Effect of the Statistical Nature of Fiber Strength on the Predictability of Tensile Properties of Polymer Composites Reinforced with Bamboo Fibers: Comparison of Linear- and Power-Law Weibull Models

In fibrous composites, tensile strength of reinforcements exhibits a stochastic nature, and the mechanical properties of the composites are significantly influenced by such strength variability. The present study aims at providing a comparative investigation of the influence of the statistical variation in fiber strength on the tensile properties of unidirectional composites reinforced by bamboo fibers. Monte-Carlo simulations coupled with the linear- and power-law Weibull distributions are performed to conduct numerical predictions for damage evolution and strength variability of the composites, and the predicted mean strength and failure strain are compared with the experimental results. The Weibull parameters used are achieved through the Maximum Likelihood Estimation with multiple data sets of fiber lengths. Fiber strength statistics is found to have an effect on composite mechanical properties. The results further indicate that the use of the power-law model is relatively efficient for modeling purposes in comparison to the linear-law model, which could be attributed to fiber diameter variation.