基于多岛遗传算法的翼型多目标优化设计

Multi-objective optimal design of airfoil based on multi-island genetic algorithm

  • 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,采用类形函数变换(CST) 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NACA 63813/63815/63816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14%,15%,20%,升阻比分别增大了14%,16%,28%。
    结论 数值验证结果表明,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 to address the problem of the complex operating conditions of large horizontal axis hydraulic turbine blades.
    Methods An airfoil optimization model is established based on the multi-island genetic algorithm, the airfoil is parametrically fitted using the class shape function transformation (CST) function method, and the whole optimization process is integrated on the Isight platform to achieve automatic optimization.
    Results Using the above method, NACA 63813/63815/63816 airfoils are selected as the initial airfoils for multi-objective optimization, CFD numerical validation is carried out on the obtained airfoils using the Fluent turning model, and the lift-to-drag ratios and lifting forces at the airfoil attack angle of 5° are selected as the optimization objectives, resulting in the optimized airfoils gaining increased lift coefficients of 14%, 15% and 20%, and increased lift-to-drag ratios of 14%, 16% and 28%, respectively.
    Conclusions Numerical validation shows that the lift-to-drag ratios of the optimized airfoil is higher than those of the original airfoils with the same thickness under several operating conditions, and the structural strength of the blade is improved while ensuring good aerodynamic performance, making it more suitable than conventional airfoils for large-scale tidal current energy horizontal axis hydraulic turbines.

     

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