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Modeling of CNT-reinforced nanocomposite with complex morphologies using modified embedded finite element technique

机译：使用改进的嵌入式有限元技术对复杂形态的CNT增强纳米复合材料进行建模

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摘要

In this article, we overcome the limitations of traditional finite element (FE) method in modeling CNT-reinforced nanocomposites with complex morphologies by developing a modified embedded finite element (mEFE) method. The composite constituents in the mEFE model are discretized independently but simulated simultaneously as a coupled system. The major advantage of this approach is discretizing the matrix as a regular grid, irrespective of the complex nature of the CNT network. The developed modeling approach allowed us to simulate realistic representative volume elements (RVEs) containing randomly dispersed CNTs of different curvatures, orientations, aspect ratios and volume fractions. An advanced Monte Carlo based algorithm was also developed to generate complex CNT networks. The proposed mEFE method requires a significantly shorter preprocessing effort and is more computationally efficient when compared to traditional FE method. It allowed us to study large scale RVEs reinforced with high CNT concentrations. The results of this idealised case showed that the elastic modulus of the nanocomposite increases with increasing the volume fraction of the CNTs; reaching 200 % improvement at 5 % volume fraction. However, the enhancement in the properties was not obvious at higher concentrations due to the poor dispersion and agglomeration of the dispersed CNTs.
机译：在本文中，我们通过开发一种改进的嵌入式有限元（mEFE）方法，克服了传统有限元（FE）方法在建模复杂形态的CNT增强纳米复合材料方面的局限性。 mEFE模型中的复合成分被独立离散，但同时作为耦合系统进行模拟。这种方法的主要优点是将矩阵离散为规则网格，而不管CNT网络的复杂性质如何。发达的建模方法使我们能够模拟包含不同曲率，方向，长宽比和体积分数的随机分散的CNT的真实的代表性体积元素（RVE）。还开发了一种基于蒙特卡洛的高级算法来生成复杂的CNT网络。与传统的有限元方法相比，提出的mEFE方法所需的预处理时间明显缩短，并且计算效率更高。它使我们能够研究用高CNT浓度增强的大规模RVE。这种理想情况的结果表明，纳米复合材料的弹性模量随CNT的体积分数的增加而增加。体积分数为5％时达到200％的改善。然而，由于分散的CNT的差的分散和附聚，在较高的浓度下性能的增强不明显。

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