Effect of microstructural and morphological parameters on the formability of BCC metal sheets

Abstract

The determination of forming limit strains in sheet metal forming industry is a useful way for quantifying metals in terms of formability. However, such forming limit diagrams (FLDs) remain very difficult to obtain experimentally. Therefore, the numerical prediction of forming limit strains represents a convenient alternative to replace this time consuming and expensive experimental process. Moreover, a combined theoretical-numerical model allows investigating the impact of essential microstructural aspects (e.g., initial and induced textures, dislocation density evolution, softening mechanisms, ...) and deformation mechanisms on the ductility of polycrystalline aggregates. In this paper, the impact of microstructural and morphological parameters, particularly the mean grain size, on the formability limit of BCC materials is investigated. To this end, an elastic-plastic self-consistent (EPSC) polycrystalline model, coupled with a bifurcation-based localization criterion, is adopted to numerically simulate FLDs. The FLDs thus determined using the Bifurcation-EPSC model for an IF-Ti single-phase steel are compared to the FLDs given by ArcelorMittal, demonstrating the predictive capability of the proposed approach in investigations of sheet metal formability. The role of the averaging scheme is also shown to be significant by comparing the critical limit strains predicted with the self-consistent scale-transition scheme to those obtained with the more classical full-constraint Taylor model. Finally, numerical simulations for different values of mean grain size are provided in order to analyze the impact of mean grain size on the formability of BCC metal sheets. In this study, an elastic-plastic self-consistent (EPSC) polycrystalline model is coupled with a bifurcation-based localization criterion to investigate relationships between microstructural and morphological properties and formability of single-phase BCC steels. The interest in such a combined theoretical-numerical prediction tool is to classify materials in terms of ductility and to optimize material properties or to design new grades of steel with enhanced in-use mechanical properties.