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Journal of Flow Visualization and Image Processing
SJR: 0.161 SNIP: 0.312 CiteScore™: 0.1

ISSN Печать: 1065-3090
ISSN Онлайн: 1940-4336

Выпуски:
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Journal of Flow Visualization and Image Processing

DOI: 10.1615/JFlowVisImageProc.2012004130
pages 57-80

VISUALIZATION OF FLOW THROUGH THE TURBINE BLADE CASCADE WITH OPTIMIZED STREAMWISE BOUNDARY LAYER FENCE

K. N. Kumar
Thermal Turbomachines Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, India
Mukka Govardhan
Thermal Turbomachines Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Madras Chennai, India

Краткое описание

The present study focuses on the study of critical points formed on the surfaces of a turbine cascade with and without streamwise endwall fences with the help of flow visualization. A fence whose height varies linearly from the leading edge to the trailing edge and is located in the middle of the flow passage produces the least Coefficient of Secondary Kinetic Energy (CSKE) and is the optimum fence. The reduction in CSKE by the optimum fence is 27% compared to the baseline case. The geometry of the fence is new and is reported for the first time. The objective of the fence is to block the passage vortex from crossing the passage and impinging on the suction surface of the blade. A saddle point is formed near the leading edge on the endwall for baseline and optimum fence cases. There is nearly no change in saddle point location. Distribution of critical points on the endwall near the trailing edge of the blade is symmetrical for the baseline case, while no symmetry exists for the optimum fence case. Based on skin friction line patterns, it is clear that the pressure-side leg of the horseshoe vortex is diverted by the optimum fence, and hence, impinged on the suction surface of the blade with reduced intensity. Skin friction lines on the suction surface show that with application of the optimum fence, the spanwise penetration of the passage vortex is reduced by 33%.


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