No abstract

Under certain conditions of extrusion temperature and strain rate Al-Mg-Si alloys produce coarse recrystallized grains at and near the surface. Current FEM models are able to analyze grain size evolution for extruded profiles, but cannot predict the coarse recrystallized grains near the surface. A new model using DEFORM 2D and local state variables such as strain, strain rate and temperature is compared with Al-Mg-Si rods extruded at 440°C and 500°C for two extremes of strain rate. The model is found to be sensitive to the processing conditions and to accurately predict the recrystallized grain size and fraction.

In the present work, we develop a state parameter-based model for the treatment of simultaneous precipitation and recrystallization based on a single-parameter representation of the total dislocation density and a multi-particle multi-component framework for precipitation kinetics. In contrast to conventional approaches, the interaction of particles with recrystallization is described with a non-zero grain boundary mobility even for the case where the Zener pressure exceeds the driving pressure for recrystallization. The model successfully reproduces the experimentally observed particle-induced recrystallization stasis and subsequent continuation in micro-alloyed steel with a single consistent set of input parameters. In addition, as a state parameter-based approach, our model naturally supports introspection into the physical mechanisms governing the competing recrystallization and recovery processes.

Recrystallization is a major means for controlling the grain size of steel during hot deformation. Usually, small grain sizes deliver superior mechanical properties. To aid the grain size controlling effect of recrystallization, small precipitates of carbo-nitride particles can be utilized to hinder the movement of grain boundaries. Interestingly, these particles are not only effective during grain growth, but also during recrystallization. In the present work, a recently developed state-parameter based model is introduced that is capable of describing both, the individual processes of static recrystallization, dynamic and static recovery and precipitation as well as the mutual interaction of these mechanisms in the course of elevated temperature processing. The evolution of state parameters within the model is discussed and the simulation results are compared to experimental information. Within our approach, a vast amount of experimental data for microalloyed steel is reproduced on basis of a single set of input parameters