Effect of convergence ratio variation on the mechanism of turbine internal losses

The convergence ratio, serving as a critical parameter influencing internal flow in turbines, characterizes the degree of channel convergence in turbine cascades. This study employs a combined approach of experimental investigation and numerical simulation to systematically investigate the flow mechanisms in the turbine end wall region under varying convergence ratios and inlet boundary layer thicknesses. By comparing the secondary flow distribution patterns and loss characteristics of three blade configurations with convergence ratios of 1.525, 1.718, and 1.985 under different inlet boundary layer thickness conditions, the research comprehensively explores the aerodynamic behavior in the turbine end wall region. The findings reveal that the increased convergence ratio intensifies the flow acceleration and pressure reduction within the cascade passage. This consequently reduces the transverse pressure gradient, ultimately leading to weakened secondary flow intensity in the end wall region and diminished spatial influence of the vortex system. Compared to blades with a low convergence ratio, the secondary flow loss in high convergence ratio blades demonstrates a 29.14% reduction. Reducing secondary flow losses plays a crucial role in improving turbine stage efficiency and achieving a more uniform stage loading distribution, which enhances the overall aerodynamic performance of the turbine. This study demonstrates that increased inlet boundary layer thickness induces more pronounced variations in secondary flow intensity within the cascade passage under different convergence ratios. Comparative analysis with loss model predictions reveals that the total loss estimation demonstrates reasonable accuracy.

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Publication Details

Journal
Physics of Fluids
Published
2025-12-01
DOI
https://doi.org/10.1063/5.0302775
Primary Topic
Turbomachinery Performance and Optimization
Type
article
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article

Effect of convergence ratio variation on the mechanism of turbine internal losses

Xingen Lu, Jiahui Xiang, X.F. Zhang, Mai Li et al.
Physics of Fluids
Turbomachinery Performance and Optimization
article

Effect of convergence ratio variation on the mechanism of turbine internal losses

Xingen Lu, Jiahui Xiang, X.F. Zhang, Mai Li, Yanfeng Zhang, Xu Dong
article en

Abstract

The convergence ratio, serving as a critical parameter influencing internal flow in turbines, characterizes the degree of channel convergence in turbine cascades. This study employs a combined approach of experimental investigation and numerical simulation to systematically investigate the flow mechanisms in the turbine end wall region under varying convergence ratios and inlet boundary layer thicknesses. By comparing the secondary flow distribution patterns and loss characteristics of three blade configurations with convergence ratios of 1.525, 1.718, and 1.985 under different inlet boundary layer thickness conditions, the research comprehensively explores the aerodynamic behavior in the turbine end wall region. The findings reveal that the increased convergence ratio intensifies the flow acceleration and pressure reduction within the cascade passage. This consequently reduces the transverse pressure gradient, ultimately leading to weakened secondary flow intensity in the end wall region and diminished spatial influence of the vortex system. Compared to blades with a low convergence ratio, the secondary flow loss in high convergence ratio blades demonstrates a 29.14% reduction. Reducing secondary flow losses plays a crucial role in improving turbine stage efficiency and achieving a more uniform stage loading distribution, which enhances the overall aerodynamic performance of the turbine. This study demonstrates that increased inlet boundary layer thickness induces more pronounced variations in secondary flow intensity within the cascade passage under different convergence ratios. Comparative analysis with loss model predictions reveals that the total loss estimation demonstrates reasonable accuracy.

Physics of FluidsVol. 37(12)
Institute of Engineering Thermophysics (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 50%
Turbomachinery Performance and Optimization
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