Abstract
A framework is developed for structural optimization using an Element Free Galerkin (EFG) method for analyzing the structure, a kriging for surrogate model, and a Genetic Algorithm (GA) for finding the optimum design. The framework is tested for a plate with curvilinear stiffeners which are now possible with additive manufacturing such as 3-D printing. The efficiency and accuracy of the framework is compared with two other approaches: 1) MD.PATRAN, MD.NASTRAN and VisualDOC as implemented in EBF3PanelOpt, a Computational Design Environment being developed at Virginia Tech to optimally design panels with curvilinear stiffeners, and 2) a kriging, MD.PATRAN and MD.NASTRAN and genetic algorithms. All three approaches use optimization methods on both the shape and size design variables. The optimization scheme is a two-step optimization approach that divides the design variables into size and shape variables. First, the buckling parameter is maximized over the shape design variable, and then the mass is minimized over the size variable with constraint on buckling. The comparison between the three approaches shows the efficiency of the developed framework.
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