Parameter identification in elasto-plasticity: distance between parameters and impact of measurement errors

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

A special aspect of parameter identification in finite-strain elasto-plasticity is considered. Namely, we analyze the impact of the measurement errors on the resulting set of material parameters. In order to define the sensitivity of parameters with respect to the measurement errors, a mechanics-based distance between two sets of parameters is introduced. Using this distance function, we assess the reliability of certain parameter identification procedures. The assessment involves introduction of artificial noise to the experimental data; the noise can be both correlated and uncorrelated. An analytical procedure to speed up Monte Carlo simulations is presented. As a result, a simple tool for estimating the robustness of parameter identification is obtained. The efficiency of the approach is illustrated using a model of finite-strain viscoplasticity, which accounts for combined isotropic and kinematic hardening. It is shown that dealing with correlated measurement errors, most stable identification results are obtained for non-diagonal weighting matrix. At the same time, there is a conflict between the stability and accuracy.

Original languageEnglish
Article number201800340
Number of pages13
JournalZAMM Zeitschrift fur Angewandte Mathematik und Mechanik
Volume99
Issue number8
DOIs
Publication statusPublished - Aug 2019

Keywords

  • 74C15
  • 74D10
  • 74E10
  • 74P10
  • distance between parameters
  • finite strain
  • isotropic and kinematic hardening
  • measurement error
  • parameter identification
  • viscoplasticity
  • CALIBRATION
  • BEHAVIOR
  • FINITE-STRAIN VISCOPLASTICITY
  • SENSITIVITY
  • SIMULATION
  • VIRTUAL FIELDS METHOD
  • ELEMENTS
  • INTEGRATION
  • INELASTIC CONSTITUTIVE MODELS

Fingerprint

Dive into the research topics of 'Parameter identification in elasto-plasticity: distance between parameters and impact of measurement errors'. Together they form a unique fingerprint.

Cite this