Data-driven models for crashworthiness optimisation: intrusive and non-intrusive model order reduction techniques
To enable multi-query analyses, such as optimisations of large-scale crashworthiness problems, a numerically efficient model is crucial for the development process. Therefore, data-driven Model Order Reduction (MOR) aims at generating low-fidelity models that approximate the solution while strongly...
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| Vydáno v: | Structural and multidisciplinary optimization Ročník 65; číslo 7 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.07.2022
Springer Nature B.V |
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| ISSN: | 1615-147X, 1615-1488 |
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| Abstract | To enable multi-query analyses, such as optimisations of large-scale crashworthiness problems, a numerically efficient model is crucial for the development process. Therefore, data-driven Model Order Reduction (MOR) aims at generating low-fidelity models that approximate the solution while strongly reducing the computational cost. MOR methods for crashworthiness became only available in recent years; a detailed and comparative assessment of their potential is still lacking. Hence, this work evaluates the advantages and drawbacks of intrusive and non-intrusive projection based MOR methods in the framework of non-linear structural transient analysis. Both schemes rely on the collection of full-order training simulations and a subsequent subspace construction via Singular Value Decomposition. The intrusive MOR is based on a Galerkin projection and a consecutive hyper-reduction step. In this work, its inter-and extrapolation abilities are compared to the non-intrusive technique, which combines the subspace approach with machine learning methods. Moreover, an optimisation analysis incorporating the MOR methods is proposed and discussed for a crashworthiness example. |
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| AbstractList | To enable multi-query analyses, such as optimisations of large-scale crashworthiness problems, a numerically efficient model is crucial for the development process. Therefore, data-driven Model Order Reduction (MOR) aims at generating low-fidelity models that approximate the solution while strongly reducing the computational cost. MOR methods for crashworthiness became only available in recent years; a detailed and comparative assessment of their potential is still lacking. Hence, this work evaluates the advantages and drawbacks of intrusive and non-intrusive projection based MOR methods in the framework of non-linear structural transient analysis. Both schemes rely on the collection of full-order training simulations and a subsequent subspace construction via Singular Value Decomposition. The intrusive MOR is based on a Galerkin projection and a consecutive hyper-reduction step. In this work, its inter-and extrapolation abilities are compared to the non-intrusive technique, which combines the subspace approach with machine learning methods. Moreover, an optimisation analysis incorporating the MOR methods is proposed and discussed for a crashworthiness example. |
| ArticleNumber | 190 |
| Author | Duddeck, Fabian Bach, Christopher Czech, Catharina Lesjak, Mathias |
