Python programming predictions of thermal behavioral aspects of orange peel and coconut-coir reinforced epoxy composites

Abstract

Using a hand lay-up approach, both orange peel and coconut coir flbres are used in particulate form with an epoxy matrix to create partly green biodegradable composites. The flndings indicate great opportunities for employing these natural flbres. The thermal conductivity of orange peel and coconut-coir epoxy composites was measured experimentally for various volume fractions of particulate flbres. The experimental flndings show that as flbre concentration increases, thermal conductivity decreases. Experimental data are compared to theoretical models to determine the change in thermal conductivity with flbre amount fraction. There was a clear correlation between the hypotheses and the actual results. Regression analysis using Python programming is also done for the prediction of the thermal properties of particulate orange peel and coconut-coir flbre composites. It is observed that coir flbre composites outperformed the orange peel, indicating that the coir flbre composite is a proper thermal insulator that can be used in many industries, like the automotive industry, buildings, and steam pipes, to reduce heat transfer and thereby save a lot of energy.