摘要
旋流式竖井溢洪道因具有很多优点而被许多工程采用,为了对该类溢洪道的设计运行防护提供更多有益的参考,需要对旋流式竖井溢洪道水力特性作更深入的研究。基于物理模型试验方法研究了折流角变化下的涡室脉动压强幅值特性和频谱特性。研究结果表明:涡室脉压强度随折流角增大而增大,脉压强度与能量耗散密切相关;脉动压强概率密度基本符合正态分布,但不服从标准正态分布。偏态系数与折流角的相关性较弱,峰态系数随折流角增大总趋势是减小的,但脉动幅值范围增大;脉动压强优势频率随折流角增大其频率范围有所拓宽并逐渐向高频转移,脉动能量主要由高频大尺度涡漩决定。
The rotary flow shaft spillways are widely used in many projects because of their many advantages.In order to provide more references for the design,operation and protecting of this kind of spillways,the hydraulic characteristics of the shaft spillways are needed to be investigated further more.Mainly based on the physical model experiment,the amplitude of the flow pulsating pressures and its frequency spectrum characteristics in the vortex chamber of the vertical shaft spillways with different baffle angles are studied.The experimental and the analytic results show that the flow fluctuating pressure intensity in the vortex chamber increases with the increase in the baffle angle,and the fluctuating pressure intensity is closely related to flow energy dissipation.The probability density of the flow fluctuating pressure conforms basically to normal distribution,but it is not the standard normal distribution.The relationship of the skewness coefficient to the baffle angle is weak.The kurtosis coefficient decreases with the increase in the baffle angle,but the range of the amplitude for the kurtosis coefficient increases.With the increase in the baffle angle,the dominant frequency range of the fluctuating pressure widens and gradually shifts to high frequency.The pulse energy of flow is mainly determined by the large-scale vortex with high frequency.
作者
苟超
杨红宣
沈春颖
赵国安
马江霞
GOU Chao;YANG Hong-xuan;SHEN Chun-ying;ZHAO Guo-an;MA Jiang-xia(School of Electric Power Engineering,Kunming University of Science and Technology,Kunming 650000,China)
出处
《中国农村水利水电》
北大核心
2022年第7期214-220,共7页
China Rural Water and Hydropower
基金
国家自然科学基金项目(52069009)
云南省教育厅科学研究基金项目(2020J0056)。
关键词
竖井溢洪道
折流坎
涡室
脉压强度
概率密度
物理模型试验
shaft spillway
baffle side wall
vortex chamber
fluctuating pressure strength
probability density
physical modelling experiment