| Author_xml | – sequence: 1 givenname: Catharina orcidid: 0000-0001-8628-7492 surname: Czech fullname: Czech, Catharina email: catharina.czech@tum.de organization: TUM School of Engineering and Design, Technical University of Munich – sequence: 2 givenname: Mathias surname: Lesjak fullname: Lesjak, Mathias organization: TUM School of Engineering and Design, Technical University of Munich, BMW Group, Research and Innovation Centre – sequence: 3 givenname: Christopher surname: Bach fullname: Bach, Christopher organization: BMW Group, Research and Innovation Centre – sequence: 4 givenname: Fabian surname: Duddeck fullname: Duddeck, Fabian organization: TUM School of Engineering and Design, Technical University of Munich |
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| Cites_doi | 10.1007/s00158-016-1592-1 10.1002/nme.5801 10.1177/0954410019890721 10.1137/090766498 10.1186/s40323-020-00151-8 10.1007/978-3-319-67988-4_137 10.1007/s00158-007-0130-6 10.1007/s00158-015-1315-z 10.1002/nme.167 10.1090/qam/910462 10.1007/s11831-018-9258-3 10.1016/j.cma.2020.113192 10.1002/nme.5535 10.1016/j.jcp.2016.10.033 10.1016/j.cma.2018.07.017 10.1002/nme.4668 10.1145/1457515.1409118 10.1016/j.compfluid.2018.07.021 10.1002/nme.6243 10.1177/0954407019893841 10.1007/s40324-019-00208-8 10.1016/j.cma.2016.10.022 10.1016/j.cma.2019.112650 10.1007/s12239-019-0026-7 10.1016/j.cma.2018.03.005 10.1002/nme.5283 10.1002/nme.6712 10.1080/13873954.2016.1198385 10.1016/j.compfluid.2004.11.006 10.1023/A:1008202821328 10.1016/j.cma.2020.112947 10.1002/nme.4820 10.1115/1.1760540 10.1007/BF02288367 10.1016/j.cma.2018.10.029 10.1002/nme.6009 10.1007/s00158-019-02485-3 10.1145/355744.355745 10.1016/j.tws.2013.08.021 10.1093/qmath/11.1.50 10.1007/s00158-016-1579-y 10.1002/nme.6303 10.2514/1.35374 10.2514/6.2004-889 |
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| Keywords | Intrusive reduced order modelling Reduced order model Optimisation Crashworthiness Nonlinear model order reduction Non-intrusive modelling |
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| References | Friedman, Bentley, Finkel (CR20) 1977; 3 Rocha, van der Meer, Sluys (CR37) 2020; 358 Willcox (CR46) 2006; 35 Mirsky (CR31) 1960; 11 Taylor, Glauser (CR44) 2004; 126 CR39 Bach, Ceglia, Song, Duddeck (CR7) 2019; 118 CR38 Carlberg, Barone, Antil (CR10) 2017; 330 Klinke, Schumacher (CR27) 2018; 1 Kast, Guo, Hesthaven (CR26) 2020; 364 Guo, Hesthaven (CR23) 2019; 345 Caicedo, Mroginski, Toro, Raschi, Huespe, Oliver (CR9) 2019; 26 Guo, Hesthaven (CR22) 2017; 341 Duan, Sun, Cui, Chen, Cheng, Li (CR13) 2016; 53 Phalippou, Bouabdallah, Breitkopf, Villon, Zarroug (CR33) 2020; 121 Swischuk, Mainini, Peherstorfer, Willcox (CR43) 2019; 179 Xiao, Lu, Breitkopf, Raghavan, Dutta, Zhang (CR47) 2020 CR6 Hernández, Caicedo, Ferrer (CR25) 2017; 313 CR5 CR8 Farhat, Avery, Chapman, Cortial (CR17) 2014; 98 Rasmussen, Williams (CR34) 2006 Storn, Price (CR41) 1997; 11 CR45 Eckart, Young (CR15) 1936; 1 Hernández (CR24) 2020; 368 Fehr, Holzwarth, Eberhard (CR19) 2016; 22 An, Kim, James (CR3) 2008; 27 Sirovich (CR40) 1987; 45 Rocha, van der Meer, Mororó, Sluys (CR36) 2020 Oxberry, Kostova-Vassilevska, Arrighi, Chand (CR32) 2017; 109 Krysl, Lall, Marsden (CR29) 2001; 51 Amsallem, Farhat (CR2) 2008; 46 Kneifl, Grunert, Fehr (CR28) 2021 Zahr, Avery, Farhat (CR50) 2017; 112 Le Guennec, Brunet, Daim, Chau, Tourbier (CR30) 2018; 338 Ren, Min, Ma, Wang (CR35) 2020; 234 Sun, Zhang, Fang, Li, Li (CR42) 2017; 55 Fang, Sun, Qiu, Kim, Li (CR16) 2017; 55 Alaimo, Auricchio, Bianchini, Lanzarone (CR1) 2018; 115 Farhat, Chapman, Avery (CR18) 2015; 102 Assou, Tourbier, Gstalter, Charrier, Dessombz, Jézéquel (CR4) 2019 Duddeck (CR14) 2008; 35 Xu, Sun, Li, Li (CR48) 2014; 74 Gstalter, Assou, Tourbier, De Vuyst (CR21) 2020 Yu, Yan, Guo (CR49) 