time dependence of a hierarchy of scaled L^2m -norms D_m,[STIX]x1D714 and D_m,[STIX]x1D703 of the vorticity [STIX]x1D74E=[STIX]x1D735 u and the density gradient [STIX]x1D735[STIX]x1D703 , where [STIX]x1D703= ([STIX]x1D70C^ /[STIX]x1D70C_0^ ) , in a buoyancy-driven turbulent flow as simulated by Livescu &amp;amp; Ristorcelli ( J. Fluid Mech. , vol. 591, 2007, pp. 43–71). Here, [STIX]x1D70C^ (x,t) is the composition density of a mixture of two incompressible miscible fluids with fluid densities [STIX]x1D70C_2^ &gt;[STIX]x1D70C_1^  , and [STIX]x1D70C_0^  is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the L^2 -spatial average of the density gradient [STIX]x1D735[STIX]x1D703 can reach extremely large values at intermediate times, even in flows with low Atwood number At=([STIX]x1D70C_2^ -[STIX]x1D70C_1^ )/([STIX]x1D70C_2^ +[STIX]x1D70C_1^ )=0.05 , implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient [STIX]x1D735[STIX]x1D703 might blow up in a finite time.},\n bibtype = {article},\n author = {Rao, P and Caulfield, C P and Gibbon, J D},\n doi = {10.1017/jfm.2016.719},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We consider the time dependence of a hierarchy of scaled L^2m -norms D_m,[STIX]x1D714 and D_m,[STIX]x1D703 of the vorticity [STIX]x1D74E=[STIX]x1D735 u and the density gradient [STIX]x1D735[STIX]x1D703 , where [STIX]x1D703= ([STIX]x1D70C^ /[STIX]x1D70C_0^ ) , in a buoyancy-driven turbulent flow as simulated by Livescu &amp; Ristorcelli ( J. Fluid Mech. , vol. 591, 2007, pp. 43–71). Here, [STIX]x1D70C^ (x,t) is the composition density of a mixture of two incompressible miscible fluids with fluid densities [STIX]x1D70C_2^ >[STIX]x1D70C_1^  , and [STIX]x1D70C_0^  is a reference normalization density. Using data from the publicly available Johns Hopkins turbulence database, we present evidence that the L^2 -spatial average of the density gradient [STIX]x1D735[STIX]x1D703 can reach extremely large values at intermediate times, even in flows with low Atwood number At=([STIX]x1D70C_2^ -[STIX]x1D70C_1^ )/([STIX]x1D70C_2^ +[STIX]x1D70C_1^ )=0.05 , implying that very strong mixing of the density field at small scales can arise in buoyancy-driven turbulence. This large growth raises the possibility that the density gradient [STIX]x1D735[STIX]x1D703 might blow up in a finite time.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017', 'https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article', event);\">\n    A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Drivas,  T., D.;  and Eyink,  G., L.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 829: 236-279. 4 2017.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article\"\n     onclick=\"log_download('drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017', 'https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2017.571\"\n     onclick=\"log_download('drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017', 'http://doi.org/10.1017/jfm.2017.571', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('drivas-eyink-alagrangianfluctuationdissipationrelationforscalarturbulencepartiiwallboundedflows-2017')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Lagrangian fluctuation - dissipation relation for scalar turbulence . Part II . Wall-bounded flows},\n type = {article},\n year = {2017},\n keywords = {mathematical foundations,turbulence theory,turbulent mixing},\n pages = {236-279},\n volume = {829},\n websites = {https://www.cambridge.org/core/product/identifier/S0022112017005717/type/journal_article},\n month = {4},\n publisher = {Cambridge University Press},\n id = {ab7a41aa-5bfe-3e00-be27-392ff5926cb1},\n created = {2021-04-09T15:24:41.296Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:41.296Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We derive here Lagrangian fluctuation–dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values, boundary values and internal sources, as those are sampled backward in time by stochastic Lagrangian trajectories. New probabilistic concepts are required to represent scalar boundary conditions at the walls: the boundary local-time density at points on the wall where scalar fluxes are imposed and the boundary first hitting time at points where scalar values are imposed. These concepts are illustrated both by analytical results for the problem of pure heat conduction and by numerical results from a database of channel-flow turbulence, which also demonstrate the scalar mixing properties of near-wall turbulence. As an application of the fluctuation–dissipation relation, we examine for wall-bounded flows the relation between anomalous scalar dissipation and Lagrangian spontaneous stochasticity, i.e. the persistent non-determinism of Lagrangian particle trajectories in the limit of vanishing viscosity and diffusivity. In Part I of this series, we showed that spontaneous stochasticity is the only possible mechanism for anomalous dissipation of passive or active scalars, away from walls. Here it is shown that this remains true when there are no scalar fluxes through walls. Simple examples show, on the other hand, that a distinct mechanism of non-vanishing scalar dissipation can be thin scalar boundary layers near the walls. Nevertheless, we prove for general wall-bounded flows that spontaneous stochasticity is another possible mechanism of anomalous scalar dissipation.},\n bibtype = {article},\n author = {Drivas, Theodore D and Eyink, Gregory L},\n doi = {10.1017/jfm.2017.571},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We derive here Lagrangian fluctuation–dissipation relations for advected scalars in wall-bounded flows. The relations equate the dissipation rate for either passive or active scalars to the variance of scalar inputs from the initial values, boundary values and internal sources, as those are sampled backward in time by stochastic Lagrangian trajectories. New probabilistic concepts are required to represent scalar boundary conditions at the walls: the boundary local-time density at points on the wall where scalar fluxes are imposed and the boundary first hitting time at points where scalar values are imposed. These concepts are illustrated both by analytical results for the problem of pure heat conduction and by numerical results from a database of channel-flow turbulence, which also demonstrate the scalar mixing properties of near-wall turbulence. As an application of the fluctuation–dissipation relation, we examine for wall-bounded flows the relation between anomalous scalar dissipation and Lagrangian spontaneous stochasticity, i.e. the persistent non-determinism of Lagrangian particle trajectories in the limit of vanishing viscosity and diffusivity. In Part I of this series, we showed that spontaneous stochasticity is the only possible mechanism for anomalous dissipation of passive or active scalars, away from walls. Here it is shown that this remains true when there are no scalar fluxes through walls. Simple examples show, on the other hand, that a distinct mechanism of non-vanishing scalar dissipation can be thin scalar boundary layers near the walls. Nevertheless, we prove for general wall-bounded flows that spontaneous stochasticity is another possible mechanism of anomalous scalar dissipation.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2016\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2016')\"\n      onkeypress=\"toggleGroup('group_2016')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2016</span>\n      <span class=\"bibbase_group_count\">\n        \n        (16)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005048\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005048', event);\">\n    Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lozano-Durán,  A.; Holzner,  M.;  and Jiménez,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 803: 356-394. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005048\"\n     onclick=\"log_download('lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005048', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932 [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2016.504\"\n     onclick=\"log_download('lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016', 'http://doi.org/10.1017/jfm.2016.504', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lozanodurn-holzner-jimnez-multiscaleanalysisofthetopologicalinvariantsinthelogarithmicregionofturbulentchannelsatafrictionreynoldsnumberof932-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932},\n type = {article},\n year = {2016},\n keywords = {turbulence simulation,turbulent boundary layers,turbulent flows},\n pages = {356-394},\n volume = {803},\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005048},\n month = {4},\n id = {7e9d65e4-b575-3200-b915-dd2f7127ea25},\n created = {2021-04-09T15:23:13.084Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:13.084Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The invariants of the velocity gradient tensor, R and Q, and their enstrophy and strain components are studied in the logarithmic layer of an incompressible turbulent channel flow. The velocities are filtered in the three spatial directions and the results analyzed at different scales. We show that the R–Q plane does not capture the changes undergone by the flow as the filter width increases, and that the enstrophy/enstrophy-production and strain/strain-production planes represent better choices. We also show that the conditional mean trajectories may differ significantly from the instantaneous behavior of the flow since they are the result of an averaging process where the mean is 3-5 times smaller than the corresponding standard deviation. The orbital periods in the R–Q plane are shown to be independent of the intensity of the events, and of the same order of magnitude than those in the enstrophy/enstrophy-production and strain/strain-production planes. Our final goal is to test whether the dynamics of the flow are self-similar in the inertial range, and the answer turns out to be no. The mean shear is found to be responsible for the absence of self-similarity and progressively controls the dynamics of the eddies observed as the filter width increases. However, a self-similar behavior emerges when the calculations are repeated for the fluctuating velocity gradient tensor. Finally, the turbulent cascade in terms of vortex stretching is considered by computing the alignment of the vorticity at a given scale with the strain at a different one. These results generally support a non-negligible role of the phenomenological energy-cascade model formulated in terms of vortex stretching.},\n bibtype = {article},\n author = {Lozano-Durán, A and Holzner, M and Jiménez, J},\n doi = {10.1017/jfm.2016.504},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The invariants of the velocity gradient tensor, R and Q, and their enstrophy and strain components are studied in the logarithmic layer of an incompressible turbulent channel flow. The velocities are filtered in the three spatial directions and the results analyzed at different scales. We show that the R–Q plane does not capture the changes undergone by the flow as the filter width increases, and that the enstrophy/enstrophy-production and strain/strain-production planes represent better choices. We also show that the conditional mean trajectories may differ significantly from the instantaneous behavior of the flow since they are the result of an averaging process where the mean is 3-5 times smaller than the corresponding standard deviation. The orbital periods in the R–Q plane are shown to be independent of the intensity of the events, and of the same order of magnitude than those in the enstrophy/enstrophy-production and strain/strain-production planes. Our final goal is to test whether the dynamics of the flow are self-similar in the inertial range, and the answer turns out to be no. The mean shear is found to be responsible for the absence of self-similarity and progressively controls the dynamics of the eddies observed as the filter width increases. However, a self-similar behavior emerges when the calculations are repeated for the fluctuating velocity gradient tensor. Finally, the turbulent cascade in terms of vortex stretching is considered by computing the alignment of the vorticity at a given scale with the strain at a different one. These results generally support a non-negligible role of the phenomenological energy-cascade model formulated in terms of vortex stretching.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4939471\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016', 'http://aip.scitation.org/doi/10.1063/1.4939471', event);\">\n    The anisotropic structure of turbulence and its energy spectrum.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Elsinga,  G., E.;  and Marusic,  I.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 28(1): 11701. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4939471\"\n     onclick=\"log_download('elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016', 'http://aip.scitation.org/doi/10.1063/1.4939471', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"The anisotropic structure of turbulence and its energy spectrum [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.4939471\"\n     onclick=\"log_download('elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016', 'http://doi.org/10.1063/1.4939471', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('elsinga-marusic-theanisotropicstructureofturbulenceanditsenergyspectrum-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {The anisotropic structure of turbulence and its energy spectrum},\n type = {article},\n year = {2016},\n pages = {11701},\n volume = {28},\n websites = {http://aip.scitation.org/doi/10.1063/1.4939471},\n month = {4},\n id = {15cb2dab-6eab-3807-90eb-f579a18bc5c5},\n created = {2021-04-09T15:23:13.967Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:13.967Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The spectral energy distribution in turbulent flows is observed to follow a k−5/3 power scaling, as originally predicted by Kolmogorov’s theory. However, the underlying assumptions in Kolmogorov’s theory appear not to hold with most experimental and numerical data showing evidence of small-scale anisotropy and significant direct energy transfer between the large- and the small-scales. Here, we present a flow structure that reconciles the k−5/3 spectrum with small-scale universality, small-scale anisotropy, and direct scale interactions. The flow structure is a shear layer, which contains the small-scales of motion and is bounded by the large-scales. The anisotropic shear layer reveals the expected scaling of the energy spectrum in nearly all directions.},\n bibtype = {article},\n author = {Elsinga, G E and Marusic, I},\n doi = {10.1063/1.4939471},\n journal = {Physics of Fluids},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The spectral energy distribution in turbulent flows is observed to follow a k−5/3 power scaling, as originally predicted by Kolmogorov’s theory. However, the underlying assumptions in Kolmogorov’s theory appear not to hold with most experimental and numerical data showing evidence of small-scale anisotropy and significant direct energy transfer between the large- and the small-scales. Here, we present a flow structure that reconciles the k−5/3 spectrum with small-scale universality, small-scale anisotropy, and direct scale interactions. The flow structure is a shear layer, which contains the small-scales of motion and is bounded by the large-scales. The anisotropic shear layer reveals the expected scaling of the energy spectrum in nearly all directions.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arc.aiaa.org/doi/10.2514/6.2016-1048\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016', 'http://arc.aiaa.org/doi/10.2514/6.2016-1048', event);\">\n    Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schneiders,  J.; Caridi,  G., C., A.; Sciacchitano,  A.;  and Scarano,  F.\n</span>\n\n  \n\n</span>\n\n  In <i>54th AIAA Aerospace Sciences Meeting</i>, 4 2016. American Institute of Aeronautics and Astronautics\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arc.aiaa.org/doi/10.2514/6.2016-1048\"\n     onclick=\"log_download('schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016', 'http://arc.aiaa.org/doi/10.2514/6.2016-1048', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2016-1048\"\n     onclick=\"log_download('schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016', 'http://doi.org/10.2514/6.2016-1048', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schneiders-caridi-sciacchitano-scarano-instantaneouspressuremeasurementsfromlargescaletomoptvwithhfsbtracerspastasurfacemountedfinitecylinder-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Instantaneous Pressure Measurements from Large-Scale Tomo-PTV with HFSB Tracers past a Surface-Mounted Finite Cylinder},\n type = {inproceedings},\n year = {2016},\n websites = {http://arc.aiaa.org/doi/10.2514/6.2016-1048},\n month = {4},\n publisher = {American Institute of Aeronautics and Astronautics},\n id = {064e72ac-06e5-3458-8c9e-86c71f12040e},\n created = {2021-04-09T15:23:22.630Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:22.630Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {© 2016, American Institute of Aeronautics and Astronautics Inc, AIAA . All rights reserved. Instantaneous and time-resolved pressure is evaluated in a 6-liter measurement volume by making use of tomographic PTV with Helium-filled soap bubbles (HFSB) as tracers. This volume is two orders of magnitude larger than conventional tomographic experiments. The experiment considers the near-wake of a surface mounted cylinder (Re D = 3.6×10 4 ), which is highly unsteady and fully three-dimensional. Pressure is calculated from the tomographic velocity measurement by invoking the incompressible momentum equation. The time-averaged, RMS and instantaneous pressure is validated against simultaneous and independent pressure measurements made by pressure transducers in the surface. The mean and RMS pressure is in good correspondence to the reference measurements. Cross-correlation of the instantaneous pressure time-series with the reference measurement signal yields a cross-correlation coefficient peak value of 0.6. The present study shows that instantaneous pressure can be measured non-intrusively in a large measurement volume by making use of tomographic PTV with HFSB as tracers, which allows significantly reduced model complexity as the use of pressure transducers is avoided.},\n bibtype = {inproceedings},\n author = {Schneiders, Jan and Caridi, Giuseppe Carlo Alp and Sciacchitano, Andrea and Scarano, Fulvio},\n doi = {10.2514/6.2016-1048},\n booktitle = {54th AIAA Aerospace Sciences Meeting}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA . All rights reserved. Instantaneous and time-resolved pressure is evaluated in a 6-liter measurement volume by making use of tomographic PTV with Helium-filled soap bubbles (HFSB) as tracers. This volume is two orders of magnitude larger than conventional tomographic experiments. The experiment considers the near-wake of a surface mounted cylinder (Re D = 3.6×10 4 ), which is highly unsteady and fully three-dimensional. Pressure is calculated from the tomographic velocity measurement by invoking the incompressible momentum equation. The time-averaged, RMS and instantaneous pressure is validated against simultaneous and independent pressure measurements made by pressure transducers in the surface. The mean and RMS pressure is in good correspondence to the reference measurements. Cross-correlation of the instantaneous pressure time-series with the reference measurement signal yields a cross-correlation coefficient peak value of 0.6. The present study shows that instantaneous pressure can be measured non-intrusively in a large measurement volume by making use of tomographic PTV with HFSB as tracers, which allows significantly reduced model complexity as the use of pressure transducers is avoided.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016', 'http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230', event);\">\n    Complex Networks Unveiling Spatial Patterns in Turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Scarsoglio,  S.; Iacobello,  G.;  and Ridolfi,  L.\n</span>\n\n  \n\n</span>\n\n  <i>International Journal of Bifurcation and Chaos</i>, 26(13): 1650223. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230\"\n     onclick=\"log_download('scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016', 'http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Complex Networks Unveiling Spatial Patterns in Turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1142/S0218127416502230\"\n     onclick=\"log_download('scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016', 'http://doi.org/10.1142/S0218127416502230', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('scarsoglio-iacobello-ridolfi-complexnetworksunveilingspatialpatternsinturbulence-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Complex Networks Unveiling Spatial Patterns in Turbulence},\n type = {article},\n year = {2016},\n keywords = {Complex networks,spatial correlation,spatiotemporal patterns,time series analysis,turbulent flows},\n pages = {1650223},\n volume = {26},\n websites = {http://www.worldscientific.com/doi/abs/10.1142/S0218127416502230},\n month = {4},\n publisher = {World Scientific Publishing Company},\n id = {90dfeab9-ddc5-3436-b6a3-2af6cf730f25},\n created = {2021-04-09T15:23:23.612Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:23.612Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.},\n bibtype = {article},\n author = {Scarsoglio, Stefania and Iacobello, Giovanni and Ridolfi, Luca},\n doi = {10.1142/S0218127416502230},\n journal = {International Journal of Bifurcation and Chaos},\n number = {13}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on the complex network theory, offering a powerful framework to explore complex systems with a huge number of interacting elements. Although interest on complex networks has been increasing in the last years, few recent studies have been applied to turbulence. We propose an investigation starting from a two-point correlation for the kinetic energy of a forced isotropic field numerically solved. Among all the metrics analyzed, the degree centrality is the most significant, suggesting the formation of spatial patterns which coherently move with similar vorticity over the large eddy turnover time scale. Pattern size can be quantified through a newly-introduced parameter (i.e., average physical distance) and varies from small to intermediate scales. The network analysis allows a systematic identification of different spatial regions, providing new insights into the spatial characterization of turbulent flows. Based on present findings, the application to highly inhomogeneous flows seems promising and deserves additional future investigation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016', 'http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b', event);\">\n    A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Higham,  J., E.; Brevis,  W.;  and Keylock,  C., J.\n</span>\n\n  \n\n</span>\n\n  <i>Measurement Science and Technology</i>, 27(12): 125303. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b\"\n     onclick=\"log_download('higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016', 'http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/0957-0233/27/12/125303\"\n     onclick=\"log_download('higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016', 'http://doi.org/10.1088/0957-0233/27/12/125303', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>2 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('higham-brevis-keylock-arapidnoniterativeproperorthogonaldecompositionbasedoutlierdetectionandcorrectionforpivdata-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data},\n type = {article},\n year = {2016},\n keywords = {experimental fluid mechanics,image processing,outlier detection,particle image velocimetry,proper orthogonal decomposition},\n pages = {125303},\n volume = {27},\n websites = {http://stacks.iop.org/0957-0233/27/i=12/a=125303?key=crossref.26d2feee32438be525049958db339b1b},\n month = {4},\n id = {dba5bfce-3af7-344f-b0c3-c53a04d6e84e},\n created = {2021-04-09T15:23:26.054Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:26.054Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.},\n bibtype = {article},\n author = {Higham, J E and Brevis, W and Keylock, C J},\n doi = {10.1088/0957-0233/27/12/125303},\n journal = {Measurement Science and Technology},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2129-5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016', 'http://link.springer.com/10.1007/s00348-016-2129-5', event);\">\n    Full-field pressure from snapshot and time-resolved volumetric PIV.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Laskari,  A.; de Kat,  R.;  and Ganapathisubramani,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 57(3): 1-14. