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The mechanical properties of steels are influenced by their microstructure and particularly the grain size, with a small grain size giving high strength and toughness. A significant process for grain size control is recrystallisation during hot rolling, where the recrystallisation kinetics and recrystallised grain size are affected by the material’s initial grain size, alloy content, temperature, strain and strain rate. It is desirable to be able to model the recrystallisation process to optimise hot rolling schedules and to provide a known microstructure for subsequent prediction of phase transformation on cooling.
A physically based 3D cellular automata model, developed for predicting recrystallisation kinetics and phase transformation in hot rolled steels, has been modified to give accurate predictions of recrystallised grain size distributions for different deformation strains and temperatures. Modification was required to correct for predicted temperature sensitivity for the recrystallised grain size that is not seen in experimental results.
In order to correctly model both the recrystallisation kinetics and resultant grain size distribution, accurate representation of recrystallisation nucleation and nucleus growth to critical size are essential and these are driven by the local conditions. This paper reports on the implementation of a boundary intensity factor (BIF), giving a higher dislocation density at the grain boundary than grain interior, to drive the recrystallisation nucleation event and subsequent growth to exceed the critical nucleus. The concept of a BIF is supported by EBSD misorientation data, related to dislocation density, on deformed samples, which have been used to define the boundary intensity factor magnitude and boundary width. The effect of the BIF on the recrystallisation kinetics and recrystallised grain size distribution has been assessed using a model Fe-30Ni steel, with a starting grain size of 160 µm, deformed at a strain of 0.3 at 900 °C and 950°C.