Surrogate Modeling of Computational Aerodynamic Responses for a Generic Hypersonic Vehicle
Abstract
In the xC;field of multidisciplinary hypersonic vehicle design, striking the balance between the accuracy and efficiency of a predictive aerodynamic response model is a significant challenge. In response to this challenge, the objective of this thesis is to evaluate the aerodynamic performance of a Generic Hypersonic Vehicle (GHV) using the technique of surrogate modeling Computational Fluid Dynamic data points across a large range of ight conditions. To accomplish this, the full CFD process was conducted by preparing the vehicle geometry, generating a grid, computing the ow, and post-processing the data. A three-dimensional, quasi-random distribution of 1000 points dexC;fined the design space of the study which consisted of varied Mach number, angle of attack, and ight altitude. Using inviscid CFD training data from the design space, surrogate models of integrated forces and critical surface pressures were generated using the Kriging method, and the suitability of these models was evaluated using additional validation CFD data. Additional studies were conducted to evaluate the optimal correlation and regression functions for the Kriging models and to determine the optimal number of training points needed for a sufficiently accurate model.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2022
- Accession Number
- AD1177658
Entities
People
- Jacob R. Johanik
Organizations
- Air Force Institute of Technology