Multi-shape memory polymers (m-SMP) and their composites, as new kind of smart
materials, can change their shapes and keep the deformed states under external
forces. When stimulated by specific stimuli, m-SMP and its composite can reversibly
return to the original shapes. m-SMP and its composite are widely used in
various complex sensing devices, biomedical, aerospace and other intelligent
devices due to their advantages of large deformation, high recovery rate,
easy configuration and easy adjustment of shape response temperature. In
this paper, we established a new three-dimensional constitutive model for
m-SMP and its composite by introducing the level-set method into viscoelastic
constitutive equations. In this model, we regarded m-SMP and its composite as
inhomogeneous bodies consisting of different phases and used the level-set functions
to describe the phase transformation relationships. We took dual-shape memory
polymer (SMP) and triple-shape memory polymeric composite (TSPC) as
examples to illustrate the process of establishing the model. SMP includes two
phases, glass phase and rubber phase, and TSPC includes three phases,
rubbery–liquid-like phase, rubbery–semicrystalline phase and glass phase. We used
the developed constitutive model to numerically simulate the complete shape
memory processes and numerically simulate the mechanical behavior of each
process with different correlative rates of SMP and TSPC. The simulation
results of shape memory process show that the new constitutive model can
describe shape memory behaviors accurately with comparing the simulated
result and the existing text data. And the simulation results of each process
reflect that the shape memory process has a strong rate correlation. The
constitutive model established in this paper can provide a theoretical basis for the
application of SMP and TSPC, and can be further extended to m-SMP and its
composite.