A modified cellular automata model for simulation of non-isothermal static recrystallization: a case study on pure copper annealing

In this paper, the static recrystallization (SRX) during non-isothermal annealing is simulated using a new modified probabilistic cellular automata (PCA) model. In this model, the microstructural evolution during non-isothermal annealing is considered as successive non-isothermal time steps. Furthermore, unlike the simplified conventional assumptions, the suggested model assumes that the temperature is variable within each time step. So the conventional algorithm is modified, and new formulations are proposed to calculate the time step, the probability of state transitions, and nucleation. The validity of the algorithm is examined practically on a case study by simulating the non-isothermal annealing of a cold-worked commercially pure copper with 99.99% purity. Comparing the performances of the modified and conventional PCA algorithms in predicting the non-isothermal SRX kinetics illustrates that the new PCA model is generally more accurate than the conventional one. The results reveal that the modified model, unlike the conventional ones, is able to calculate the time step and predict the SRX kinetics during non-isothermal annealing at a wide range of temperatures and temperature variations with more accuracy. Also, the comparison of the model predictions and the experimental observation shows a reasonable consistency between the predicted and the experimental results.