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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
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa60866
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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 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.
College: Faculty of Science and Engineering
Funders: Open Access funding enabled and organized by Projekt DEAL.
Issue: 6
Start Page: 4285
End Page: 4318

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