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Shape Optimization of NREL S809 Airfoil for Wind Turbine Blades Using a Multiobjective Genetic Algorithm

机译:利用多目标遗传算法形状优化风力涡轮机叶片的NREL S809翼型

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The goal of this paper is to employ a multiobjective genetic algorithm (MOGA) to optimize the shape of a well-known wind turbine airfoil S809 to improve its lift and drag characteristics, in particular to achieve two objectives, that is, to increase its lift and its lift to drag ratio. The commercially available software FLUENT is employed to calculate the flow field on an adaptive structured mesh using the Reynolds-Averaged Navier-Stokes (RANS) equations in conjunction with a two-equationk-ωSST turbulence model. The results show significant improvement in both lift coefficient and lift to drag ratio of the optimized airfoil compared to the original S809 airfoil. In addition, MOGA results are in close agreement with those obtained by the adjoint-based optimization technique.
机译:本文的目的是采用多目标遗传算法(MOGA)来优化众所周知的风力涡轮机翼型S809的形状,以改善其提升和拖曳特性,特别是实现两个目标,即增加其升力它提升到拖动比率。商业上可获得的软件流畅,用于使用reynolds平均的Navier-Stokes(RANS)方程配合与双均衡k-ωsst湍流模型一起计算自适应结构网格上的流场。结果显示出升力系数和升力与原始S809翼型相比,升力系数和升力与优化翼型的比率的升力。此外,MOGA结果与基于伴随的优化技术获得的人密切一致。

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