Development, characterization, and parametric analysis of dry sliding wear behavior of epoxy-short betel nut fiber composite using response surface method and neural computation

Abstract

This work reports on the mechanical and wear performance of epoxy composite reinforced with short betel nut fiber (SBF). Composite samples with different weight percentages (0, 2, 3, 4, 6, and 8 wt%) of fiber content are fabricated through hand lay-up route. Mechanical properties such as tensile and flexural strengths are evaluated by conducting tests as per appropriate ASTM standards. Sliding wear tests are performed on a pin-on-disc test apparatus as per ASTM G99 standard. A non-linear regression model is developed in accordance with face-centered central composite design (FCCCD) of Response Surface Methodology (RSM). An artificial neural network (ANN) approach is applied to predict the wear rate of the composite and compared with the RSM predicted results. It is found that with the incorporation of short betel nut fiber both tensile and flexural strength of the composite shows an increasing trend. It is also observed that reinforcement of short betel nut fiber enhances the wear performance of epoxy. Surface morphologies of the worn samples have been studied to analyze the wear mechanism of the composite samples.