2019; 233 Chaturantabut, Sorensen (CR11) 2010; 32 Chen, Xu, Zhang, Wu, Dong (CR12) 2019; 20 JH Friedman (3282_CR20) 1977; 3 L Mirsky (3282_CR31) 1960; 11 GM Oxberry (3282_CR32) 2017; 109 M Guo (3282_CR23) 2019; 345 R Storn (3282_CR41) 1997; 11 P Krysl (3282_CR29) 2001; 51 M Xiao (3282_CR47) 2020 Y Chen (3282_CR12) 2019; 20 IB Rocha (3282_CR37) 2020; 358 D Amsallem (3282_CR2) 2008; 46 J Taylor (3282_CR44) 2004; 126 G Sun (3282_CR42) 2017; 55 3282_CR45 M Guo (3282_CR22) 2017; 341 G Alaimo (3282_CR1) 2018; 115 K Carlberg (3282_CR10) 2017; 330 F Duddeck (3282_CR14) 2008; 35 SS An (3282_CR3) 2008; 27 E Gstalter (3282_CR21) 2020 K Willcox (3282_CR46) 2006; 35 S Chaturantabut (3282_CR11) 2010; 32 C Ren (3282_CR35) 2020; 234 J Yu (3282_CR49) 2019; 233 S Assou (3282_CR4) 2019 M Caicedo (3282_CR9) 2019; 26 3282_CR8 3282_CR6 J Fang (3282_CR16) 2017; 55 Y Le Guennec (3282_CR30) 2018; 338 3282_CR5 JA Hernández (3282_CR24) 2020; 368 L Sirovich (3282_CR40) 1987; 45 P Phalippou (3282_CR33) 2020; 121 CE Rasmussen (3282_CR34) 2006 C Farhat (3282_CR17) 2014; 98 3282_CR38 3282_CR39 JA Hernández (3282_CR25) 2017; 313 J Kneifl (3282_CR28) 2021 IB Rocha (3282_CR36) 2020 M Kast (3282_CR26) 2020; 364 L Duan (3282_CR13) 2016; 53 N Klinke (3282_CR27) 2018; 1 J Fehr (3282_CR19) 2016; 22 R Swischuk (3282_CR43) 2019; 179 C Eckart (3282_CR15) 1936; 1 C Farhat (3282_CR18) 2015; 102 C Bach (3282_CR7) 2019; 118 F Xu (3282_CR48) 2014; 74 MJ Zahr (3282_CR50) 2017; 112 |
| References_xml | – volume: 55 start-page: 1899 issue: 5 year: 2017 end-page: 1916 ident: CR42 article-title: Multi-objective and multi-case reliability-based design optimization for tailor rolled blank (TRB) structures publication-title: Struct Multidisc Optim doi: 10.1007/s00158-016-1592-1 – ident: CR45 – volume: 115 start-page: 189 issue: 2 year: 2018 end-page: 208 ident: CR1 article-title: Applying functional principal components to structural topology optimization publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5801 – volume: 233 start-page: 5896 issue: 16 year: 2019 end-page: 5912 ident: CR49 article-title: Non-intrusive reduced-order modeling for fluid problems: A brief review publication-title: Proc Inst Mech Eng Part G J Aerosp Eng doi: 10.1177/0954410019890721 – volume: 32 start-page: 2737 issue: 5 year: 2010 end-page: 2764 ident: CR11 article-title: Nonlinear model reduction via discrete empirical interpolation publication-title: SIAM J Sci Comput doi: 10.1137/090766498 – year: 2006 ident: CR34 publication-title: Gaussain processes for machine learning – ident: CR39 – year: 2020 ident: CR21 article-title: Toward new methods for optimization study in automotive industry including recent reduction techniques publication-title: Adv Model Simul Eng Sci doi: 10.1186/s40323-020-00151-8 – volume: 1 start-page: 1833 year: 2018 end-page: 1850 ident: CR27 article-title: Parameterization setup for metamodel based optimizations of tailor rolled blanks publication-title: Adv Struct Multidisc Optim doi: 10.1007/978-3-319-67988-4_137 – ident: CR8 – volume: 35 start-page: 375 issue: 4 year: 2008 end-page: 389 ident: CR14 article-title: Multidisciplinary optimization of car bodies publication-title: Struct Multidisc Optim doi: 10.1007/s00158-007-0130-6 – volume: 53 start-page: 321 issue: 2 year: 2016 end-page: 338 ident: CR13 article-title: Crashworthiness design of vehicle structure with tailor rolled blank publication-title: Struct Multidisc Optim doi: 10.1007/s00158-015-1315-z – volume: 51 start-page: 479 issue: 4 year: 2001 end-page: 504 ident: CR29 article-title: