Surrogate Modeling of a Generic Hypersonic Vehicle Through a Novel Extension of the Multi-Fidelity Polynomial Chaos Expansion
Date of Award
8-1-2024
Degree Name
M.S. in Aerospace Engineering
Department
Department of Mechanical and Aerospace Engineering
Advisor/Chair
Markus Rumpfkeil
Abstract
Traditional conceptual-level aerodynamic analysis is limited to empirical and/or inviscid models due to considerations of computational cost and complexity. There is a distinct desire to incorporate higher-fidelity analysis into the conceptual-design process as early as possible. This work seeks to enable the use of high-fidelity data by developing and applying multi-fidelity surrogate models that can efficiently predict the underlying response of a system with high accuracy. To that end, a novel form of the multi-fidelity polynomial chaos expansion (PCE) method is introduced, extending the surrogate modeling technique to accept three distinct fidelities of input. The PCE implementation is evaluated for a series of analytical test functions, showing excellent accuracy in creating multi-fidelity surrogate models. Aerodynamic analysis of a generic hypersonic vehicle (GHV) is performed using three codes of increasing fidelity: CBAERO (panel code), Cart3D (Euler), and FUN3D (RANS). The multi-fidelity PCE technique is used to model the aerodynamic responses of the GHV over a broad, five-dimensional input domain defined by Mach number, dynamic pressure, angle of attack, and left and right control surface settings. Mono-, bi-, and tri-fidelity PCE surrogates are generated and evaluated against a high-fidelity “truth” database to assess the global error of the surrogates focusing on the prediction of lift, drag, and pitching moment coefficients. Both monofidelity and multi-fidelity surrogates show excellent predictive capabilities. Multi-fidelity PCE models show significant promise, generating aerodynamic databases anchored to RANS fidelity at a fraction of the cost of direct evaluation.
Keywords
surrogate modeling; polynomial chaos expansion; hypersonics; multifidelity; conceptual design; aerodynamics; computational fluid dynamics;
Rights Statement
Copyright © 2024, author.
Recommended Citation
Burke, Evan J., "Surrogate Modeling of a Generic Hypersonic Vehicle Through a Novel Extension of the Multi-Fidelity Polynomial Chaos Expansion" (2024). Graduate Theses and Dissertations. 7399.
https://ecommons.udayton.edu/graduate_theses/7399
