Multi-objective optimal design of airfoil based on multi-island genetic algorithm
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摘要: 【目的】针对大型水平轴水轮机叶片运行工况复杂的问题，提出一种多目标优化算法。【方法】基于多岛遗传算法建立翼型优化模型，采用CST(Class Shape function Transformation)类形函数变换法对翼型进行参数化拟合，整个优化过程集成于Isight平台，实现自动优化。【结果】采用上述方法，选用NACA63816 、NACA63815、NACA63813翼型作为初始翼型进行多目标优化，利用Fluent转捩模型对得到的翼型进行CFD数值验证，选择翼型攻角5°时的升阻比、升力等为优化目标参数，得到优化后的翼型升力系数分别增大了20%/15%/14%，升阻比增大了28%/16%/14%。【结论】数值验证表明，优化后的翼型在多个工况点下的升阻比均高于同厚度原始翼型，在具有良好的水动力动性能的同时还提高了叶片的结构强度，相比于传统的翼型更适用于大型潮流能水平轴水轮机。Abstract: [Objectives] A multi-objective optimization algorithm is proposed for the problem of complex operating conditions of large horizontal axis hydraulic turbine blades. [Methods] An airfoil optimization model is established based on the multi-island genetic algorithm, and the airfoil is parametrically fitted using the CST function method, and the whole optizisation process is integrated in the Isight platform to achieve automatic optizisation..[Results] Using the above method, NACA63816, NACA63815 and NACA63813 airfoils were selected as the initial airfoils for multi-objective optizisation, and the CFD numerical validation was carried out on the obtained airfoils using the Fluent turning model, and the lift-to-drag ratios and lifting forces at the airfoil angle of attack of 5° were selected as the optizisation objectives, which resulted in the optizised airfoils having a lift coefficient increased by 20%/15%/14%, and lift-to-drag ratios increased by 28%/16%/14%, respectively..[Conclusions] Numerical validation shows that the lift-to-drag ratio of the optimised airfoil is higher than that of the original airfoil with the same thickness under several operating conditions, and the structural strength of the blade is improved while having good aerodynamic performance, which makes it more suitable for large-scale tidal current energy horizontal axis hydraulic turbines compared with conventional airfoils.
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