Dimensional model reduction in non-linear finite element dynamics of solids and structures publication-title: Int J Numer Methods Eng doi: 10.1002/nme.167 – volume: 45 start-page: 561 issue: 10 year: 1987 end-page: 571 ident: CR40 article-title: Turbulence and the dynamics of coherent structures. I. Coherent structures publication-title: Q Appl Math doi: 10.1090/qam/910462 – volume: 26 start-page: 771 issue: 4 year: 2019 end-page: 792 ident: CR9 article-title: High performance reduced order modeling techniques based on optimal energy quadrature: application to geometrically non-linear multiscale inelastic material modeling publication-title: Arch Comput Methods Eng doi: 10.1007/s11831-018-9258-3 – volume: 368 year: 2020 ident: CR24 article-title: A multiscale method for periodic structures using domain decomposition and ECM-hyperreduction publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2020.113192 – volume: 112 start-page: 855 issue: 8 year: 2017 end-page: 881 ident: CR50 article-title: A multilevel projection-based model order reduction framework for nonlinear dynamic multiscale problems in structural and solid mechanics publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5535 – volume: 330 start-page: 693 year: 2017 end-page: 734 ident: CR10 article-title: Galerkin v. least-squares petrov-galerkin projection in nonlinear model reduction publication-title: J Comput Phys doi: 10.1016/j.jcp.2016.10.033 – volume: 341 start-page: 807 year: 2017 end-page: 826 ident: CR22 article-title: Reduced order modeling for nonlinear structural analysis using Gaussian process regression publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.07.017 – volume: 98 start-page: 625 issue: 9 year: 2014 end-page: 662 ident: CR17 article-title: Dimensional reduction of nonlinear finite element dynamic models with finite rotations and energy-based mesh sampling and weighting for computational efficiency publication-title: Numer Methods Eng doi: 10.1002/nme.4668 – volume: 27 start-page: 165 issue: 5 year: 2008 ident: CR3 article-title: Optimizing cubature for efficient integration of subspace deformations publication-title: ACM Trans Gr doi: 10.1145/1457515.1409118 – ident: CR5 – volume: 179 start-page: 704 issue: August year: 2019 end-page: 717 ident: CR43 article-title: Projection-based model reduction: formulations for physics-based machine learning publication-title: Comput Fluids doi: 10.1016/j.compfluid.2018.07.021 – volume: 121 start-page: 763 year: 2020 end-page: 777 ident: CR33 article-title: Sparse POD modal subsets for reduced-order nonlinear explicit dynamics publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6243 – volume: 234 start-page: 1897 issue: 7 year: 2020 end-page: 1911 ident: CR35 article-title: Efficient structure crash topology optimization strategy using a model order reduction method combined with equivalent static loads publication-title: Proc Inst Mech Eng Part D J Automob Eng doi: 10.1177/0954407019893841 – year: 2019 ident: CR4 article-title: A reduced model using random forest: application on car crash optimization publication-title: SeMA J doi: 10.1007/s40324-019-00208-8 – volume: 313 start-page: 687 year: 2017 end-page: 722 ident: CR25 article-title: Dimensional hyper-reduction of nonlinear finite element models via empirical cubature publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2016.10.022 – volume: 358 year: 2020 ident: CR37 article-title: An adaptive domain-based POD/ECM hyper-reduced modeling framework without offline training publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2019.112650 – volume: 20 start-page: 265 issue: 2 year: 2019 end-page: 275 ident: CR12 article-title: Discrete optimization design of tailor-welded blanks (TWBs) thin-walled structures under dynamic crashing publication-title: Int J Automot Technol doi: 10.1007/s12239-019-0026-7 – volume: 338 start-page: 186 year: 2018 end-page: 207 ident: CR30 article-title: A parametric and non-intrusive reduced order model of car crash simulation publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.03.005 – volume: 109 start-page: 198 issue: 2 year: 2017 end-page: 217 ident: CR32 article-title: Limited-memory adaptive snapshot selection for proper orthogonal decomposition publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5283 – year: 2021 ident: CR28 article-title: A nonintrusive nonlinear model reduction method for structural dynamical problems based on machine learning publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6712 – volume: 22 start-page: 380 issue: 4 year: 2016 end-page: 396 ident: CR19 article-title: Interface and model reduction for efficient explicit simulations-a case study with nonlinear vehicle crash models publication-title: Math Comput Model Dyn Syst doi: 10.1080/13873954.2016.1198385 – volume: 35 start-page: 208 issue: 2 year: 2006 end-page: 226 ident: CR46 article-title: Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition publication-title: Comput Fluids doi: 10.1016/j.compfluid.2004.11.006 – volume: 11 start-page: 341 issue: 4 year: 1997 end-page: 359 ident: CR41 article-title: Differential evolution—a simple and efficient heuristic for global optimization over continuous space publication-title: J Glob Optim doi: 10.1023/A:1008202821328 – ident: CR6 – volume: 364 year: 2020 ident: CR26 article-title: A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2020.112947 – volume: 102 start-page: 1077 year: 2015 end-page: 1110 ident: CR18 article-title: Structure-preserving, stability, and accuracy properties of the energy-conserving sampling and weighting method for the hyper reduction of nonlinear finite element dynamic models publication-title: Numer Methods Eng doi: 10.1002/nme.4820 – volume: 126 start-page: 337 issue: 3 year: 2004 end-page: 345 ident: CR44 article-title: Towards practical flow sensing and control via POD and LSE based low-dimensional tools publication-title: J Fluids Eng doi: 10.1115/1.1760540 – volume: 1 start-page: 211 issue: 3 year: 1936 end-page: 218 ident: CR15 article-title: The approximation of one matrix by another of lower rank publication-title: Psychometrika doi: 10.1007/BF02288367 – volume: 345 start-page: 75 year: 2019 end-page: 99 ident: CR23 article-title: Data-driven reduced order modeling for time-dependent problems publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.10.029 – volume: 118 start-page: 209 issue: 4 year: 2019 end-page: 241 ident: CR7 article-title: Randomized low-rank approximation methods for projection-based model order reduction of large nonlinear dynamical problems publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6009 – ident: CR38 – year: 2020 ident: CR47 article-title: On-the-fly model reduction for large-scale structural topology optimization using principal components analysis publication-title: Struct Multidisc Optim doi: 10.1007/s00158-019-02485-3 – volume: 3 start-page: 209 issue: 3 year: 1977 end-page: 226 ident: CR20 article-title: An algorithm for finding best matches in logarithmic expected time publication-title: ACM Trans Math Softw doi: 10.1145/355744.355745 – volume: 74 start-page: 12 year: 2014 end-page: 27 ident: CR48 article-title: Experimental study on crashworthiness of tailor-welded blank (TWB) thin-walled high-strength steel (HSS) tubular structures publication-title: Thin-Walled Struct doi: 10.1016/j.tws.2013.08.021 – volume: 11 start-page: 50 issue: 1 year: 1960 end-page: 59 ident: CR31 article-title: Symmetric gauge functions and unitarily invariant norms publication-title: Q J Math doi: 10.1093/qmath/11.1.50 – volume: 55 start-page: 1091 issue: 3 year: 2017 end-page: 1119 ident: CR16 article-title: On design optimization for structural crashworthiness and its state of the art publication-title: Struct Multidisc Optim doi: 10.1007/s00158-016-1579-y – year: 2020 ident: CR36 article-title: Accelerating crack growth simulations through adaptive model order reduction publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6303 – volume: 46 start-page: 1803 issue: 7 year: 2008 end-page: 1813 ident: CR2 article-title: Interpolation method for adapting reduced-order models and application to aeroelasticity publication-title: AIAA J doi: 10.2514/1.35374 – volume: 102 start-page: 1077 year: 2015 ident: 3282_CR18 publication-title: Numer Methods Eng doi: 10.1002/nme.4820 – volume: 233 start-page: 5896 issue: 16 year: 2019 ident: 3282_CR49 publication-title: Proc Inst Mech Eng Part G J Aerosp Eng doi: 10.1177/0954410019890721 – volume: 27 start-page: 165 issue: 5 year: 2008 ident: 3282_CR3 publication-title: ACM Trans Gr doi: 10.1145/1457515.1409118 – ident: 3282_CR6 – volume: 358 year: 2020 ident: 3282_CR37 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2019.112650 – volume: 26 start-page: 771 issue: 4 year: 2019 ident: 3282_CR9 publication-title: Arch Comput Methods Eng doi: 10.1007/s11831-018-9258-3 – volume: 330 start-page: 693 year: 2017 ident: 3282_CR10 publication-title: J Comput Phys doi: 10.1016/j.jcp.2016.10.033 – ident: 3282_CR38 – volume-title: Gaussain processes for machine learning year: 2006 ident: 3282_CR34 – volume: 364 year: 2020 ident: 3282_CR26 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2020.112947 – ident: 3282_CR39 doi: 10.2514/6.2004-889 – year: 2019 ident: 3282_CR4 publication-title: SeMA J doi: 10.1007/s40324-019-00208-8 – volume: 341 start-page: 807 year: 2017 ident: 3282_CR22 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.07.017 – year: 2020 ident: 3282_CR47 publication-title: Struct Multidisc Optim doi: 10.1007/s00158-019-02485-3 – volume: 35 start-page: 375 issue: 4 year: 2008 ident: 3282_CR14 publication-title: Struct Multidisc Optim doi: 10.1007/s00158-007-0130-6 – volume: 345 start-page: 75 year: 2019 ident: 3282_CR23 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.10.029 – volume: 115 start-page: 189 issue: 2 year: 2018 ident: 3282_CR1 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5801 – volume: 74 start-page: 12 year: 2014 ident: 3282_CR48 publication-title: Thin-Walled Struct doi: 10.1016/j.tws.2013.08.021 – ident: 3282_CR5 – volume: 45 start-page: 561 issue: 10 year: 1987 ident: 3282_CR40 publication-title: Q Appl Math doi: 10.1090/qam/910462 – ident: 3282_CR45 doi: 10.1115/1.1760540 – volume: 121 start-page: 763 year: 2020 ident: 3282_CR33 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6243 – volume: 98 start-page: 625 issue: 9 year: 2014 ident: 3282_CR17 publication-title: Numer Methods Eng doi: 10.1002/nme.4668 – volume: 22 start-page: 380 issue: 4 year: 2016 ident: 3282_CR19 publication-title: Math Comput Model Dyn Syst doi: 10.1080/13873954.2016.1198385 – volume: 112 start-page: 