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Optimal design of two-dimensional wings in ground effect using multi-objective genetic algorithm

机译:基于多目标遗传算法的地基二维机翼优化设计

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The shape optimization of the 2-dimensional wing in ground effect (WIG) has been performed by the integration of CFD (computational fluid dynamics) and MOGA (multi-objective genetic algorithm). Because of the trade-off between the aerodynamic forces and the height stability, it is difficult to satisfy the design requirements of efficiency and stability at the same time. In this study, the lift coefficient, the lift-drag ratio and the static height stability are chosen as the objective functions to obtain the optimal wing profiles of a WIG craft. An NACA0015 airfoil is used for the baseline model; the aerodynamic characteristics of the base model are compared with that of the optimal solutions. The profile of the airfoil is constructed by four Bezier curves with fourteen control points resulting in the eighteen coordinates, which are adopted as the design variables. The optimal solutions of the multi-objective optimization are not unique but a set of the non-dominated optima: the Pareto frontiers or a Pareto set. As the results of the multi-objective optimization, the forty Pareto optima, which include high-lift, high-efficiency, and more stable airfoils on the edge of the 3-dimensional objective space, are obtained at thirty evolutions of the generation.
机译:二维机翼地面效应(WIG)的形状优化是通过CFD(计算流体动力学)和MOGA(多目标遗传算法)的集成完成的。由于在空气动力和高度稳定性之间进行折衷,因此难以同时满足效率和稳定性的设计要求。在这项研究中,选择升力系数,升阻比和静态高度稳定性作为目标函数,以获得WIG飞机的最佳机翼轮廓。基准模型使用NACA0015机翼;将基本模型的空气动力学特性与最优解进行比较。机翼轮廓由四个Bezier曲线和十四个控制点构成,形成十八个坐标,这些坐标被用作设计变量。多目标优化的最优解不是唯一的,而是一组非支配的最优:帕累托边界或帕累托集合。作为多目标优化的结果,在生成的30个演化过程中获得了40个帕累托最优值,其中包括3维目标空间边缘上的高升力,高效和更稳定的翼型。

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