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Utility of 2D Finite Element Simulations for Predicting Effective Thermomechanical Properties of Particle-Reinforced Composites

机译:用于预测粒子增强复合材料的有效热机械性能的2D有限元模拟的效用

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In the last two decades, researchers have implemented two-dimensional (2D) Finite Element (FE) simulations of particle-reinforced composites for various purposes, including prediction of effective properties and failure modes. The present work aspires to examine the validity of the hypothesis that 2D FE simulations can provide accurate predictions for various thermomechanical properties of high volume fraction (VF) particle-reinforced composites. For this purpose, the random sequential adsorption (RSA) algorithm is implemented to generate FE simulations of various composites. The uniqueness in the methodology of the present work is in the generation of FE simulation of composites with more than two material types as reinforcement, as well as thorough and concurrent comparison of multiple thermal and mechanical properties. The adequacy of the simulations is verified statistically, and the results are compared to predictions from established schemes as well as certain experimental findings. These comparisons show that the predictive power of 2D FE simulations is lower for elastic properties, and higher for coefficient of thermal expansion (CTE) and thermal conductivity of particle-reinforced composites. The findings of this research can guide the researchers in making better decisions for implementing Finite Element Method (FEM) for designing high VF composites.
机译:在过去的二十年中,研究人员已经实施了颗粒增强复合材料的两维(2D)有限元(FE)模拟用于各种目的,包括的有效性能和失效模式预测。本工作渴望检查的假设2D有限元模拟可以提供高体积分数(VF)颗粒增强复合材料的各种热机械性能的准确预测的有效性。为此目的,实现了随机顺序吸附(RSA)算法以生成各种复合材料的FE模拟。本作方法的方法中的唯一性在于具有两种以上材料类型的复合材料的FE模拟,作为加固,以及多种热和机械性能的彻底和经常比较。统计上验证了模拟的充分性,并将结果与​​来自既定方案的预测和某些实验结果进行了比较。这些比较表明,弹性特性的2D Fe模拟的预测力较低,热膨胀系数(CTE)和颗粒增强复合材料的导热率较高。该研究的结果可以指导研究人员制定更好的决定,用于实现用于设计高VF复合材料的有限元方法(FEM)。

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