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Automatic generation of material laws based on rheological models using a genetic algorithm
Author(s) -
Wulf Hans,
Kießling Robert,
Gypstuhl Richard,
Ihlemann Jörn
Publication year - 2019
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201900379
Subject(s) - rheology , representation (politics) , tree (set theory) , algorithm , computer science , experimental data , set (abstract data type) , field (mathematics) , genetic algorithm , basis (linear algebra) , identification (biology) , mathematics , machine learning , law , materials science , statistics , mathematical analysis , geometry , botany , politics , political science , pure mathematics , composite material , biology , programming language
Abstract Developing material laws based on rheological models is an established method in the field of material modelling. Here, the identification of an appropriate rheological model fitting a given set of experimental data is often a challenging task. This contribution presents an automated method for searching such rheological models. To this end, a tree representation for rheological models is defined first. Then, a generic material law, that can implement any rheological model given by a model tree, is introduced. Based on this, a genetic algorithm is used to generate rheological models, which are subsequently evaluated by fitting to measurements. This methods allows to search for a global optimum in the space of material models. Successful applications to both synthetic and actual experimental data are demonstrated.