Simulation of discontinuous dynamic recrystallization in pure Cu using a probabilistic cellular automaton

A cellular automaton algorithm with probabilistic cell switches is employed in the simulation of dynamic discontinuous recrystallization. Recrystallization kinetics are formulated on a microlevel where, once nucleated, new grains grow under the driving pressure available from the competing processes of stored energy minimization and boundary energy reduction. Simulations of the microstructural changes in pure Cu under hot compression are performed where the influence of different thermal conditions are studied. The model is shown to capture both the microstructural evolution in terms of grain size and grain shape changes and also the macroscopic flow stress behavior of the material. The latter gives the expected transition from single- to multiple-peak serrated flow with increasing temperature. Further, the effects on macroscopic flow stress by varying the initial grain size is analyzed and the model is found to replicate the shift towards more serrated flow as the initial grain size is reduced. Conversely, the flow stress is stabilized by larger initial grain sizes. The extent of recrystallization as obtained from simulations are compared to classical JMAK theory and proper agreement with theory is established. In addition, by tracing the strain state during the simulations, a post-processing step is devised to obtain the macroscopic deformation of the cellular automaton domain, giving the expected deformation of the equiaxed recrystallized grains due to the macroscopic compression.