ICCM Conferences, The 8th International Conference on Computational Methods (ICCM2017)

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Probabilistic fracture toughness prediction of composite materials
Yan Li, Min Zhou

Last modified: 2017-09-28


One of the biggest challenges in material sensitive design is to predict the variation of key material properties such as strength and fracture toughness. It has been proved that the stochastic nature of microstructure is the primary reason for fracture toughness scatter. Although Weibull distribution has been widely used to determine the probability of material fracture, its role has been confined to fitting fracture toughness data rather than providing predictive insight of material fracture toughness and the magnitude of scatter. Besides, the Weibull parameters which are obtained through curve fitting carry little physical significance. In this paper, an integrated computational and analytical model is developed to predict fracture toughness in a statistical sense. The Weibull distribution parameters are correlated with the statistical measures of microstructure characteristics and the statistical characterization of the competition between crack deflection and crack penetration at matrix/reinforcement interfaces. The approach and model will lead to more reliable material design through microstructure tailoring.

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