Blank design is an important task in sheet metal forming process optimization. The initial blank shape has direct effect on the part quality. This paper presents a deformation based blank design approach to determine the initial blank shape for a formed part. The blank design approach is integrated separately into ABAQUS, and DD3IMP, a research purpose in-house FEA code, to demonstrate its compatibility with any FEA code. The algorithm uses FE results to optimize the blank shape for a part. Deep drawing simulation of a rectangular cup geometry was carried out with an initial blank shape determined empirically. The blank shape was iteratively modified, based on the deformation history, until an optimal blank shape for the part is achieved. The optimal blank shapes predicted by the algorithm using both FEA softwares were similar. Marginal differences in the shape error indicate that the deformation history based push/pull technique can effectively determine an optimal blank shape for a part with any FEA software. For the shape error selected, both procedures estimate the optimal blank shape for the part within five iterations.
This paper presents a multiscale study of the quasi-static behaviour of a Ti6Al4V titanium alloy sheet. Tensile and compressive tests were carried out on specimens along several orientations from the rolling direction in order to characterise the material anisotropy. In parallel, X-Ray diffraction texture measurements were performed before and after deformation in tension. A phenomenological model (CPB06exn) and a multiscale crystal plasticity model (Multisite) were investigated to describe the mechanical behaviour of the tested material. The identification of the material parameters provides good predictions of the plastic anisotropy using both tensile and compressive data. The crystal plasticity model is in good agreement with the experiments in tension but it was observed that some improvements should be done to take into account the tension-compression asymmetry displayed by the material. Moreover both models lead to a good prediction of the Lankford's coefficients and yield strength.
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