research-article

Recent advances and applications of surrogate models for finite element method computations: a review

Authors:

Radomil MatousekAuthors Info & Claims

Soft Computing, Volume 26, Issue 24

Pages 13709 - 13733

https://doi.org/10.1007/s00500-022-07362-8

Published: 01 December 2022 Publication History

Abstract

The utilization of surrogate models to approximate complex systems has recently gained increased popularity. Because of their capability to deal with black-box problems and lower computational requirements, surrogates were successfully utilized by researchers in various engineering and scientific fields. An efficient use of surrogates can bring considerable savings in computational resources and time. Since literature on surrogate modelling encompasses a large variety of approaches, the appropriate choice of a surrogate remains a challenging task. This review discusses significant publications where surrogate modelling for finite element method-based computations was utilized. We familiarize the reader with the subject, explain the function of surrogate modelling, sampling and model validation procedures, and give a description of the different surrogate types. We then discuss main categories where surrogate models are used: prediction, sensitivity analysis, uncertainty quantification, and surrogate-assisted optimization, and give detailed account of recent advances and applications. We review the most widely used and recently developed software tools that are used to apply the discussed techniques with ease. Based on a literature review of 180 papers related to surrogate modelling, we discuss major research trends, gaps, and practical recommendations. As the utilization of surrogate models grows in popularity, this review can function as a guide that makes surrogate modelling more accessible.

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Mauder TKudela JKlimeš LZálešák MCharvát PLi XHandl J(2024)Hot Off the Press: Soft computing methods in the solution of an inverse heat transfer problem with phase changeProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3664073(47-48)Online publication date: 14-Jul-2024
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Tao RZhou HMeng ZLiu Z(2024)An integrated firefly algorithm for the optimization of constrained engineering design problemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09305-328:4(3207-3250)Online publication date: 1-Feb-2024
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Zani MPanettieri EMontemurro M(2024)A metamodel of the wire arc additive manufacturing process based on basis spline entitiesEngineering with Computers10.1007/s00366-023-01926-440:4(2037-2061)Online publication date: 1-Aug-2024
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cover image Soft Computing - A Fusion of Foundations, Methodologies and Applications

Soft Computing - A Fusion of Foundations, Methodologies and Applications Volume 26, Issue 24

Dec 2022

815 pages

ISSN:1432-7643

EISSN:1433-7479

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© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

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Springer-Verlag

Berlin, Heidelberg

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Published: 01 December 2022

Accepted: 07 June 2022

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Cited By

Mauder TKudela JKlimeš LZálešák MCharvát PLi XHandl J(2024)Hot Off the Press: Soft computing methods in the solution of an inverse heat transfer problem with phase changeProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3664073(47-48)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638530.3664073
Tao RZhou HMeng ZLiu Z(2024)An integrated firefly algorithm for the optimization of constrained engineering design problemsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09305-328:4(3207-3250)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s00500-023-09305-3
Zani MPanettieri EMontemurro M(2024)A metamodel of the wire arc additive manufacturing process based on basis spline entitiesEngineering with Computers10.1007/s00366-023-01926-440:4(2037-2061)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00366-023-01926-4
Kůdela JDobrovský L(2024)Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics ProblemsParallel Problem Solving from Nature – PPSN XVIII10.1007/978-3-031-70068-2_19(303-321)Online publication date: 14-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70068-2_19
Kudela JJuricek MSilva SPaquete L(2023)Computational and Exploratory Landscape Analysis of the GKLS GeneratorProceedings of the Companion Conference on Genetic and Evolutionary Computation10.1145/3583133.3590653(443-446)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583133.3590653
Kůdela JMatoušek R(2023)Combining Lipschitz and RBF surrogate models for high-dimensional computationally expensive problemsInformation Sciences: an International Journal10.1016/j.ins.2022.11.045619:C(457-477)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.ins.2022.11.045
Aissat SIratni AHafaifa AGuemana MAlshammari OColak I(2023)Identification of twin-shaft gas turbine based on hybrid decoupled state multiple model approachSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08059-227:22(17267-17289)Online publication date: 29-Apr-2023
https://dl.acm.org/doi/10.1007/s00500-023-08059-2
Wang BSha RYan LYu TDuan X(2023)Gradient-based adaptive sampling framework and application in the laser-driven ion accelerationStructural and Multidisciplinary Optimization10.1007/s00158-023-03669-866:10Online publication date: 22-Sep-2023
https://dl.acm.org/doi/10.1007/s00158-023-03669-8
Yang JWu ZWang ZZhang DWang WWen QZhang W(2023)Enhanced anisotropic radius basis function metamodel based on recursive evolution Latin hypercube design and fast K-fold cross-validationStructural and Multidisciplinary Optimization10.1007/s00158-023-03597-766:7Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1007/s00158-023-03597-7

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