Characterization of damage and anisotropy of DC06 sheet metal applied to deep drawing

Abstract

This study explores the integration of the Gurson-Tvergaard-Needleman (GTN) micromechanical damage model as a promising alternative to traditional forming limit curves by assessment of the formability in a deep drawing process. The success of the deep drawing process depends mainly on the material characterization. The sheet metal used in this thesis work is DC06EK. The mechanical characterization of this sheet metal was first the subject of a characterization of anisotropic behavior and then to isotropic and anisotropic plastic yield criteria from tensile tests on a specimen with a constant cross-section. Then, to characterize the GTN damage model and a hardening law, a new inverse identification strategy was proposed with a tensile test on a specimen with a variable (notched) cross-section. This strategy entails using both global and local observables, such as force and plastic strain, in two distinct zones within the tensile test specimen: a localization of deformation in one zone and the stagnation of deformation in another zone of the specimen with the variable cross-section indicates the moment of necking onset. The inverse identification was performed on a pseudo-experimental database to validate and test the reliability of the used algorithm considering three cases: the first one using only the force as a global observable, the second case adding a local observable, which is the plastic strain at the center of the specimen where rupture occurs, and the third case adding the plastic strain stagnation in a shifted zone from the center. Next, the validated approach was similarly used on an experimental tensile test to identify the GTN damage model coupled with hardening law parameters. The inverse identification process demonstrated good agreement between experimental and numerical results, emphasizing the importance of combining global and local observables for accurate parameter determination. In the second step, the identified parameters of the GTN damage model coupled with the hardening law were implemented into a numerical simulation of an industrial deep drawing application. This application concerns the deep drawing of a wheelbarrow tray. The findings demonstrated that the GTN damage model can significantly influence the prediction of wrinkling defects and accurately predict the zone and moment of necking onset, while traditional forming limit curves indicate the presence or absence of rupture, the case which could not be obtained via the GTN model.