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2129-5\"\n     onclick=\"log_download('laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016', 'http://link.springer.com/10.1007/s00348-016-2129-5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Full-field pressure from snapshot and time-resolved volumetric PIV [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-016-2129-5\"\n     onclick=\"log_download('laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016', 'http://doi.org/10.1007/s00348-016-2129-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('laskari-dekat-ganapathisubramani-fullfieldpressurefromsnapshotandtimeresolvedvolumetricpiv-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Full-field pressure from snapshot and time-resolved volumetric PIV},\n type = {article},\n year = {2016},\n pages = {1-14},\n volume = {57},\n websites = {http://link.springer.com/10.1007/s00348-016-2129-5},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {7301db0a-bf15-37e9-a0f6-62747dd8aaab},\n created = {2021-04-09T15:23:29.050Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:29.050Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Laskari, A and de Kat, R and Ganapathisubramani, B},\n doi = {10.1007/s00348-016-2129-5},\n journal = {Experiments in Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2189-6\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016', 'http://link.springer.com/10.1007/s00348-016-2189-6', event);\">\n    An irrotation correction on pressure gradient and orthogonal-path integration for PIV-based pressure reconstruction.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wang,  Z.; Gao,  Q.; Wang,  C.; Wei,  R.;  and Wang,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 57(6): 104. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2189-6\"\n     onclick=\"log_download('wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016', 'http://link.springer.com/10.1007/s00348-016-2189-6', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"An irrotation correction on pressure gradient and orthogonal-path integration for PIV-based pressure reconstruction [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-016-2189-6\"\n     onclick=\"log_download('wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016', 'http://doi.org/10.1007/s00348-016-2189-6', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wang-gao-wang-wei-wang-anirrotationcorrectiononpressuregradientandorthogonalpathintegrationforpivbasedpressurereconstruction-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {An irrotation correction on pressure gradient and orthogonal-path integration for PIV-based pressure reconstruction},\n type = {article},\n year = {2016},\n pages = {104},\n volume = {57},\n websites = {http://link.springer.com/10.1007/s00348-016-2189-6},\n month = {4},\n id = {450552f0-5512-3d43-b994-555bf6625074},\n created = {2021-04-09T15:23:29.744Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:29.744Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Wang, Zhongyi and Gao, Qi and Wang, Chengyue and Wei, Runjie and Wang, Jinjun},\n doi = {10.1007/s00348-016-2189-6},\n journal = {Experiments in Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10494-015-9643-z\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016', 'http://link.springer.com/10.1007/s10494-015-9643-z', event);\">\n    A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Schwarzkopf,  J., D.; Livescu,  D.; Baltzer,  J., R.; Gore,  R., A.;  and Ristorcelli,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Flow, Turbulence and Combustion</i>, 96(1): 1-43. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10494-015-9643-z\"\n     onclick=\"log_download('schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016', 'http://link.springer.com/10.1007/s10494-015-9643-z', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10494-015-9643-z\"\n     onclick=\"log_download('schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016', 'http://doi.org/10.1007/s10494-015-9643-z', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('schwarzkopf-livescu-baltzer-gore-ristorcelli-atwolengthscaleturbulencemodelforsinglephasemultifluidmixing-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A Two-length Scale Turbulence Model for Single-phase Multi-fluid Mixing},\n type = {article},\n year = {2016},\n keywords = {Compressible flows,DNS,Density fluctuations,Favre average,Homogeneous turbulence,Linear Interaction Approximation,Mixing,RANS,Rayleigh-Taylor,Reynolds stress,Richtmyer-Meshkov,Shear,Turbulence,Two-length scale,Two-time scale,Variable density},\n pages = {1-43},\n volume = {96},\n websites = {http://link.springer.com/10.1007/s10494-015-9643-z},\n month = {4},\n publisher = {Springer Netherlands},\n id = {cbacad99-a22a-316d-ba88-7841c0cd0d26},\n created = {2021-04-09T15:23:36.618Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:36.618Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.},\n bibtype = {article},\n author = {Schwarzkopf, J D and Livescu, D and Baltzer, J R and Gore, R A and Ristorcelli, J R},\n doi = {10.1007/s10494-015-9643-z},\n journal = {Flow, Turbulence and Combustion},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-29971-6_8\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016', 'http://link.springer.com/10.1007/978-3-319-29971-6_8', event);\">\n    Compression and heuristic caching for GPU particle tracing in turbulent vector fields.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Treib,  M.; Bürger,  K.; Wu,  J.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Communications in Computer and Information Science</i>, 598: 144-165.  2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-319-29971-6_8\"\n     onclick=\"log_download('treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016', 'http://link.springer.com/10.1007/978-3-319-29971-6_8', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Compression and heuristic caching for GPU particle tracing in turbulent vector fields [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-319-29971-6_8\"\n     onclick=\"log_download('treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016', 'http://doi.org/10.1007/978-3-319-29971-6_8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('treib-brger-wu-westermann-compressionandheuristiccachingforgpuparticletracinginturbulentvectorfields-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Compression and heuristic caching for GPU particle tracing in turbulent vector fields},\n type = {article},\n year = {2016},\n keywords = {Data compression,Data streaming,Particle tracing,Turbulence,Vector fields},\n pages = {144-165},\n volume = {598},\n websites = {http://link.springer.com/10.1007/978-3-319-29971-6_8},\n publisher = {Springer, Cham},\n id = {c967ab18-170c-3561-9b15-cf0969b9566f},\n created = {2021-04-09T15:23:40.216Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:40.216Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© Springer International Publishing Switzerland 2016. Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.},\n bibtype = {article},\n author = {Treib, Marc and Bürger, Kai and Wu, Jun and Westermann, Rüdiger},\n doi = {10.1007/978-3-319-29971-6_8},\n journal = {Communications in Computer and Information Science}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © Springer International Publishing Switzerland 2016. Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0097849316300899\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016', 'https://www.sciencedirect.com/science/article/pii/S0097849316300899', event);\">\n    Line density control in screen-space via balanced line hierarchies.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kanzler,  M.; Ferstl,  F.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Graphics</i>, 61: 29-39. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0097849316300899\"\n     onclick=\"log_download('kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016', 'https://www.sciencedirect.com/science/article/pii/S0097849316300899', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Line density control in screen-space via balanced line hierarchies [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.cag.2016.08.001\"\n     onclick=\"log_download('kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016', 'http://doi.org/10.1016/j.cag.2016.08.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('kanzler-ferstl-westermann-linedensitycontrolinscreenspaceviabalancedlinehierarchies-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Line density control in screen-space via balanced line hierarchies},\n type = {article},\n year = {2016},\n keywords = {Flow visualization,Focus + Context,Line fields,Line hierarchy,Scientific visualization},\n pages = {29-39},\n volume = {61},\n websites = {https://www.sciencedirect.com/science/article/pii/S0097849316300899},\n month = {4},\n publisher = {Pergamon},\n id = {02127f1b-afa6-31a9-ad0b-875309b32cf3},\n created = {2021-04-09T15:23:44.570Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:44.570Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {For the visualization of dense sets of 3D lines, view-dependent approaches have been proposed to avoid the occlusion of important structures. Popular concepts consider global line selection based on line importance and screen-space occupancy, and opacity optimization to resolve locally the occlusion problem. In this work, we present a novel approach to improve the spatial perception and enable the interactive visualization of large 3D line sets. Instead of making lines locally transparent, which affects a lines spatial perception and can obscure spatial relationships, we propose to adapt the line density based on line importance and screen-space occupancy. In contrast to global line selection, however, our adaptation is local and only thins out the lines where significant occlusions occur. To achieve this we present a novel approach based on minimum cost perfect matching to construct an optimal, fully balanced line hierarchy. For determining locally the desired line density, we propose a projection-based screen-space measure considering the variation in line direction, line coverage, importance, and depth. This measure can be computed in an order-independent way and evaluated efficiently on the GPU.},\n bibtype = {article},\n author = {Kanzler, Mathias and Ferstl, Florian and Westermann, Rüdiger},\n doi = {10.1016/j.cag.2016.08.001},\n journal = {Computers and Graphics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  For the visualization of dense sets of 3D lines, view-dependent approaches have been proposed to avoid the occlusion of important structures. Popular concepts consider global line selection based on line importance and screen-space occupancy, and opacity optimization to resolve locally the occlusion problem. In this work, we present a novel approach to improve the spatial perception and enable the interactive visualization of large 3D line sets. Instead of making lines locally transparent, which affects a lines spatial perception and can obscure spatial relationships, we propose to adapt the line density based on line importance and screen-space occupancy. In contrast to global line selection, however, our adaptation is local and only thins out the lines where significant occlusions occur. To achieve this we present a novel approach based on minimum cost perfect matching to construct an optimal, fully balanced line hierarchy. For determining locally the desired line density, we propose a projection-based screen-space measure considering the variation in line direction, line coverage, importance, and depth. This measure can be computed in an order-independent way and evaluated efficiently on the GPU.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005516\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005516', event);\">\n    A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  P., L.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 804: 387-419. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005516\"\n     onclick=\"log_download('johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005516', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2016.551\"\n     onclick=\"log_download('johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016', 'http://doi.org/10.1017/jfm.2016.551', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-meneveau-aclosureforlagrangianvelocitygradientevolutioninturbulenceusingrecentdeformationmappingofinitiallygaussianfields-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A closure for Lagrangian velocity gradient evolution in turbulence using recent-deformation mapping of initially Gaussian fields},\n type = {article},\n year = {2016},\n keywords = {isotropic turbulence,turbulence modelling,turbulent flows},\n pages = {387-419},\n volume = {804},\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005516},\n month = {4},\n id = {058be0e8-0927-31b3-a73c-e061a85b4271},\n created = {2021-04-09T15:23:53.201Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:53.201Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The statistics of the velocity gradient tensor in turbulent flows are of both theoretical and practical importance. The Lagrangian view provides a privileged perspective for studying the dynamics of turbulence in general, and of the velocity gradient tensor in particular. Stochastic models for the Lagrangian evolution of velocity gradients in isotropic turbulence, with closure models for the pressure Hesssian and viscous Laplacian, have been shown to reproduce important features such as non-Gaussian probability distributions, skewness and vorticity strain-rate alignments. The Recent Fluid Deformation (RFD) closure introduced the idea of mapping an isotropic Lagrangian pressure Hessian as upstream initial condition using the fluid deformation tensor. Recent work on a Gaussian fields closure, however, has shown that even Gaussian isotropic velocity fields contain significant anisotropy for the conditional pressure Hessian tensor due to the inherent velocity-pressure couplings, and that assuming an isotropic pressure Hessian as upstream condition may not be realistic. In this paper, Gaussian isotropic field statistics are used to generate more physical upstream conditions for the recent fluid deformation mapping. In this new framework, known isotropy relations can be satisfied  a priori and no DNS-tuned coefficients are necessary. A detailed comparison of results from the new model, referred to as the recent deformation of Gaussian fields (RDGF) closure, with existing models and DNS shows the improvements gained, especially in various single-time statistics of the velocity gradient tensor at moderate Reynolds numbers. Application to arbitrarily high Reynolds numbers remains an open challenge for this type of model, however.},\n bibtype = {article},\n author = {Johnson, Perry L and Meneveau, Charles},\n doi = {10.1017/jfm.2016.551},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The statistics of the velocity gradient tensor in turbulent flows are of both theoretical and practical importance. The Lagrangian view provides a privileged perspective for studying the dynamics of turbulence in general, and of the velocity gradient tensor in particular. Stochastic models for the Lagrangian evolution of velocity gradients in isotropic turbulence, with closure models for the pressure Hesssian and viscous Laplacian, have been shown to reproduce important features such as non-Gaussian probability distributions, skewness and vorticity strain-rate alignments. The Recent Fluid Deformation (RFD) closure introduced the idea of mapping an isotropic Lagrangian pressure Hessian as upstream initial condition using the fluid deformation tensor. Recent work on a Gaussian fields closure, however, has shown that even Gaussian isotropic velocity fields contain significant anisotropy for the conditional pressure Hessian tensor due to the inherent velocity-pressure couplings, and that assuming an isotropic pressure Hessian as upstream condition may not be realistic. In this paper, Gaussian isotropic field statistics are used to generate more physical upstream conditions for the recent fluid deformation mapping. In this new framework, known isotropy relations can be satisfied  a priori and no DNS-tuned coefficients are necessary. A detailed comparison of results from the new model, referred to as the recent deformation of Gaussian fields (RDGF) closure, with existing models and DNS shows the improvements gained, especially in various single-time statistics of the velocity gradient tensor at moderate Reynolds numbers. Application to arbitrarily high Reynolds numbers remains an open challenge for this type of model, however.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2173-1\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016', 'http://link.springer.com/10.1007/s00348-016-2173-1', event);\">\n    Main results of the 4th International PIV Challenge.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Kähler,  C., J.; Astarita,  T.; Vlachos,  P., P.; Sakakibara,  J.; Hain,  R.; Discetti,  S.; Foy,  R., L.;  and Cierpka,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 57(6): 97. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-016-2173-1\"\n     onclick=\"log_download('khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016', 'http://link.springer.com/10.1007/s00348-016-2173-1', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Main results of the 4th International PIV Challenge [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-016-2173-1\"\n     onclick=\"log_download('khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016', 'http://doi.org/10.1007/s00348-016-2173-1', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('khler-astarita-vlachos-sakakibara-hain-discetti-foy-cierpka-mainresultsofthe4thinternationalpivchallenge-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Main results of the 4th International PIV Challenge},\n type = {article},\n year = {2016},\n pages = {97},\n volume = {57},\n websites = {http://link.springer.com/10.1007/s00348-016-2173-1},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {df1350f7-41d2-3e6d-902b-cadcc3b62429},\n created = {2021-04-09T15:23:57.952Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:57.952Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In the last decade, worldwide PIV development have resulted in significant improvements in terms accuracy, resolution, dynamic range and extension to dimensions. To assess the achievements and to guide development efforts, an International PIV Challenge performed in Lisbon (Portugal) on July 5, 2014. leading participants, including the major system, i.e., Dantec (Denmark), LaVision (Germany), (China), PIVTEC (Germany), TSI (USA), have 5 cases. The cases and analysis explore challenges to 2D microscopic PIV (case A), 2D timeresolved (case B), 3D tomographic PIV (cases C and) and stereoscopic PIV (case E). During the event, 2D PIV images (case F) were provided to all 80 of the workshop in Lisbon, with the aim to assess impact of the user’s experience on the evaluation result. paper describes the cases and specific algorithms evaluation parameters applied by the participants and reviews the main results. For future analysis and comparison, full image database},\n bibtype = {article},\n author = {Kähler, Christian J and Astarita, Tommaso and Vlachos, Pavlos P and Sakakibara, Jun and Hain, Rainer and Discetti, Stefano and Foy, Roderick La and Cierpka, Christian},\n doi = {10.1007/s00348-016-2173-1},\n journal = {Experiments in Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In the last decade, worldwide PIV development have resulted in significant improvements in terms accuracy, resolution, dynamic range and extension to dimensions. To assess the achievements and to guide development efforts, an International PIV Challenge performed in Lisbon (Portugal) on July 5, 2014. leading participants, including the major system, i.e., Dantec (Denmark), LaVision (Germany), (China), PIVTEC (Germany), TSI (USA), have 5 cases. The cases and analysis explore challenges to 2D microscopic PIV (case A), 2D timeresolved (case B), 3D tomographic PIV (cases C and) and stereoscopic PIV (case E). During the event, 2D PIV images (case F) were provided to all 80 of the workshop in Lisbon, with the aim to assess impact of the user’s experience on the evaluation result. paper describes the cases and specific algorithms evaluation parameters applied by the participants and reviews the main results. For future analysis and comparison, full image database\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-015-2110-8\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016', 'http://link.springer.com/10.1007/s00348-015-2110-8', event);\">\n    Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Masullo,  A.;  and Theunissen,  R.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 57(3): 1-21. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-015-2110-8\"\n     onclick=\"log_download('masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016', 'http://link.springer.com/10.1007/s00348-015-2110-8', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-015-2110-8\"\n     onclick=\"log_download('masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016', 'http://doi.org/10.1007/s00348-015-2110-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('masullo-theunissen-adaptivevectorvalidationinimagevelocimetrytominimisetheinfluenceofoutlierclusters-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters},\n type = {article},\n year = {2016},\n pages = {1-21},\n volume = {57},\n websites = {http://link.springer.com/10.1007/s00348-015-2110-8},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {f3a9a6ab-3a9a-3167-8cfb-b879798e7980},\n created = {2021-04-09T15:24:18.620Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:18.620Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© 2016, The Author(s). The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096–1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.},\n bibtype = {article},\n author = {Masullo, Alessandro and Theunissen, Raf},\n doi = {10.1007/s00348-015-2110-8},\n journal = {Experiments in Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2016, The Author(s). The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096–1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005292\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005292', event);\">\n    Small-scale anisotropy in turbulent boundary layers.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pumir,  A.; Xu,  H.;  and Siggia,  E., D.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 804: 5-23. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112016005292\"\n     onclick=\"log_download('pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016', 'http://www.journals.cambridge.org/abstract_S0022112016005292', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Small-scale anisotropy in turbulent boundary layers [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2016.529\"\n     onclick=\"log_download('pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016', 'http://doi.org/10.1017/jfm.2016.529', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pumir-xu-siggia-smallscaleanisotropyinturbulentboundarylayers-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Small-scale anisotropy in turbulent boundary layers},\n type = {article},\n year = {2016},\n keywords = {turbulence theory,turbulent boundary layers,turbulent flows},\n pages = {5-23},\n volume = {804},\n websites = {http://www.journals.cambridge.org/abstract_S0022112016005292},\n month = {4},\n id = {d2a55492-2a18-3e31-81e7-c7585aa3805c},\n created = {2021-04-09T15:24:21.280Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:21.280Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ( Re_[STIX]x1D70F 1000 ), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is R_[STIX]x1D706 150 . This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of R_[STIX]x1D706 . In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.},\n bibtype = {article},\n author = {Pumir, Alain and Xu, Haitao and Siggia, Eric D},\n doi = {10.1017/jfm.2016.529},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In a channel flow, the velocity fluctuations are inhomogeneous and anisotropic. Yet, the small-scale properties of the flow are expected to behave in an isotropic manner in the very-large-Reynolds-number limit. We consider the statistical properties of small-scale velocity fluctuations in a turbulent channel flow at moderately high Reynolds number ( Re_[STIX]x1D70F 1000 ), using the Johns Hopkins University Turbulence Database. Away from the wall, in the logarithmic layer, the skewness of the normal derivative of the streamwise velocity fluctuation is approximately constant, of order 1, while the Reynolds number based on the Taylor scale is R_[STIX]x1D706 150 . This defines a small-scale anisotropy that is stronger than in turbulent homogeneous shear flows at comparable values of R_[STIX]x1D706 . In contrast, the vorticity–strain correlations that characterize homogeneous isotropic turbulence are nearly unchanged in channel flow even though they do vary with distance from the wall with an exponent that can be inferred from the local dissipation. Our results demonstrate that the statistical properties of the fluctuating velocity gradient in turbulent channel flow are characterized, on one hand, by observables that are insensitive to the anisotropy, and behave as in homogeneous isotropic flows, and on the other hand by quantities that are much more sensitive to the anisotropy. How this seemingly contradictory situation emerges from the simultaneous action of the flux of energy to small scales and the transport of momentum away from the wall remains to be elucidated.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.117.204501\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016', 'https://link.aps.org/doi/10.1103/PhysRevLett.117.204501', event);\">\n    Angular dynamics of a small particle in turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Candelier,  F.; Einarsson,  J.;  and Mehlig,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 117(20): 204501. