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Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution

机译:纤维增强复合材料的微机械建模,具有统计上等效的随机纤维分布

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Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs) with statistical equivalent fiber distribution against the actual material microstructure. The realistic statistical data is utilized as inputs of the new method, which is archived through implementation of the probability equations. Extensive statistical analysis is conducted to examine the capability of the proposed method and to compare it with existing methods. It is found that the proposed method presents a good match with experimental results in all aspects including the nearest neighbor distance, nearest neighbor orientation, Ripley’s K function, and the radial distribution function. Finite element analysis is presented to predict the effective elastic properties of a carbon/epoxy composite, to validate the generated random representative volume elements, and to provide insights of the effect of fiber distribution on the elastic properties. The present algorithm is shown to be highly accurate and can be used to generate statistically equivalent RVEs for not only fiber-reinforced composites but also other materials such as foam materials and particle-reinforced composites.
机译:模拟纤维增强复合材料的随机纤维分布对于研究Micro Scale上的材料的渐进式故障行为非常重要。在本文中,我们开发了一种新的算法,用于产生随机代表容积元件(RVE),其统计等同的光纤分布与实际的材料微观结构。现实统计数据被用作新方法的输入,通过实现概率方程来归档。进行广泛的统计分析以检查所提出的方法的能力,并将其与现有方法进行比较。结果发现,该方法在包括最近邻距离,最近邻方向,Ripley的K功能和径向分布函数的所有方面,与实验结果呈现出良好的匹配。提出有限元分析以预测碳/环氧复合材料的有效弹性性能,以验证产生的随机代表性体积元素,并提供纤维分布对弹性性质的影响的见解。该算法显示为高度准确,可用于为不仅为纤维增强复合材料产生统计上等效的杆,而且可以用于产生纤维增强复合材料,而且可以用于其他材料,例如泡沫材料和颗粒增强复合材料。

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