首页> 外文会议>Evolutionary Computation, 2001. Proceedings of the 2001 Congress on >Multi-point optimization using GAs and Nash/Stackelberg games for high lift multi-airfoil design in aerodynamics
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Multi-point optimization using GAs and Nash/Stackelberg games for high lift multi-airfoil design in aerodynamics

机译:使用GA和Nash / Stackelberg游戏进行多点优化以实现空气动力学中的高升力多翼型设计

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This paper presents the discussion and comparison of the different optimization strategies and their associated evolutionary tools for the multi-point design optimization of a multi-element airfoil system during landing and taking off operations of an aircraft. New optimization algorithms based on binary coded genetic algorithms (GAs) coupling with game theory, such as Nash GAs (N-GAs) and Stackelberg GAs (S-GAs), are introduced and implemented to optimize the position of slat and flap of a high lift system operating simultaneous at taking off and landing conditions. A cheap nondifferentiable CFD solver coupling an inviscid panel approach with laminar or turbulent boundary layers and wake is used to solve the flow field around this system. Numerical results are compared with different strategies which demonstrates the flexible capability and robustness of such algorithms for multi-objective and multidisciplinary optimization problems in aerodynamics.
机译:本文介绍和比较了飞机降落和起飞操作过程中多元素机翼系统的多点设计优化的不同优化策略及其相关的进化工具。引入并实现了基于二进制编码遗传算法(GAs)和博弈论的新优化算法,例如Nash GA(N-GAs)和Stackelberg GA(S-GAs),以优化高架板条和襟翼的位置升降机系统在起降条件下同时运行。廉价的不可微分CFD求解器将无粘性面板方法与层流或湍流边界层以及尾流相结合,用于解决该系统周围的流场。将数值结果与不同策略进行了比较,结果表明了这种算法在空气动力学中多目标和多学科优化问题的灵活性和鲁棒性。

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