Abstract

        Graphene nanocomposites have attracted much attention in materials science due to their superior me-chanical properties. It is difficult for conventional mul-tiscale methods to provide substantial assistance to the research of such materials due to their huge computa-tional costs. Nonuniform transformation field analysis is a very effective reduced order homogenization meth-od for elastoplastic multiscale analysis. However, the reduced order model derived from this method has the shortcoming of low universality and high application threshold. Therefore, an improved reduced order model is proposed by combining the nonuniform transfor-mation field analysis with the k-means clustering algo-rithm. One can embed the required microscopic consti-tutive model into the reduced order homogenization framework without the need to derive a new reduced order model. Based on the cluster-based nonuniform transformation field analysis, the influence of the mi-croscopic plastic strain field evolution on the macro-scopic response of the material under consideration is revealed, while the mechanical properties of graphene nanocomposites are predicted. The numerical results show that the new reduced order model can accurately predict the macroscopic mechanical properties of com-posite materials, and its acceleration rate compared to the traditional finite element computations reaches103-104 .
 Keywords:graphene nanocomposites; reduced order model; multiscale methods; clustering; nonuniform transfomation field analysis

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call