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Objective Function in Genetic Algorithm for Material Behaviour Modeling

Constitutive modeling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. Damage occurrence and accumulation within the material are described in this paper by means of models of kinematic and isotropic hardening according to Chaboche material model. Since the material model is non-linear, its parameter identification requires complex numerical procedures. Genetic algorithm is used for the determination of these parameters because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to influence calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed ones the research is performed to investigate it’s influence on material behaviour modeling.

Material model; Genetic algorithm; Objective function

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