On the localization and failure in aluminum shells due to crushing induced bending and tension

Abstract

The paper is concerned with the accurate numerical simulation of localized deformation that can develop into necking and failure, induced by combined bending and tension in shell structures. The study is motivated by the need to establish the onset and evolution of such failures in imploding underwater structures. Such localized zones of deformation are shown to develop under controlled conditions in experiments on Al-6061-T6 cylindrical shells crushed laterally by rigid punches. The crushing induces gradually developing local depressions in the shells, at radially constrained locations. As the crushing progresses, the depressions with a width of the order of the shell wall thickness, deepen, increase their span, become neck-like and develop inclined failures. In the experimental set-up used, the crushing was terminated when the first of four such depressions that develop ruptured. The shell was sliced along the principal plane of crushing and the most deformed cross sections of the necks were measured. The crushing experiments were simulated numerically using solid FE models. The material was modeled as a finitely deforming elastic–plastic solid that hardens isotropically using the von Mises, the non-quadratic isotropic Hosford and anisotropic Yld04–3D yield functions suitably calibrated. While the overall structural response was reproduced well by all models, differences were observed in the evolution of localization in the depressions. For the von Mises yield function, the localized deformation was significantly milder than in the experiments. The isotropic Hosford yield function produced necks that were closer to the experimental ones, while Yld04–3D produced results that were very close to the measurements. Clearly, and in concert with other applications, the adoption of a non-quadratic yield function is necessary for reproduction of localized and other challenging deformation histories in Al alloys. The addition of anisotropy in such models improves further the predictions.