In this master’s thesis, we upgraded a program for simulating static recrystallization with a model that explicitly incorporates a nucleation criterion based on the calculated subgrain size and the critical radius for nucleation. The models for subgrain growth and for the critical subgrain radius for nucleation were coupled with the recrystallization model. This was followed by evaluation and testing of the developed model. The entire framework is based on mean-field theory. We investigated the kinetics of microstructure evolution in austenitic stainless steel 1.4429, also known as 316LN(H). First, experiments were performed using the thermomechanical testing system Gleeble 3500, through which we determined the flow curves and processing parameters required for calibrating the static recrystallization model. After implementing and calibrating the nucleation model, we conducted a set of simulations under different processing conditions. We studied the influence of temperature, strain and strain rate on the kinetics of subgrain evolution, the critical subgrain radius for nucleation, and the resulting effect on static recrystallization kinetics. We found that temperature and strain have the most significant influence on nucleation kinetics. By applying the critical subgrain radius criterion for nucleation, we were also able to determine incubation times required for static recrystallization under various conditions. In general, we observed that the kinetics of all processes increase with higher temperatures, higher strains and higher strain rates. Simulations at different temperatures further revealed that it is possible to identify the temperature range within which these processes will no longer be activated due to excessively high activation energies. This finding is particularly important in industrial practice and for the further development of models for simulating microstructure evolution during thermomechanical processing.
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