Article (Scientific journals)
A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics
Rappel, Hussein; Beex, Lars; Hale, Jack et al.
2019In Archives of Computational Methods in Engineering, p. 1-25
Peer reviewed
 

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Keywords :
Bayesian inference; Bayes’ theorem; stochastic identification; statistical identification; parameter identification; elastoplasticity,; plasticity
Abstract :
[en] The aim of this contribution is to explain in a straightforward manner how Bayesian inference can be used to identify material parameters of material models for solids. Bayesian approaches have already been used for this purpose, but most of the literature is not necessarily easy to understand for those new to the field. The reason for this is that most literature focuses either on complex statistical and machine learning concepts and/or on relatively complex mechanical models. In order to introduce the approach as gently as possible, we only focus on stress–strain measurements coming from uniaxial tensile tests and we only treat elastic and elastoplastic material models. Furthermore, the stress–strain measurements are created artificially in order to allow a one-to-one comparison between the true parameter values and the identified parameter distributions.
Disciplines :
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Engineering, computing & technology: Multidisciplinary, general & others
Mechanical engineering
Materials science & engineering
Civil engineering
Author, co-author :
Rappel, Hussein ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Beex, Lars ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Hale, Jack  ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Noels, Ludovic
Bordas, Stéphane ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
yes
Language :
English
Title :
A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics
Publication date :
01 January 2019
Journal title :
Archives of Computational Methods in Engineering
ISSN :
1134-3060
Publisher :
International Center for Numerical Methods in Engineering, Barcelona, Spain
Pages :
1-25
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
FnR Project :
FNR6693582 - Advanced Computational Methods For The Simulation Of Cutting In Surgery, 2013 (01/01/2014-31/12/2015) - Jack Samuel Hale
Name of the research project :
279578 - REALTCUT - Towards real time multiscale simulation of cutting in non-linear materials with applications
Funders :
University of Luxembourg - UL ; European Research Council
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since 11 December 2018

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