The present paper exposes how Morocco’s population and economic expansion pose a challenge to its capacity to supply energy demand, especially given how the scarcity of fossil fuels and their high market price now and in the future develop and follow strategies to achieve the objectives of...

Designof stiffened panels requires evaluating their behavior under any loading circumstances by considering initial geometric imperfections and the altering effects resulting from eventual material degradation. Both static and dynamic loading scenarios are to be investigated in order to assess safety for buckling strength of these vital structures.In this work, dynamic buckling under in-plane uniform axial compression loading having the form of finite duration pulse is analyzed through nonlinear finite element modeling of the structure. Welding induced defects that consist of initial geometric imperfections modifying the skin plate curvature in the longitudinal direction were incorporated. Material degradation in the heat affected zone was also taken into account. The Budiansky and Roth buckling criterion was employed to predict instability under a given dynamic load pattern. Various profiles including rectangular, triangular, double-triangular and half-sine were considered. The obtained results have shown that both the pulse period and the pulse shape have a drastic effect on the buckling strength. For the considered boundary conditions, pulses having periods that are comparable to two times the period of the first natural mode of vibrations were found to reduce the static buckling strength up to 66% in the elastic regime and 33% in the elastic plastic regime

Designing stiffened panels requires evaluating reliability of these structures with regards to the collapse limit state as it could be affected by the presence of general localized defects. Considering the case of a small square depression located on the surface panel, the buckling strength under in-plane uniform axial compression was evaluated through nonlinear finite element modelling. Artificial neural networks were introduced for representing the collapse load as function of the key intervening design variables. A full factorial design of experiment table constructed on these variables provided samples for the training phase, and complementary samples were used to test and validate the obtained models. Separating the various sources contributing to variability of the buckling strength, Monte Carlo method was used to evaluate the probability of failure as function of the applied compression load acting on the stiffened panel system. It was found that localized defects have a drastic effect on the reliability probability. For the considered geometric parameters and boundary conditions, the localized defect present on the central segment of the stiffened panel was recognized to be the most severe one.

Buckling of stiffened panels is strongly affected by initial geometric imperfections. The panel assembling technique used can influence both the initial geometric imperfections pattern and material inohomogeneities. It was recognized for the particular case of stir friction welded stiffened panels that the presence of a weld can decrease significantly buckling strength. This is mainly due to the reduction in material strength in the weld zone. In this work, stir friction welded stiffened panels are modeled by using the finite element method. The modelling takes into account distributed and localized initial geometric imperfections as well as material degradation that are generated in the heat affect zone by this process. A parametric study was conducted on the effects of magnitude of geometric distributed imperfections; position, length and depth of a localized depression; as well as material degradation occurring near the weld stripe. Artificial neural network models were built by using the results of various simulations performed according to full factorial design of experiment tables. This has enabled to assess reliability of design of a stiffened panel with regards to the buckling limit state by means of Monte Carlo approach.