Film cooling performance and optimization of ellipse conical holes on turbine vanes leading edge
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摘要:
采用数值仿真方法对椭圆锥孔在高压涡轮导叶前缘的气膜冷却效率进行了探究,分析对比了椭圆柱孔的两个结构参数流向扩张角和径向扩张角对前缘气膜冷却效率的影响,且分别在流向扩张角为0°~18°和径向扩张角为0°~16°范围内对椭圆锥孔进行了优化。结果表明:流向扩张角为1.4°且径向扩张角为11.1°时的椭圆锥孔表现出最高的气膜冷却效率,其相较于圆柱孔的冷却效率提升了147.5%,且椭圆锥孔的结构参数随气膜冷却效率的变化规律可拟合成四次方函数关系,当径向扩张角很小时,气膜冷却效率随流向扩张角增大,反之,气膜冷却效率基本随流向扩张角增大而减小;当流向扩张角较小时,气膜冷却效率大致随径向扩张角的增大而先增后减,当流向扩张角较大时,气膜冷却效率基本保持不变或呈现一个较小的增幅。
Abstract:Simulations were employed to study the film cooling effectiveness of ellipse conical holes on the leading-edge of turbine vane. The influences of two geometry parameters, forward and lateral expansion angle, on the adiabatic film cooling effectiveness were studied comparatively. And optimization was also conducted within the range of forward and lateral expansion angle, 0°—18° and 0°—16°, respectively. Results showed that the ellipse conical hole with a forward expansion angle of 1.4° and a lateral expansion angle of 11.1° presented the highest film cooling effectiveness, which was 147.5% higher than that of the cylindrical hole. Moreover, the relationship between the two geometry parameters and the film cooling effectiveness can be fitted to quartic function. When lateral expansion angle was low, the film cooling effectiveness increased with forward expansion angle. Otherwise, the film cooling effectiveness decreased with forward expansion angle. Additionally, when forward expansion angle was lower, the film cooling effectiveness increased and then decreased with lateral expansion angle. And the film cooling effectiveness was roughly constant or showed a small increase with lateral expansion angle.
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Key words:
- film cooling effectiveness /
- shaped holes /
- expansion angle /
- turbine vane /
- leading edge
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表 1 回归方程
Table 1. Coefficients in the regression equation
参数 系数 截距 0.039641 δ 0.010705 β 0.009493 δβ − 0.00132 δ2 − 0.00211 β2 − 0.00048 δ2β 0.000041 δβ2 0.000052 δ3 0.000169 β3 0.00003 δ2β2/10−6 −2.57 δ3 β/10−7 1.70 δβ3/10−6 1.53 δ4/10−6 −4.44 β4/10−6 −1.92 表 2 回归方程可靠性验证
Table 2. Reliability verification of the regression equation
δ/(°) β/(°) 真实值 预测值 误差/% 0 0 0.0400 0.0396 −1.00 0 4 0.0712 0.0714 0.28 0 8 0.0913 0.0924 1.20 0 12 0.0976 0.0967 −0.92 0 16 0.0662 0.0664 0.30 4.5 0 0.0585 0.0587 0.34 4.5 4 0.0741 0.0733 −1.08 4.5 8 0.0851 0.0856 0.59 4.5 12 0.0922 0.0922 0 4.5 16 0.0780 0.0780 0 9 0 0.0576 0.0596 3.47 9 4 0.0643 0.0623 −3.11 9 8 0.0678 0.0678 0 9 12 0.0769 0.0754 −1.95 9 16 0.0712 0.0726 1.97 13.5 0 0.0713 0.0693 −2.81 13.5 4 0.0645 0.0658 2.02 13.5 8 0.0662 0.0669 1.06 13.5 12 0.0721 0.0745 3.33 13.5 16 0.0809 0.0786 −2.84 18 0 0.0711 0.0713 0.28 18 4 0.0663 0.0676 1.96 18 8 0.0693 0.0669 −3.46 18 12 0.0738 0.0738 0 18 16 0.0803 0.0811 1.00 -
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