Modeling and homogenization of shape memory polymer nanocomposites

Increasing applications of shape memory polymer nanocomposites calls for reliable and effective modeling techniques. Finite element analysis (FEA) is one of the popular modeling techniques mostly used for this purpose. To perform FEA, an effective constitutive law is needed to extract the behavior of material in each integration point. In this study, we have employed 3D finite element modeling to study shape memory polymers (SMPs) loaded with perfectly dispersed Graphene Nanoplateletes (GNPs). In the current work, a novel scheme is used to create representative volume elements for the purpose of modeling, and a 3D constitutive equation is derived to describe the characteristic thermomechanical behavior of SMPs. Several realizations of SMP nanocomposites with different volume fractions and aspect ratios of GNP inclusions are generated and modeled, and effective mechanical properties of generated microstructures are estimated using volume-averaged values. It is observed that SMPs loaded with3% by volume GNP inclusions recover their permanent shape when they are subjected to a small strain thermomechanical cycle. Furthermore, a considerable improvement on the elastic modulus of the composites is observed upon increasing volume fraction or aspect ratio of GNP inclusions.