855 issue: 8 year: 2017 ident: 3282_CR50 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5535 – volume: 32 start-page: 2737 issue: 5 year: 2010 ident: 3282_CR11 publication-title: SIAM J Sci Comput doi: 10.1137/090766498 – volume: 3 start-page: 209 issue: 3 year: 1977 ident: 3282_CR20 publication-title: ACM Trans Math Softw doi: 10.1145/355744.355745 – year: 2020 ident: 3282_CR21 publication-title: Adv Model Simul Eng Sci doi: 10.1186/s40323-020-00151-8 – volume: 179 start-page: 704 issue: August year: 2019 ident: 3282_CR43 publication-title: Comput Fluids doi: 10.1016/j.compfluid.2018.07.021 – volume: 1 start-page: 211 issue: 3 year: 1936 ident: 3282_CR15 publication-title: Psychometrika doi: 10.1007/BF02288367 – volume: 1 start-page: 1833 year: 2018 ident: 3282_CR27 publication-title: Adv Struct Multidisc Optim doi: 10.1007/978-3-319-67988-4_137 – volume: 55 start-page: 1899 issue: 5 year: 2017 ident: 3282_CR42 publication-title: Struct Multidisc Optim doi: 10.1007/s00158-016-1592-1 – volume: 11 start-page: 50 issue: 1 year: 1960 ident: 3282_CR31 publication-title: Q J Math doi: 10.1093/qmath/11.1.50 – ident: 3282_CR8 – volume: 55 start-page: 1091 issue: 3 year: 2017 ident: 3282_CR16 publication-title: Struct Multidisc Optim doi: 10.1007/s00158-016-1579-y – year: 2021 ident: 3282_CR28 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6712 – volume: 51 start-page: 479 issue: 4 year: 2001 ident: 3282_CR29 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.167 – volume: 368 year: 2020 ident: 3282_CR24 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2020.113192 – volume: 126 start-page: 337 issue: 3 year: 2004 ident: 3282_CR44 publication-title: J Fluids Eng doi: 10.1115/1.1760540 – volume: 35 start-page: 208 issue: 2 year: 2006 ident: 3282_CR46 publication-title: Comput Fluids doi: 10.1016/j.compfluid.2004.11.006 – volume: 109 start-page: 198 issue: 2 year: 2017 ident: 3282_CR32 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.5283 – volume: 46 start-page: 1803 issue: 7 year: 2008 ident: 3282_CR2 publication-title: AIAA J doi: 10.2514/1.35374 – volume: 234 start-page: 1897 issue: 7 year: 2020 ident: 3282_CR35 publication-title: Proc Inst Mech Eng Part D J Automob Eng doi: 10.1177/0954407019893841 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 3282_CR41 publication-title: J Glob Optim doi: 10.1023/A:1008202821328 – volume: 118 start-page: 209 issue: 4 year: 2019 ident: 3282_CR7 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6009 – year: 2020 ident: 3282_CR36 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.6303 – volume: 20 start-page: 265 issue: 2 year: 2019 ident: 3282_CR12 publication-title: Int J Automot Technol doi: 10.1007/s12239-019-0026-7 – volume: 53 start-page: 321 issue: 2 year: 2016 ident: 3282_CR13 publication-title: Struct Multidisc Optim doi: 10.1007/s00158-015-1315-z – volume: 313 start-page: 687 year: 2017 ident: 3282_CR25 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2016.10.022 – volume: 338 start-page: 186 year: 2018 ident: 3282_CR30 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2018.03.005 |
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| SubjectTerms | Algorithms Computational Mathematics and Numerical Analysis Crashworthiness Decomposition Engineering Engineering Design Impact strength Machine learning Methods Model reduction Optimization Partial differential equations Research Paper Singular value decomposition Theoretical and Applied Mechanics Transient analysis |
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