A Process for Stochastic Material Analysis based on Empirical Data

Abstract

Material properties are often dominated by imperfections and geometrical variations in micro-scale. The manufacturing process of complex parts as stringers and their assembly creates specific microscopic imperfections whose influence to phenomena like delamination growth can not be understood with a deterministic homogenised material model. This paper describes a general approach to develop a stochastic model of anisotropic micro-structure on the basis of high-resolution image data. This approach uses a surrogate model for approximating material properties of meso-scale material blocks. The empirical material properties provided by the surrogate model are analysed for their marginal distribution and spatial covariance.