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 |
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creator | Santos, Mario J 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. |
doi_str_mv | 10.2514/1.A34752 |
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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. 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.</description><identifier>ISSN: 0022-4650</identifier><identifier>EISSN: 1533-6794</identifier><identifier>DOI: 10.2514/1.A34752</identifier><language>eng</language><publisher>Reston: American Institute of Aeronautics and Astronautics</publisher><subject>Adaptive sampling ; Aerodynamics ; Computational fluid dynamics ; Computing costs ; Errors ; Heat flux ; Heat transfer ; Model accuracy ; Parallel processing ; Parameterization ; Shear forces ; Shear stress ; Software</subject><ispartof>Journal of spacecraft and rockets, 2021-01, Vol.58 (1), p.110-123</ispartof><rights>Copyright © 2020 by the authors. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at ; employ the eISSN to initiate your request. See also AIAA Rights and Permissions .</rights><rights>Copyright © 2020 by the authors. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-6794 to initiate your request. 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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. 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.</description><subject>Adaptive sampling</subject><subject>Aerodynamics</subject><subject>Computational fluid dynamics</subject><subject>Computing costs</subject><subject>Errors</subject><subject>Heat flux</subject><subject>Heat transfer</subject><subject>Model accuracy</subject><subject>Parallel processing</subject><subject>Parameterization</subject><subject>Shear forces</subject><subject>Shear stress</subject><subject>Software</subject><issn>0022-4650</issn><issn>1533-6794</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpl0EtLAzEUBeAgCtYq-BMCIriZmmSSTLIstT6gRRcq7kImD5syndRMuph_35YRXLi6d_FxDhwArjGaEIbpPZ5MS1oxcgJGmJVlwStJT8EIIUIKyhk6Bxddt0YIc8HlCHwtd00OPljXhNzDZTw-7Tf0McG598EE12Y4dSnmlUsb3cC35GwwOcQWRg8f3LaJva4bB-dtTj38dKtgGtddgjOvm85d_d4x-Hicv8-ei8Xr08tsuig0ESwXQhNKrUbSVF5iRKQtjWDCo5pRYUUpbC09ZcShynBjmJYIOVFbg5jHtJblGNwMudsUf3auy2odd6k9VCpCKyk4FSU_qLtBmRS7LjmvtilsdOoVRuq4m8Jq2O1Abweqg9Z_Yf_cHt4-axo</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Santos, Mario J</creator><creator>Hosder, Serhat</creator><creator>West, Thomas K</creator><general>American Institute of Aeronautics and Astronautics</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>202101</creationdate><title>Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles</title><author>Santos, Mario J ; Hosder, Serhat ; West, Thomas K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a285t-8a244da09c7f91029d3c858f0b548d838db9f452e07c6cc5a900e8bdc05f14b93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive sampling</topic><topic>Aerodynamics</topic><topic>Computational fluid dynamics</topic><topic>Computing costs</topic><topic>Errors</topic><topic>Heat flux</topic><topic>Heat transfer</topic><topic>Model accuracy</topic><topic>Parallel processing</topic><topic>Parameterization</topic><topic>Shear forces</topic><topic>Shear stress</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Santos, Mario J</creatorcontrib><creatorcontrib>Hosder, Serhat</creatorcontrib><creatorcontrib>West, Thomas K</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of spacecraft and rockets</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Santos, Mario J</au><au>Hosder, Serhat</au><au>West, Thomas K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multifidelity Modeling for Efficient Aerothermal Prediction of Deployable Entry Vehicles</atitle><jtitle>Journal of spacecraft and rockets</jtitle><date>2021-01</date><risdate>2021</risdate><volume>58</volume><issue>1</issue><spage>110</spage><epage>123</epage><pages>110-123</pages><issn>0022-4650</issn><eissn>1533-6794</eissn><abstract>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. 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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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