The accuracy of simulated recrystallisation textures is essential for predicting the formability of steel sheets. In a continuum modelling approach, this texture can be effectively calculated in two stages: nucleation and growth. However, the precision of the final texture depends heavily on the accuracy of the nucleation texture simulation. This paper presents a nucleation texture model that combines the strain-induced boundary migration (SIBM) mechanism with a traditional oriented nucleation model. The results indicate that the SIBM mechanism promotes the nucleation of low-stored energy grains and enhances the nucleation texture compared to using the oriented nucleation model alone. The findings suggest that the accuracy of nucleation texture could be improved by setting a minimum stored energy threshold for grains that nucleate during the early stages of recrystallisation.

In an industrial context, selecting an appropriate crystal plasticity (CP) model that balances efficiency and accuracy when modelling deformation texture (DT) is crucial. This study compared DTs in IF-steel after undergoing cold rolling reductions using different CP models for two input texture scenarios. Three mean-field (MFCP) models were utilised in their most basic configurations, without considering grain fragmentation or strain hardening, in addition to a dislocation-density-based full-field (FFCP) model. The study quantitatively compared the results from the MFCP models with those from the FFCP models. Furthermore, all CP model results were compared with experimental textures obtained from electron back-scatter diffraction (EBSD) experiments. The findings revealed that certain MFCP models could predict deformation textures as accurately as the FFCP models. Notably, one of the MFCP models exhibited a superior match with experimental textures for cold rolling reductions at 60%. Upon closer examination of specific crystallographic components, it was observed that MFCP models tended to predict a stronger {111}〈211〉 component, while the full-field model favours the {111}〈011〉 component. It is crucial to emphasise the importance of quantifying the texture within individual grains when assessing the macro-level deformation texture in rolling simulations.

This work presents an advanced crystal plasticity model for the simulation of the mechanical behavior of multiphase advanced high-strength steels. The model is based on the Visco-Plastic Self-Consistent (VPSC) model and uses information about the material’s crystallographic texture and grain morphology together with a grain constitutive law. The law used here, based on the work of Pantleon, considers how dislocations are created and annihilated, as well as how they interact with obstacles such as grain boundaries and inclusions (carbides). Additionally, strain rate sensitivity is implemented using a phenomenological expression derived from literature data that does not require any fitting parameter. The model is applied to the study of two bainitic steels obtained by applying different heat treatments. After fitting the required parameters using tensile experiments in different directions at quasi-static and high strain rates, formability properties are determined using the model for the performance of virtual experiments: uniaxial tests are used to determine r-values and stress levels and biaxial tests are used for the calculation of yield surfaces and forming limit curves.