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Inverse Parameter Identification for Orthotropic Elasto‐Plastic Sheet‐Steel
Author(s) -
Söhngen Benjamin,
Willner Kai
Publication year - 2015
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201510171
Subject(s) - orthotropic material , finite element method , measure (data warehouse) , digital image correlation , inverse , materials science , displacement (psychology) , quadratic equation , structural engineering , yield (engineering) , margin (machine learning) , displacement field , quadratic function , composite material , computer science , mathematics , engineering , geometry , psychology , database , machine learning , psychotherapist
Abstract In this contribution the Finite Element Model Updating (FEMU) approach is utilized to determine the material parameters of sheet‐steel. From experimental testing it is observed that the considered cold‐rolled steel exhibits orthotropic behaviour. To regard this in the simulation, a user‐implemented material model based on a quadratic yield function is used. Via the method of digital image correlation (DIC), the displacement field of a biaxially loaded specimen is measured from images taken at different stages of loading. Comparing the experimentally determined displacements to those obtained by simulation an error measure is defined which can be minimized by optimization algorithms. Starting with initial values for the orthotropic elasto‐plastic material parameters, the FEM model is thus updated consecutively until a specified error margin is reached. (© 2015 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)