This article presents a novel approach to model the mechanical response of smart polymeric materials. A cyclobutane-based mechanophore, named "smart particle" in this article, is embedded in an epoxy polymer matrix to form the self-sensing smart material. A spring-bead model is developed based on the results from molecular dynamics simulation at the nanoscale to represent bond clusters of a smart polymer. The spring-bead network model is developed through parametric studies and mechanical equivalence optimization to represent the microstructure of the material. A statistical network model is introduced, which is capable of bridging the high-accuracy molecular dynamics model at the nanoscale and the computationally efficient finite element model at the macroscale. A comparison between experimental and simulation results shows that the multiscale model can capture global mechanical response and local material properties.@en

This paper presents a multiscale approach for capturing the mechanical response of smart polymer materials. A spring-bead model is developed at the microscale based on results from molecular dynamics simulation to represent a bond cluster of polymer. Through parametric studies and mechanical equivalence optimization, a statistical network model is developed to represent the microstructure of the materials at the mesoscale. The introduction of the spring-bead based network model bridges the high accuracy molecular dynamics model at the microscale and the computationally efficient finite element model at the macroscale. A comparison between experimental and simulation results shows that the multiscale model is capable of capturing global mechanical response and local material properties.@en