Optimal error functional for parameter identification in anisotropic finite strain elasto-plasticity

A. V. Shutov, A. A. Kaygorodtseva, N. S. Dranishnikov

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

A problem of parameter identification for a model of finite strain elasto-plasticity is discussed. The utilized phenomenological material model accounts for nonlinear isotropic and kinematic hardening; the model kinematics is described by a nested multiplicative split of the deformation gradient. A hierarchy of optimization problems is considered. First, following the standard procedure, the material parameters are identified through minimization of a certain least square error functional. Next, the focus is placed on finding optimal weighting coefficients which enter the error functional. Toward that end, a stochastic noise with systematic and non-systematic components is introduced to the available measurement results; a superordinate optimization problem seeks to minimize the sensitivity of the resulting material parameters to the introduced noise. The advantage of this approach is that no additional experiments are required; it also provides an insight into the robustness of the identification procedure. As an example, experimental data for the steel 42CrMo4 are considered and a set of weighting coefficients is found, which is optimal in a certain class.

Original languageEnglish
Article number012133
Number of pages7
JournalJournal of Physics: Conference Series
Volume894
Issue number1
DOIs
Publication statusPublished - 22 Oct 2017

Keywords

  • INELASTIC CONSTITUTIVE MODELS
  • VISCOPLASTICITY
  • INTEGRATION
  • SIMULATIONS

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