基于遗传算法的无人机层流翼型优化设计

Optimization Design of UAV Laminar Aerofoil Based on Genetic Algorithm

以高空长航时无人机大展弦比机翼的层流翼型为研究对象,在低雷诺数范围内,把遗传算法与N-S方程气动数值解法相结合,依靠计算流体动力学CFD计算技术,对翼型进行气动外形优化设计。在基准翼型的基础上,翼型描述采用了解析函数线性叠加法,个体以解析函数中的变量构成,结合锦标赛选择、均匀交叉,进行了以提高升阻比为目标的优化设计。优化后翼型在低雷诺数条件下的升力系数及升阻比有所提高,这说明了利用遗传算法进行层流翼型气动外形优化的可行性。

The object in this article is a laminar aerofoil, which belongs to a high altitude long endurance UAV with big wing aspect ratio. With the help of advanced technology of computation fluid dynamics （CFD） , joining genetic algorithms with N-S equations, the aerofoil optimization design is conducted at the bound of low Reynolds number. The aerofoil is described by equations of linearity adding ana- lytic function at the base aerofoil, individual is formatted by variables of the equations. Combining with stochastic tournament selection and uniform crossover, the optimized aerofoil at the aim of rising lift-drag ratio is designed, lift-drag ratio and lift coefficient of optimized aerofoil is increase at low Reynolds number. The optimization results illustrate that genetic algorithm is an effectively way for the aerofoil optimization design.