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论文基于炭黑填充橡胶复合材料具有周期性细观结构的假设,采用一种新的、改进的随机序列吸附算法建立了三维多球颗粒随机分布式代表性体积单元,并通过细观力学有限元方法对炭黑颗粒填充橡胶复合材料的力学行为进行了模拟仿真.研究结果表明:采用改进的随机序列吸附算法所建立的模型更加便于有限元离散化;模拟中周期性边界条件的约束,使其更加符合实际约束的真实情况;炭黑填充橡胶复合材料的有效模量明显高于未填充橡胶材料,并随着炭黑颗粒所占体积分数的增加而增大;通过比较发现,论文提出的多球颗粒随机分布式三维数值模型对复合材料的应力-应变行为和有效弹性模量的预测结果与实验结果吻合良好,证实了该模型能够用于炭黑颗粒增强橡胶基复合材料有效性能的模拟分析.
Based on the assumption that the carbon black filled rubber composites have a periodic mesostructure, a new and improved random sequence adsorption algorithm was used to establish the three-dimensional multi-spherical particles randomly distributed representative volume elements. Through the meso-mechanics finite element method Method was used to simulate the mechanical behavior of carbon black filled rubber composites.The results show that the model established by the improved random sequence adsorption algorithm is more convenient for the finite element discretization and the constraint of the periodic boundary conditions in the simulation makes it Which is more in line with the actual situation of the actual constraints; the effective modulus of carbon black filled rubber composites is significantly higher than that of unfilled rubber material, and increases with the increase of the volume fraction of carbon black particles; By comparison, The results of the prediction of the stress-strain behavior and the effective modulus of elasticity of the composites are in good agreement with the experimental data, which proves that the model can be used to simulate the effective performance of the carbon black particle reinforced rubber matrix composites .