Bayesian inference to identify parameters in viscoelasticity
| Autor: | Lars Beex, Stéphane Bordas, Hussein Rappel |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Estimation theory Mechanical Engineering General Chemical Engineering Aerospace Engineering Experimental data Bayesian network 02 engineering and technology Bayesian inference 01 natural sciences Viscoelasticity 010101 applied mathematics Bayes' theorem 020303 mechanical engineering & transports 0203 mechanical engineering General Materials Science Statistical physics 0101 mathematics Standard linear solid model Uncertainty analysis Mathematics |
| Zdroj: | Mechanics of Time-Dependent Materials |
| ISSN: | 1385-2000 |
| DOI: | 10.1007/s11043-017-9361-0 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink