Multi-Fidelity Modeling for Efficient Aerothermal Prediction of Deployable Re-Entry Vehicles

The objective of this work was to investigate a multi-fidelity modeling approach to accurately and efficiently predict the aerothermal response of a large diameter deployable hypersonic re-entry vehicle in Mars entry. A co-Kriging based multi-fidelity modeling approach was developed that utilized several refinements including LU-decomposition for parallelization, distance weighted root mean square error adaptive sampling, and surface distribution parameterization using Hicks-Henne bump functions. Several computational tools of varying fidelity were investigated to model the surface heat flux, shear stress, and pressure in the multi-fidelity modeling process. The LAURA CFD software with thermochemical nonequilibrium and with calorically perfect gas models were used as high and low-fidelity tools, respectively, to model laminar convective heat flux, surface pressure, and shear stress. A second low-fidelity tool investigated utilized the Sutton-Graves equation with surface correlations by Krasnov for the convective heat flux, and the modified Newtonian method for surface pressure. The multi-fidelity model was found to have a mean convective heat rate error of 4.6%, a mean pressure force error of 0.81%, and a mean shear force error of 2.86% when compared to high-fidelity CFD simulations. Compared to a Kriging model of the high-fidelity data only, the multi-fidelity model required approximately one-half the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of constructing and evaluating the multi-fidelity model were approximately one and five orders of magnitude less, respectively, than one high-fidelity model simulation.