Stochastic Discrete Damage Simulations of Laminate Composites

In this paper, probabilistic failure response and damage patterns in polymer matrix composite laminates was investigated by considering spatially varying strength properties. For this purpose, an efficient random field modeling framework for multiple cross-correlated random fields is proposed whereby different a set of uncorrelated random variables in the Karhunen-Loeve (KL) expansion are generated by Latin hypercube sampling technique and transformed to sets of correlated random variables. Discrete Damage Modeling (DDM) is performed by means of Regularized eXtended-Finite Element Method (Rx-FEM). The strength properties represented by spatially varying cross-correlated random fields define the matrix crack insertion patterns, whereas their propagation as well as the delamination growth is governed by cohesive law models with constant fracture toughness properties. One composite laminate a quasi-isotropic carbon/epoxy (Hexply IM7/8552) [45/90/-45/90](s) was modeled by using probabilistic DDM. The effect of statistical parameters such as the correlation length, variance and correlation coefficient between random fields of normal and shear strength within DDM framework was examined for the first time. Significant effects of the statistical parameters on the failure behavior and ultimate component strength was observed, manifesting importance of accurate definitions of the statistical properties for predicting probabilistic failure behavior and damage tolerance of laminate composites.