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- Author or Editor: A. Limam x
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Considering a stiffened panel made from an elastic homogeneous and isotropic material which suffers a single localized initial geometric imperfection, assessment of the buckling limit state under in-plane uniform axial compression in the direction of stiffeners was performed. Giving a topological configuration of the stiffened plate, focus was aimed at the combined effect resulting from geometrical dimensions and localized defect characteristics. The perfect stiffened plate taken as reference and diverse imperfect stiffened plates suffering a single localized initial geometric defect of the form of a square depression were analyzed in this work. Extensive parametric finite element simulations were performed according to full factorial design of experiment tables that were built on key intervening factors. It was found that the main parameters controlling the buckling stress for the perfect plate are the plate width, then the web height and width, then finally the interaction between plate width and web height. In case of imperfect plates, the most adverse situation was obtained with the defect placed on the intermediate segments of the stiffened plate. A reduction of the buckling stress as low as 56% was reached in this situation. The main factors influencing the buckling load for the imperfect plate differ according to the defect configuration.
In this work, reconstruction of pressure time signal rising during a non-punctual impact occurring on an elastic structure has been achieved through using direct Bayesian approach. This was performed by means of posterior distribution of probabilities integrating the likelihood and prior random information. In the case of a noisy linear system for which the densities of probabilities associated to the prior information and noise could be assumed to be Gaussians and mutually independent, a new algorithm consisting of two steps was proposed. The first step works like a Wiener filter action and enables to determine the input pressure mean, while the second step yields evaluations of variability of the input pressure signal around that mean. It was found that the proposed method achieved perfect reconstruction of the original pressure taken at the input of the system.
Detection of cracks in mechanical components as early as possible enables monitoring structural health and scheduling efficiently the maintenance tasks such as replacing the critical parts just in time. Vibration analysis based techniques for crack detection have been largely considered in the framework of beam-like structures. This methodology relies essentially on the observed changes of beam frequencies and mode shapes induced by the presence of damage. In the present work, using an explicit analytical model assessing the effect of a crack on beam strain energy, the beam first resonance frequencies as they depend on a single crack defect characteristics were evaluated. The crack equations were obtained by means of fracture mechanics approach. Variations of the first beam frequencies and modes shapes were then related explicitly to the location and depth of the crack. Measuring the beam frequency changes and monitoring their variations can be used to perform identification of the crack defect parameters by solution of an inverse problem.
Reconstructing impact forces can improve considerably structural health monitoring as the extent of damage can be better made out. In this work an inverse problem formulation to identify the pressure generated by a non punctual impact is investigated. Considering the case of linear elastic layered composite structures, reconstruction of impact pressure is performed through a finite element model of the structure and impulse response functions between the impact zone and sensors placed at known positions. Assuming that the pressure is uniform, reconstruction is carried out by regularized deconvolution based on generalized singular value decomposition. The infl uence of mesh size, modal truncation and time sampling on the reconstructed pressure is discussed.