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A systematic and statistical approach to evaluate and predict the properties of random discontinuous natural fiber reinforced composites. Different composites based on polypropylene and reinforced with natural fibers have been made and their mechanical properties are measured together with the distribution of the fiber size and the fiber diameter. The values obtained have been related to the theoretical predictions, using a combination of the Griffith theory for the effective properties of the natural fibers and the Halpin-Tsai equation for the elastic modulus of the composites. The relationships between experimental results and theoretical predictions are statistically analyzed using a probability density function estimation approach based on neural networks. The results show a more accurate expected value with respect to the traditional statistical function estimation approach. In order to point out the particular features of natural fibers, the same proposed method is also applied to PP-glass fiber composites.

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