Image Computation Algorithm for Determination of Microstructural Properties of Rice Husk-Sisal-Kenaf Fiber Reinforced Hybrid Composite

Abstract

In the current work, the morphological and mechanical features of a hybrid epoxy matrix composite created by hand layup and reinforced with fibers from rice husk, sisal, and kenaf are predicted by using Watershed segmentation algorithm. To forecast the effect of coating composition on physical performance of a composite, Tensile and hardness tests were used to define the resulting hybrid composites' mechanical characteristics. The objective of the empirical investigation presented in this work is to understand the mechanical behavior of hybrid natural fiber composites. The production of rose husk-sisal-kenaf-epoxy hybrid samples is done by hand layup, with the planned plies being alternately stacked and the weight of the matrix and fibers being kept between 40% and 60%. Samples are sliced from a laminate that has been manufactured in accordance with ASTM specifications in order to undertake various experiments. Dog bone and flat bar shapes were used to cut specimens for tensile test & flexural test. Tensile strength and flexural strength were measured following execution of experiment under UTM and contrasted with base values of used epoxy polymer to identify constant change in strength.