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Journal of Applied Fluid Mechanics، جلد ۱۸، شماره ۱، صفحات ۲۲۲-۲۴۰
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عنوان انگلیسی Optimized Reduction in Draft Tube Pressure Pulsation for a Francis Turbine
چکیده انگلیسی مقاله As a core component of hydroelectric power generation, the stable and safe operation of the Francis turbine is very important for the operation of the project. Therefore, attention must be paid to the problem of pressure pulsation in the Francis turbine. In this study, the efficiency, power, and pressure pulsation of the turbine are first compared based on computational fluid dynamics (CFD), combined with numerical simulation and experimental results. It was found that the numerical simulation method was reliable. Therefore, based on the genetic algorithm (GA) and pulsation tracking network (PTN), this article optimizes the draft tube pressure pulsation (DTPP) problem of the Francis turbine and finds that the DTPP is mainly dominated by rotation frequencies (fn) of 0.2, 0.4, 0.6, and 0.8. This research optimized the placement angle of the runner blade’s 0.75span and 1.0span using the genetic algorithm. The PTN method was used to analyze the changes in pressure pulsation signals from the perspectives of the pressure velocity vector, main frequency, pulsation intensity, and phase change. After optimization, the value of β0.75 was reduced from 160.59° to 160.452°, and the value of β1.0 was increased from 160.6° to 161.865°. The pressure pulsation intensity of each working condition was also weakened. Therefore, this research provides a new and effective analysis and optimization method for the pressure pulsation problem in turbine machinery.
کلیدواژه‌های انگلیسی مقاله Francis turbine,Draft tube,Pressure pulsation,Genetic Algorithm,Pulsation tracking
نویسندگان مقاله R. Tao |
College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China

R. Tao |
College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China

نشانی اینترنتی https://www.jafmonline.net/article_2554_78db8d93ed2d4c20ab53be8fdd5b5913.pdf
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