ABSTRACT
This chapter focuses on the modeling of rubber-like material behaviour under several modes of deformation using hyperelastic constitutive equations. It aims to systematically compare nineteen models proposed in the literature to classify them with respect to their ability to fit experimental data. A procedure based on genetic algorithms coupled to classical optimisation methods is proposed to identify the parameters of the models upon experimental data given in the literature. This leads to the classification of nineteen models with respect to criteria related to their capability to predict material behaviour. Over the last decades, development of phenomenological models tends to introduce physical considerations. The problematic of identification makes analytical solutions to coincide with experimental measurements. Among all possible minimization methods, the chapter focuses on classical gradient methods and genetic algorithms. The choice of the identification algorithm is added to the strategy. Models are first identified with genetic algorithms and material parameters are used as initial parameters in the Levenberg-Marquardt method.
