A Stochastic Progressive Damage Simulation Model for Fiber Reinforced Polymer Laminates

Abstract

Fiber reinforced polymer matrix composites (FRPMC) laminate composites are widely used for its high strength and high stiffness-to-weight ratio. Although FRPMC holds many advantages, it has low matrix strength. This thesis proposes a stochastic progressive damage simulation model for FRPMC laminates. Damage mechanisms considered in this thesis are internal damages of fiber and matrix. Deterministic predictions by the existing damage progressive analysis model of laminate composites could be very different from the experimental global strength and failure modes due to effects of material uncertainties. In polymer matrix composites, such material uncertainties arise from different cure kinetics and chemically induced shrinkage. Therefore, uncertainties of constituents physical properties were taken into account in this study. An anisotropic damage model was used for damage initiation and evolution of each layer. Strength and fracture energy of layers were modelled as spatially varying random fields through the Karhunen-Loeve expansion method. For demonstrations of the proposed stochastic progressive damage analysis, a three-dimensional meso-scale finite element model of a multiple-layer was developed.