Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles

The objective of this work was to investigate a multifidelity modeling approach to accurately and efficiently predict the aerothermal response of a large-diameter deployable hypersonic entry vehicle in Mars entry. A cokriging-based multifidelity modeling approach was developed that used several refi...

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Veröffentlicht in:Journal of spacecraft and rockets 2021-01, Vol.58 (1), p.110-123
Hauptverfasser: Santos, Mario J, Hosder, Serhat, West, Thomas K
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Hosder, Serhat
West, Thomas K
description The objective of this work was to investigate a multifidelity modeling approach to accurately and efficiently predict the aerothermal response of a large-diameter deployable hypersonic entry vehicle in Mars entry. A cokriging-based multifidelity modeling approach was developed that used several refinements including lower–upper 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 convective heat flux, shear stress, pressure, and radiative heat flux in the multifidelity modeling process. The multifidelity model was found to have a mean convective heat rate error of 4.6%, a mean pressure force error of 0.81%, a mean shear force error of 2.86%, and a mean radiative heat rate error of 11.1% when compared to high-fidelity computational fluid dynamics simulations. Compared to a single-fidelity model, the multifidelity 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 multifidelity model were approximately one and five orders of magnitude less, respectively, than one high-fidelity model simulation.
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A cokriging-based multifidelity modeling approach was developed that used several refinements including lower–upper 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 convective heat flux, shear stress, pressure, and radiative heat flux in the multifidelity modeling process. The multifidelity model was found to have a mean convective heat rate error of 4.6%, a mean pressure force error of 0.81%, a mean shear force error of 2.86%, and a mean radiative heat rate error of 11.1% when compared to high-fidelity computational fluid dynamics simulations. Compared to a single-fidelity model, the multifidelity model required approximately one-half the number of high-fidelity model evaluations to obtain the same accuracy level. 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subjects Adaptive sampling
Aerodynamics
Computational fluid dynamics
Computing costs
Errors
Heat flux
Heat transfer
Model accuracy
Parallel processing
Parameterization
Shear forces
Shear stress
Software
title Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles
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