A statistically-based continuum anisotropic constitutive model of fiber-reinforced shape memory hydrogel composites

Abstract Shape memory hydrogel composites (SMHCs) have been developed to enhance the performance of shape memory hydrogels (SMHs), serving as smart soft materials with superior shape and performance programmability. The establishment of a constitutive model is crucial for the utilization of SMHCs, yet research in this area remains limited. Herein, based on the transient network theory and the Fung-type elastic model, a micro-macroscopic anisotropic constitutive model for SMHCs incorporating double-network SMHs and the distribution of fibers was developed. Mechanical behaviors and shape memory effects of SMHCs were investigated with three different fiber distributions: unidirectional, planar uniform, and volumetric uniform. The efficacy of model was validated by implementing it into a user-defined materials subroutine (UMAT). Various parameters of SMHCs, such as ambient temperature, instantaneous shear modulus of the network, and fiber stiffness, were examined for their effects on mechanical behaviors and shape memory effects. The proposed model can capture the shape memory effects of double network SMHCs. Simulation examples involving SMHC-based stents were provided to illustrate the practical implications of our work in SMHCs applications.