Global/Local Iteration for Blended Composite Laminate Panel Structure Optimization Subproblems
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Abstract
Composite panel structure optimization is commonly decomposed into panel optimization subproblems. Previous work applied a guide based design approach to the problem for a structure where the local loads were assumed to be fixed for each panel throughout the design process. This paper examines the application of guide based design to a more realistic representation of the structure where the local loads for each panel are determined through a global level analysis that is coupled with the stacking sequence for every design panel. A small problem is selected for which an exhaustive search of the subproblem design space verifies the optimality of the solution found through the global/local iteration process introduced in this work. The efficient discovery of solutions to these guide based design subproblems creates an opportunity to incorporate the solutions into a global level optimization process. A parallel genetic algorithm is proposed to control global optimization in which evaluating the fitness of each member of the population requires the solution of a guide based design subproblem where parallelism is solely within fitness evaluations. Results are presented for a wingbox design problem and compared with known solutions for the same problem to demonstrate weight reductions in a problem thought to already be near optimally solved.