5315 複数目標GAおよび応答曲面法を用いた風力発電用CF/GF複合材ブレードの構造最適化(J17-3 解析・設計の高度化・最適化(3)(設計の高度化),J17 解析・設計の高度化・最適化:解析の高度化)

概要

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Large wind tuebine blade is prospected to be CF/GF hybrid blade made with Carbon Fiber Reinforsced Plastic and Glass Fiber Reinforced Plastic, and structural optimization of the blade is multi-objective optimization problem (MOOP) about weight and cost. The optimum solutions for MOOP are Pareto optimum solutions. In this paper, the MOOP is solved using Multi-Objectibe Genetic Algorithm (MOGA). Meanwhile, blade structure is necessary to satisfy a constraint not to fracture under maximum load. To evaluate the constraint, FEM analysis is used. This cause enormous calculation cost. In this paper, to reduce this, response surface approximating the degree of constraint satisfaction is created. Since Pareto solutions obtained using response surface don't necessarily satisfy the constraint, it should be confirmed whether they satisfy the constraint or not using FEM analysis. If some of the solutions don't satisfy the constraint, whose response data is added in, and the response surface is restructured to improve its accuracy. Repeating restructuring, obtained Pareto solutions will converge to exact Pareto Optima. At this point, in the MOGA Optimization, the accuracy of convergence of solutions is improved using quasi-Pareto Optimum Initial Population to reduce the number of restructuring. As a result, the the number of FEM analysis is reduced to 1400 times.
2006-09-15