Article (Scientific journals)
Bayesian inference to identify parameters in viscoelasticity
Rappel, Hussein; Beex, Lars; Bordas, Stéphane
2017In Mechanics of Time-Dependent Materials
Peer reviewed
 

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Keywords :
Bayesian inference; Bayes’ theorem; Statistical identification; Parameter identification; Viscoelasticity
Abstract :
[en] This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii) to show that this influence decreases for an increasing number of measurements and (iii) to show how different types of experiments influence the identified parameters and their uncertainties. The standard linear solid model is the material description of interest and a relaxation test, a constant strain-rate test and a creep test are the tensile experiments focused on. The experimental data are artificially created, allowing us to make a one-to-one comparison between the input parameters and the identified parameter values. Besides dealing with the aforementioned issues, we believe that this contribution forms a comprehensible start for those interested in applying BI in viscoelasticity.
Disciplines :
Aerospace & aeronautics engineering
Engineering, computing & technology: Multidisciplinary, general & others
Mechanical engineering
Materials science & engineering
Civil engineering
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
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
Bordas, Stéphane ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
no
Language :
English
Title :
Bayesian inference to identify parameters in viscoelasticity
Publication date :
10 August 2017
Journal title :
Mechanics of Time-Dependent Materials
ISSN :
1385-2000
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Funders :
University of Luxembourg - UL
Fonds National de la Recherche Luxembourg- FNR
ERC RealTCut
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since 02 February 2017

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