Three-Dimensional Analysis of the Effect of Material Randomness on the Damage Behaviour of CFRP Laminates with Stochastic Cohesive-Zone Elements

This article was published in the journal Applied Composite Materials [© Springer Science+Business Media]. The definitive version is available at: http://dx.doi.org/10.1007/s10443-013-9354-3Laminated carbon fibre-reinforced polymer (CFRP) composites are already well established in structural applications where high specific strength and stiffness are required. Damage in these laminates is usually localised and may involve numerous mechanisms, such as matrix cracking, laminate delamination, fibre de-bonding or fibre breakage. Microstructures in CFRPs are non-uniform and irregular, resulting in an element of randomness in the localised damage. This may in turn affect the global properties and failure parameters of components made of CFRPs. This raises the question of whether the inherent stochasticity of localised damage is of significance in terms of the global properties and design methods for such materials. This paper presents a numerical modelling based analysis of the effect of material randomness on delamination damage in CFRP materials by the implementation of a stochastic cohesive-zone model (CZM) within the framework of the finite-element (FE) method. The initiation and propagation of delamination in a unidirectional CFRP double-cantilever beam (DCB) specimen loaded under mode-I was analyzed, accounting for the inherent microstructural stochasticity exhibited by such laminates via the stochastic CZM. Various statistical realizations for a half-scatter of 50 % of fracture energy were performed, with a probability distribution based on Weibull's two-parameter probability density function. The damaged area and the crack lengths in laminates were analyzed, and the results showed higher values of those parameters for random realizations compared to the uniform case for the same levels of applied displacement. This indicates that deterministic analysis of composites using average properties may be non-conservative and a method based on probability may be more appropriate. © 2013 Springer Science+Business Media Dordrecht