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.117.204501\"\n     onclick=\"log_download('candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016', 'https://link.aps.org/doi/10.1103/PhysRevLett.117.204501', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Angular dynamics of a small particle in turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevLett.117.204501\"\n     onclick=\"log_download('candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016', 'http://doi.org/10.1103/PhysRevLett.117.204501', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('candelier-einarsson-mehlig-angulardynamicsofasmallparticleinturbulence-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Angular dynamics of a small particle in turbulence},\n type = {article},\n year = {2016},\n pages = {204501},\n volume = {117},\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.117.204501},\n month = {4},\n id = {9868f702-ead3-3e01-8357-e5578df0b81f},\n created = {2021-04-09T15:24:34.259Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:34.259Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We compute the angular dynamics of a neutrally buoyant nearly spherical particle immersed in an unsteady fluid. We assume that the particle is small, that its translational slip velocity is negligible, and that unsteady and convective inertia are small perturbations. We derive an approximation for the torque on the particle that determines the first inertial corrections to Jeffery&#x27;s equation. These corrections arise as a consequence of local vortex stretching, and can be substantial in turbulence where local vortex stretching is strong and closely linked to the irreversibility of turbulence.},\n bibtype = {article},\n author = {Candelier, F and Einarsson, J and Mehlig, B},\n doi = {10.1103/PhysRevLett.117.204501},\n journal = {Physical Review Letters},\n number = {20}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We compute the angular dynamics of a neutrally buoyant nearly spherical particle immersed in an unsteady fluid. We assume that the particle is small, that its translational slip velocity is negligible, and that unsteady and convective inertia are small perturbations. We derive an approximation for the torque on the particle that determines the first inertial corrections to Jeffery's equation. These corrections arise as a consequence of local vortex stretching, and can be substantial in turbulence where local vortex stretching is strong and closely linked to the irreversibility of turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016', 'http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512', event);\">\n    A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chapelier,  J., B.; Lodato,  G.;  and Jameson,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Computers and Fluids</i>, 139: 261-280. 4 2016.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512\"\n     onclick=\"log_download('chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016', 'http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.compfluid.2016.03.006\"\n     onclick=\"log_download('chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016', 'http://doi.org/10.1016/j.compfluid.2016.03.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chapelier-lodato-jameson-astudyonthenumericaldissipationofthespectraldifferencemethodforfreelydecayingandwallboundedturbulence-2016')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A study on the numerical dissipation of the Spectral Difference method for freely decaying and wall-bounded turbulence},\n type = {article},\n year = {2016},\n keywords = {High-order methods,Large-Eddy simulation,Spectral Difference method},\n pages = {261-280},\n volume = {139},\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S0045793016300512},\n month = {4},\n id = {eb50f798-2dbb-3002-b3d1-ac088b613ddd},\n created = {2021-04-09T15:24:39.658Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:39.658Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper aims at understanding the numerical dissipation mechanisms related to the Spectral Difference (SD) method in the context of three-dimensional (3D) turbulence. The numerical dissipation stemming from the discretization of the convective terms is studied by performing inviscid computations of the transitional Taylor–Green vortex and isotropic turbulence configurations. The Taylor–Green vortex computations show that the increase in the order of accuracy restricts the numerical dissipation to smaller scales which, in turn, leads to a better representation of transitional mechanisms. However, isotropic turbulence computations using a fifth-order accuracy or above show obvious manifestations of under-resolution (such as the onset of oscillations and numerical noise), which suggests that the high-order numerical dissipation alone is unable to mimic the dissipation originating from sub-grid scales in the case freely decaying turbulence. Computations of the channel flow configuration at Reτ=1000 at typical large-eddy simulation resolutions show that under-resolved SD discretizations using a high order of accuracy (fifth and sixth) lead to an excellent prediction of the wall-friction, the velocity profiles, the turbulent structures near the wall and the energy spectra, while lower order discretizations lead to an underestimation of the wall-friction and globally a poor representation of wall-bounded turbulence. The present study emphasizes the benefit of using high-order SD discretizations for an accurate representation of turbulent phenomena (namely, transitional and wall-bounded turbulence) but also the necessity of combining this approach with dynamic large-eddy simulation models or appropriate regularization techniques which would activate only where needed to recover physically consistent results, e.g., in regions where fully developed turbulence is present.},\n bibtype = {article},\n author = {Chapelier, J B and Lodato, G and Jameson, A},\n doi = {10.1016/j.compfluid.2016.03.006},\n journal = {Computers and Fluids}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper aims at understanding the numerical dissipation mechanisms related to the Spectral Difference (SD) method in the context of three-dimensional (3D) turbulence. The numerical dissipation stemming from the discretization of the convective terms is studied by performing inviscid computations of the transitional Taylor–Green vortex and isotropic turbulence configurations. The Taylor–Green vortex computations show that the increase in the order of accuracy restricts the numerical dissipation to smaller scales which, in turn, leads to a better representation of transitional mechanisms. However, isotropic turbulence computations using a fifth-order accuracy or above show obvious manifestations of under-resolution (such as the onset of oscillations and numerical noise), which suggests that the high-order numerical dissipation alone is unable to mimic the dissipation originating from sub-grid scales in the case freely decaying turbulence. Computations of the channel flow configuration at Reτ=1000 at typical large-eddy simulation resolutions show that under-resolved SD discretizations using a high order of accuracy (fifth and sixth) lead to an excellent prediction of the wall-friction, the velocity profiles, the turbulent structures near the wall and the energy spectra, while lower order discretizations lead to an underestimation of the wall-friction and globally a poor representation of wall-bounded turbulence. The present study emphasizes the benefit of using high-order SD discretizations for an accurate representation of turbulent phenomena (namely, transitional and wall-bounded turbulence) but also the necessity of combining this approach with dynamic large-eddy simulation models or appropriate regularization techniques which would activate only where needed to recover physically consistent results, e.g., in regions where fully developed turbulence is present.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2015\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2015')\"\n      onkeypress=\"toggleGroup('group_2015')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2015</span>\n      <span class=\"bibbase_group_count\">\n        \n        (11)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-015-1940-8\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015', 'http://link.springer.com/10.1007/s00348-015-1940-8', event);\">\n    On PIV random error minimization with optimal POD-based low-order reconstruction.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Raiola,  M.; Discetti,  S.;  and Ianiro,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 56(4): 75. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-015-1940-8\"\n     onclick=\"log_download('raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015', 'http://link.springer.com/10.1007/s00348-015-1940-8', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On PIV random error minimization with optimal POD-based low-order reconstruction [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-015-1940-8\"\n     onclick=\"log_download('raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015', 'http://doi.org/10.1007/s00348-015-1940-8', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('raiola-discetti-ianiro-onpivrandomerrorminimizationwithoptimalpodbasedloworderreconstruction-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On PIV random error minimization with optimal POD-based low-order reconstruction},\n type = {article},\n year = {2015},\n pages = {75},\n volume = {56},\n websites = {http://link.springer.com/10.1007/s00348-015-1940-8},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {e02969e8-fdd8-3b3d-8ee5-c7c59492f1d8},\n created = {2021-04-09T15:23:20.692Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:20.692Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© 2015, Springer-Verlag Berlin Heidelberg. Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows.},\n bibtype = {article},\n author = {Raiola, Marco and Discetti, Stefano and Ianiro, Andrea},\n doi = {10.1007/s00348-015-1940-8},\n journal = {Experiments in Fluids},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2015, Springer-Verlag Berlin Heidelberg. Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.osti.gov/servlets/purl/1221181/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015', 'http://www.osti.gov/servlets/purl/1221181/', event);\">\n    Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Templeton,  J., A.; Blaylock,  M., L.; Domino,  S., P.; Hewson,  J., C.; Kumar,  P., R.; Ling,  J.; Najm,  H., N.; Ruiz,  A.; Safta,  C.; Sargsyan,  K.; Stewart,  A.;  and Wagner,  G.\n</span>\n\n  \n\n</span>\n\n  4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.osti.gov/servlets/purl/1221181/\"\n     onclick=\"log_download('templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015', 'http://www.osti.gov/servlets/purl/1221181/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2172/1221181\"\n     onclick=\"log_download('templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015', 'http://doi.org/10.2172/1221181', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('templeton-blaylock-domino-hewson-kumar-ling-najm-ruiz-etal-calibrationandforwarduncertaintypropagationforlargeeddysimulationsofengineeringflows-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows},\n type = {misc},\n year = {2015},\n websites = {http://www.osti.gov/servlets/purl/1221181/},\n month = {4},\n institution = {Sandia National Laboratories (SNL)},\n id = {92304c26-4a57-3361-b9af-462cc2475259},\n created = {2021-04-09T15:23:21.473Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:21.473Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {report},\n private_publication = {false},\n bibtype = {misc},\n author = {Templeton, Jeremy Alan and Blaylock, Myra L and Domino, Stefan P and Hewson, John C and Kumar, Pritvi Raj and Ling, Julia and Najm, Habib N and Ruiz, Anthony and Safta, Cosmin and Sargsyan, Khachik and Stewart, Alessia and Wagner, Gregory},\n doi = {10.2172/1221181}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevB.91.104517\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015', 'https://link.aps.org/doi/10.1103/PhysRevB.91.104517', event);\">\n    Local and nonlocal dynamics in superfluid turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Sherwin-Robson,  L., K.; Barenghi,  C., F.;  and Baggaley,  A., W.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review B</i>, 91(10): 104517. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevB.91.104517\"\n     onclick=\"log_download('sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015', 'https://link.aps.org/doi/10.1103/PhysRevB.91.104517', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Local and nonlocal dynamics in superfluid turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevB.91.104517\"\n     onclick=\"log_download('sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015', 'http://doi.org/10.1103/PhysRevB.91.104517', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>6 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('sherwinrobson-barenghi-baggaley-localandnonlocaldynamicsinsuperfluidturbulence-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Local and nonlocal dynamics in superfluid turbulence},\n type = {article},\n year = {2015},\n pages = {104517},\n volume = {91},\n websites = {https://link.aps.org/doi/10.1103/PhysRevB.91.104517},\n month = {4},\n publisher = {American Physical Society},\n id = {7bb1275f-e165-3b14-a23e-732c494ccda4},\n created = {2021-04-09T15:23:27.432Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:27.432Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Turbulence in superfluid helium~II is a tangle of quantized vortex lines which interact via the classical Biot-Savart law. We show that vortex tangles with the same vortex line density will have different energy spectra, depending on the normal fluid which feeds energy into the superfluid component, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the &#x27;worms&#x60; of ordinary turbulence.},\n bibtype = {article},\n author = {Sherwin-Robson, L K and Barenghi, C F and Baggaley, A W},\n doi = {10.1103/PhysRevB.91.104517},\n journal = {Physical Review B},\n number = {10}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Turbulence in superfluid helium~II is a tangle of quantized vortex lines which interact via the classical Biot-Savart law. We show that vortex tangles with the same vortex line density will have different energy spectra, depending on the normal fluid which feeds energy into the superfluid component, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the 'worms` of ordinary turbulence.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4928699\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4928699', event);\">\n    Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Johnson,  P., L.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 27(8): 85110. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4928699\"\n     onclick=\"log_download('johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4928699', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.4928699\"\n     onclick=\"log_download('johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015', 'http://doi.org/10.1063/1.4928699', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('johnson-meneveau-largedeviationjointstatisticsofthefinitetimelyapunovspectruminisotropicturbulence-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Large-deviation joint statistics of the finite-time Lyapunov spectrum in isotropic turbulence},\n type = {article},\n year = {2015},\n pages = {85110},\n volume = {27},\n websites = {http://aip.scitation.org/doi/10.1063/1.4928699},\n month = {4},\n id = {62e0a3b8-f203-3460-bb83-528b9ee3de45},\n created = {2021-04-09T15:23:49.861Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:49.861Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Johnson, Perry L and Meneveau, Charles},\n doi = {10.1063/1.4928699},\n journal = {Physics of Fluids},\n number = {8}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112015004528\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015', 'http://www.journals.cambridge.org/abstract_S0022112015004528', event);\">\n    On velocity gradient dynamics and turbulent structure.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lawson,  J., M.;  and Dawson,  J., R.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 780: 60-98. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112015004528\"\n     onclick=\"log_download('lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015', 'http://www.journals.cambridge.org/abstract_S0022112015004528', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On velocity gradient dynamics and turbulent structure [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2015.452\"\n     onclick=\"log_download('lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015', 'http://doi.org/10.1017/jfm.2015.452', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lawson-dawson-onvelocitygradientdynamicsandturbulentstructure-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On velocity gradient dynamics and turbulent structure},\n type = {article},\n year = {2015},\n keywords = {homogeneous turbulence,turbulence modelling,turbulent flows},\n pages = {60-98},\n volume = {780},\n websites = {http://www.journals.cambridge.org/abstract_S0022112015004528},\n month = {4},\n id = {9b621a34-c3f3-3ac7-b9dd-a490b7dff598},\n created = {2021-04-09T15:23:55.819Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:55.819Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The statistics of the velocity gradient tensor [STIX]x1D63C=u , which embody the fine scales of turbulence, are influenced by turbulent ‘structure’. Whilst velocity gradient statistics and dynamics have been well characterised, the connection between structure and dynamics has largely focused on rotation-dominated flow and relied upon data from numerical simulation alone. Using numerical and spatially resolved experimental datasets of homogeneous turbulence, the role of structure is examined for all local (incompressible) flow topologies characterisable by [STIX]x1D63C . Structures are studied through the footprints they leave in conditional averages of the Q=-Tr([STIX]x1D63C^2)/2 field, pertinent to non-local strain production, obtained using two complementary conditional averaging techniques. The first, stochastic estimation, approximates the Q field conditioned upon [STIX]x1D63C and educes quantitatively similar structure in both datasets, dissimilar to that of random Gaussian velocity fields. Moreover, it strongly resembles a promising model for velocity gradient dynamics recently proposed by Wilczek &amp;amp; Meneveau ( J. Fluid Mech. , vol. 756, 2014, pp. 191–225), but is derived under a less restrictive premise, with explicitly determined closure coefficients. The second technique examines true conditional averages of the Q field, which is used to validate the stochastic estimation and provide insights towards the model’s refinement. Jointly, these approaches confirm that vortex tubes are the predominant feature of rotation-dominated regions and additionally show that shear layer structures are active in strain-dominated regions. In both cases, kinematic features of these structures explain alignment statistics of the pressure Hessian eigenvectors and why local and non-local strain production act in opposition to each other.},\n bibtype = {article},\n author = {Lawson, J M and Dawson, J R},\n doi = {10.1017/jfm.2015.452},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The statistics of the velocity gradient tensor [STIX]x1D63C=u , which embody the fine scales of turbulence, are influenced by turbulent ‘structure’. Whilst velocity gradient statistics and dynamics have been well characterised, the connection between structure and dynamics has largely focused on rotation-dominated flow and relied upon data from numerical simulation alone. Using numerical and spatially resolved experimental datasets of homogeneous turbulence, the role of structure is examined for all local (incompressible) flow topologies characterisable by [STIX]x1D63C . Structures are studied through the footprints they leave in conditional averages of the Q=-Tr([STIX]x1D63C^2)/2 field, pertinent to non-local strain production, obtained using two complementary conditional averaging techniques. The first, stochastic estimation, approximates the Q field conditioned upon [STIX]x1D63C and educes quantitatively similar structure in both datasets, dissimilar to that of random Gaussian velocity fields. Moreover, it strongly resembles a promising model for velocity gradient dynamics recently proposed by Wilczek &amp; Meneveau ( J. Fluid Mech. , vol. 756, 2014, pp. 191–225), but is derived under a less restrictive premise, with explicitly determined closure coefficients. The second technique examines true conditional averages of the Q field, which is used to validate the stochastic estimation and provide insights towards the model’s refinement. Jointly, these approaches confirm that vortex tubes are the predominant feature of rotation-dominated regions and additionally show that shear layer structures are active in strain-dominated regions. In both cases, kinematic features of these structures explain alignment statistics of the pressure Hessian eigenvectors and why local and non-local strain production act in opposition to each other.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015', 'http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf', event);\">\n    Active Pointillistic Pattern Search.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Ma,  Y.; Sutherland,  D., J.; Garnett,  R.;  and Schneider,  J.\n</span>\n\n  \n\n</span>\n\n  In <i>AISTATS</i>, pages 672-680, 4 2015. \n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf\"\n     onclick=\"log_download('ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015', 'http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/pdf.svg\"\n\t     alt=\"Active Pointillistic Pattern Search [pdf]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('ma-sutherland-garnett-schneider-activepointillisticpatternsearch-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Active Pointillistic Pattern Search},\n type = {inproceedings},\n year = {2015},\n pages = {672-680},\n websites = {http://proceedings.mlr.press/v38/ma15.html,http://jmlr.org/proceedings/papers/v38/ma15.pdf},\n month = {4},\n id = {87abb4bb-fb22-349d-bf7c-053866f19df0},\n created = {2021-04-09T15:23:59.817Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:59.817Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {We introduce the problem of active pointillistic pattern search (APPS), which seeks to discover regions of a domain exhibiting desired behavior with limited observations. Unusually, the patterns we consider are defined by large-scale proper-ties of an underlying function that we can only observe at a limited number of points. Given a description of the desired patterns (in the form of a classifier taking functional inputs), we se-quentially decide where to query function values to identify as many regions matching the pattern as possible, with high confience. For one broad class of models the expected reward of each un-observed point can be computed analytically. We demonstrate the proposed algorithm on three dif-ficult search problems: locating polluted regions in a lake via mobile sensors, forecasting winning electoral districts with minimal polling, and iden-tifying vortices in a fluid flow simulation.},\n bibtype = {inproceedings},\n author = {Ma, Yifei and Sutherland, Dougal J and Garnett, Roman and Schneider, Jeff},\n booktitle = {AISTATS}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We introduce the problem of active pointillistic pattern search (APPS), which seeks to discover regions of a domain exhibiting desired behavior with limited observations. Unusually, the patterns we consider are defined by large-scale proper-ties of an underlying function that we can only observe at a limited number of points. Given a description of the desired patterns (in the form of a classifier taking functional inputs), we se-quentially decide where to query function values to identify as many regions matching the pattern as possible, with high confience. For one broad class of models the expected reward of each un-observed point can be computed analytically. We demonstrate the proposed algorithm on three dif-ficult search problems: locating polluted regions in a lake via mobile sensors, forecasting winning electoral districts with minimal polling, and iden-tifying vortices in a fluid flow simulation.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.115.025001\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015', 'https://link.aps.org/doi/10.1103/PhysRevLett.115.025001', event);\">\n    Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lalescu,  C., C.; Shi,  Y., K.; Eyink,  G., L.; Drivas,  T., D.; Vishniac,  E., T.;  and Lazarian,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 115(2): 25001. