[SY-F2] Experimental-Computational Analysis of Primary Static Recrystallizazion in DC04 Steel
Low-alloyed steels with body-centered cubic crystal structure (bcc, ferrite) are a material class which is widely used in automotive sheet metal forming applications. When produced with an adequate crystallographic texture, the mechanical behavior of steels for forming applications is characterized by an isotropic in-plane flow behavior in combination with a low yield strength. To obtain these beneficial mechanical properties, an adequate cold rolling strategy in terms of the number of passes, deformation rates, and total reduction needs to be followed by an annealing procedure with a time-temperature profile that facilitates primary static recrystallization. The most fundamental connection between cold rolling and heat treatment consists in the reduction of the dislocation-related free energy stored during deformation by the formation of new grains with a very small dislocation content. Hence, the local variation in crystallographic orientation and defect population lead to very inhomogeneous grain boundary migration velocities.
We present here results of a coupled experimental-computational approach for studying microstructure evolution in industrially cold rolled DC04 steel under quasi-isothermal conditions. For the experimental characterization, quasi in-situ experiments consisting of interrupted isothermal holding at 600°C and subsequent Electron Backscatter Diffraction (EBSD) orientation imaging were conducted. The results reveal a strong correlation between local dislocation density, quantified via the Kernel Average Misorientation (KAM), and the local increase of recrystallized volume fraction. To complement the experimental findings and gain further insights into the influence of the sub-surface microstructure, a Cellular Automata (CA) model was utilized. The employed three-dimensional microstructure model was directly built from the experimentally characterized deformation microstructure. Different approaches of scaling the KAM into dislocation density values, i.e. the driving force for recrystallization, are employed. Similarities and deviations between experimental and computational results are discussed with the aim at increasing the understanding the mechanisms of static primary recrystallization.
We present here results of a coupled experimental-computational approach for studying microstructure evolution in industrially cold rolled DC04 steel under quasi-isothermal conditions. For the experimental characterization, quasi in-situ experiments consisting of interrupted isothermal holding at 600°C and subsequent Electron Backscatter Diffraction (EBSD) orientation imaging were conducted. The results reveal a strong correlation between local dislocation density, quantified via the Kernel Average Misorientation (KAM), and the local increase of recrystallized volume fraction. To complement the experimental findings and gain further insights into the influence of the sub-surface microstructure, a Cellular Automata (CA) model was utilized. The employed three-dimensional microstructure model was directly built from the experimentally characterized deformation microstructure. Different approaches of scaling the KAM into dislocation density values, i.e. the driving force for recrystallization, are employed. Similarities and deviations between experimental and computational results are discussed with the aim at increasing the understanding the mechanisms of static primary recrystallization.