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The application of cellular automata in materials science requires the conversion of the automata’s rules and abstract general properties to rules and properties associated with the material and phenomena under study. In this paper we propose a model which uses cellular automata to simulate recrystallization and grain growth during isothermal and non-isothermal treatments of cold worked polycrystalline materials. The algorithm’s spatial and temporal scaling is based on known experimental results for recrystallization and grain growth in highly cold-worked commercially pure titanium grade 2. In the recrystallization, the best agreement between experimental and computational results in terms of the process kinetics and the average diameter of recrystallized grains is obtained from a nucleation model that considers the temperature-dependent nuclei formation rate. In the simulation of grain growth after primary recrystallization, the results indicate the normal growth of an equiaxed grain structure whose kinetics and dimensions are comparable to those observed experimentally.

Simulation of CP-Ti Recrystallization and Grain Growth by a Cellular Automata Algorithm: Simulated Versus Experimental Results