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.115.025001\"\n     onclick=\"log_download('lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015', 'https://link.aps.org/doi/10.1103/PhysRevLett.115.025001', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevLett.115.025001\"\n     onclick=\"log_download('lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015', 'http://doi.org/10.1103/PhysRevLett.115.025001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lalescu-shi-eyink-drivas-vishniac-lazarian-inertialrangereconnectioninmagnetohydrodynamicturbulenceandinthesolarwind-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Inertial-Range Reconnection in Magnetohydrodynamic Turbulence and in the Solar Wind},\n type = {article},\n year = {2015},\n pages = {25001},\n volume = {115},\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.115.025001},\n month = {4},\n id = {4a6557a7-2f59-3fed-9845-28f0b8412a15},\n created = {2021-04-09T15:24:07.560Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:07.560Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In situ spacecraft data on the solar wind show events identified as magnetic reconnection with wide outflows and extended “X lines,” 103–104 times ion scales. To understand the role of turbulence at these scales, we make a case study of an inertial-range reconnection event in a magnetohydrodynamic simulation. We observe stochastic wandering of field lines in space, breakdown of standard magnetic flux freezing due to Richardson dispersion, and a broadened reconnection zone containing many current sheets. The coarse-grain magnetic geometry is like large-scale reconnection in the solar wind, however, with a hyperbolic flux tube or apparent X line extending over integral length scales.},\n bibtype = {article},\n author = {Lalescu, Cristian C and Shi, Yi Kang and Eyink, Gregory L and Drivas, Theodore D and Vishniac, Ethan T and Lazarian, Alexander},\n doi = {10.1103/PhysRevLett.115.025001},\n journal = {Physical Review Letters},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In situ spacecraft data on the solar wind show events identified as magnetic reconnection with wide outflows and extended “X lines,” 103–104 times ion scales. To understand the role of turbulence at these scales, we make a case study of an inertial-range reconnection event in a magnetohydrodynamic simulation. We observe stochastic wandering of field lines in space, breakdown of standard magnetic flux freezing due to Richardson dispersion, and a broadened reconnection zone containing many current sheets. The coarse-grain magnetic geometry is like large-scale reconnection in the solar wind, however, with a hyperbolic flux tube or apparent X line extending over integral length scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4936140\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4936140', event);\">\n    Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fang,  L.; Bos,  W., J., T.;  and Jin,  G., D.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 27(12): 125102. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4936140\"\n     onclick=\"log_download('fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4936140', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.4936140\"\n     onclick=\"log_download('fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015', 'http://doi.org/10.1063/1.4936140', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fang-bos-jin-shorttimeevolutionoflagrangianvelocitygradientcorrelationsinisotropicturbulence-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Short-time evolution of Lagrangian velocity gradient correlations in isotropic turbulence},\n type = {article},\n year = {2015},\n pages = {125102},\n volume = {27},\n websites = {http://aip.scitation.org/doi/10.1063/1.4936140},\n month = {4},\n id = {f140aa79-c55c-3afc-8d4e-6b5afcb58f77},\n created = {2021-04-09T15:24:09.828Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:09.828Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {© 2015 AIP Publishing LLC. We show by direct numerical simulation (DNS) that the Lagrangian cross correlation of velocity gradients in homogeneous isotropic turbulence increases at short times, whereas its auto-correlation decreases. Kinematic considerations allow to show that two invariants of the turbulent velocity field determine the short-time velocity gradient correlations. In order to get a more intuitive understanding of the dynamics for longer times, heuristic models are proposed involving the combined action of local shear and rotation. These models quantitatively reproduce the effects and disentangle the different physical mechanisms leading to the observations in the DNS.},\n bibtype = {article},\n author = {Fang, L and Bos, W J T and Jin, G D},\n doi = {10.1063/1.4936140},\n journal = {Physics of Fluids},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  © 2015 AIP Publishing LLC. We show by direct numerical simulation (DNS) that the Lagrangian cross correlation of velocity gradients in homogeneous isotropic turbulence increases at short times, whereas its auto-correlation decreases. Kinematic considerations allow to show that two invariants of the turbulent velocity field determine the short-time velocity gradient correlations. In order to get a more intuitive understanding of the dynamics for longer times, heuristic models are proposed involving the combined action of local shear and rotation. These models quantitatively reproduce the effects and disentangle the different physical mechanisms leading to the observations in the DNS.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4913501\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4913501', event);\">\n    Shape-dependence of particle rotation in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Byron,  M.; Einarsson,  J.; Gustavsson,  K.; Voth,  G.; Mehlig,  B.;  and Variano,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 27(3): 35101. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4913501\"\n     onclick=\"log_download('byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015', 'http://aip.scitation.org/doi/10.1063/1.4913501', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Shape-dependence of particle rotation in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.4913501\"\n     onclick=\"log_download('byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015', 'http://doi.org/10.1063/1.4913501', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('byron-einarsson-gustavsson-voth-mehlig-variano-shapedependenceofparticlerotationinisotropicturbulence-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Shape-dependence of particle rotation in isotropic turbulence},\n type = {article},\n year = {2015},\n pages = {35101},\n volume = {27},\n websites = {http://aip.scitation.org/doi/10.1063/1.4913501},\n month = {4},\n id = {fcd7cc5c-da75-3d52-a57a-f3d9ead99673},\n created = {2021-04-09T15:24:10.552Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:10.552Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We consider the rotation of neutrally buoyant axisymmetric particles suspended in isotropic turbulence. Using laboratory experiments as well as numerical and analytical calculations, we explore how particle rotation depends upon particle shape. We find that shape strongly affects orientational trajectories, but that it has negligible effect on the variance of the particle angular velocity. Previous work has shown that shape significantly affects the variance of the tumbling rate of axisymmetric particles. It follows that shape affects the spinning rate in a way that is, on average, complementary to the shape-dependence of the tumbling rate. We confirm this relationship using direct numerical simulations, showing how tumbling rate and spinning rate variances show complementary trends for rod-shaped and disk-shaped particles. We also consider a random but non-turbulent flow. This allows us to explore which of the features observed for rotation in turbulent flow are due to the effects of particle alignment in vortex tubes.},\n bibtype = {article},\n author = {Byron, M and Einarsson, J and Gustavsson, K and Voth, G and Mehlig, B and Variano, E},\n doi = {10.1063/1.4913501},\n journal = {Physics of Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We consider the rotation of neutrally buoyant axisymmetric particles suspended in isotropic turbulence. Using laboratory experiments as well as numerical and analytical calculations, we explore how particle rotation depends upon particle shape. We find that shape strongly affects orientational trajectories, but that it has negligible effect on the variance of the particle angular velocity. Previous work has shown that shape significantly affects the variance of the tumbling rate of axisymmetric particles. It follows that shape affects the spinning rate in a way that is, on average, complementary to the shape-dependence of the tumbling rate. We confirm this relationship using direct numerical simulations, showing how tumbling rate and spinning rate variances show complementary trends for rod-shaped and disk-shaped particles. We also consider a random but non-turbulent flow. This allows us to explore which of the features observed for rotation in turbulent flow are due to the effects of particle alignment in vortex tubes.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://arc.aiaa.org/doi/10.2514/6.2016-3403\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015', 'http://arc.aiaa.org/doi/10.2514/6.2016-3403', event);\">\n    Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  X.; Siddle-mitchel,  S.; Rybarczyk,  R.;  and Katz,  J.\n</span>\n\n  \n\n</span>\n\n  <i>32nd AIAA Aerodynamic Measurement Technology and Ground Testing Conference</i>,1-11. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://arc.aiaa.org/doi/10.2514/6.2016-3403\"\n     onclick=\"log_download('liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015', 'http://arc.aiaa.org/doi/10.2514/6.2016-3403', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.2514/6.2016-3403\"\n     onclick=\"log_download('liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015', 'http://doi.org/10.2514/6.2016-3403', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-siddlemitchel-rybarczyk-katz-investigationoftheinfluenceofthesubgridscalestressonnonintrusivespatialpressuremeasurementusinganisotropicturbulencedatabase-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Investigation of the influence of the subgrid-scale stress on non-intrusive spatial pressure measurement using an isotropic turbulence database},\n type = {article},\n year = {2015},\n pages = {1-11},\n websites = {http://arc.aiaa.org/doi/10.2514/6.2016-3403},\n month = {4},\n publisher = {American Institute of Aeronautics and Astronautics},\n id = {719dacb2-6fd9-3d09-a4d7-a80d14f4bac6},\n created = {2021-04-09T15:24:31.394Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:31.394Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Liu, Xiaofeng and Siddle-mitchel, Seth and Rybarczyk, Rachel and Katz, Joseph},\n doi = {10.2514/6.2016-3403},\n journal = {32nd AIAA Aerodynamic Measurement Technology and Ground Testing Conference}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00024-014-0874-z\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015', 'http://link.springer.com/10.1007/s00024-014-0874-z', event);\">\n    Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic Web.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Chang,  T.; chin Wu,  C.; Echim,  M.; Lamy,  H.; Vogelsberger,  M.; Hernquist,  L.;  and Sijacki,  D.\n</span>\n\n  \n\n</span>\n\n  <i>Pure and Applied Geophysics</i>, 172(7): 2025-2043. 4 2015.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00024-014-0874-z\"\n     onclick=\"log_download('chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015', 'http://link.springer.com/10.1007/s00024-014-0874-z', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic Web [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00024-014-0874-z\"\n     onclick=\"log_download('chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015', 'http://doi.org/10.1007/s00024-014-0874-z', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('chang-chinwu-echim-lamy-vogelsberger-hernquist-sijacki-complexityphenomenaandromaoftheearthsmagnetosphericcusphydrodynamicturbulenceandthecosmicweb-2015')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Complexity Phenomena and ROMA of the Earth’s Magnetospheric Cusp, Hydrodynamic Turbulence, and the Cosmic Web},\n type = {article},\n year = {2015},\n keywords = {Fractals,ROMA,cosmic gas,fluid turbulence,magnetospheric cusp},\n pages = {2025-2043},\n volume = {172},\n websites = {http://link.springer.com/10.1007/s00024-014-0874-z},\n month = {4},\n publisher = {Springer Basel},\n id = {b553ef8e-fc2f-38f3-a3c1-dacf3828984f},\n created = {2021-04-09T15:24:41.947Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:41.947Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Chang, Tom and chin Wu, Cheng and Echim, Marius and Lamy, Hervé and Vogelsberger, Mark and Hernquist, Lars and Sijacki, Debora},\n doi = {10.1007/s00024-014-0874-z},\n journal = {Pure and Applied Geophysics},\n number = {7}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2014\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2014')\"\n      onkeypress=\"toggleGroup('group_2014')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2014</span>\n      <span class=\"bibbase_group_count\">\n        \n        (7)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.112.014501\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014', 'https://link.aps.org/doi/10.1103/PhysRevLett.112.014501', event);\">\n    Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gustavsson,  K.; Einarsson,  J.;  and Mehlig,  B.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 112(1): 14501. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.112.014501\"\n     onclick=\"log_download('gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014', 'https://link.aps.org/doi/10.1103/PhysRevLett.112.014501', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevLett.112.014501\"\n     onclick=\"log_download('gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014', 'http://doi.org/10.1103/PhysRevLett.112.014501', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gustavsson-einarsson-mehlig-tumblingofsmallaxisymmetricparticlesinrandomandturbulentflows-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Tumbling of Small Axisymmetric Particles in Random and Turbulent Flows},\n type = {article},\n year = {2014},\n pages = {14501},\n volume = {112},\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.112.014501},\n month = {4},\n publisher = {American Physical Society},\n id = {3894f9ae-c4f5-365a-9482-522b9a30d427},\n created = {2021-04-09T15:23:23.153Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:23.153Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of Lagrangian correlation functions. These capture preferential sampling of the fluid gradients which in turn can give rise to differences in the tumbling rates of disks and rods. We show that this is a weak effect in Gaussian random flows. But in turbulent flows persistent regions of high vorticity cause disks to tumble much faster than rods, as observed in direct numerical simulations [Parsa et al., Phys. Rev. Lett. 109 (2012) 134501]. For larger particles (at finite Stokes numbers), rotational and translational inertia affects the tumbling rate and the angle at which particles collide, due to the formation of rotational caustics.},\n bibtype = {article},\n author = {Gustavsson, K and Einarsson, J and Mehlig, B},\n doi = {10.1103/PhysRevLett.112.014501},\n journal = {Physical Review Letters},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of Lagrangian correlation functions. These capture preferential sampling of the fluid gradients which in turn can give rise to differences in the tumbling rates of disks and rods. We show that this is a weak effect in Gaussian random flows. But in turbulent flows persistent regions of high vorticity cause disks to tumble much faster than rods, as observed in direct numerical simulations [Parsa et al., Phys. Rev. Lett. 109 (2012) 134501]. For larger particles (at finite Stokes numbers), rotational and translational inertia affects the tumbling rate and the angle at which particles collide, due to the formation of rotational caustics.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4871106\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014', 'http://aip.scitation.org/doi/10.1063/1.4871106', event);\">\n    Kolmogorov spectrum consistent optimization for multi-scale flow decomposition.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Mishra,  M.; Liu,  X.; Skote,  M.;  and Fu,  C., W.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 26(5): 55106. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.4871106\"\n     onclick=\"log_download('mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014', 'http://aip.scitation.org/doi/10.1063/1.4871106', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Kolmogorov spectrum consistent optimization for multi-scale flow decomposition [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.4871106\"\n     onclick=\"log_download('mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014', 'http://doi.org/10.1063/1.4871106', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('mishra-liu-skote-fu-kolmogorovspectrumconsistentoptimizationformultiscaleflowdecomposition-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Kolmogorov spectrum consistent optimization for multi-scale flow decomposition},\n type = {article},\n year = {2014},\n pages = {55106},\n volume = {26},\n websites = {http://aip.scitation.org/doi/10.1063/1.4871106},\n month = {4},\n id = {489c5ab7-e1ff-3915-994f-e4aae3de0d50},\n created = {2021-04-09T15:23:25.571Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:25.571Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide ...},\n bibtype = {article},\n author = {Mishra, M and Liu, X and Skote, M and Fu, C W},\n doi = {10.1063/1.4871106},\n journal = {Physics of Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide ...\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.113.054501\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014', 'https://link.aps.org/doi/10.1103/PhysRevLett.113.054501', event);\">\n    Time-reversal-symmetry breaking in turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Jucha,  J.; Xu,  H.; Pumir,  A.;  and Bodenschatz,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review Letters</i>, 113(5): 54501. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevLett.113.054501\"\n     onclick=\"log_download('jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014', 'https://link.aps.org/doi/10.1103/PhysRevLett.113.054501', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Time-reversal-symmetry breaking in turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevLett.113.054501\"\n     onclick=\"log_download('jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014', 'http://doi.org/10.1103/PhysRevLett.113.054501', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('jucha-xu-pumir-bodenschatz-timereversalsymmetrybreakinginturbulence-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Time-reversal-symmetry breaking in turbulence},\n type = {article},\n year = {2014},\n pages = {54501},\n volume = {113},\n websites = {https://link.aps.org/doi/10.1103/PhysRevLett.113.054501},\n month = {4},\n id = {63563e3e-b931-33fc-928b-86829f9249e1},\n created = {2021-04-09T15:23:32.941Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:32.941Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In three-dimensional turbulent flows, the flux of energy from large to small scales breaks time symmetry. We show here that this irreversibility can be quantified by following the relative motion of several Lagrangian tracers. We find by analytical calculation, numerical analysis and experimental observation that the existence of the energy flux implies that, at short times, two particles separate temporally slower forwards than backwards, and the difference between forward and backward dispersion grows as t^3. We also find the geometric deformation of material volumes, surrogated by four points spanning an initially regular tetrahedron, to show sensitivity to the time-reversal with an effect growing linearly in t. We associate this with the structure of the strain rate in the flow.},\n bibtype = {article},\n author = {Jucha, Jennifer and Xu, Haitao and Pumir, Alain and Bodenschatz, Eberhard},\n doi = {10.1103/PhysRevLett.113.054501},\n journal = {Physical Review Letters},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In three-dimensional turbulent flows, the flux of energy from large to small scales breaks time symmetry. We show here that this irreversibility can be quantified by following the relative motion of several Lagrangian tracers. We find by analytical calculation, numerical analysis and experimental observation that the existence of the energy flux implies that, at short times, two particles separate temporally slower forwards than backwards, and the difference between forward and backward dispersion grows as t^3. We also find the geometric deformation of material volumes, surrogated by four points spanning an initially regular tetrahedron, to show sensitivity to the time-reversal with an effect growing linearly in t. We associate this with the structure of the strain rate in the flow.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014', 'http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111', event);\">\n    Flight-crash events in turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xu,  H.; Pumir,  A.; Falkovich,  G.; Bodenschatz,  E.; Shats,  M.; Xia,  H.; Francois,  N.;  and Boffetta,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Proceedings of the National Academy of Sciences</i>, 111(21): 7558-7563. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111\"\n     onclick=\"log_download('xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014', 'http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Flight-crash events in turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1073/pnas.1321682111\"\n     onclick=\"log_download('xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014', 'http://doi.org/10.1073/pnas.1321682111', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xu-pumir-falkovich-bodenschatz-shats-xia-francois-boffetta-flightcrasheventsinturbulence-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Flight-crash events in turbulence},\n type = {article},\n year = {2014},\n keywords = {Lagrangian description,direct and inverse turbulent energy cascades,nonequilibrium statistical mechanics,nonequilibrium systems,turbulent mixing},\n pages = {7558-7563},\n volume = {111},\n websites = {http://www.ncbi.nlm.nih.gov/pubmed/24794529,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4040622,http://www.pnas.org/cgi/doi/10.1073/pnas.1321682111},\n month = {4},\n publisher = {National Academy of Sciences},\n id = {fda3961e-245e-3a03-a910-a65e04ccf982},\n created = {2021-04-09T15:23:34.122Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:34.122Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The statistical properties of turbulence differ in an essential way from those of systems in or near thermal equilibrium because of the flux of energy between vastly different scales at which energy is supplied and at which it is dissipated. We elucidate this difference by studying experimentally and numerically the fluctuations of the energy of a small fluid particle moving in a turbulent fluid. We demonstrate how the fundamental property of detailed balance is broken, so that the probabilities of forward and backward transitions are not equal for turbulence. In physical terms, we found that in a large set of flow configurations, fluid elements decelerate faster than accelerate, a feature known all too well from driving in dense traffic. The statistical signature of rare &quot;flight-crash&quot; events, associated with fast particle deceleration, provides a way to quantify irreversibility in a turbulent flow. Namely, we find that the third moment of the power fluctuations along a trajectory, nondimensionalized by the energy flux, displays a remarkable power law as a function of the Reynolds number, both in two and in three spatial dimensions. This establishes a relation between the irreversibility of the system and the range of active scales. We speculate that the breakdown of the detailed balance characterized here is a general feature of other systems very far from equilibrium, displaying a wide range of spatial scales.},\n bibtype = {article},\n author = {Xu, Haitao and Pumir, Alain and Falkovich, Gregory and Bodenschatz, Eberhard and Shats, Michael and Xia, Hua and Francois, Nicolas and Boffetta, Guido},\n doi = {10.1073/pnas.1321682111},\n journal = {Proceedings of the National Academy of Sciences},\n number = {21}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The statistical properties of turbulence differ in an essential way from those of systems in or near thermal equilibrium because of the flux of energy between vastly different scales at which energy is supplied and at which it is dissipated. We elucidate this difference by studying experimentally and numerically the fluctuations of the energy of a small fluid particle moving in a turbulent fluid. We demonstrate how the fundamental property of detailed balance is broken, so that the probabilities of forward and backward transitions are not equal for turbulence. In physical terms, we found that in a large set of flow configurations, fluid elements decelerate faster than accelerate, a feature known all too well from driving in dense traffic. The statistical signature of rare \"flight-crash\" events, associated with fast particle deceleration, provides a way to quantify irreversibility in a turbulent flow. Namely, we find that the third moment of the power fluctuations along a trajectory, nondimensionalized by the energy flux, displays a remarkable power law as a function of the Reynolds number, both in two and in three spatial dimensions. This establishes a relation between the irreversibility of the system and the range of active scales. We speculate that the breakdown of the detailed balance characterized here is a general feature of other systems very far from equilibrium, displaying a wide range of spatial scales.