It has been demonstrated that adding a few percent of nanoscale reinforcements, leads to remarkable improvement in mechanical properties of the polymers such as stiffness, damping, and energy absorption. These lightweight materials are attractive substitutes for the heavy metallic structural parts in the automotive, military, aerospace and many other industries. However, due to complexity of these multiphase materials, accurate modeling of their behavior in real loading cases is still ambiguous. The impact simulation is a vital step in design procedure of a vehicle, where a strain rate-dependent model of its components is required. In this paper, an elasto-viscoplastic modeling procedure of the polymer-based nanocomposites, assuming the elastic behavior of the nano-phase is presented; whereas the polymeric matrix deformation is dependent to the loading rate and is characterized by the method of Genetic algorithm optimization-based fitting to the experimental observations. By introducing a modified Halpin-Tsai method, the nanocomposite is then modeled as a homogenized material where the modification algorithm is the main challenge. A combination of approaches including parametric analysis, central composite design of experiments and response surface method is proposed to modify the tangent modulus of the polymeric matrix to be passed as the input to the Halpin-Tsai equations. Finally, the procedure is implemented to a set of epoxy-GNP nanocomposites under unidirectional compressive loads with different rates and the stress-strain curves are predicted with a decent precision.

已经证明，添加百分之几的纳米级增强材料可以显着改善聚合物的机械性能，例如刚度、阻尼和能量吸收。这些轻质材料是汽车、军事、航空航天和许多其他行业中重金属结构部件的有吸引力的替代品。然而，由于这些多相材料的复杂性，它们在实际负载情况下的行为的准确建模仍然不明确。碰撞模拟是车辆设计过程中的重要步骤，其中需要其部件的应变率相关模型。在本文中，假设纳米相的弹性行为，聚合物基纳米复合材料的弹粘塑性建模程序；而聚合物基体变形取决于加载速率，并通过基于遗传算法优化的实验观察拟合方法进行表征。通过引入改进的 Halpin-Tsai 方法，纳米复合材料随后被建模为均质材料，其中修改算法是主要挑战。提出了包括参数分析、实验的中心复合设计和响应面方法在内的方法的组合，以修改聚合物基体的切线模量，以作为 Halpin-Tsai 方程的输入。最后，该程序在具有不同速率的单向压缩载荷下对一组环氧树脂-GNP 纳米复合材料实施，并以不错的精度预测应力-应变曲线。