Abstract This paper presents a novel mesoscale finite element model for predicting the effective mechanical properties of concrete-like particle-reinforced composites with concave aggregates. In the mesoscale model, unit cells (UC) with randomly distributed non-convex particles and period boundaries are generated through computationally efficient algorithms to represent the periodic microstructures of concrete composites. Numerical homogenization is performed to calculate the effective mechanical parameters based on an unsorted node set technique. The results predicted by the proposed model show good agreement with the experimental measurements. The parametric study also indicates that UC models with periodic placement of particles at the boarders yield higher elastic modulus compared with those without periodic boundary particle placement, and the influence of boarder particles on homogenized material properties decreases as the UC size increases. Moreover, computational studies show that the elastic moduli of composites consisting of concavity particles are larger than those with the round and smooth particles given the same particle volume fraction. The proposed mesoscale modeling approach can serve as an easy and fast tool in assisting the design and optimization of strong, light-weight and reliable particle-reinforced composites.

中文翻译：

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具有非凸集料的类混凝土颗粒增强复合材料的中尺度计算建模

摘要 本文提出了一种新的中尺度有限元模型，用于预测具有凹骨料的类混凝土颗粒增强复合材料的有效力学性能。在中尺度模型中，通过计算效率高的算法生成具有随机分布的非凸粒子和周期边界的晶胞 (UC)，以表示混凝土复合材料的周期性微观结构。基于未分类节点集技术，执行数值均化以计算有效力学参数。所提出的模型预测的结果与实验测量结果非常吻合。参数研究还表明，与没有周期性边界粒子放置的模型相比，在边界处周期性放置粒子的 UC 模型产生更高的弹性模量，随着 UC 尺寸的增加，边界颗粒对均质材料性能的影响减小。此外，计算研究表明，在相同颗粒体积分数的情况下，由凹形颗粒组成的复合材料的弹性模量大于具有圆形和光滑颗粒的复合材料。所提出的中尺度建模方法可以作为一种简单快捷的工具，协助设计和优化坚固、轻质和可靠的颗粒增强复合材料。