A surrogate-based optimization framework for hypersonic aerothermoelastic scaling laws with application to skin panels

Daning Huang, Peretz P. Friedmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study describes the development of an optimization framework for generating hypersonic aerothermoelastic scaling laws using a novel two-pronged approach. The approach combines a classical scaling approach based on dimensional analysis with augmentation from numerical simulations of the specific problem. From the comparison and adjustment of the full-scale prototype and the scaled model, the “numerical similarity solutions” are generated to replace the analytical similarity solutions for refinement of the scaling laws. The search for an aerothermoelastically scaled model is formulated as an multi-objective optimization problem, which is solved using a surrogate-based optimization algorithm. The effectiveness of the two-pronged approach is demonstrated by its application to the development of refined hypersonic aerothermoelastic scaling law for a composite skin panel configuration.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
DOIs
StatePublished - Jan 1 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum

Conference

ConferenceAIAA Scitech Forum, 2019
CountryUnited States
CitySan Diego
Period1/7/191/11/19

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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    Huang, D., & Friedmann, P. P. (2019). A surrogate-based optimization framework for hypersonic aerothermoelastic scaling laws with application to skin panels. In AIAA Scitech 2019 Forum (AIAA Scitech 2019 Forum). American Institute of Aeronautics and Astronautics Inc, AIAA. https://doi.org/10.2514/6.2019-1120