This research addresses issues central to material modeling and process simulations. Here, issues related for developing constitutive model for crystallizable shape memory polymers are addressed in details. Shape memory polymers are novel material that can be easily formed into complex shapes, retaining memory of their original shape even after undergoing large deformations. The temporary shape is stable and return to the original shape is triggered by a suitable mechanism such heating the polymer above a transition temperature. Crystallizable shape memory polymers are called crystallizable because the temporary shape is fixed by a crystalline phase, while return to the original shape is due to the melting of this crystalline phase.

A set of constitutive equations has been developed to model the thermomechanical behavior of crystallizable shape memory polymers using elements of thermodynamics, continuum mechanics and polymer science. Models are developed for the original amorphous phase, the temporary semi-crystalline phase and transition between these phases. Modeling of the crystallization process is done using a framework that was developed recently for studying crystallization in polymers and is based on the theory of multiple natural configurations. Using the same frame work, the melting of the crystalline phase to capture the return of the polymer to its original shape is also modeled. The developed models are used to simulate a range of boundary value problems commonly encountered in the use of these materials. Predictions of the model are verified against experimental data available in literature and the agreement between theory and experiments are good. The model is able to accurately capture the drop in stress observed on cooling and the return to the original shape on heating. To solve complex boundary value problems in realistic geometries a user material subroutine (UMAT) for this model has been developed for use in conjunction with the commercial finite element software ABAQUS. The accuracy of the UMAT has been verified by testing it against problems for which the results are known. The UMAT was then used to solve complex 2-D and 3-D boundary value problems of practical interest.