Inverse identification of a coupled hardening law with GTN damage model parameters for cold-rolled steel: application to the deep drawing process

Abstract

This study considers the Gurson-Tvergaard-Needleman (GTN) micromechanical damage model as a potential alternative to the traditional forming limit curves used in industrial deep drawing applications. In the first step, the parameters of a coupled hardening law with the GTN damage model were identified through parametric identification using inverse analysis. This technique relies on tensile test results obtained from notched specimens cut from cold-rolled steel (DC06EK). The study's originality lies in utilizing both global and local experimental data, focusing principally on the force–displacement curves and the evolution of equivalent plastic strain within two zones of the specimen: rupture and deformation stagnation. The parameter identification demonstrated a good agreement between experimental data and numerical results. In the second step, the determined work hardening law coupled with the GTN damage model was implemented in a numerical simulation of an industrial deep drawing process for a wheelbarrow tray (WBT). The outcomes of the numerical simulation, in terms of thickness reduction in the deep-drawn WBT, were compared with the experimental results, showing very good agreement. A further comparison was made between the numerical results with and without the GTN model, as well as with a previous study (without GTN) on the same numerical simulation. This demonstrated the value of incorporating a hardening law coupled with the GTN model, as it allowed for more accurate determination of wrinkling and necking prior to rupture based on the applied blank holder pressure, helping to prevent those defects during the deep drawing process of the WBT.