Reference : A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Multidisciplinary, general & others
Engineering, computing & technology : Civil engineering
Engineering, computing & technology : Materials science & engineering
Engineering, computing & technology : Mechanical engineering
Engineering, computing & technology : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/37698
A Tutorial on Bayesian Inference to Identify Material Parameters in Solid Mechanics
English
Rappel, Hussein mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Beex, Lars mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Hale, Jack mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Noels, Ludovic []
Bordas, Stéphane mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
1-Jan-2019
Archives of Computational Methods in Engineering
International Center for Numerical Methods in Engineering
1-25
Yes
International
1134-3060
Barcelona
Spain
[en] Bayesian inference ; Bayes’ theorem ; stochastic identification ; statistical identification ; parameter identification ; elastoplasticity, ; plasticity
[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.
University of Luxembourg - UL ; European Research Council
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/10993/37698
10.1007/s11831-018-09311-x
FnR ; FNR6693582 > Jack Samuel Hale > > Advanced Computational Methods for the Simulation of Cutting in Surgery > 01/01/2014 > 31/12/2015 > 2013

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