Simulation of primary static recrystallization with cellular operator model
1. Based on the modified cellular automata approach of Reher [60] a cellular operator model has been developed that is capable of accounting for spatial and temporal inhomogeneity on a finer scale. For this a scalable subgrid automaton is introduced that allows for a high spatial resolution on demand and still high computational efficiency. The scalable subgrid permits to track the minute changes of growth front during recrystallization owing to local variations of boundary mobility and net driving force. This approach substantially improves the prediction of grain morphology and grain statistics.2. This new cellular operator model for recrystallization (CORe) has been connected to the grain cluster deformation texture model GIA to account for different nucleation mechanisms. The GIA model renders the deformation texture in terms of grain cluster that in sum properly reflects the deformation texture. Moreover, the GIA model is interfaced to a work hardening model 3IVM that provides information on the dislocation densities of the individual grains in a cluster, depending on the total amount of slip. The individual clusters are evaluated with regards to their behaviour during deformation. Divergence of grain orientation is taken as measure for nucleation in transition band, large stored energy differences (e.g. large difference in dislocation density) across grain boundaries are interpreted as nucleation along grain boundaries and stored energy differences across the deformation zone around the randomly distributed second phase particles are considered as particle stimulated nucleation. Each process contributes specific nucleus orientation. 3. The information on the property of grain to a specific nucleation mechanism is coupled with the information on the local dislocation density to predict the absolute number of nuclei of a specific orientation and location as needed for quantitative recrystallization texture prediction. For this purpose a statistical model for the probability of nucleation sites has been developed based on the imbalance of driving force at interfaces, i.e. grain boundaries or band like structures (transition band). The model renders information on the absolute number of nuclei without adjustable parameters and allows quantitative grain size and texture prediction.4. Since the model has been mainly developed for Al alloys, recovery during annealing was taken into account to reduce the local driving force. Different kinds of recovery mechanisms has been included in this model based on the dislocation climb and cross slip.5. The CORe model has also been interfaced to a microchemistry model (ClaNG) that provides information on the temporal evolution of precipitates volume fraction, precipitate size distribution and solute content in solution. The information is available for any grid element at any time and can be utilized to determine the Zener drag and solute drag at the recrystallization growth front.6. The developed advanced recrystallization model has been subjected to parameter studies to probe the influence of material chemistry and processing conditions on recrystallization kinetics, morphology and texture. In particular their effect on the evolution of cube texture has been investigated.7. In particular, the model predicts a dependency of recrystallization kinetics, grain size and cube intensity on initial grain size. A strong cube texture in the deformed structure and strong growth competition produce a strong cube texture. An increase of the nucleation rate invariably tends to randomize the texture, irrespective of what growth law was used. Good agreement of the model predictions with experimental results has been ascertained.
info:eu-repo/classification/ddc/620, Ingenieurwissenschaften, Recrystallization, Cellular Operator Model
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