SU2: An open-source suite for multiphysics simulation and design. Economon, T. D., Palacios, F., Copeland, S. R., Lukaczyk, T. W., & Alonso, J. J. AIAA Journal, 54(3):828–846, American Institute of Aeronautics and Astronautics Inc., 2016.
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This paper presents the main objectives and a description of the SU2 suite, including the novel software architecture and open-source software engineering strategy. SU2 is a computational analysis and design package that has been developed to solve multiphysics analysis and optimization tasks using unstructured mesh topologies. Its unique architecture iswell suited for extensibility to treat partial-differential-equation-based problems not initially envisioned. The common framework adopted enables the rapid implementation of newphysics packages that can be tightly coupled to form a powerful ensemble of analysis tools to address complex problems facing many engineering communities. The framework is demonstrated on a number, solving both the flow and adjoint systems of equations to provide a highfidelity predictive capability and sensitivity information that can be used for optimal shape design using a gradientbased framework, goal-oriented adaptive mesh refinement, or uncertainty quantification.
@article{economon2016a,
	title = {{SU2}: {An} open-source suite for multiphysics simulation and design},
	volume = {54},
	doi = {10.2514/1.J053813},
	abstract = {This paper presents the main objectives and a description of the SU2 suite, including the novel software architecture and open-source software engineering strategy. SU2 is a computational analysis and design package that has been developed to solve multiphysics analysis and optimization tasks using unstructured mesh topologies. Its unique architecture iswell suited for extensibility to treat partial-differential-equation-based problems not initially envisioned. The common framework adopted enables the rapid implementation of newphysics packages that can be tightly coupled to form a powerful ensemble of analysis tools to address complex problems facing many engineering communities. The framework is demonstrated on a number, solving both the flow and adjoint systems of equations to provide a highfidelity predictive capability and sensitivity information that can be used for optimal shape design using a gradientbased framework, goal-oriented adaptive mesh refinement, or uncertainty quantification.},
	number = {3},
	journal = {AIAA Journal},
	publisher = {American Institute of Aeronautics and Astronautics Inc.},
	author = {Economon, Thomas D. and Palacios, Francisco and Copeland, Sean R. and Lukaczyk, Trent W. and Alonso, Juan J.},
	year = {2016},
	pages = {828--846},
}

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