13 - Experimental determination of tribo behavior of fiber-reinforced composites and its prediction with artificial neural networks

Abstract

This chapter assesses the advantages of composite materials over conventional materials, explains the significance of natural fiber polymer composites over synthetic fiber polymer composites, defines the need to study tribological behavior of fiber-reinforced composite material, and reviews the extensive literature on wear behavior of synthetic and natural fiber-reinforced polymer composites. The main objective of the work was to develop cotton fiber-reinforced polyester composites (CFPCs) with different weight concentrations of fly-ash fillers using the hand layup compression molding process, and study the influence of different concentrations of fillers on the wear response of CFPCs under the effect of different operating parameters. The test results reveal that the fly-ash fillers have a significant effect on the response. To get a better insight into the results drawn from the experimental observations, predictive analysis was done through an artificial neural network (ANN). The validation of results revealed the ANN to be an efficient tool to calculate the wear response of CFPCs.