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- Publisher
- Springer Journals
- Copyright
- 2017 Springer Science+Business Media B.V.
- ISSN
- 1385-2000
- eISSN
- 1573-2738
- DOI
- 10.1007/s11043-017-9361-0
- Publisher site
- See Article on Publisher Site
Abstract
Abstract 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.
Journal
Mechanics of Time-Dependent Materials – Springer Journals
Published: May 1, 2018
Keywords: Solid Mechanics; Classical Mechanics; Characterization and Evaluation of Materials; Polymer Sciences