Research On Energy Conversion Characteristics And Impeller Optimization Of Pump As Turbine

There is a large number of high-pressure liquid in many industrial processes such as petrochemical, coal chemical industry, seawater desalination industry and so on. Recycling this part of the pressure energy has an important practical significance and economic value. Hydraulic turbine is a kind of device for recovering l iquid pressure energy,and pump as turbine is widely used at present. From the relevant literature and actual production, pump as turbine generally ha s the problem of energy conversion efficiency is not high. This is related to the lack of understanding about the internal energy conversion characteristics of pump as turbine. In order to solve this problem, based on the centrifugal pump as turbine, the external characteristics of the pump as turbine was studied by numerical calculation and experiment, and the accuracy of the numerical calculation method is verified by the experimental results. The energy co nversion characteristics in impeller and volute of the pump as turbine are studied by numerical calculation method, which provides a reference for the fo llowing optimization design. The optimization system of pump as turbin is established based on agent model and intelligent optimization algorithm. On the basis of the above, the optimization of the turbine impeller was carried out. There are three main par ts in this paper as follows:1. Internal energy conversion characteristics of pump as turbineSeveral energy conversion characteristics such as the process of flow energy transfer and conversion within the impeller and volute were studied based on CFD technique, by analyzing the energy features, including the distribution of the shaft power change in different positions of impeller and volute, the input net energy of each region, the power at different parts and the hydraulic loss distribution. Results show that the fluid acting critical region on the impeller lie in the front and middle region, mainly reflecting as pressure acting; the posterior part of the impeller acting on the impeller is relatively small in a small flow rate condition, and in the large flow rate condition this region not only does not acting, but also consumes mechanical energy, and energy conversion efficiency of impeller is low. For the volute, the static pressure decreases along the direction of fluid flow while the dynamic pressure s hows the irregular fluctuation; the static pressure and dynamic pressure change regularly along the fluid flow direction in the shrink tube segment. The volute energy loss mainly o ccur downstream region of the volute throat.2. Establish optimized system of pump as turbineIt provides a reference for the optimized design by studying the internal energy conversion characteristics of the pump as turbine, but in the optimization, it is necessary to establish the specific optimization method. In this paper, doing the optimization of geometrical parameters of hydraulic turbine impeller, the objective function is the hydraulic performance parameters of the hydraulic turbine. However, the flow in the pump as turbine is complex turbulent flow, combined with compl ex geometry flow path and rotating coordinate system lead to the complex implicit relationship between the impeller geometry parameter and its hydraulic performance.Traditional optimized methods are difficult to do the optimization, while genetic mechanism of the intelligent optimization algorithms by imitating nature selection and genetic mechanisms to find the optimal solution of the objective function. It can make the global optimization e ffective in the form of probability and low demand for the optimiz ation problem. Therefore, the paper chooses the genetic algorithm to optimize the turbine geometry. In the process of optimization, the CFD numerical calculation is undoubtedly very time-consuming, so the genetic algorithm-back propagation GA-BP neural network was introduced to replace the CFD numerical calculation which used to get the pe rformance parameters of the turbine in the optimization process. At the result of this, the optimum design method of GA-BP neural network combining genetic algorithm has been formed. Finally, all optimized process is controlled by program so as to establish an optimized system.3. Optimal design impeller of pump as turbineIt found that it has poor matches between the variation law in flow area of the pump as turbine impeller and the internal flow patterns through the analysis of the a xial flow characteristics. So the paper does research on the axial plane projection by optimized method. The design variables1?, 2?, 1R, 2R and3 R can control the impeller shape, the efficiency of the turbine at the optimum operating conditions is used as the objective function, pressure head is the constraint condition. After optimization the turbine performance has been greatly improved.Through the analysis of pump as turbine energy conversion characteristics, we can find that the impeller has the low energy conversion efficiency. In the turbine i mpeller, the blade is the core component of energy conversion, so the blade of the centrifugal pump is not well suited to working in the turbine conditions. In this paper, non-uniform B-spline curves are used to constrain the blade profile, and the control point parameters as the design variables, hydraulic efficiency of the three points near the turbine optimum operating conditions as the objective functions and head values of the three points as the constraint conditions. After optimization, the turbine ef ficiency has been greatly improved, and it satisfies the ini tial set pressure head restraint, which means the energy conversion has been enhanced of blade. Using the above optimized method is feasibility to the blade profile optimization.It is found that within the impeller exist the larger vortex areas, through analysis on flow field of optimized impeller of tur bine. Therefore, by increasing the numbers of blades improve the performance of pump as turbine. By increasing the number of blades can enhance the power capability and efficiency. However, there will be more serious blade crowding phenomenon in the impeller flow impeller, if the number of leaves increase excessive. At the same time, the total surface area of the fluid and blades contact will increase, lead to the fluid friction losses will increase and it is not conducive to the efficiency improvement.The problem can be solved by adding the splitter blades considering the severe blade crowding and wall friction loss caused by too many impeller bl ades.