期刊
COMPOSITE STRUCTURES
卷 228, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compstruct.2019.111331
关键词
Particulate polymer matrix composite; Statistical RVE modeling; Fourier descriptors; Thermoelastic properties; Stone composite
Particulate polymer matrix composites (PPMCs) play a significant role in a wide range of applications from tissue engineering to aero-structures. Modeling thermoelastic properties of PPMCs can save sizable experimental time and costs, as it provides the capability of predicting the composite's response to different loading conditions with acceptable accuracies. Micromechanical modeling approach is employed in this investigation to predict the thermoelastic properties of a new particulate polymer matrix composite, made of granite powder as inclusion and the acrylonitrile butadiene styrene (ABS) as matrix-called green stone composite. The reinforcing particles are modeled according to their shape irregularities. Namely, a statistical representative volume element (SRVE) is developed using the concept of integral range, with randomly distributed particles with irregular shapes. Experiments have been conducted to examine the validity of the proposed modeling approach. Numerical and experimental results both show that adding granite powder to pure ABS up to 38% (volume fraction) can notably increase the composite's thermoelastic properties (bulk and shear moduli as well as thermal conductivity), as high as 200%.
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