Premium
An Unified Computational Framework for Parameter Identification of Material Models in Finite Inelasticity
Author(s) -
Scheday G.,
Miehe C.
Publication year - 2002
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/1617-7061(200203)1:1<189::aid-pamm189>3.0.co;2-k
Subject(s) - identification (biology) , sensitivity (control systems) , computer science , class (philosophy) , function (biology) , mathematical optimization , mathematics , parameter identification problem , optimization problem , algorithm , model parameter , artificial intelligence , engineering , botany , biology , electronic engineering , evolutionary biology
Parameter identification processes concern the determination of parameters in a material model in order to fit experimental data. We provide a distinct, unified algorithmic setting of a generic class of material models and discuss the associated gradient–based optimization problem. Gradient–based optimization algorithms need derivatives of the objective function with respect to the material parameter vector κ . In order to obtain the necessary derivatives, an analytical sensitivity analysis is pointed out for the unified class of algorithmic material models. The quality of the parameter identification is demonstrated for a representative example.