直升机桨叶气动外形多目标优化设计

基于自由尾迹方法建立了直升机桨叶空气动力学分析模型,应用人工神经网络方法建立代理模型,采用改进的多目标遗传算法构建了优化框架,对直升机的悬停和大速度前飞状态进行优化.以悬停效率、旋翼等效升阻比及桨叶叶素的最大阻力系数为约束,对两个飞行状态的需用功率进行优化,得到了Pareto最优解集.并以UH-60A直升机的桨叶为算例,对其外形进行优化设计,优化结果表明,提出的桨叶气动外形多目标优化框架是有效可行的. 

Multi-objective optimization for aerodynamic shape of helicopter blade

An aerodynamic model of helicopter rotor was set up based upon free-wake theory and surrogate model was created with artificial neural networks. Based on this aerodynamic model and surrogate model, an optimization framework with improved multi-objective genetic algorithm was used to optimize blade aerodynamic shape in hover and large speed level flight. Rotor shaft powers were minimized in these two flight conditions with constraints of figure of merit, effective lift-drag-ratio and maximum drag coefficient of blade element, and Pareto front was generated. The blade of UH-60A helicopter was taken as an example, and the result indicated that the multi-objective optimization framework of aerodynamic shape was feasible and efficient.