Study On The Theory Of Flood Discharging Atomization And It's Mathematic Model In Hydropower Station

Many researches have been carried out on the hydraulics jump atomization mathematical model (HJAMM) and overflow atomization mathematical model (OFAMM), which can be summarized into three parts in this dissertation.In the first part, the establishment of HJAMM and the prediction of influence scope of atomization were involved.Firstly, an equation of the source flux of HJA was derived from dimensional analysis based on the mechanism analysis of HJA. Under the condition of linear atomization source and arbitrary wind direction, the diffusion of water fog was studied by using of Gauss diffusion equation, in which the topographical effect was considered by valley mode. With the consideration of the fog-rain self-shift, coagulation, condensation and evaporation of fog drop, the distributions of water fog density, temperature, relative humidity and rainfall intensity in the field of atomization source downstream were obtained. Then the feedback analysis of the atomization for Wantang hydropower station was performed, through which some parameters for HJAMM were determined. Fore more the availability of HJAMM was verified based on the prototype observed data of atomization for Gezhouba Hydropower Station No.2 water release gate. At last, the prediction of atomization influence for Xiangjiaba Hydropower Station was conducted by HJAMM. The water fog density, temperature, relative humidity and the rainfall intensity and their influence range were determined.In the second part, the establishment of OFAMM and the prediction of influence scope of atomization, which includes jet motion, droplet random splash and spray diffusion were involved. Firstly, the differential equation of jet movement was established with the consideration of jet diffusion and aeration and worked out with Runge-Kutta method. The collision of two aerated jets was studied. A new mathematical model of droplet random splash was proposed, and the corresponding differential equation was set up and worked out by Runge-Kutta and Monte-Carlo method. Meanwhile, the rainfall intensity was determined. The differential equation of spray diffusion under random condition was studied and the expressions of spray density and rainfall intensity were derived from the two-dimension steady flow diffusion equation. Then the feedback analysis of atomization for Manwan and Lijiaxia Hydropower Station was carried out, through which some parameters in OFAMM were determined. Fore more the availability of OFAMM was verified based on the prototype observed data of atomization for Wujiangdu and Ertan Hydropower Station. At last, the prediction of atomization influence scope for Longtan, Laxiwa and Nuozadu Hydropower Station was made by OFAMM, through which the storm and drizzle intensity and their influence scope were determined separately. In the third part, the establishment of the Back-Propagation Neural Network model for OFA and the prediction of influence scope of atomization were involved.Firstly, Back-Propagation Neural Network models for the length and width of storm range and drizzle range for OFA were established separately. Then the prototype observed data and calculated data for Manwan, LijiaXia, Ertan and Dongjiang Hydropower Station were employed as sample to train the above-established Back-Propagation Network Model. At last, the prediction of atomization influence scope for Laxiwa Hydropower Station was made, the storm and drizzle ranges were determined by the Back-Propagation Network Neural Model.