Browsing by Subject "buckling load"

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    Influence of Employing Laminated Isogrid Configuration on Mechanical Behavior of Grid Structures
    (Sage, 2019-08) Ehsani, Amir; Dalir, Hamid; Mechanical Engineering and Energy, School of Engineering and Technology
    For a long time, a single grid layer, such as isogrid, have been utilized to strengthen a shell or plate or as an independent structural member for various applications. Laminated grid structures consist of several grid layers that can have different in-plane orientations or can be made from different materials. Therefore, using laminated configuration instead of conventional grids yields to an extensive variety of configurations with different coupling effects and cost. In the current paper, to evaluate the appropriateness of laminated isogrids, the vibration and stability behaviors of a conventional isogrid are compared with corresponding laminated isogrid plate. The first-order shear deformation plate theory as well as the Ritz theorem is utilized to achieve the critical buckling loads and free vibration frequencies of the plates. The influence of increasing the number of isogrid plies and changing pattern geometries on mechanical behaviors of the laminated isogrid plate is also investigated. The results imply that utilization of the laminated isogrids remarkably enhances the buckling load and free vibration frequency values of the plates.
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    Multi-Objective Optimization of Composite Angle Grid Plates for Maximum Buckling Load and Minimum Weight Using Genetic Algorithms and Neural Networks
    (Elsevier, 2019-12) Ehsani, Amir; Dalir, Hamid; Mechanical and Energy Engineering, School of Engineering and Technology
    The present work describes an optimization process based on the ε-constraint method to find an optimum design to maximize the critical buckling load and minimize the structural weight of an angle grid plate. A comprehensive geometrical model is considered including all geometrical design variables of the grid. In order to achieve a precise and effective approximation of the buckling load, an artificial neural network (ANN) is employed. Training data for ANN is obtained by the Mindlin plate theory as well as the Ritz method. The ANN is combined with genetic algorithms (GA) to find the optimized design variables for an angle grid structure. The results provide a wide range of geometrical data for designers to choose the maximum buckling load at the minimum structural weight.