Predictive modeling of grain refinement during multi-pass cold rolling

Recently, grain refinement and grain misorientation have been experimentally studied for various materials with ultra-fine grained microstructures, which are achieved by the multi-pass cold rolling process. In this paper, a numerical framework is developed to model the evolution of grain size and grain misorientation based on a dislocation density-based material model. Novel finite element models embedded with the dislocation density-based material subroutine are developed to model the plastic deformation and microstructural evolution during the multi-pass cold rolling process. The multi-pass cold rolling processes of commercially pure titanium (CP Ti) and aluminum (AA 1200) are simulated in order to assess the validity of the numerical solution through comparison with experiments. The dislocation density-based material models are developed for CP Ti and AA 1200, which reproduce the observed material constitutive mechanical behavior under various strains, strain rates and temperatures occurring in the cold rolling process. It is shown that the developed model captures the essential features of the material mechanical behaviors and predicts a minimum grain size of below 100 nm after five-pass cold rolling of CP Ti with equivalent strains up to 2.07 and the average incidental dislocation boundary (IDB) misorientation angle increased to 4.6° after six-pass cold rolling of AA 1200 with equivalent strains accumulated to 5.77.