Prediction of particle-reinforced composite material properties based on an improved Halpin–Tsai model
Source abstract
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.
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Research context
OpenAlex topics: Natural Fiber Reinforced Composites · Composite Material Mechanics · Polymer Nanocomposites and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Automotive Engineering, Hubei University of Automotive Technology 1 , Shiyan 442002, China
Hubei Key Laboratory of Automotive Power Transmission and Electronic Control 2 , Shiyan 442002, China
College of Civil Engineering and Architecture, Southwest University of Science and Technology 3 , Mianyang 621010, China
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences 4 , Guangzhou 510301, China
Funding
The Doctoral Research Fund of the HUAT · Hubei Provincial Department of Education Project · Open fund of Hubei Key Laboratory of Automotive Power Train and Electronic Control
References (47)
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