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-014-1812-7\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014', 'http://link.springer.com/10.1007/s00348-014-1812-7', event);\">\n    Long-range μPIV to resolve the small scales in a jet at high Reynolds number.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Fiscaletti,  D.; Westerweel,  J.;  and Elsinga,  G., E.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 55(9): 1-15. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-014-1812-7\"\n     onclick=\"log_download('fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014', 'http://link.springer.com/10.1007/s00348-014-1812-7', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Long-range μPIV to resolve the small scales in a jet at high Reynolds number [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-014-1812-7\"\n     onclick=\"log_download('fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014', 'http://doi.org/10.1007/s00348-014-1812-7', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('fiscaletti-westerweel-elsinga-longrangepivtoresolvethesmallscalesinajetathighreynoldsnumber-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Long-range μPIV to resolve the small scales in a jet at high Reynolds number},\n type = {article},\n year = {2014},\n keywords = {High Reynolds number,Long-range μPIV,Small scales},\n pages = {1-15},\n volume = {55},\n websites = {http://link.springer.com/10.1007/s00348-014-1812-7},\n month = {4},\n publisher = {Springer Berlin Heidelberg},\n id = {7ec67954-6936-3b40-80b4-1bcddac0c0ad},\n created = {2021-04-09T15:24:28.325Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:28.325Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a self- similar round jet at high Reynolds numbers (Rek ? 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and kci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vor- ticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissi- pation tend to organize in the form of sheets with a char- acteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of long- range lPIV for characterizing turbulent flow structures at high Reynolds number. D.},\n bibtype = {article},\n author = {Fiscaletti, D and Westerweel, J and Elsinga, G E},\n doi = {10.1007/s00348-014-1812-7},\n journal = {Experiments in Fluids},\n number = {9}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The investigation of flows at high Reynolds number is of great interest for the theory of turbulence, in that the large and the small scales of turbulence show a clear separation. But, as the Reynolds number of the flow increases, the size of the Kolmogorov length scale (g) drops almost proportionally. Aiming at achieving the adequate spatial resolution in the central region of a self- similar round jet at high Reynolds numbers (Rek ? 350), a long-range lPIV system was applied. A vector spacing of 1:5g was achieved, where the Kolmogorov length scale was estimated to be 55 lm. The resulting velocity fields were used to characterize the small-scale flow structures in this jet. The autocorrelation maps of vorticity and kci (the imaginary part of the eigenvalue of the reduced velocity gradient tensor) reveal that the structures of intense vor- ticity have a characteristic diameter of approximately 10g. From the autocorrelation map of the reduced (2D) rate of dissipation, it is inferred that the regions of intense dissi- pation tend to organize in the form of sheets with a char- acteristic thickness of approximately 10g. The regions of intense dissipation have the tendency to appear in the vicinity of intense vortices. Furthermore, the joint pdf of the two invariants of the reduced velocity gradient tensor exhibits the characteristic teapot-shape. These results, based on a statistical analysis of the data, are in agreement with previous numerical and experimental studies at lower Reynolds number, which validates the suitability of long- range lPIV for characterizing turbulent flow structures at high Reynolds number. D.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.89.041003\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014', 'https://link.aps.org/doi/10.1103/PhysRevE.89.041003', event);\">\n    Asymptotic results for backwards two-particle dispersion in a turbulent flow.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Benveniste,  D.;  and Drivas,  T., D.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 89(4): 41003. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.89.041003\"\n     onclick=\"log_download('benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014', 'https://link.aps.org/doi/10.1103/PhysRevE.89.041003', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Asymptotic results for backwards two-particle dispersion in a turbulent flow [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.89.041003\"\n     onclick=\"log_download('benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014', 'http://doi.org/10.1103/PhysRevE.89.041003', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('benveniste-drivas-asymptoticresultsforbackwardstwoparticledispersioninaturbulentflow-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Asymptotic results for backwards two-particle dispersion in a turbulent flow},\n type = {article},\n year = {2014},\n pages = {41003},\n volume = {89},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.89.041003},\n month = {4},\n id = {c0be1397-382a-3ab4-a087-8d8134ed9ee6},\n created = {2021-04-09T15:24:30.893Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:30.893Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We derive an exact equation governing two-particle backwards mean-squared dispersion for both deterministic and stochastic tracer particles in turbulent flows. For the deterministic trajectories, we probe the consequences of our formula for short times and arrive at approximate expressions for the mean-squared dispersion which involve second order structure functions of the velocity and acceleration fields. For the stochastic trajectories, we analytically compute an exact t^3 contribution to the squared separation of stochastic paths. We argue that this contribution appears also for deterministic paths at long times and present direct numerical simulation results for incompressible Navier-Stokes flows to support this claim. We also numerically compute the probability distribution of particle separations for the deterministic paths and the stochastic paths and show their strong self-similar nature.},\n bibtype = {article},\n author = {Benveniste, Damien and Drivas, Theodore D},\n doi = {10.1103/PhysRevE.89.041003},\n journal = {Physical Review E},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We derive an exact equation governing two-particle backwards mean-squared dispersion for both deterministic and stochastic tracer particles in turbulent flows. For the deterministic trajectories, we probe the consequences of our formula for short times and arrive at approximate expressions for the mean-squared dispersion which involve second order structure functions of the velocity and acceleration fields. For the stochastic trajectories, we analytically compute an exact t^3 contribution to the squared separation of stochastic paths. We argue that this contribution appears also for deterministic paths at long times and present direct numerical simulation results for incompressible Navier-Stokes flows to support this claim. We also numerically compute the probability distribution of particle separations for the deterministic paths and the stochastic paths and show their strong self-similar nature.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevX.4.041006\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014', 'https://link.aps.org/doi/10.1103/PhysRevX.4.041006', event);\">\n    Redistribution of kinetic energy in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Pumir,  A.; Xu,  H.; Boffetta,  G.; Falkovich,  G.;  and Bodenschatz,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review X</i>, 4(4): 41006. 4 2014.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevX.4.041006\"\n     onclick=\"log_download('pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014', 'https://link.aps.org/doi/10.1103/PhysRevX.4.041006', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Redistribution of kinetic energy in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevX.4.041006\"\n     onclick=\"log_download('pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014', 'http://doi.org/10.1103/PhysRevX.4.041006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('pumir-xu-boffetta-falkovich-bodenschatz-redistributionofkineticenergyinturbulentflows-2014')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Redistribution of kinetic energy in turbulent flows},\n type = {article},\n year = {2014},\n keywords = {Fluid dynamics,Nonlinear dynamics,Statistical physics},\n pages = {41006},\n volume = {4},\n websites = {https://link.aps.org/doi/10.1103/PhysRevX.4.041006},\n month = {4},\n id = {078fb0f4-b620-36e6-ab06-b4a0bbf5dce8},\n created = {2021-04-09T15:24:35.860Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:35.860Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In statistically homogeneous turbulent flows, pressure forces provide the main mechanism to redistribute kinetic energy among fluid elements, without net contribution to the overall energy budget. This holds true in both two-dimensional (2D) and three-dimensional (3D) flows, which show fundamentally different physics. As we demonstrate here, pressure forces act on fluid elements very differently in these two cases. We find in numerical simulations that in 3D pressure forces strongly accelerate the fastest fluid elements, and that in 2D this effect is absent. In 3D turbulence, our findings put forward a mechanism for a possibly singular buildup of energy, and thus may shed new light on the smoothness problem of the solution of the Navier-Stokes equation in 3D.},\n bibtype = {article},\n author = {Pumir, Alain and Xu, Haitao and Boffetta, Guido and Falkovich, Gregory and Bodenschatz, Eberhard},\n doi = {10.1103/PhysRevX.4.041006},\n journal = {Physical Review X},\n number = {4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In statistically homogeneous turbulent flows, pressure forces provide the main mechanism to redistribute kinetic energy among fluid elements, without net contribution to the overall energy budget. This holds true in both two-dimensional (2D) and three-dimensional (3D) flows, which show fundamentally different physics. As we demonstrate here, pressure forces act on fluid elements very differently in these two cases. We find in numerical simulations that in 3D pressure forces strongly accelerate the fastest fluid elements, and that in 2D this effect is absent. In 3D turbulence, our findings put forward a mechanism for a possibly singular buildup of energy, and thus may shed new light on the smoothness problem of the solution of the Navier-Stokes equation in 3D.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2013\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2013')\"\n      onkeypress=\"toggleGroup('group_2013')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2013</span>\n      <span class=\"bibbase_group_count\">\n        \n        (6)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.nature.com/articles/nature12128\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013', 'http://www.nature.com/articles/nature12128', event);\">\n    Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eyink,  G.; Vishniac,  E.; Lalescu,  C.; Aluie,  H.; Kanov,  K.; Bürger,  K.; Burns,  R.; Meneveau,  C.;  and Szalay,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Nature</i>, 497(7450): 466-469. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.nature.com/articles/nature12128\"\n     onclick=\"log_download('eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013', 'http://www.nature.com/articles/nature12128', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1038/nature12128\"\n     onclick=\"log_download('eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013', 'http://doi.org/10.1038/nature12128', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>3 downloads</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eyink-vishniac-lalescu-aluie-kanov-brger-burns-meneveau-etal-fluxfreezingbreakdowninhighconductivitymagnetohydrodynamicturbulence-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Flux-freezing breakdown in high-conductivity magnetohydrodynamic turbulence},\n type = {article},\n year = {2013},\n keywords = {Applied mathematics,Astronomy and astrophysics,Astrophysical plasmas,Information technology},\n pages = {466-469},\n volume = {497},\n websites = {http://www.nature.com/articles/nature12128},\n month = {4},\n publisher = {Nature Publishing Group},\n id = {6a88f6fa-126a-376e-be84-8a2f914b8b62},\n created = {2021-04-09T15:23:16.064Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:16.064Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The idea of &#x27;frozen-in&#x27; magnetic field lines for ideal plasmas is useful to explain diverse astrophysical phenomena, for example the shedding of excess angular momentum from protostars by twisting of field lines frozen into the interstellar medium. Frozen-in field lines, however, preclude the rapid changes in magnetic topology observed at high conductivities, as in solar flares. Microphysical plasma processes are a proposed explanation of the observed high rates, but it is an open question whether such processes can rapidly reconnect astrophysical flux structures much greater in extent than several thousand ion gyroradii. An alternative explanation is that turbulent Richardson advection brings field lines implosively together from distances far apart to separations of the order of gyroradii. Here we report an analysis of a simulation of magnetohydrodynamic turbulence at high conductivity that exhibits Richardson dispersion. This effect of advection in rough velocity fields, which appear non-differentiable in space, leads to line motions that are completely indeterministic or &#x27;spontaneously stochastic&#x27;, as predicted in analytical studies. The turbulent breakdown of standard flux freezing at scales greater than the ion gyroradius can explain fast reconnection of very large-scale flux structures, both observed (solar flares and coronal mass ejections) and predicted (the inner heliosheath, accretion disks, γ-ray bursts and so on). For laminar plasma flows with smooth velocity fields or for low turbulence intensity, stochastic flux freezing reduces to the usual frozen-in condition.},\n bibtype = {article},\n author = {Eyink, Gregory and Vishniac, Ethan and Lalescu, Cristian and Aluie, Hussein and Kanov, Kalin and Bürger, Kai and Burns, Randal and Meneveau, Charles and Szalay, Alexander},\n doi = {10.1038/nature12128},\n journal = {Nature},\n number = {7450}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The idea of 'frozen-in' magnetic field lines for ideal plasmas is useful to explain diverse astrophysical phenomena, for example the shedding of excess angular momentum from protostars by twisting of field lines frozen into the interstellar medium. Frozen-in field lines, however, preclude the rapid changes in magnetic topology observed at high conductivities, as in solar flares. Microphysical plasma processes are a proposed explanation of the observed high rates, but it is an open question whether such processes can rapidly reconnect astrophysical flux structures much greater in extent than several thousand ion gyroradii. An alternative explanation is that turbulent Richardson advection brings field lines implosively together from distances far apart to separations of the order of gyroradii. Here we report an analysis of a simulation of magnetohydrodynamic turbulence at high conductivity that exhibits Richardson dispersion. This effect of advection in rough velocity fields, which appear non-differentiable in space, leads to line motions that are completely indeterministic or 'spontaneously stochastic', as predicted in analytical studies. The turbulent breakdown of standard flux freezing at scales greater than the ion gyroradius can explain fast reconnection of very large-scale flux structures, both observed (solar flares and coronal mass ejections) and predicted (the inner heliosheath, accretion disks, γ-ray bursts and so on). For laminar plasma flows with smooth velocity fields or for low turbulence intensity, stochastic flux freezing reduces to the usual frozen-in condition.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013', 'http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation', event);\">\n    Fluctuation dynamos and their Faraday rotation signatures.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Bhat,  P.;  and Subramanian,  K.\n</span>\n\n  \n\n</span>\n\n  <i>Monthly Notices of the Royal Astronomical Society</i>, 429(3): 2469-2481. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation\"\n     onclick=\"log_download('bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013', 'http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Fluctuation dynamos and their Faraday rotation signatures [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1093/mnras/sts516\"\n     onclick=\"log_download('bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013', 'http://doi.org/10.1093/mnras/sts516', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('bhat-subramanian-fluctuationdynamosandtheirfaradayrotationsignatures-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Fluctuation dynamos and their Faraday rotation signatures},\n type = {article},\n year = {2013},\n pages = {2469-2481},\n volume = {429},\n websites = {http://academic.oup.com/mnras/article/429/3/2469/1008313/Fluctuation-dynamos-and-their-Faraday-rotation},\n month = {4},\n publisher = {Oxford University Press},\n id = {411f3d9f-938e-3b01-9d5d-a75cabb68633},\n created = {2021-04-09T15:23:19.834Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:19.834Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Bhat, Pallavi and Subramanian, Kandaswamy},\n doi = {10.1093/mnras/sts516},\n journal = {Monthly Notices of the Royal Astronomical Society},\n number = {3}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5', event);\">\n    Invariants of the reduced velocity gradient tensor in turbulent flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Cardesa,  J., A., I.; Mistry,  D.; Gan,  L.;  and Dawson,  J., A., R.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 716: 597-615. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5\"\n     onclick=\"log_download('cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013', 'https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Invariants of the reduced velocity gradient tensor in turbulent flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2012.558\"\n     onclick=\"log_download('cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013', 'http://doi.org/10.1017/jfm.2012.558', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('cardesa-mistry-gan-dawson-invariantsofthereducedvelocitygradienttensorinturbulentflows-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Invariants of the reduced velocity gradient tensor in turbulent flows},\n type = {article},\n year = {2013},\n keywords = {isotropic turbulence,turbulence theory,turbulent flows},\n pages = {597-615},\n volume = {716},\n websites = {https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/invariants-of-the-reduced-velocity-gradient-tensor-in-turbulent-flows/50C6BB1567C4FBD3ADA346C3B70938A5},\n month = {4},\n id = {c1df0993-9b68-35fd-9b00-e89c04ec2e25},\n created = {2021-04-09T15:24:05.475Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:05.475Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In this paper we examine the invariants p and q of the reduced 2 × 2 velocity gradient tensor (VGT) formed from a two-dimensional (2D) slice of an incompressible three-dimensional (3D) flow. Using data from both 2D particle image velocimetry (PIV) measurements and 3D direct numerical simulations of various turbulent flows, we show that the joint probability density functions (p.d.f.s) of p and q exhibit a common characteristic asymmetric shape consistent with &lt; 0. An explanation for this inequality is proposed. Assuming local homogeneity we derive = 0 and = 0. With the addition of local isotropy the sign of is proved to be the same as that of the skewness of ∂u 1 /∂x 1 , hence negative. This suggests that the observed asymmetry in the joint p.d.f.s of p–q stems from the universal predominance of vortex stretching at the smallest scales. Some advantages of this joint p.d.f. compared with that of Q–R obtained from the full 3 × 3 VGT are discussed. Analysing the eigenvalues of the reduced strain-rate matrix associated with the reduced VGT, we prove that in some cases the 2D data can unambiguously discriminate between the bi-axial (sheet-forming) and axial (tube-forming) strain-rate configurations of the full 3 × 3 strain-rate tensor. 1. Introduction With the arrival of data sets providing access to the full three-dimensional velocity gradient tensor (3D VGT), new ways of analysing this wealth of information have been introduced. The 3D VGT can be written as A ij = ∂u i /∂x j = S ij + W ij , where S ij is the symmetric rate-of-strain tensor and W ij is the antisymmetric rate-of-rotation tensor. One approach is to examine the eigenvalues of S ij . They indicate if the strain-rate tensor is compressing or extending along its principal axes, which in turn determines whether or not the overall strain-rate configuration at a point is sheet forming or tube forming. Another approach is to analyse the local flow topology using the invariants of A ij , as set out by the work of Chong, Perry &amp; Cantwell (1990). In an incompressible flow the number of non-vanishing similarity invariants of the second-order tensor A ij reduces to two, namely Q and R. These two quantities can fully characterize the category to which the local flow topology belongs. The local flow topology refers to the streamline pattern of a region of the flow in the immediate vicinity of the point},\n bibtype = {article},\n author = {Cardesa, J A I and Mistry, D and Gan, L and Dawson, J A R},\n doi = {10.1017/jfm.2012.558},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper we examine the invariants p and q of the reduced 2 × 2 velocity gradient tensor (VGT) formed from a two-dimensional (2D) slice of an incompressible three-dimensional (3D) flow. Using data from both 2D particle image velocimetry (PIV) measurements and 3D direct numerical simulations of various turbulent flows, we show that the joint probability density functions (p.d.f.s) of p and q exhibit a common characteristic asymmetric shape consistent with < 0. An explanation for this inequality is proposed. Assuming local homogeneity we derive = 0 and = 0. With the addition of local isotropy the sign of is proved to be the same as that of the skewness of ∂u 1 /∂x 1 , hence negative. This suggests that the observed asymmetry in the joint p.d.f.s of p–q stems from the universal predominance of vortex stretching at the smallest scales. Some advantages of this joint p.d.f. compared with that of Q–R obtained from the full 3 × 3 VGT are discussed. Analysing the eigenvalues of the reduced strain-rate matrix associated with the reduced VGT, we prove that in some cases the 2D data can unambiguously discriminate between the bi-axial (sheet-forming) and axial (tube-forming) strain-rate configurations of the full 3 × 3 strain-rate tensor. 1. Introduction With the arrival of data sets providing access to the full three-dimensional velocity gradient tensor (3D VGT), new ways of analysing this wealth of information have been introduced. The 3D VGT can be written as A ij = ∂u i /∂x j = S ij + W ij , where S ij is the symmetric rate-of-strain tensor and W ij is the antisymmetric rate-of-rotation tensor. One approach is to examine the eigenvalues of S ij . They indicate if the strain-rate tensor is compressing or extending along its principal axes, which in turn determines whether or not the overall strain-rate configuration at a point is sheet forming or tube forming. Another approach is to analyse the local flow topology using the invariants of A ij , as set out by the work of Chong, Perry & Cantwell (1990). In an incompressible flow the number of non-vanishing similarity invariants of the second-order tensor A ij reduces to two, namely Q and R. These two quantities can fully characterize the category to which the local flow topology belongs. The local flow topology refers to the streamline pattern of a region of the flow in the immediate vicinity of the point\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112013002759\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013', 'http://www.journals.cambridge.org/abstract_S0022112013002759', event);\">\n    Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  X.;  and Katz,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 728: 417-457. