Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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This paper deals with the characterization of the static mechanical behaviour of an energetic material. Due to the constituents (crystals and a polymeric binder), the behaviour is complex. Therefore, a complete experimental rotocol and a model have been developed. The behaviour is described using a general Maxwell model in which all the branches are affected by isotropic damage. The first branch takes into account an elastic-plastic behaviour. The yield stress evolution is described by a parabolic criterion and by an isotropic hardening law. The plastic flow rule is nonassociated. The other branches are viscoelastic. A genetic algorithm has been used to optimise the parameters. At last, comparisons between the model and the experiments are proposed.