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ARTICLE
Wide estimation of dynamic properties of viscoelastic materials using Bayesian inference
| 1 | Federal University of Paraná, Postgraduate Program in Mechanical Engineering, Curitiba, Brazil |
| 2 | Federal University of Paraná, Postgraduate Program in Engineering and Science of Materials, Curitiba, Brazil |
| 3 | Federal University of Paraná, Department of Statistics, Curitiba, Brazil |
Submission date: 2020-11-30
Acceptance date: 2021-03-29
Online publication date: 2021-05-29
Publication date: 2021-07-25
Journal of Theoretical and Applied Mechanics 2021;59(3):369–384
KEYWORDS
ABSTRACT
The dynamic behavior of a typical viscoelastic material in wide ranges of frequency and tem-
perature is characterized. A four-parameter fractional derivative model was considered in the
frequency domain along with the Arrhenius and WLF models, also for including tempera-
ture as a source of variation. A Bayesian framework is adopted and inferences on parameters
governing the model quantities of interest are based on samples from posterior distributions
obtained by Monte Carlo Markov Chain (MCMC) methods. Posterior predictive checks were
conducted to ensure the goodness-of-fit of the model. Based on the results we argue that the
Bayesian framework allows more complete and suitable inference about dynamic properties
of typical viscoelastic materials, as required for broad and sound vibration control actions.
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