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112013002759\"\n     onclick=\"log_download('liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013', 'http://www.journals.cambridge.org/abstract_S0022112013002759', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/jfm.2013.275\"\n     onclick=\"log_download('liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013', 'http://doi.org/10.1017/jfm.2013.275', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-katz-vortexcornerinteractionsinacavityshearlayerelucidatedbytimeresolvedmeasurementsofthepressurefield-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vortex-corner interactions in a cavity shear layer elucidated by time-resolved measurements of the pressure field},\n type = {article},\n year = {2013},\n keywords = {Flow structure interactions,Shear layer turbulence,Vortex dynamics},\n pages = {417-457},\n volume = {728},\n websites = {http://www.journals.cambridge.org/abstract_S0022112013002759},\n month = {4},\n publisher = {Cambridge University Press},\n id = {f07ba240-7dc8-3d45-90d2-e2f8bd3cee75},\n created = {2021-04-09T15:24:24.005Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:24.005Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The flow structure and turbulence in an open cavity shear layer has been investigated experimentally at a Reynolds number of 4.0 × 104, with an emphasis on interactions of the unsteady pressure field with the cavity corners. A large database of time-resolved two-dimensional PIV measurements has been used to obtain the velocity distributions and calculate the pressure by spatially integrating the material acceleration at a series of sample areas covering the entire shear layer and the flow surrounding the corners. Conditional sampling, low-pass filtering and time correlations among variables enable us to elucidate several processes, which have distinctly different frequency ranges, that dominate the shear layer interactions with the corners. Kelvin-Helmholtz shear layer eddies have the expected Strouhal number range of 0.5-3.2. Their interactions with the trailing corner introduce two sources of vorticity fluctuations above the corner. The first is caused by the expected advection of remnants of the shear layer eddies. The second source involves fluctuations in local viscous vorticity flux away from the wall caused by periodic variations in the streamwise pressure gradients. This local production peaks when the shear layer vortices are located away from the corner, creating a lingering region with peak vorticity just above the corner. The associated periodic pressure minima there are lower than any other point in the entire flow field, making the region above the corner most prone to cavitation inception. Flapping of the shear layer and boundary layer upstream of the leading corner occurs at very low Strouhal numbers of ~0.05, affecting all the flow and turbulence quantities around both corners. Time-dependent correlations of the shear layer elevation show that the flapping starts in the boundary layer upstream of the leading corner and propagates downstream at the free stream speed. Near the trailing corner, when the shear layer elevation is low, the stagnation pressure in front of the wall, the downward jetting flow along this wall, the fraction of shear layer vorticity entrained back into the cavity, and the magnitude of the pressure minimum above the corner are higher than those measured when the shear layer is high. However, the variations in downward jetting decay rapidly with increasing distance from the trailing corner, indicating that it does not play a direct role in a feedback mechanism that sustains the flapping. There is also low correlation between the boundary/shear layer elevation and the returning flow along the upstream vertical wall, providing little evidence that this returning flow affects the flapping directly. However, the characteristic period of flapping, ~0.6 s, is consistent with recirculation time of the fluid within the cavity away from boundaries. The high negative correlations of shear/boundary layer elevation with the streamwise pressure gradient above the leading corner introduce a plausible mechanism that sustains the flapping: when the shear layer is low, the boundary layer is subjected to high adverse streamwise pressure gradients that force it to widen, and when the shear layer is high, the pressure gradients decrease, allowing the boundary layer to thin down. Flow mechanisms that would cause the flapping-induced pressure changes, and their relations to the flow within the cavity are discussed. © 2013 Cambridge University Press.},\n bibtype = {article},\n author = {Liu, Xiaofeng and Katz, Joseph},\n doi = {10.1017/jfm.2013.275},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The flow structure and turbulence in an open cavity shear layer has been investigated experimentally at a Reynolds number of 4.0 × 104, with an emphasis on interactions of the unsteady pressure field with the cavity corners. A large database of time-resolved two-dimensional PIV measurements has been used to obtain the velocity distributions and calculate the pressure by spatially integrating the material acceleration at a series of sample areas covering the entire shear layer and the flow surrounding the corners. Conditional sampling, low-pass filtering and time correlations among variables enable us to elucidate several processes, which have distinctly different frequency ranges, that dominate the shear layer interactions with the corners. Kelvin-Helmholtz shear layer eddies have the expected Strouhal number range of 0.5-3.2. Their interactions with the trailing corner introduce two sources of vorticity fluctuations above the corner. The first is caused by the expected advection of remnants of the shear layer eddies. The second source involves fluctuations in local viscous vorticity flux away from the wall caused by periodic variations in the streamwise pressure gradients. This local production peaks when the shear layer vortices are located away from the corner, creating a lingering region with peak vorticity just above the corner. The associated periodic pressure minima there are lower than any other point in the entire flow field, making the region above the corner most prone to cavitation inception. Flapping of the shear layer and boundary layer upstream of the leading corner occurs at very low Strouhal numbers of ~0.05, affecting all the flow and turbulence quantities around both corners. Time-dependent correlations of the shear layer elevation show that the flapping starts in the boundary layer upstream of the leading corner and propagates downstream at the free stream speed. Near the trailing corner, when the shear layer elevation is low, the stagnation pressure in front of the wall, the downward jetting flow along this wall, the fraction of shear layer vorticity entrained back into the cavity, and the magnitude of the pressure minimum above the corner are higher than those measured when the shear layer is high. However, the variations in downward jetting decay rapidly with increasing distance from the trailing corner, indicating that it does not play a direct role in a feedback mechanism that sustains the flapping. There is also low correlation between the boundary/shear layer elevation and the returning flow along the upstream vertical wall, providing little evidence that this returning flow affects the flapping directly. However, the characteristic period of flapping, ~0.6 s, is consistent with recirculation time of the fluid within the cavity away from boundaries. The high negative correlations of shear/boundary layer elevation with the streamwise pressure gradient above the leading corner introduce a plausible mechanism that sustains the flapping: when the shear layer is low, the boundary layer is subjected to high adverse streamwise pressure gradients that force it to widen, and when the shear layer is high, the pressure gradients decrease, allowing the boundary layer to thin down. Flow mechanisms that would cause the flapping-induced pressure changes, and their relations to the flow within the cavity are discussed. © 2013 Cambridge University Press.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013', 'https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464', event);\">\n    Accurate estimate of turbulent dissipation rate using PIV data.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xu,  D.;  and Chen,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experimental Thermal and Fluid Science</i>, 44: 662-672. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464\"\n     onclick=\"log_download('xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013', 'https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Accurate estimate of turbulent dissipation rate using PIV data [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.expthermflusci.2012.09.006\"\n     onclick=\"log_download('xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013', 'http://doi.org/10.1016/j.expthermflusci.2012.09.006', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xu-chen-accurateestimateofturbulentdissipationrateusingpivdata-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Accurate estimate of turbulent dissipation rate using PIV data},\n type = {article},\n year = {2013},\n keywords = {Energy spectra,PIV,Structure function,Turbulent dissipation rate},\n pages = {662-672},\n volume = {44},\n websites = {https://www.sciencedirect.com/science/article/pii/S0894177712002464#,https://www.sciencedirect.com/science/article/pii/S0894177712002464},\n month = {4},\n publisher = {Elsevier},\n id = {eb9c0ce8-55c3-3c88-a7b6-067038618599},\n created = {2021-04-09T15:24:33.718Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:33.718Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the -5/3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes. © 2012 Elsevier Inc.},\n bibtype = {article},\n author = {Xu, Duo and Chen, Jun},\n doi = {10.1016/j.expthermflusci.2012.09.006},\n journal = {Experimental Thermal and Fluid Science}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Quantifying the turbulent dissipation rate provides insight into the physics of the turbulent flows. However, the accuracy of estimating turbulent dissipation rate using velocity data measured by planar PIV is affected by the way of modeling the unresolved velocity gradient terms and the PIV spatial resolution. In this paper, we first give a brief review of different methods used to estimate turbulent dissipation rate. Then synthetic PIV data are generated from a turbulence DNS dataset for validating the effectiveness of different methods. Direct estimate of turbulent dissipation rate from its definition using velocity gradients, with the assumption of isotropy, local axisymmetry, or local isotropy, shows significant decrease as interrogation window size increases. On the other hand, the indirect estimation of turbulent dissipation rate from energy spectra and structure function demonstrate less severe decrease as interrogation window size increases. We further propose two modified methods. The Modified Structure Function Method relies on an empirical relationship established by analyzing the synthetic PIV data. For a given measured value turbulent dissipation rate under a given interrogation window size, the true value can be determined from this relationship. The Modified Spectra Curvefit Method accounts the averaging effect introduced by the interrogation window in PIV processing algorithm and thus gives a better calculation of the energy spectra. When the new spectra data are used to curve fit the -5/3 slope, an improved estimate of turbulent dissipation rate is expected. Both modified methods are applied to experimental PIV data acquired from a turbulent jet experiment. They give nearly converged estimates of turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes. © 2012 Elsevier Inc.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.88.013005\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013', 'https://link.aps.org/doi/10.1103/PhysRevE.88.013005', event);\">\n    Vorticity statistics and the time scales of turbulent strain.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Moriconi,  L.;  and Pereira,  R., M.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 88(1): 13005. 4 2013.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.88.013005\"\n     onclick=\"log_download('moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013', 'https://link.aps.org/doi/10.1103/PhysRevE.88.013005', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Vorticity statistics and the time scales of turbulent strain [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.88.013005\"\n     onclick=\"log_download('moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013', 'http://doi.org/10.1103/PhysRevE.88.013005', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('moriconi-pereira-vorticitystatisticsandthetimescalesofturbulentstrain-2013')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Vorticity statistics and the time scales of turbulent strain},\n type = {article},\n year = {2013},\n pages = {13005},\n volume = {88},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.88.013005},\n month = {4},\n publisher = {American Physical Society},\n id = {9326f9aa-e723-3f33-8803-969549fd326b},\n created = {2021-04-09T15:24:37.611Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:37.611Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of Lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual “1/s” strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.},\n bibtype = {article},\n author = {Moriconi, L and Pereira, R M},\n doi = {10.1103/PhysRevE.88.013005},\n journal = {Physical Review E},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Time scales of turbulent strain activity, denoted as the strain persistence times of first and second order, are obtained from time-dependent expectation values and correlation functions of Lagrangian rate-of-strain eigenvalues taken in particularly defined statistical ensembles. Taking into account direct numerical simulation data, our approach relies on heuristic closure hypotheses which allow us to establish a connection between the statistics of vorticity and strain. It turns out that softly divergent prefactors correct the usual “1/s” strain time-scale estimate of standard turbulence phenomenology, in a way which is consistent with the phenomenon of vorticity intermittency.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2012\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2012')\"\n      onkeypress=\"toggleGroup('group_2012')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2012</span>\n      <span class=\"bibbase_group_count\">\n        \n        (5)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012', 'http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27', event);\">\n    On coarse-grained simulations of turbulent material mixing.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grinstein,  F., F.; Gowardhan,  A., A.; Ristorcelli,  J., R.;  and Wachtor,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Physica Scripta</i>, 86(5): 58203. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27\"\n     onclick=\"log_download('grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012', 'http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"On coarse-grained simulations of turbulent material mixing [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1088/0031-8949/86/05/058203\"\n     onclick=\"log_download('grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012', 'http://doi.org/10.1088/0031-8949/86/05/058203', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grinstein-gowardhan-ristorcelli-wachtor-oncoarsegrainedsimulationsofturbulentmaterialmixing-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {On coarse-grained simulations of turbulent material mixing},\n type = {article},\n year = {2012},\n pages = {58203},\n volume = {86},\n websites = {http://stacks.iop.org/1402-4896/86/i=5/a=058203?key=crossref.eec1a2f2d01c989b1e54037b82792a27},\n month = {4},\n publisher = {IOP Publishing},\n id = {b59e8f66-df49-356c-9971-4e3390d30396},\n created = {2021-04-09T15:23:28.097Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:28.097Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.},\n bibtype = {article},\n author = {Grinstein, F F and Gowardhan, A A and Ristorcelli, J R and Wachtor, A J},\n doi = {10.1088/0031-8949/86/05/058203},\n journal = {Physica Scripta},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Under-resolved computer simulations are typically unavoidable in many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. In such applications, coarse-grained simulation (CGS) becomes the effective simulation strategy, mostly by necessity rather than by choice. In CGS strategies, resolved/unresolved scale separation is assumed possible, large energy-containing structures are mostly resolved, smaller structures are spatially filtered out and unresolved subgrid effects are modeled; this includes classical large-eddy simulation (LES) strategies with the explicit use of closure subgrid scale models and implicit LES, relying on subgrid modeling implicitly provided by physics-capturing numerical algorithms. Predictability issues in CGS of under-resolved mixing of material scalars driven by under-resolved velocity fields and initial conditions are addressed in this paper, and shock-driven turbulent mixing is a particular focus.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://doi.wiley.com/10.1029/2011JF002127\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012', 'http://doi.wiley.com/10.1029/2011JF002127', event);\">\n    A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keylock,  C., J.; Nishimura,  K.;  and Peinke,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Geophysical Research: Earth Surface</i>, 117(1): n/a-n/a. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://doi.wiley.com/10.1029/2011JF002127\"\n     onclick=\"log_download('keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012', 'http://doi.wiley.com/10.1029/2011JF002127', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1029/2011JF002127\"\n     onclick=\"log_download('keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012', 'http://doi.org/10.1029/2011JF002127', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keylock-nishimura-peinke-aclassificationschemeforturbulencebasedonthevelocityintermittencystructurewithanapplicationtonearwallflowandwithimplicationsforbedloadtransport-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A classification scheme for turbulence based on the velocity-intermittency structure with an application to near-wall flow and with implications for bed load transport},\n type = {article},\n year = {2012},\n pages = {n/a-n/a},\n volume = {117},\n websites = {http://doi.wiley.com/10.1029/2011JF002127},\n month = {4},\n id = {cf45c3cd-ec34-3554-a185-77fd023702b3},\n created = {2021-04-09T15:23:41.333Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:41.333Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Kolmogorov�s classic theory for turbulence assumed an independence velocity increments and the value for the velocity itself., recent work has called this assumption in to question, which implications for the structure of atmospheric, oceanic and fluvial. Here we propose a conceptually simple analytical framework studying velocity-intermittency coupling that is similar in essence the popular quadrant analysis method for studying near-wall flows., we study the dominant (longitudinal) velocity component with a measure of the roughness of the signal, given mathematically its series of H�lder exponents. Thus, we permit a possible dependence velocity and intermittency. We compare boundary layer data in a wind tunnel to turbulent jets and wake flows. These classes all have distinct characteristics, which cause them be readily distinguished using our technique and the results are to changes in flow Reynolds numbers. Classification of environmental is then possible based on their similarities to the idealized classes and we demonstrate this using laboratory data for flow a parallel-channel confluence. Our results have clear implications sediment transport in a range of geophysical applications as suggest that the recently proposed impulse-based methods for bed load transport are particularly relevant in domains as gravel bed river flows where the boundary layer is disrupted wake interactions predominate.},\n bibtype = {article},\n author = {Keylock, C J and Nishimura, K and Peinke, J},\n doi = {10.1029/2011JF002127},\n journal = {Journal of Geophysical Research: Earth Surface},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Kolmogorov�s classic theory for turbulence assumed an independence velocity increments and the value for the velocity itself., recent work has called this assumption in to question, which implications for the structure of atmospheric, oceanic and fluvial. Here we propose a conceptually simple analytical framework studying velocity-intermittency coupling that is similar in essence the popular quadrant analysis method for studying near-wall flows., we study the dominant (longitudinal) velocity component with a measure of the roughness of the signal, given mathematically its series of H�lder exponents. Thus, we permit a possible dependence velocity and intermittency. We compare boundary layer data in a wind tunnel to turbulent jets and wake flows. These classes all have distinct characteristics, which cause them be readily distinguished using our technique and the results are to changes in flow Reynolds numbers. Classification of environmental is then possible based on their similarities to the idealized classes and we demonstrate this using laboratory data for flow a parallel-channel confluence. Our results have clear implications sediment transport in a range of geophysical applications as suggest that the recently proposed impulse-based methods for bed load transport are particularly relevant in domains as gravel bed river flows where the boundary layer is disrupted wake interactions predominate.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s00348-012-1374-5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012', 'http://link.springer.com/10.1007/s00348-012-1374-5', event);\">\n    Pulsed, high-power LED illumination for tomographic particle image velocimetry.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Buchmann,  N., A.; Willert,  C., E.;  and Soria,  J.\n</span>\n\n  \n\n</span>\n\n  <i>Experiments in Fluids</i>, 53(5): 1545-1560. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s00348-012-1374-5\"\n     onclick=\"log_download('buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012', 'http://link.springer.com/10.1007/s00348-012-1374-5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Pulsed, high-power LED illumination for tomographic particle image velocimetry [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s00348-012-1374-5\"\n     onclick=\"log_download('buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012', 'http://doi.org/10.1007/s00348-012-1374-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('buchmann-willert-soria-pulsedhighpowerledilluminationfortomographicparticleimagevelocimetry-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Pulsed, high-power LED illumination for tomographic particle image velocimetry},\n type = {article},\n year = {2012},\n pages = {1545-1560},\n volume = {53},\n websites = {http://link.springer.com/10.1007/s00348-012-1374-5},\n month = {4},\n publisher = {Springer-Verlag},\n id = {20ac55ec-3931-33b8-bee4-44ff227b4ec7},\n created = {2021-04-09T15:24:08.857Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:08.857Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 mu s duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of approximate to 3-4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2-0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.},\n bibtype = {article},\n author = {Buchmann, Nicolas A and Willert, Christian E and Soria, Julio},\n doi = {10.1007/s00348-012-1374-5},\n journal = {Experiments in Fluids},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  This paper investigates the use of high-power light-emitting diode (LED) illumination for tomographic particle image velocimetry (PIV) as an alternative to traditional laser-based illumination. Modern solid-state LED devices can provide averaged radiant power in excess of 10 W and by operating the LED with short high current pulses theoretical pulse energies up to several tens of mJ can be achieved. In the present work, a custom-built drive circuit is used to drive a Luminus PT-120 high-power LED at pulsed currents of up to 150 A and 1 mu s duration. Volumetric illumination is achieved by directly projecting the LED into the flow to produce a measurement volume of approximate to 3-4 times the size of the LED die. The feasibility of the volumetric LED illumination is assessed by performing tomographic PIV of homogenous, grid-generated turbulence. Two types of LEDs are investigated, and the results are compared with measurements of the same flow using pulsed Nd:YAG laser illumination and DNS data of homogeneous isotropic turbulence. The quality of the results is similar for both investigated LEDs with no significant difference between the LED and Nd:YAG illumination. Compared with the DNS, some differences are observed in the power spectra and the probability distributions of the fluctuating velocity and velocity gradients. These differences are attributed to the limited spatial resolution of the experiments and noise introduced during the tomographic reconstruction (i.e. ghost particles). The uncertainty in the velocity measurements associated with the LED illumination is estimated to approximately 0.2-0.3 pixel for both LEDs, which compares favourably with similar tomographic PIV measurements of turbulent flows. In conclusion, the proposed high-power, pulsed LED volume illumination provides accurate and reliable tomographic PIV measurements in water and presents a promising technique for flow diagnostics and velocimetry.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012', 'http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124', event);\">\n    Turbulence visualization at the terascale on desktop PCs.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Treib,  M.; Burger,  K.; Reichl,  F.; Meneveau,  C.; Szalay,  A.;  and Westermann,  R.\n</span>\n\n  \n\n</span>\n\n  <i>IEEE Transactions on Visualization and Computer Graphics</i>, 18(12): 2169-2177. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124\"\n     onclick=\"log_download('treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012', 'http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Turbulence visualization at the terascale on desktop PCs [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1109/TVCG.2012.274\"\n     onclick=\"log_download('treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012', 'http://doi.org/10.1109/TVCG.2012.274', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('treib-burger-reichl-meneveau-szalay-westermann-turbulencevisualizationattheterascaleondesktoppcs-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Turbulence visualization at the terascale on desktop PCs},\n type = {article},\n year = {2012},\n keywords = {Visualization system and toolkit design,data compression,data streaming,vector fields,volume rendering},\n pages = {2169-2177},\n volume = {18},\n websites = {http://ieeexplore.ieee.org/document/6327475/,http://www.ncbi.nlm.nih.gov/pubmed/26357124},\n month = {4},\n id = {40c4dabb-3c4d-39df-998a-492543c75ed1},\n created = {2021-04-09T15:24:14.491Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:14.491Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small-and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. © 1995-2012 IEEE.},\n bibtype = {article},\n author = {Treib, Marc and Burger, Kai and Reichl, Florian and Meneveau, Charles and Szalay, Alex and Westermann, Rudiger},\n doi = {10.1109/TVCG.2012.274},\n journal = {IEEE Transactions on Visualization and Computer Graphics},\n number = {12}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small-and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. © 1995-2012 IEEE.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0031320312002051\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012', 'https://www.sciencedirect.com/science/article/pii/S0031320312002051', event);\">\n    Detecting singular patterns in 2D vector fields using weighted Laurent polynomial.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  W.;  and Ribeiro,  E.\n</span>\n\n  \n\n</span>\n\n  <i>Pattern Recognition</i>, 45(11): 3912-3925. 4 2012.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0031320312002051\"\n     onclick=\"log_download('liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012', 'https://www.sciencedirect.com/science/article/pii/S0031320312002051', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Detecting singular patterns in 2D vector fields using weighted Laurent polynomial [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.patcog.2012.04.025\"\n     onclick=\"log_download('liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012', 'http://doi.org/10.1016/j.patcog.2012.04.025', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-ribeiro-detectingsingularpatternsin2dvectorfieldsusingweightedlaurentpolynomial-2012')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Detecting singular patterns in 2D vector fields using weighted Laurent polynomial},\n type = {article},\n year = {2012},\n keywords = {Complex-valued function,Laurent polynomials,Scale- and rotation-invariance,Singular-pattern detection,Vector fields},\n pages = {3912-3925},\n volume = {45},\n websites = {https://www.sciencedirect.com/science/article/pii/S0031320312002051},\n month = {4},\n publisher = {Pergamon},\n id = {cbfa91e7-6cad-35ed-9166-39b6d4808341},\n created = {2021-04-09T15:24:38.546Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:38.546Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. © 2012 Elsevier Ltd. All rights reserved.},\n bibtype = {article},\n author = {Liu, Wei and Ribeiro, Eraldo},\n doi = {10.1016/j.patcog.2012.04.025},\n journal = {Pattern Recognition},\n number = {11}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In this paper, we propose a method for detecting patterns of interest in vector fields. Our method detects patterns in a scale- and rotation-invariant manner. It works by approximating the vector-field data locally using a Laurent polynomial weighted by radial basis functions. The proposed representation is able to model both analytic and non-analytic flow fields. Invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale-space parameter of the radial basis functions. Promising detection results are obtained on a variety of fluid-flow sequences. © 2012 Elsevier Ltd. All rights reserved.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2011\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2011')\"\n      onkeypress=\"toggleGroup('group_2011')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2011</span>\n      <span class=\"bibbase_group_count\">\n        \n        (6)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.nonlin-processes-geophys.net/18/261/2011/\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011', 'https://www.nonlin-processes-geophys.net/18/261/2011/', event);\">\n    Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Wu,  C., C.;  and Chang,  T.\n</span>\n\n  \n\n</span>\n\n  <i>Nonlinear Processes in Geophysics</i>, 18(2): 261-268. 4 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.nonlin-processes-geophys.net/18/261/2011/\"\n     onclick=\"log_download('wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011', 'https://www.nonlin-processes-geophys.net/18/261/2011/', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5194/npg-18-261-2011\"\n     onclick=\"log_download('wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011', 'http://doi.org/10.5194/npg-18-261-2011', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('wu-chang-rankorderedmultifractalanalysisromaofprobabilitydistributionsinfluidturbulence-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Rank-Ordered Multifractal Analysis (ROMA) of probability distributions in fluid turbulence},\n type = {article},\n year = {2011},\n pages = {261-268},\n volume = {18},\n websites = {https://www.nonlin-processes-geophys.net/18/261/2011/},\n month = {4},\n id = {8f32c50d-8599-33b6-a5d8-0a33019102dd},\n created = {2021-04-09T15:23:22.180Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:22.180Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.},\n bibtype = {article},\n author = {Wu, C C and Chang, T},\n doi = {10.5194/npg-18-261-2011},\n journal = {Nonlinear Processes in Geophysics},\n number = {2}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Abstract. Rank-Ordered Multifractal Analysis (ROMA) was introduced by Chang and Wu (2008) to describe the multifractal characteristic of intermittent events. The procedure provides a natural connection between the rank-ordered spectrum and the idea of one-parameter scaling for monofractals. This technique has successfully been applied to MHD turbulence simulations and turbulence data observed in various space plasmas. In this paper, the technique is applied to the probability distributions in the inertial range of the turbulent fluid flow, as given in the vast Johns Hopkins University (JHU) turbulence database. In addition, a new way of finding the continuous ROMA spectrum and the scaled probability distribution function (PDF) simultaneously is introduced.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011', 'https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models', event);\">\n    Group Anomaly Detection using Flexible Genre Models.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Xiong,  L.; Poczos,  B.;  and Schneider,  J.\n</span>\n\n  \n\n</span>\n\n  In <i>Advances in Neural Information Processing Systems</i>, pages 1071-1079,  2011. Neural Information Processing Systems\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models\"\n     onclick=\"log_download('xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011', 'https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Group Anomaly Detection using Flexible Genre Models [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.5591/978-1-57735-516-8/IJCAI11-254\"\n     onclick=\"log_download('xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011', 'http://doi.org/10.5591/978-1-57735-516-8/IJCAI11-254', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('xiong-poczos-schneider-groupanomalydetectionusingflexiblegenremodels-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@inproceedings{\n title = {Group Anomaly Detection using Flexible Genre Models},\n type = {inproceedings},\n year = {2011},\n pages = {1071-1079},\n websites = {https://dl.acm.org/citation.cfm?id=2986579,http://papers.nips.cc/paper/4299-group-anomaly-detection-using-flexible-genre-models},\n publisher = {Neural Information Processing Systems},\n id = {8a5cc374-2abf-3d97-ac43-391fd8dc4019},\n created = {2021-04-09T15:23:31.713Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:31.713Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {An important task in exploring and analyzing real-world data sets is to detect unusual and interesting phenomena. In this paper, we study the group anomaly detection problem. Unlike traditional anomaly detection research that focuses on data points, our goal is to discover anomalous aggregated behaviors of groups of points. For this purpose, we propose the Flexible Genre Model (FGM). FGM is designed to characterize data groups at both the point level and the group level so as to detect various types of group anomalies. We evaluate the effectiveness of FGM on both synthetic and real data sets including images and turbulence data, and show that it is superior to existing approaches in detecting group anomalies.},\n bibtype = {inproceedings},\n author = {Xiong, Liang and Poczos, Barnabas and Schneider, Jeff},\n doi = {10.5591/978-1-57735-516-8/IJCAI11-254},\n booktitle = {Advances in Neural Information Processing Systems}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  An important task in exploring and analyzing real-world data sets is to detect unusual and interesting phenomena. In this paper, we study the group anomaly detection problem. Unlike traditional anomaly detection research that focuses on data points, our goal is to discover anomalous aggregated behaviors of groups of points. For this purpose, we propose the Flexible Genre Model (FGM). FGM is designed to characterize data groups at both the point level and the group level so as to detect various types of group anomalies. We evaluate the effectiveness of FGM on both synthetic and real data sets including images and turbulence data, and show that it is superior to existing approaches in detecting group anomalies.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"eyink-stochasticfluxfreezingandmagneticdynamo-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.83.056405\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'eyink-stochasticfluxfreezingandmagneticdynamo-2011', 'https://link.aps.org/doi/10.1103/PhysRevE.83.056405', event);\">\n    Stochastic flux freezing and magnetic dynamo.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Eyink,  G., L.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 83(5): 56405. 4 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.83.056405\"\n     onclick=\"log_download('eyink-stochasticfluxfreezingandmagneticdynamo-2011', 'https://link.aps.org/doi/10.1103/PhysRevE.83.056405', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Stochastic flux freezing and magnetic dynamo [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.83.056405\"\n     onclick=\"log_download('eyink-stochasticfluxfreezingandmagneticdynamo-2011', 'http://doi.org/10.1103/PhysRevE.83.056405', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/eyink-stochasticfluxfreezingandmagneticdynamo-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('eyink-stochasticfluxfreezingandmagneticdynamo-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Stochastic flux freezing and magnetic dynamo},\n type = {article},\n year = {2011},\n pages = {56405},\n volume = {83},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.83.056405},\n month = {4},\n publisher = {American Physical Society},\n id = {86fc86ac-22a9-3fa9-917f-b58302cd9209},\n created = {2021-04-09T15:23:45.122Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:45.122Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the &quot;spontaneous stochasticity&quot; of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.},\n bibtype = {article},\n author = {Eyink, Gregory L},\n doi = {10.1103/PhysRevE.83.056405},\n journal = {Physical Review E},\n number = {5}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the \"spontaneous stochasticity\" of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011', 'http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047', event);\">\n    A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Keylock,  C., J.; Tokyay,  T., E.;  and Constantinescu,  G.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Turbulence</i>, 12: N45. 4 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047\"\n     onclick=\"log_download('keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011', 'http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1080/14685248.2011.636047\"\n     onclick=\"log_download('keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011', 'http://doi.org/10.1080/14685248.2011.636047', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('keylock-tokyay-constantinescu-amethodforcharacterisingthesensitivityofturbulentflowfieldstothestructureofinletturbulence-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {A method for characterising the sensitivity of turbulent flow fields to the structure of inlet turbulence},\n type = {article},\n year = {2011},\n pages = {N45},\n volume = {12},\n websites = {http://www.tandfonline.com/doi/abs/10.1080/14685248.2011.636047},\n month = {4},\n id = {d9d6d4ff-bbf2-3017-9a97-263565beec5a},\n created = {2021-04-09T15:24:03.970Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:03.970Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The specification of inlet conditions for eddy-resolving simulations is an important research question in turbulence research. A large number of schemes have been proposed but comparisons to a benchmark simulation are usually undertaken in such a way that it is ambiguous as to whether the source of the improved preservation of the properties of the benchmark case is due to the physics captured in the inlet generation algorithm or to differences in the precise values or spectra generated at a particular position. This article uses gradual wavelet reconstruction to degrade a precursor simulation such that the time series input at each cell has the same histogram and Fourier spectrum as the original precursor case, thereby removing this source of variability. A parameter, ρ, is used to index the nature of the degraded inlets and as ρ increases from 0 to 1 the cross-correlative and nonlinear properties of the precursor are increasingly preserved too. We compare the results of four large-eddy simulations for the flow over a wall-mounted square rib and show that there are clear differences between these simulations for the flow before and over the rib, and in the far-field. However, in the wake, the intense shearing and mixing means that any differences are harder to attribute to the nature of the inlet. Hence, for flows that are mixed strongly, there is less of a need to preserve the cross-correlative structure of the inlet condition as long as the individual velocity components are modelled with an appropriate set of values and Fourier spectrum. By comparing particular inlet generation algorithms in terms of the value for ρ that they can attain, their suitability for modelling flows of particular configurations may be determined.},\n bibtype = {article},\n author = {Keylock, C J and Tokyay, T E and Constantinescu, G},\n doi = {10.1080/14685248.2011.636047},\n journal = {Journal of Turbulence}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The specification of inlet conditions for eddy-resolving simulations is an important research question in turbulence research. A large number of schemes have been proposed but comparisons to a benchmark simulation are usually undertaken in such a way that it is ambiguous as to whether the source of the improved preservation of the properties of the benchmark case is due to the physics captured in the inlet generation algorithm or to differences in the precise values or spectra generated at a particular position. This article uses gradual wavelet reconstruction to degrade a precursor simulation such that the time series input at each cell has the same histogram and Fourier spectrum as the original precursor case, thereby removing this source of variability. A parameter, ρ, is used to index the nature of the degraded inlets and as ρ increases from 0 to 1 the cross-correlative and nonlinear properties of the precursor are increasingly preserved too. We compare the results of four large-eddy simulations for the flow over a wall-mounted square rib and show that there are clear differences between these simulations for the flow before and over the rib, and in the far-field. However, in the wake, the intense shearing and mixing means that any differences are harder to attribute to the nature of the inlet. Hence, for flows that are mixed strongly, there is less of a need to preserve the cross-correlative structure of the inlet condition as long as the individual velocity components are modelled with an appropriate set of values and Fourier spectrum. By comparing particular inlet generation algorithms in terms of the value for ρ that they can attain, their suitability for modelling flows of particular configurations may be determined.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.3555635\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011', 'http://aip.scitation.org/doi/10.1063/1.3555635', event);\">\n    Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Grinstein,  F., F.; Gowardhan,  A., A.;  and Wachtor,  A., J.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 23(3): 34106. 4 2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.3555635\"\n     onclick=\"log_download('grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011', 'http://aip.scitation.org/doi/10.1063/1.3555635', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.3555635\"\n     onclick=\"log_download('grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011', 'http://doi.org/10.1063/1.3555635', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('grinstein-gowardhan-wachtor-simulationsofrichtmyermeshkovinstabilitiesinplanarshocktubeexperiments-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Simulations of Richtmyer-Meshkov instabilities in planar shock-tube experiments},\n type = {article},\n year = {2011},\n pages = {34106},\n volume = {23},\n websites = {http://aip.scitation.org/doi/10.1063/1.3555635},\n month = {4},\n id = {4c17b164-a584-3e14-b6d0-bb2be167808d},\n created = {2021-04-09T15:24:08.268Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:08.268Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper-flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer-Meshkov instabilities in planar shock-tube laboratory experiments is reported. Our particular focus is devoted to the initial material interface characterization and modeling difficulties, and effects of initial condition specifics (resolved spectral content) on transitional and late-time turbulent mixing-which were not previously addressed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3555635]},\n bibtype = {article},\n author = {Grinstein, F F and Gowardhan, A A and Wachtor, A J},\n doi = {10.1063/1.3555635},\n journal = {Physics of Fluids},\n number = {3}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  In the large eddy simulation (LES) approach, large-scale energy-containing structures are resolved, smaller structures are filtered out, and unresolved subgrid effects are modeled. Extensive recent work has demonstrated that predictive under-resolved simulations of the velocity fields in turbulent flows are possible without resorting to explicit subgrid models when using a class of physics-capturing high-resolution finite-volume numerical algorithms. This strategy is denoted as implicit LES (ILES). Tests in fundamental applications ranging from canonical to complex flows indicate that ILES is competitive with conventional LES in the LES realm proper-flows driven by large-scale features. The performance of ILES in the substantially more difficult problem of under-resolved material mixing driven by under-resolved velocity fields and initial conditions is a focus of the present work. Progress in addressing relevant resolution issues in studies of mixing driven by Richtmyer-Meshkov instabilities in planar shock-tube laboratory experiments is reported. Our particular focus is devoted to the initial material interface characterization and modeling difficulties, and effects of initial condition specifics (resolved spectral content) on transitional and late-time turbulent mixing-which were not previously addressed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3555635]\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011', 'http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611', event);\">\n    Assessment of the modulated gradient model in decaying isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lu,  H.\n</span>\n\n  \n\n</span>\n\n  <i>Theoretical and Applied Mechanics Letters</i>, 1(4): 41004.  2011.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611\"\n     onclick=\"log_download('lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011', 'http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Assessment of the modulated gradient model in decaying isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/2.1104104\"\n     onclick=\"log_download('lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011', 'http://doi.org/10.1063/2.1104104', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lu-assessmentofthemodulatedgradientmodelindecayingisotropicturbulence-2011')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Assessment of the modulated gradient model in decaying isotropic turbulence},\n type = {article},\n year = {2011},\n keywords = {isotropic turbulence,large-eddy simulation,subgrid-scale model},\n pages = {41004},\n volume = {1},\n websites = {http://linkinghub.elsevier.com/retrieve/pii/S2095034915300611},\n id = {946ab0e5-f9b6-3355-95e1-780cbcb83d88},\n created = {2021-04-09T15:24:09.345Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:09.345Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n bibtype = {article},\n author = {Lu, Hao},\n doi = {10.1063/2.1104104},\n journal = {Theoretical and Applied Mechanics Letters},\n number = {4}\n}</pre>\n</div>\n\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2010\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2010')\"\n      onkeypress=\"toggleGroup('group_2010')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2010</span>\n      <span class=\"bibbase_group_count\">\n        \n        (4)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.3442477\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010', 'http://aip.scitation.org/doi/10.1063/1.3442477', event);\">\n    Viscous tilting and production of vorticity in homogeneous turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Holzner,  M.; Guala,  M.; Lüthi,  B.; Liberzon,  A.; Nikitin,  N.; Kinzelbach,  W.;  and Tsinober,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Physics of Fluids</i>, 22(6): 1-4. 4 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://aip.scitation.org/doi/10.1063/1.3442477\"\n     onclick=\"log_download('holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010', 'http://aip.scitation.org/doi/10.1063/1.3442477', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Viscous tilting and production of vorticity in homogeneous turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1063/1.3442477\"\n     onclick=\"log_download('holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010', 'http://doi.org/10.1063/1.3442477', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('holzner-guala-lthi-liberzon-nikitin-kinzelbach-tsinober-viscoustiltingandproductionofvorticityinhomogeneousturbulence-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Viscous tilting and production of vorticity in homogeneous turbulence},\n type = {article},\n year = {2010},\n keywords = {flow simulation,flow visualisation,turbulence,vortices},\n pages = {1-4},\n volume = {22},\n websites = {http://aip.scitation.org/doi/10.1063/1.3442477},\n month = {4},\n publisher = {American Institute of Physics},\n id = {13eeab2c-f93a-38bc-8939-c93fd2904977},\n created = {2021-04-09T15:23:52.216Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:23:52.216Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Viscous depletion of vorticity is an essential and well known property of turbulent flows, balancing, in the mean, the net vorticity production associated with the vortex stretching mechanism. In this letter we however demonstrate that viscous effects are not restricted to a mere destruction process, but play a more complex role in vorticity dynamics that is as important as vortex stretching. Based on results from particle tracking experiments (3D-PTV) and direct numerical simulation (DNS) of homogeneous and quasi isotropic turbulence, we show that the viscous term in the vorticity equation can also locally induce production of vorticity and changes of its orientation (viscous tilting).