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Gradient‐based optimization of a viscoelastic Ogden type model for cellular polymers
Author(s) -
Klar O.,
Ehlers W.,
Markert B.
Publication year - 2002
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/1617-7061(200203)1:1<141::aid-pamm141>3.0.co;2-v
Subject(s) - sequential quadratic programming , ogden , viscoelasticity , identification (biology) , computation , nonlinear system , computer science , mathematics , quadratic programming , mathematical optimization , materials science , algorithm , physics , composite material , botany , quantum mechanics , biology
Abstract The parameter identification is the interface between a theoretical material model and its application in numerical computations. Only by an accurate identification of the theoretically introduced material parameters, an applicable simulation of the material is achieved. An increasing standard of the parameter identification is set by the requirements of complex material models used in computer‐aided engineering. A common identification strategy is a gradient‐based optimization of a least‐squares functional, e. g. the sequential quadratic programming (SQP) technique. In this paper, the SQP method is used to optimize material models of cellular polymers. In particular, the optimization is shown for a viscoelastic polyurethane (PU) foam. Due to the high‐grade nonlinear material behaviour, the foam is modelled by a finite viscoelastic Ogden type law in the framework of the Theory of Porous Media (TPM).