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Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics

Nima Noii, Amirreza Khodadadian, Jacinto Ulloa, Fadi Aldakheel Aldakheel, Thomas Wick, Stijn François, Peter Wriggers

Archives of Computational Methods in Engineering, Volume: 29, Issue: 6, Pages: 4285 - 4318

Swansea University Author: Fadi Aldakheel Aldakheel

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DOI (Published version): 10.1007/s11831-022-09751-6

Abstract

The complexity of many problems in computational mechanics calls for reliable programming codes and accurate simulation systems. Typically, simulation responses strongly depend on material and model parameters, where one distinguishes between backward and forward models. Providing reliable informati...

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Published in: Archives of Computational Methods in Engineering
ISSN: 1134-3060 1886-1784
Published: Springer Science and Business Media LLC 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa60866
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first_indexed 2022-08-22T10:00:11Z
last_indexed 2023-01-13T19:21:19Z
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spelling 2022-09-23T16:19:42.2361369 v2 60866 2022-08-22 Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics bb7431e24b5e9e843b3718eb09b49d2e Fadi Aldakheel Aldakheel Fadi Aldakheel Aldakheel true false 2022-08-22 The complexity of many problems in computational mechanics calls for reliable programming codes and accurate simulation systems. Typically, simulation responses strongly depend on material and model parameters, where one distinguishes between backward and forward models. Providing reliable information for the material/model parameters, enables us to calibrate the forward model (e.g., a system of PDEs). Markov chain Monte Carlo methods are efficient computational techniques to estimate the posterior density of the parameters. In the present study, we employ Bayesian inversion for several mechanical problems and study its applicability to enhance the model accuracy. Seven different boundary value problems in coupled multi-field (and multi-physics) systems are presented. To provide a comprehensive study, both rate-dependent and rate-independent equations are considered. Moreover, open source codes (https://doi.org/10.5281/zenodo.6451942) are provided, constituting a convenient platform for future developments for, e.g., multi-field coupled problems. The developed package is written in MATLAB and provides useful information about mechanical model problems and the backward Bayesian inversion setting. Journal Article Archives of Computational Methods in Engineering 29 6 4285 4318 Springer Science and Business Media LLC 1134-3060 1886-1784 1 10 2022 2022-10-01 10.1007/s11831-022-09751-6 COLLEGE NANME COLLEGE CODE Swansea University Open Access funding enabled and organized by Projekt DEAL. 2022-09-23T16:19:42.2361369 2022-08-22T10:58:46.1703923 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Nima Noii 1 Amirreza Khodadadian 2 Jacinto Ulloa 3 Fadi Aldakheel Aldakheel 4 Thomas Wick 5 Stijn François 6 Peter Wriggers 7 60866__24982__9a33c48d2d4348298f05f6e3392144bd.pdf 60866.pdf 2022-08-22T11:00:44.4698710 Output 4083713 application/pdf Version of Record true Copyright: The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
spellingShingle Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
Fadi Aldakheel Aldakheel
title_short Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
title_full Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
title_fullStr Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
title_full_unstemmed Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
title_sort Bayesian Inversion with Open-Source Codes for Various One-Dimensional Model Problems in Computational Mechanics
author_id_str_mv bb7431e24b5e9e843b3718eb09b49d2e
author_id_fullname_str_mv bb7431e24b5e9e843b3718eb09b49d2e_***_Fadi Aldakheel Aldakheel
author Fadi Aldakheel Aldakheel
author2 Nima Noii
Amirreza Khodadadian
Jacinto Ulloa
Fadi Aldakheel Aldakheel
Thomas Wick
Stijn François
Peter Wriggers
format Journal article
container_title Archives of Computational Methods in Engineering
container_volume 29
container_issue 6
container_start_page 4285
publishDate 2022
institution Swansea University
issn 1134-3060
1886-1784
doi_str_mv 10.1007/s11831-022-09751-6
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description The complexity of many problems in computational mechanics calls for reliable programming codes and accurate simulation systems. Typically, simulation responses strongly depend on material and model parameters, where one distinguishes between backward and forward models. Providing reliable information for the material/model parameters, enables us to calibrate the forward model (e.g., a system of PDEs). Markov chain Monte Carlo methods are efficient computational techniques to estimate the posterior density of the parameters. In the present study, we employ Bayesian inversion for several mechanical problems and study its applicability to enhance the model accuracy. Seven different boundary value problems in coupled multi-field (and multi-physics) systems are presented. To provide a comprehensive study, both rate-dependent and rate-independent equations are considered. Moreover, open source codes (https://doi.org/10.5281/zenodo.6451942) are provided, constituting a convenient platform for future developments for, e.g., multi-field coupled problems. The developed package is written in MATLAB and provides useful information about mechanical model problems and the backward Bayesian inversion setting.
published_date 2022-10-01T04:19:20Z
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score 11.035874

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