Ahmadi Moghaddam Hamidreza, Mertiny Pierre
Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
Materials (Basel). 2019 Aug 29;12(17):2777. doi: 10.3390/ma12172777.
Polymers have become indispensable in many engineering applications because of their attractive properties, including low volumetric mass density and excellent resistance to corrosion. However, polymers typically lack in mechanical, thermal, and electrical properties that may be required for certain engineering applications. Therefore, researchers have been seeking to improve properties by modifying polymers with particulate fillers. In the research presented herein, a numerical modeling framework was employed that is capable of predicting the properties of binary or higher order composites with randomly distributed fillers in a polymer matrix. Specifically, mechanical properties, i.e., elastic modulus, Poisson's ratio, and thermal expansion coefficient, were herein explored for the case of size-distributed spherical filler particles. The modeling framework, employing stochastic finite element analysis, reduces efforts for assessing material properties compared to experimental work, while increasing the level of accuracy compared to other available approaches, such as analytical methods. Results from the modeling framework are presented and contrasted with findings from experimental works available in the technical literature. Numerical predictions agree well with the non-linear trends observed in the experiments, i.e., elastic modulus predictions are within the experimental data scatter, while numerical data deviate from experimental Poisson's ratio data for filler volume fractions greater than 0.15. The latter may be the result of morphology changes in specimens at higher filler volume fractions that do not comply with modelling assumptions.
聚合物因其具有吸引力的性能，包括低体积质量密度和优异的耐腐蚀性，在许多工程应用中已变得不可或缺。然而，聚合物通常缺乏某些工程应用可能所需的机械、热和电性能。因此，研究人员一直在寻求通过用颗粒填料改性聚合物来改善其性能。在本文提出的研究中，采用了一种数值建模框架，该框架能够预测聚合物基体中具有随机分布填料的二元或更高阶复合材料的性能。具体而言，本文针对尺寸分布的球形填料颗粒情况，探讨了机械性能，即弹性模量、泊松比和热膨胀系数。与实验工作相比，采用随机有限元分析的建模框架减少了评估材料性能的工作量，同时与其他可用方法（如解析方法）相比提高了精度水平。展示了建模框架的结果，并与技术文献中现有实验工作的结果进行了对比。数值预测与实验中观察到的非线性趋势吻合良好，即弹性模量预测值在实验数据的离散范围内，而对于填料体积分数大于0.15的情况，数值数据与实验泊松比数据存在偏差。后者可能是由于在较高填料体积分数下试样的形态变化不符合建模假设所致。
