ON THE OPTIMIZATION OF THE TENSOR POLYNOMIAL FAILURE THEORY WITH A GENETIC ALGORITHM

Abstract

Using previously published experimental data for an anisotropic material, it is shown that a genetic algorithm can be used to optimize the parameters of the tensor polynomial failure theory. This method, adapted from studies in the biological sciences, allows the user to obtain an improved correlation between experimental data and the analytical failure envelope for this material.