@inproceedings{
 title = {Assessment of High-Temperature Effects on Hypersonic Aerothermoelastic Analysis using Multi-Fidelity Multi-Variate Surrogates},
 type = {inproceedings},
 year = {2021},
 websites = {https://arc.aiaa.org/doi/10.2514/6.2021-1610},
 month = {1},
 publisher = {AIAA Paper 2021-1610},
 id = {69f83e72-ca48-36ad-9d9c-0961a4bb4ec6},
 created = {2021-01-05T20:43:35.491Z},
 accessed = {2021-01-05},
 file_attached = {true},
 profile_id = {6476e386-2170-33cc-8f65-4c12ee0052f0},
 group_id = {5a9f751c-3662-3c8e-b55d-a8b85890ce20},
 last_modified = {2021-01-06T00:27:17.172Z},
 read = {true},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 citation_key = {sadagopan:scitech:2021},
 private_publication = {false},
 abstract = {This study investigates the impact of the high-temperature effect, esp. the real gas effect and the chemical reactions, on hypersonic aerothermodynamic solutions of double cone and double wedge configurations, as well as the aerothermoelastic behavior of a double wedge configuration in hypersonic flow. First, a high-temperature computational fluid dynamics code was benchmarked and correlated with experimental results, emphasizing the impact of high-temperature effects as well as turbulence modeling on heat flux prediction. Subsequently, an aerothermal surrogate based on the multi-fidelity Gaussian process regression method was developed. The model achieves a balance between model accuracy and computational cost of sample generation, using the combination of a few high-fidelity sample and many low-fidelity samples. Finally, the new aerothermal surrogate was applied to study the impact of the high-temperature effect on the aerothermoelastic response of a hypersonic skin panel, emphasizing the necessity of the accurate characterization of the localized heat flux for reasonable assessment of the response of a compliant structure in high-speed high-temperature flowfield.},
 bibtype = {inproceedings},
 author = {Sadagopan, Aravinth and Huang, Daning and Martin, Liza E. and Hanquist, Kyle M.},
 doi = {10.2514/6.2021-1610},
 booktitle = {AIAA Scitech 2021 Forum}
}

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First, a high-temperature computational fluid dynamics code was benchmarked and correlated with experimental results, emphasizing the impact of high-temperature effects as well as turbulence modeling on heat flux prediction. Subsequently, an aerothermal surrogate based on the multi-fidelity Gaussian process regression method was developed. The model achieves a balance between model accuracy and computational cost of sample generation, using the combination of a few high-fidelity sample and many low-fidelity samples. 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