Data-driven analysis and prediction of tensile behavior of coir-based composites

Abstract

Coconut husk-derived coir fiber composites, an eco-friendly alternative to conventional polymer composites, are being considered as a viable substitute for non-structural applications. The current research endeavor aims to develop a framework for analyzing and predicting the tensile properties of short coir-based composites (SCBCs) using neural networks. The effect of parameters such as fiber treatment, fiber content, fiber aspect ratio, manufacturing process, and matrix type on the tensile properties of SCBCs has been considered. The standard performance metrics assessed the feasibility of the developed model. The coefficient of determination (R2) of 0.9661 and 0.9816 was obtained for the tensile strength and tensile modulus prediction model, respectively.