Prediction of particle-reinforced composite material properties based on an improved Halpin–Tsai model

Abstract

This paper introduces an improved Halpin–Tsai model to predict the mechanical, thermal, and electrical properties of silicon-carbide-reinforced polypropylene composites. The model considers the influence of porosity and corresponding silicon-carbide volume fractions and derives relationships between material property shape factors and the aspect ratio, silicon-carbide volume fraction, and porosity. The improved model’s predictions exhibit errors of 4.00% for mechanical properties, 2.13% for thermal properties, and 2.24% for electrical properties when compared to finite element analysis. This study demonstrates that the improved Halpin–Tsai model can effectively predict the properties of silicon-carbide-reinforced polypropylene composites, aiding in the design and optimization of these materials.