Comparison of bayesian methods on parameter identification for viscoplastic model with damage

HIGHLIGHTS

  • who: from the Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA have published the paper: Comparison of Bayesian Methods on Parameter Identification for Viscoplastic Model with Damage, in the Journal: Metals 2020, 10, 876 of /2020/
  • what: The aim of this study is to observe which one of the mentioned methods is more suitable and efficient to identify the model and damage parameters of a material model as a highly non-linear model using a limited surface displacement measurement vector and see how much information is indeed needed to estimate . . .

     

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