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Parameter identification based on multiple inhomogeneous experiments of practical relevance
Author(s) -
Schellenberg Dirk,
Juhre Daniel,
Ihlemann Jörn
Publication year - 2012
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201210303
Subject(s) - relevance (law) , identification (biology) , computer science , machine learning , artificial intelligence , statistical physics , mathematics , physics , biology , political science , botany , law
Existing procedures to identify material parameters are based on experiments with simple specimens. Additionally, the load distribution is approximately homogeneous. But there are only few feasible experiments which produce homogeneous or almost homogeneous load distributions. Furthermore, deviations from homogeneity and their consequences cannot be avoided, but are often ignored. We present a solution algorithm which takes several different experimental results into account. Thereby, the experiments are performed on specimens which respond with inhomogeneous distributions of strains and stresses. The restriction to homogeneous loads is not necessary. Thus, it is possible to use different measured data of multiple load cases on one and the same test specimen. The component‐oriented design of the specimen permits to consider the specific properties of product groups, the load types and the effect of the manufacturing process on the final material properties already during the identification process. (© 2012 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)