Reinforcement of polymer matrices with nanosized objects contributes to the improvement of the mechanical properties of matrices, which strongly depend on the distribution of nanoinclusions in the matrix. In this paper, a new multilevel modeling method has been proposed for estimating the Young's modulus of polymers reinforced with graphene nanoplatelets. The developed methodology covered sequential modeling from nano to macro scale. To describe the elastic responses of each system, a molecular dynamics model was used at nano and micro scales and a micromechanical model was applied for meso and macro levels. To eliminate uncertainties of the size, volume fraction and spatial orientation of a nanoplatelet, a stochastic approach was applied. Results of the technique approbation were in good agreement with the experimental data presented in scientific literature. The developed assessment method is valuable both from scientific and practical points of view. Modeling with this technique can predict how the mechanical properties of nanocomposites manifest themselves at different levels, which makes possible the expansion of the scope of its application.

用纳米尺寸的物体增强聚合物基质有助于改善基质的机械性能，这在很大程度上取决于纳米夹杂物在基质中的分布。在本文中，提出了一种新的多级建模方法，用于估计石墨烯纳米片增强的聚合物的杨氏模量。所开发的方法论涵盖了从纳米到宏观的顺序建模。为了描述每个系统的弹性响应，在纳米和微米尺度上使用了分子动力学模型，在介观和宏观水平上应用了微力学模型。为了消除纳米片的大小，体积分数和空间方向的不确定性，采用了随机方法。技术认可的结果与科学文献中提供的实验数据非常吻合。从科学和实践的角度来看，开发的评估方法都是有价值的。用这种技术进行建模可以预测纳米复合材料的机械性能如何在不同的水平上表现出来，从而有可能扩大其应用范围。