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Optimization of the Aerodynamic and Aeroacoustic Performance of an Axial-Flow Fan

机译：轴流风机的空气动力学和空气声学性能的优化

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摘要

A multidisciplinary optimization to simultaneously enhance the aerodynamic and aeroacoustic performance of an axial-flow fan was performed. Flow analysis through the axial-flow fan was conducted by solving three-dimensional steady and unsteady Reynolds-averaged Navier-Stokes equations with the shear-stress transport turbulence model. Starting with the results for the unsteady flow, aeroacoustic analysis was performed by solving the Ffowcs Williams-Hawkings equations. A single-objective optimization for high-efficiency design was carried out before the multi-objective optimization. The single-objective optimization was conducted using a weighted average surrogate model with five design variables defining the hub-to-tip ratio, hubcap installation distance, hubcap ratio, and angle distributions at the midspan and blade tip. The objective function (i.e., the efficiency) was evaluated at the design points, sampled by Latin hypercube sampling in the design space, to construct the surrogate model. Then, multi-objective optimization on the basis of the single-objective optimization result was performed to simultaneously improve the efficiency and reduce the sound pressure level through a hybrid multi-objective evolutionary algorithm coupled with a response surface approximation surrogate model with two design variables defining the sweep and lean angles at the blade tip. These objective functions were numerically accessed through the aerodynamic and aeroacoustic analyses. Arbitrary selected optimum designs in the Pareto-optimal solutions yielded increases in efficiency and decreases in the sound pressure level compared to the reference design.
机译：进行了多学科优化，以同时增强轴流风扇的空气动力学和空气声学性能。通过使用切应力传递湍流模型求解三维稳态和非稳态雷诺平均Navier-Stokes方程，进行了轴流风扇的流量分析。从非稳态流动的结果开始，通过求解Ffowcs Williams-Hawkings方程进行了空气声学分析。在进行多目标优化之前，先对高效设计进行了单目标优化。使用加权平均替代模型进行单目标优化，该模型具有五个设计变量，这些变量定义了轮毂与齿尖的比率，轮毂盖的安装距离，轮毂盖的比率以及中跨和叶片尖端的角度分布。在设计点评估目标函数（即效率），并在设计空间中通过拉丁超立方体采样进行采样，以构建替代模型。然后，通过混合多目标进化算法结合具有两个设计变量的响应面近似替代模型，基于单目标优化结果进行多目标优化，以同时提高效率并降低声压级。叶片尖端的后掠角和倾斜角。这些目标函数通过空气动力学和空气声学分析进行了数值访问。与参考设计相比，帕累托最优解决方案中的任意选择的最佳设计可提高效率，并降低声压级。

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  • 来源
    《AIAA Journal》 |2014年第9期|2032-2044|共13页
  • 作者

    Kim Jin-Hyuk; Ovgor Bavuudorj; Cha Kyung-Hun; Kim Joo-Hyung; Lee Seungbae; Kim Kwang-Yong;

  • 作者单位

    Inha Univ, Korea Inst Ind Technol, Inchon 402751, South Korea;

    Inha Univ, Natl Renewable Energy Ctr Mongolia, Inchon 402751, South Korea;

    Inha Univ, Dept Mech Engn, Inchon 402751, South Korea;

    Inha Univ, Dept Mech Engn, Inchon 402751, South Korea;

    Inha Univ, Dept Mech Engn, Inchon 402751, South Korea;

    Inha Univ, Dept Mech Engn, Inchon 402751, South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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