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Multi-objective optimization of laidback fan-shaped film cooling hole on Turbine Vane Suction Surface

机译:涡轮叶片吸力面上的后备扇形薄膜冷却孔的多目标优化

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摘要

A CFD-based multi-objective optimization is performed for improving the film cooling performance of the laidback fan-shaped holes on the suction surface of a turbine guide vane under a typical blowing ratio of M=1.5. Among the main geometric parameters, the inclination angle (), lateral expansion angle () and forward expansion angle () are selected as the design variables, with respective lower and upper bounds of (25 degrees, 55 degrees), (10 degrees, 20 degrees) and (3 degrees, 15 degrees) in turns. Two independent objective functions that are simultaneously optimized are selected as the spatially-averaged adiabatic film cooling effectiveness (ranging from s/d=0 to s/d=12) and the discharge coefficient. By using a variant of non-dominated sorting genetic algorithm (NSGA-II) coupled with the RBFNN-based surrogate model, the Pareto front of optimal solutions is obtained, providing a variety of options for seeking the maximum spatially-averaged adiabatic film cooling effectiveness, the maximum discharge coefficient, or the compromise of both aspects. The optimized results show that the optimal geometers of (, , ) are (50.3 degrees, 19.5 degrees, 9.8 degrees), (25 degrees, 18.7 degrees, 11.8 degrees) and (27.3 degrees, 19 degrees, 5.1 degrees) for achieving the most maximum film cooling effectiveness, the most maximum discharge coefficient and the compromise of both aspects, respectively. In general, a large lateral expansion angle of the laidback fan-shaped film-cooling hole is necessary in the shape optimization for all of the optimal options. However, with regard to the other design variables, their selections are very distinct following the optimal option. Further, the influence role of optimal fan-shaped geometry on the film cooling performance is illustrated according to the detailed flow and thermal behaviors.
机译:进行基于CFD的多目标优化,以在典型的M = 1.5的吹气比下改善涡轮导向叶片吸力表面上的后备扇形孔的薄膜冷却性能。在主要几何参数中,选择倾斜角(),横向膨胀角()和向前膨胀角()作为设计变量,上下限分别为(25度,55度),(10度,20度)度)和(3度,15度)依次旋转。选择两个同时优化的独立目标函数作为空间平均绝热膜的冷却效率(从s / d = 0到s / d = 12)和放电系数。通过使用非主导排序遗传算法(NSGA-II)的变体与基于RBFNN的替代模型相结合,可以获得最优解的Pareto前沿,为寻求最大的空间平均绝热膜冷却效率提供了多种选择,最大放电系数或两者兼顾。优化结果表明,(,,)的最佳几何尺寸为(50.3度,19.5度,9.8度),(25度,18.7度,11.8度)和(27.3度,19度,5.1度)最大的薄膜冷却效率,最大的最大排放系数和这两个方面的折衷。通常,对于所有最佳选择,在形状优化中都需要较大的后备扇形薄膜冷却孔的横向膨胀角。但是,关于其他设计变量,根据最佳选择,它们的选择非常不同。此外,根据详细的流动和热行为,说明了最佳扇形几何形状对薄膜冷却性能的影响作用。

著录项

  • 来源
    《Heat and mass transfer》 |2019年第4期|1181-1194|共14页
  • 作者单位

    Nanjing Univ Aeronaut & Astronaut, Jiangsu Prov Key Lab Aerosp Power Syst, Coll Energy & Power Engn, Nanjing 210016, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Jiangsu Prov Key Lab Aerosp Power Syst, Coll Energy & Power Engn, Nanjing 210016, Jiangsu, Peoples R China|Collaborat Innovat Ctr Adv Aeroengine, Beijing 100191, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Jiangsu Prov Key Lab Aerosp Power Syst, Coll Energy & Power Engn, Nanjing 210016, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Jiangsu Prov Key Lab Aerosp Power Syst, Coll Energy & Power Engn, Nanjing 210016, Jiangsu, Peoples R China;

  • 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
  • 中图分类
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