Influence of the correlation length on the probabilistic material modeling of short fiber‐reinforced composites on the component level

Abstract

In this study, an approach to numerical modeling of short fiber-reinforced composites is presented. Based on the multi-scale approach, elastic material parameters are transferred from the mesoscale to the macroscale, while maintaining their stochastic properties. For this, a complete description of the stochastic properties, consisting of mean, standard deviation and correlation structure in the mesoscale is determined. This information provides a basis for the creation of second order Gaussian random fields, which are used for a FEM simulation. An analysis of the numerical simulation, including a comparison with experimental values, shows the influence of the correlation length on the global material behavior. What is more, it can be demonstrated that the standard deviation is a function of the correlation length, while the mean value remains independent of it.