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Winglet multi-objective shape optimization

机译:小波多目标形状优化

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A series of multi-objective winglet shape optimizations are performed to find the Pareto front between the wing aerodynamic drag and the wing structural weight for a wing equipped with a winglet. The paper discusses the addition of winglets to existing aircraft designs. The outer shape of the wing is therefore fixed but the internal structure and associated weight are adjusted based on the change of spanwise loading (magnitude and distribution) due to the addition of the winglet. In order to estimate the aerodynamic and structural characteristics of a non-planar wing, a quasi-three-dimensional aerodynamic solver is integrated with a quasi-analytical weight estimation method inside an optimization framework. Using those tools, the aerodynamic drag and the structural weight of a wing equipped with various winglets are estimated with a high level of accuracy. A multi-objective genetic algorithm is used to determine the Pareto front for two objective functions: minimum wing drag and minimum wing weight. In order to find the best winglet shape among the winglets on the Pareto front, three figures of merit are used: the aircraft Maximum Takeoff Weight (MTOW), the aircraft fuel weight and the aircraft Direct Operating Cost (DOC). The optimization results showed that about 3.8% reduction in fuel weight and about 29M$ reduction in 15 years DOC of a Boeing 747 type aircraft can be achieved by using winglets.
机译:进行了一系列多目标小翼形状优化,以找到配备有小翼的机翼的空气动力学阻力和机翼结构重量之间的帕累托锋线。本文讨论了在现有飞机设计中添加小翼的方法。因此,机翼的外形是固定的,但是由于增加了小翼,因此基于翼展方向载荷(大小和分布)的变化来调整内部结构和相关的重量。为了估算非平面机翼的空气动力学和结构特性,在优化框架内将准三维空气动力学求解器与拟分析重量估算方法集成在一起。使用这些工具,可以高度精确地估算配备有各种小翼的机翼的气动阻力和结构重量。多目标遗传算法用于确定两个目标函数的帕累托锋:最小机翼阻力和最小机翼重量。为了在Pareto正面的小翼中找到最佳的小翼形状,使用了三个品质因数:飞机最大起飞重量(MTOW),飞机燃油重量和飞机直接运营成本(DOC)。优化结果显示,通过使用小翼,波音747型飞机的燃油重量可减少约3.8%,DOC在15年内可减少约29M $。

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