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PC expansion for material parameters using artificial data and statistical methods
Author(s) -
Caylak Ismail,
Nörenberg Nicole,
Mahnken Rolf
Publication year - 2016
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201610084
Subject(s) - discretization , polynomial chaos , ogden , mathematics , stochastic modelling , displacement (psychology) , probability distribution , distribution (mathematics) , stochastic process , statistical physics , mathematical analysis , statistics , physics , monte carlo method , thermodynamics , psychology , psychotherapist
This paper investigates the uncertainty of a hyper‐elastic model by random material parameters as stochastic variables. For its stochastic discretization a polynomial chaos (PC) is used to expand the coefficients into deterministic and stochastic parts. Then, from experimental data in combination with artificial data for elastomers the distribution of the force‐displacement curves are known. In the numerical example the PC‐based stochastic and the deterministic parameter identification are used for generation of the distribution of Ogden's material parameters. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)