A cellular operator model for the simulation of static recrystallization

This paper introduces an advanced recrystallization model, based on the principles of cellular automata. The model employs a scalable subgrid technique for efficient tracking of local variations during recrystallization and provides excellent statistics of grain size and texture after recrystallization. Grain boundary nucleation, transition band nucleation and particle-stimulated nucleation were incorporated in the model. This model can interface with other microstructural models, such as a deformation texture model, a dislocation density based flow stress model and a precipitation model. The sensitivity of the model with respect to minute changes of microstructure and microchemistry was tested. Finally, a through-process exercise was conducted to assess the performance of the model in multi-step simulations.