10.2514/6.2024-4578">
 

Conceptual Aerothermal-Structural Design Space Exploration Using Adaptive Machine Learning

Document Type

Conference Proceeding

Publication Date

7-29-2024

Abstract

Excerpt: This study presents an active machine learning approach for exploring the conceptual design space of hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. Therefore, it is crucial to consider aerothermal-structural interactions from the early stage of conceptual design development.

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The full text of this conference paper is available by subscription or purchase through the DOI link below.

Conference Session: Metamodeling and Reduced-Order Models

Source Publication

AIAA AVIATION FORUM AND ASCEND 2024

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