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.

Cite: Shutov A.V. , Kaygorodtseva A.A.
Parameter identification in elasto‐plasticity: distance between parameters and impact of measurement errors
ZAMM Zeitschrift fur Angewandte Mathematik und Mechanik. 2019. V.99. N8. e201800340 :1-13. DOI: 10.1002/zamm.201800340 WOS Scopus РИНЦ OpenAlex

Dates:

Published print:

May 30, 2019

Identifiers:

Web of science:	WOS:000478754500008
Scopus:	2-s2.0-85066464215
Elibrary:	38270209
OpenAlex:	W2917879813

Citing:

DB	Citing
Scopus	15
OpenAlex	5
Elibrary	12
Web of science	10

Altmetrics: