Multi-Fidelity Heating Prediction of Adaptable, Deployable Entry Placement Technology Vehicles
Abstract
The objective of this work was to investigate a multi-fidelity modeling approach to accurately and efficiently predict the laminar and turbulent convective heating on adaptable, deployable entry placement technology vehicles in Mars entry. A previously developed co-Kriging based multi-fidelity modeling approach was used to model the laminar and turbulent convective heat fluxes at several surface locations along the vehicle, including the rib sections. The laminar convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 3% when compared to high-fidelity CFD simulations. The turbulent convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 8% when compared to high-fidelity CFD simulations. Compared to a single fidelity model, the multi-fidelity model required approximately one-third the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of evaluating the multi-fidelity model was approximately five orders of magnitude less than one high-fidelity model simulation.
Recommended Citation
M. Santos et al., "Multi-Fidelity Heating Prediction of Adaptable, Deployable Entry Placement Technology Vehicles," Proceedings of the AIAA Scitech 2021 Forum (2021, Nashville, TN), pp. 1 - 18, American Institute of Aeronautics and Astronautics (AIAA), Jan 2021.
The definitive version is available at https://doi.org/10.2514/6.2021-1632
Meeting Name
AIAA Scitech 2021 Forum (2021: Jan.11-15, Nashville, TN)
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
International Standard Book Number (ISBN)
978-162410609-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 American Institute of Aeronautics and Astronautics (AIAA), All rights reserved.
Publication Date
15 Jan 2021
Comments
National Science Foundation, Grant 80NSSC17K0170