2014 年 62 巻 1 号 p. 1-8
In Super Sonic Transport (SST), thin wing structure is necessary to satisfy the high speed, economic viability and environmental compatibility requirements. Among many structures in thin wing, the lug structure which is between the body and the main wing plays important role. However, it is difficult to design of the lug structure because it is subjected many loads that have uncertainties such as magnitude or direction of loading caused by aeroelastic forces. Robust topology optimization is, therefore, necessary to determine the optimal structural lay out solutions insensitive to loading uncertainties for design of the lug structure. The present paper proposes robust topology optimization using NSGA-IIa algorithm which is one of the most popular in Multi-Objective Evolutionary Algorithms (MOEA) with multiload formulation. In proposed method, Monte Carlo simulations were used to estimate the robustness of topology from Pareto optima obtained with NSGA-IIa. The obtained robust topology solutions are explored by Self-Organizing Map that is an appropriate tool to visualize and explore properties of the high dimension data. Finally, proposed method approach is applied for the lug structure robust topology optimization.