},\n bibtype = {article},\n author = {Holzner, M and Guala, M and Lüthi, B and Liberzon, A and Nikitin, N and Kinzelbach, W and Tsinober, A},\n doi = {10.1063/1.3442477},\n journal = {Physics of Fluids},\n number = {6}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Viscous depletion of vorticity is an essential and well known property of turbulent flows, balancing, in the mean, the net vorticity production associated with the vortex stretching mechanism. In this letter we however demonstrate that viscous effects are not restricted to a mere destruction process, but play a more complex role in vorticity dynamics that is as important as vortex stretching. Based on results from particle tracking experiments (3D-PTV) and direct numerical simulation (DNS) of homogeneous and quasi isotropic turbulence, we show that the viscous term in the vorticity equation can also locally induce production of vorticity and changes of its orientation (viscous tilting).\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/s10494-010-9256-5\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010', 'http://link.springer.com/10.1007/s10494-010-9256-5', event);\">\n    Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Yu,  H.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Flow, Turbulence and Combustion</i>, 85(3-4): 457-472. 4 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/s10494-010-9256-5\"\n     onclick=\"log_download('yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010', 'http://link.springer.com/10.1007/s10494-010-9256-5', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/s10494-010-9256-5\"\n     onclick=\"log_download('yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010', 'http://doi.org/10.1007/s10494-010-9256-5', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('yu-meneveau-scalingofconditionallagrangiantimecorrelationfunctionsofvelocityandpressuregradientmagnitudesinisotropicturbulence-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Scaling of conditional lagrangian time correlation functions of velocity and pressure gradient magnitudes in isotropic turbulence},\n type = {article},\n year = {2010},\n keywords = {Direct numerical simulation,Isotropic turbulence,Lagrangian statistics,Refined Kolomogorov similarity hypothesis,Turbulence database},\n pages = {457-472},\n volume = {85},\n websites = {http://link.springer.com/10.1007/s10494-010-9256-5},\n month = {4},\n publisher = {Springer Netherlands},\n id = {4f1f9075-6def-3580-8365-e90f69ed1485},\n created = {2021-04-09T15:24:13.990Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:13.990Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {We study Lagrangian statistics of the magnitudes of velocity and pressure gradients in isotropic turbulence by quantifying their correlation functions and their characteristic time scales. In a recent work (Yu and Meneveau, Phys Rev Lett 104:084502, 2010), it has been found that the Lagrangian time-correlations of the velocity and pressure gradient tensor and vector elements scale with the locally- definedKolmogorov time scale, evaluated from the locally-averaged dissipation-rate (?r) and viscosity (ν) according to τK,r = √ν/?r. In thiswork, we study theLagrangian time-correlations of the absolute values of velocity and pressure gradients. It has long been known that such correlations display longer memories into the inertial- range as well as possible intermittency effects. We explore the appropriate temporal scales with the aim to achieve collapse of the correlation functions. The data used in this study are sampled from the web-services accessible public turbulence database (http://turbulence.pha.jhu.edu). The database archives a 10244 (space+time) pseudo- spectral direct numerical simulation of forced isotropic turbulence with Taylor- scale Reynolds number Reλ = 433, and supports spatial differentiation and spa- tial/temporal interpolation inside the database. The analysis shows that the temporal auto-correlations of the absolute values extend deep into the inertial range where they are determined not by the local Kolmogorov time-scale but by the local eddy-turnover time scale defined as τe,r = r2/3?−1/3 r .However, considerable scatter remains and appears to be reduced only after a further (intermittency) correction factor of the form of (r/L)χ is introduced, where L is the turbulence integral scale. The exponent χ varies for different variables. The collapse of the correlation functions for absolute values is, however, less satisfactory than the collapse observed for the more rapidly decaying strain-rate tensor element correlation functions in the viscous range.},\n bibtype = {article},\n author = {Yu, Huidan and Meneveau, Charles},\n doi = {10.1007/s10494-010-9256-5},\n journal = {Flow, Turbulence and Combustion},\n number = {3-4}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We study Lagrangian statistics of the magnitudes of velocity and pressure gradients in isotropic turbulence by quantifying their correlation functions and their characteristic time scales. In a recent work (Yu and Meneveau, Phys Rev Lett 104:084502, 2010), it has been found that the Lagrangian time-correlations of the velocity and pressure gradient tensor and vector elements scale with the locally- definedKolmogorov time scale, evaluated from the locally-averaged dissipation-rate (?r) and viscosity (ν) according to τK,r = √ν/?r. In thiswork, we study theLagrangian time-correlations of the absolute values of velocity and pressure gradients. It has long been known that such correlations display longer memories into the inertial- range as well as possible intermittency effects. We explore the appropriate temporal scales with the aim to achieve collapse of the correlation functions. The data used in this study are sampled from the web-services accessible public turbulence database (http://turbulence.pha.jhu.edu). The database archives a 10244 (space+time) pseudo- spectral direct numerical simulation of forced isotropic turbulence with Taylor- scale Reynolds number Reλ = 433, and supports spatial differentiation and spa- tial/temporal interpolation inside the database. The analysis shows that the temporal auto-correlations of the absolute values extend deep into the inertial range where they are determined not by the local Kolmogorov time-scale but by the local eddy-turnover time scale defined as τe,r = r2/3?−1/3 r .However, considerable scatter remains and appears to be reduced only after a further (intermittency) correction factor of the form of (r/L)χ is introduced, where L is the turbulence integral scale. The exponent χ varies for different variables. The collapse of the correlation functions for absolute values is, however, less satisfactory than the collapse observed for the more rapidly decaying strain-rate tensor element correlation functions in the viscous range.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://link.springer.com/10.1007/978-3-642-14980-1_51\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010', 'http://link.springer.com/10.1007/978-3-642-14980-1_51', event);\">\n    Scale and rotation invariant detection of singular patterns in vector flow fields.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Liu,  W.;  and Ribeiro,  E.\n</span>\n\n  \n\n</span>\n\n   2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://link.springer.com/10.1007/978-3-642-14980-1_51\"\n     onclick=\"log_download('liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010', 'http://link.springer.com/10.1007/978-3-642-14980-1_51', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Scale and rotation invariant detection of singular patterns in vector flow fields [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1007/978-3-642-14980-1_51\"\n     onclick=\"log_download('liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010', 'http://doi.org/10.1007/978-3-642-14980-1_51', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('liu-ribeiro-scaleandrotationinvariantdetectionofsingularpatternsinvectorflowfields-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {Scale and rotation invariant detection of singular patterns in vector flow fields},\n type = {misc},\n year = {2010},\n source = {Structural, Syntactic, and Statistical Pattern Recognition},\n pages = {522-531},\n volume = {6218},\n websites = {http://link.springer.com/10.1007/978-3-642-14980-1_51},\n publisher = {Springer, Berlin, Heidelberg},\n id = {87624f2f-71c5-35a8-8049-4b22ce15c2a2},\n created = {2021-04-09T15:24:19.096Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:19.096Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {book_section},\n private_publication = {false},\n abstract = {We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based inner-product. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.},\n bibtype = {misc},\n author = {Liu, Wei and Ribeiro, Eraldo},\n doi = {10.1007/978-3-642-14980-1_51}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomials form an orthogonal basis for analytic flows with respect to a correlation-based inner-product. We investigate the invariance properties of the coefficients of the approximation polynomials under both rotation and scaling operators. We then propose a descriptor for local flow patterns, and developed a method for comparing them invariantly against rigid transformations. Additionally, we propose a SIFT-like detector that can automatically detect singular flow patterns at different scales and orientations. Promising detection results are obtained on different fluid flow data.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0376042109000335\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010', 'https://www.sciencedirect.com/science/article/pii/S0376042109000335', event);\">\n    A new two-scale model for large eddy simulation of wall-bounded flows.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Gungor,  A., G.;  and Menon,  S.\n</span>\n\n  \n\n</span>\n\n  4 2010.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://www.sciencedirect.com/science/article/pii/S0376042109000335\"\n     onclick=\"log_download('gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010', 'https://www.sciencedirect.com/science/article/pii/S0376042109000335', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"A new two-scale model for large eddy simulation of wall-bounded flows [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1016/j.paerosci.2009.10.001\"\n     onclick=\"log_download('gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010', 'http://doi.org/10.1016/j.paerosci.2009.10.001', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n  &nbsp;\n  <span class=\"bibbase_stats_paper\" style=\"color: #777;\">\n    <span>1 download</span>\n  </span>\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('gungor-menon-anewtwoscalemodelforlargeeddysimulationofwallboundedflows-2010')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@misc{\n title = {A new two-scale model for large eddy simulation of wall-bounded flows},\n type = {misc},\n year = {2010},\n source = {Progress in Aerospace Sciences},\n keywords = {Large eddy simulation,Near-wall modeling,Two-scale model,Wall-bounded flows},\n pages = {28-45},\n volume = {46},\n issue = {1},\n websites = {https://www.sciencedirect.com/science/article/pii/S0376042109000335},\n month = {4},\n publisher = {Pergamon},\n id = {4ccb1c94-15b2-3ba4-bb44-eb3f823029b8},\n created = {2021-04-09T15:24:26.762Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:26.762Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {generic},\n private_publication = {false},\n abstract = {A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS-LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS-LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS-LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS-LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number. © 2009 Elsevier Ltd. All rights reserved.},\n bibtype = {misc},\n author = {Gungor, Ayse Gul and Menon, Suresh},\n doi = {10.1016/j.paerosci.2009.10.001}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS-LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS-LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS-LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS-LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number. © 2009 Elsevier Ltd. All rights reserved.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n  <div class=\"bibbase_group_whole\" id=\"group_2009\">\n    <div class=\"bibbase_group\"\n      onclick=\"toggleGroup('group_2009')\"\n      onkeypress=\"toggleGroup('group_2009')\"\n      tabindex=\"0\">\n      <i class=\"fa fa-angle-down bibbase_group_head_icon\"></i>&nbsp;\n      <span>2009</span>\n      <span class=\"bibbase_group_count\">\n        \n        (2)\n        \n      </span>\n    </div>\n    <div class=\"bibbase_group_body\">\n      \n  \n  <div class=\"bibbase_paper\" id=\"lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112009991947\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009', 'http://www.journals.cambridge.org/abstract_S0022112009991947', event);\">\n    Expanding the Q-R space to three dimensions.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Lthi,  B.; Holzner,  M.;  and Tsinober,  A.\n</span>\n\n  \n\n</span>\n\n  <i>Journal of Fluid Mechanics</i>, 641: 497-507. 4 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"http://www.journals.cambridge.org/abstract_S0022112009991947\"\n     onclick=\"log_download('lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009', 'http://www.journals.cambridge.org/abstract_S0022112009991947', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Expanding the Q-R space to three dimensions [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1017/S0022112009991947\"\n     onclick=\"log_download('lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009', 'http://doi.org/10.1017/S0022112009991947', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('lthi-holzner-tsinober-expandingtheqrspacetothreedimensions-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n  \n  \n  \n  \n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Expanding the Q-R space to three dimensions},\n type = {article},\n year = {2009},\n keywords = {Dynamics,Isotropic,Theory},\n pages = {497-507},\n volume = {641},\n websites = {http://www.journals.cambridge.org/abstract_S0022112009991947},\n month = {4},\n publisher = {Cambridge University Press},\n id = {55fd8e33-1071-34c1-9965-1831405aefe6},\n created = {2021-04-09T15:24:30.382Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:30.382Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {The two-dimensional space spanned by the velocity gradient invariants Q and R is expanded to three dimensions by the decomposition of R into its strain production −1/3sijsjkski and enstrophy production 1/4ωiωjsij terms. The Q; R space is a planar projection of the new three-dimensional representation. In the Q; −sss; ωωs space the Lagrangian evolution of the velocity gradient tensor Aij is studied via conditional mean trajectories (CMTs) as introduced by Martín et al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence of Reλ ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to the Q–R plane. The relatively weak cyclic evolution in the Q–R space is thus only a projection of a much stronger cycle in the Q; −sss; ωωs space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian of Aij, on the other hand, seems the main responsible for intermittently alternating between low and high intensity Aij states.},\n bibtype = {article},\n author = {Lthi, Beat and Holzner, Markus and Tsinober, Arkady},\n doi = {10.1017/S0022112009991947},\n journal = {Journal of Fluid Mechanics}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  The two-dimensional space spanned by the velocity gradient invariants Q and R is expanded to three dimensions by the decomposition of R into its strain production −1/3sijsjkski and enstrophy production 1/4ωiωjsij terms. The Q; R space is a planar projection of the new three-dimensional representation. In the Q; −sss; ωωs space the Lagrangian evolution of the velocity gradient tensor Aij is studied via conditional mean trajectories (CMTs) as introduced by Martín et al. (Phys. Fluids, vol. 10, 1998, p. 2012). From an analysis of a numerical data set for isotropic turbulence of Reλ ~ 434, taken from the Johns Hopkins University (JHU) turbulence database, we observe a pronounced cyclic evolution that is almost perpendicular to the Q–R plane. The relatively weak cyclic evolution in the Q–R space is thus only a projection of a much stronger cycle in the Q; −sss; ωωs space. Further, we find that the restricted Euler (RE) dynamics are primarily counteracted by the deviatoric non-local part of the pressure Hessian and not by the viscous term. The contribution of the Laplacian of Aij, on the other hand, seems the main responsible for intermittently alternating between low and high intensity Aij states.\n</div>\n\n\n</div>\n\n\n  <div class=\"bibbase_paper\" id=\"li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009\">\n  <span class=\"bibbase_paper_titleauthoryear\">\n\n  \n  <span class=\"bibbase_paper_title\">\n  \n  \n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.79.016305\"\n     onclick=\"return trackOutboundLink('publications', 'click', 'li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009', 'https://link.aps.org/doi/10.1103/PhysRevE.79.016305', event);\">\n    Matrix exponential-based closures for the turbulent subgrid-scale stress tensor.\n  </a>\n  \n  \n  \n</span>\n\n  <span class=\"bibbase_paper_author\">\n  Li,  Y.; Chevillard,  L.; Eyink,  G.;  and Meneveau,  C.\n</span>\n\n  \n\n</span>\n\n  <i>Physical Review E</i>, 79(1): 16305. 4 2009.\n  <span class=\"note\"></span>\n\n<span class=\"bibbase_note\"></span>\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content dontprint\">\n\n  \n  <a href=\"https://link.aps.org/doi/10.1103/PhysRevE.79.016305\"\n     onclick=\"log_download('li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009', 'https://link.aps.org/doi/10.1103/PhysRevE.79.016305', event.ctrlKey, event)\">\n    <img src=\"//bibbase.org/img/filetypes/link.svg\"\n\t     alt=\"Matrix exponential-based closures for the turbulent subgrid-scale stress tensor [link]\"\n       title=\"Website\"\n\t     class=\"bibbase_icon\"\n         ><span class=\"bibbase_icon_text\">Website</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"http://doi.org/10.1103/PhysRevE.79.016305\"\n     onclick=\"log_download('li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009', 'http://doi.org/10.1103/PhysRevE.79.016305', event.ctrlKey)\"\n     class=\"bibbase doi link\">\n    <span>doi</span></a>\n  &nbsp;\n  \n\n  \n  <a href=\"//bibbase.org/network/publication/li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009\"\n     class=\"bibbase bibbase_page link\">link</a>\n  &nbsp;\n  \n\n  <a href=\"#\"\n     onclick=\"showBib(event); return false;\"\n     class=\"bibbase bibtex link\">bibtex\n    <i class=\"fa fa-caret-down\"></i></a>\n\n  \n  &nbsp;\n  <a class=\"bibbase_abstract_link bibbase link\"\n     href=\"#\"\n     onclick=\"showAbstract(event); return false;\">\n    abstract <i class=\"fa fa-caret-down\"></i></a>\n  \n\n  \n\n  <!-- <a class=\"bibbase read link hidden\" -->\n  <!--    href=\"javascript:toggleRead('li-chevillard-eyink-meneveau-matrixexponentialbasedclosuresfortheturbulentsubgridscalestresstensor-2009')\" -->\n  <!--    title=\"Marking this paper as read adds it to your library on BibBase.\" -->\n  <!--    > -->\n  <!--   <i class=\"fa fa-check\"></i>&nbsp; -->\n  <!--   <span>mark as read</span> -->\n  <!-- </a> -->\n\n  &nbsp;\n  \n  \n\n</span>\n\n<div class=\"well well-small bibbase\" data-type=\"bibtex\"\n     style=\"display:none\">\n  <pre style=\"white-space: pre-wrap;\">@article{\n title = {Matrix exponential-based closures for the turbulent subgrid-scale stress tensor},\n type = {article},\n year = {2009},\n pages = {16305},\n volume = {79},\n websites = {https://link.aps.org/doi/10.1103/PhysRevE.79.016305},\n month = {4},\n publisher = {American Physical Society},\n id = {10a7b192-a61d-398c-87e8-0b2c2e32adc1},\n created = {2021-04-09T15:24:39.135Z},\n file_attached = {false},\n profile_id = {75799766-8e2d-3c98-81f9-e3efa41233d0},\n group_id = {c9329632-2a50-3043-b803-cadc8dbdfc3f},\n last_modified = {2021-04-09T15:24:39.135Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n source_type = {article},\n private_publication = {false},\n abstract = {Two approaches for closing the turbulence subgrid-scale stress tensor in terms of matrix exponentials are introduced and compared. The first approach is based on a formal solution of the stress transport equation in which the production terms can be integrated exactly in terms of matrix exponentials. This formal solution of the subgrid-scale stress transport equation is shown to be useful to explore special cases, such as the response to constant velocity gradient, but neglecting pressure-strain correlations and diffusion effects. The second approach is based on an Eulerian-Lagrangian change of variables, combined with the assumption of isotropy for the conditionally averaged Lagrangian velocity gradient tensor and with the recent fluid deformation approximation. It is shown that both approaches lead to the same basic closure in which the stress tensor is expressed as the matrix exponential of the resolved velocity gradient tensor multiplied by its transpose. Short-time expansions of the matrix exponentials are shown to provide an eddy-viscosity term and particular quadratic terms, and thus allow a reinterpretation of traditional eddy-viscosity and nonlinear stress closures. The basic feasibility of the matrix-exponential closure is illustrated by implementing it successfully in large eddy simulation of forced isotropic turbulence. The matrix-exponential closure employs the drastic approximation of entirely omitting the pressure-strain correlation and other nonlinear scrambling terms. But unlike eddy-viscosity closures, the matrix exponential approach provides a simple and local closure that can be derived directly from the stress transport equation with the production term, and using physically motivated assumptions about Lagrangian decorrelation and upstream isotropy.},\n bibtype = {article},\n author = {Li, Yi and Chevillard, Laurent and Eyink, Gregory and Meneveau, Charles},\n doi = {10.1103/PhysRevE.79.016305},\n journal = {Physical Review E},\n number = {1}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" data-type=\"abstract\"\n     style=\"display:none\">\n  Two approaches for closing the turbulence subgrid-scale stress tensor in terms of matrix exponentials are introduced and compared. The first approach is based on a formal solution of the stress transport equation in which the production terms can be integrated exactly in terms of matrix exponentials. This formal solution of the subgrid-scale stress transport equation is shown to be useful to explore special cases, such as the response to constant velocity gradient, but neglecting pressure-strain correlations and diffusion effects. The second approach is based on an Eulerian-Lagrangian change of variables, combined with the assumption of isotropy for the conditionally averaged Lagrangian velocity gradient tensor and with the recent fluid deformation approximation. It is shown that both approaches lead to the same basic closure in which the stress tensor is expressed as the matrix exponential of the resolved velocity gradient tensor multiplied by its transpose. Short-time expansions of the matrix exponentials are shown to provide an eddy-viscosity term and particular quadratic terms, and thus allow a reinterpretation of traditional eddy-viscosity and nonlinear stress closures. The basic feasibility of the matrix-exponential closure is illustrated by implementing it successfully in large eddy simulation of forced isotropic turbulence. The matrix-exponential closure employs the drastic approximation of entirely omitting the pressure-strain correlation and other nonlinear scrambling terms. But unlike eddy-viscosity closures, the matrix exponential approach provides a simple and local closure that can be derived directly from the stress transport equation with the production term, and using physically motivated assumptions about Lagrangian decorrelation and upstream isotropy.\n</div>\n\n\n</div>\n\n\n\n\n\n    </div>\n  </div>\n\n\n\n\n  </div>\n\n\n  <!-- Modal -->\n\n  <!-- <iframe id=\"bibbase_network_frame\" -->\n  <!--         src=\"//bibbase.org/network/control\" -->\n  <!--         style=\"display: none;\"> -->\n  <!-- </iframe> -->\n\n</div>\n"}; document.write(bibbase_data.data);