Abstract

Stiffened panels are usually the basic structural building blocks of airplanes, vessels and other structures with high requirements of strength-to-weight ratio. They typically consist of a plate with equally spaced longitudinal stiffeners on one side, often with intermediate transverse stiffeners. Large aeronautical and naval parts are primarily designed based on their longitudinal compressive strength. The structural stability of such thin-walled structures, when subjected to compressive loads, is highly dependent on the buckling strength of the structure as a whole and of each structural member. In the present work, a number of modelling and numerical calculations, based on the Finite Element Method (FEM), is carried out in order to predict the ultimate load level when stiffened panels are subjected to compressive solicitations. The simulation models account not only for the elasto-plastic nonlinear behaviour, but also for the residual stresses, material properties modifications and geometrical distortions that arise from Friction Stir Welding (FSW) operations. To construct the model considering residual stresses, their distribution in FSW butt joints are obtained by means of a numerical-experimental procedure, namely the contour method, which allows for the evaluation of the normal residual stress distribution on a specimen section. FSW samples have been sectioned orthogonally to the welding line by wire electrical discharge machining (WEDM). Displacements of the relaxed surfaces are then recorded using a Coordinate Measuring Machine and processed in a MATLAB environment. Finally, the residual stress distribution is evaluated by means of an elastic FE model of the cut sample, using the measured and digitalized out-of-plane displacements as input nodal boundary conditions. With these considerations, the main goal of the present work will then be related to the evaluation of the effect of FSW operations, in the ultimate load of stiffened panels with complex cross-section shapes, by means of realist numerical simulation models.

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