CAVITATION OPTIMIZATION FOR RESIDUAL HEAT RE- MOVAL PUMP USING ORTHOGONAL EXPERIMENTAL METHOD BASED ON PUMPLINX Tingyun Yin, Shouqi Yuan, Yin Luo, Ji Pei, Wenjie Wang ISROMAC 2016 International Symposium on Transport Phenomena and Dynamics of Rotating Machinery Hawaii, Honolulu April 10-15, 2016 Abstract To improve the performance of the centrifugal pump with a vaned diffuser, the influence of impeller geometric parameters on cavitation of the pump was investigated by Orthogonal Experimental Method (OEM) based on PUMPLINX. inlet diameter D 1, inlet incidence angle Δβ, blade wrap angle φ were selected as the main impeller geometric parameters and the orthogonal experiment of L9(3*3) was done in this study. Three-dimensional steady simulations were conducted to predict the cavitation performance of pump using constant gas mass fraction model with 2 nd order upwind. The experimental results were justified by the variance analysis method. The inner flow of the pump was also analyzed in order to obtain the flow behaviors that can affect the pump performance. The results show that the impeller inlet diameter D1 has the greatest influence on the cavitation performance. The final optimized impeller accomplished better cavitation performance, which can meet the design requirements and the velocity distribution in the optimized impeller is more regular. Keywords PUMPLINX orthogonal experimental method variance analysis cavitation optimization National Research Center of Pumps, Jiangsu University, Zhenjiang, Jiangsu, China *Corresponding author: Yintingyunwt@163.com INTRODUCTION Cavitation is a difficult problem to the development of hydraulic machinery, causing vibration, and noise, and affecting operation reliability of the pump. Residual heat removal pump is one of the key equipment in the millionkilowatt nuclear power plant, and it plays a vital role in the safety of the entire plant. Therefore, as an important characteristic of residual heat removal pump, the cavitation performance is usually studied. Improving the cavitation performance by optimizing the impeller has been successfully achieved in a lot of studies. Xie [1] applied the numerical method to optimize slots on impeller blade near inlet in six groups of hydraulic model. The stimulation results showed that slotted impeller could improve the cavitation performance. Luo [2] analyzed the effects of impeller inlet geometry on centrifugal pump cavitation performance by using CFD. The pump cavitation performance can be significantly improved with new impellers designed by properly extending the blade inlet toward the pump inlet or enlarging the blade inlet angle. Wang [3] redesigned the impeller with different vane wrap angles to study the effect of vane wrap angle on cavitation performance. It turned out that there would be an optimal value for vane wrap angle to obtain the best cavitation performance. Ran [4] et al applied the genetic algorithm to modify the leading edge ellipse ratio and blade thickness on the front 20% meanline. By using CFD simulation, optimization was completed with obvious improvements on the cavitation inception performance. The orthogonal design experiment is one of the most popular and efficient optimization methods to achieve the design objective which has many factors. Yuan [5] et al applied the orthogonal experimental to investigate the main parameters of the splitter blades on the pump performance and found that the splitter blades could make the curve of Q-H more flat and the pump with splitter blades could operate under overload conditions. Yan [6] optimized the cavitation performance of a large-scale axial-flow pump with the orthogonal experimental method and the numerical simulation. The results showed when the flow line of suction surface φ=0.7, the cavitation persistence length can be rapidly decreased and the cavitation volume fraction can be sharply cut. Shen [7] et al applied the orthogonal experimental to optimize the parameters of the complex impeller. Through the test of specimen of the best design scheme, it demonstrated that the excellent selection by using numerical simulation of whole flow field was nonoverload and high efficiency. In this study, computational fluid dynamics (CFD) technology was used to test three factors (impeller inlet diameter D1 inlet incidence angle Δ β blade wrap angle φ) affecting cavitation performance of the residual heat removal pump by Orthogonal Experimental Method (OEM) to study the cavitation characteristics of pump, as well as internal flow instability induced, and to analyze the effects of three factors on the pump hydraulic performance. Besides, the inner flow characteristics of the final optimization were analyzed compared with the original one. And the mechanism of cavitation was further discussed to obtain the optimal parameters combination for pump
design. Schematic map of optimization process as shown in Figure 1. and Technology, whose testing precision is superior to the national grade 1. As shown in the Figure 3, the performance curve was measured by the relevant measurement requirements. The pressure in the inlet and outlet was measured by the pressure sensor, both of whose precision are 0.1%. The flow rates were measured by the LWGY 200A turbine flow rate with 0.5% measurement error. Turbine flowmeter Pressure sensor at the outlet Model pump Motor Pressure sensor at the inlet Figure 1. Schematic Map of Optimization Process 1. GEMOETRY AND EXPERIMENT 1.1 Gemoetry model The 2D model of the radial diffuser pump is shown in Figure 1. The hydraulic components of the pump consist of the impeller, diffuser and volute. To be specific, the impeller is shrouded with 5 twist and backswept blades with the specific speed, ns=3.65nq0.5/h0.75=111.7. The diffuser is shrouded with 7 radial vanes. The annular volute is designed to keep the pump operating safety. The design parameters and the main parameters of the diffuser and the volute will be shown in Table 1. The optimal parameters of the impeller will be presented in next section. Figure 3. the Open Test RIG 2. NUMERICAL SIMULATION 2.1 Mesh generation cavitation model A grid generation method based on binary tree algorithm is used to generate the adaptive Cartesian grid in PUMPLINX. The coarse grids are densified based on the dichotomy method in the high-required geometric precision region by using this technique. The grid will be cut in accordance with the surface of the fluid domain boundary to precisely fit the fluid domain on the boundary. The whole computational domain made up of the inlet, impeller, diffuser and volute consists of 1060291 grids. The details of the mesh are showed in Figure 3. In this paper, three-dimensional steady simulations were conducted to predict the cavitation performance of pump using constant gas mass fraction model with 2nd order upwind. Volute Diffuser Inlet Figure 2. the 2D Model of The Radial Diffuser Pump Table 1. the Main Geometrical and Design Parameters of the Radial Centrifugal Pump Dj/mm D2/mm b2/mm φ/0 Δβ/0 Zi value 270 511 49 120 5.5 5 Diffuser D3/mm D4/mm b3/mm a3/mm α 3 /0 Zd value 515 718 55 84 9.7 7 Volute D5/mm b5/mm Qd/m3 s-1 Hd/m n/r min-1 ns value 840 250 0.253 >71 1490 111.7 1.2 External performance experiment The original model pump was tested in the open test rig in the lab of Research Center of Fluid Machinery Engineering (a) the Meridional Plane
performance characteristics of the residual heat removal pump accurately and the optimization can be achieved by using CFD. Comprised with the design parameters, the head can meet the required, but the net positive suction head required is high for the practical engineering application. In this paper, the parameter optimization of the impeller is analyzed. (b) Self-adapted Grids Figure 4. Grids of Computational Domians 2.2 BOUNDARY CONDITIONS Boundary conditions of the centrifugal pump can be set parametricly, which the inlet pressure, out flow rate, and rotor are needed in PUMPLINX. Table 2 shows main boundary conditions required for PUMPLINX, and the working fluid parameters are showed in Table 3. (a) the Head Curve Table 2. Main Boundary Conditions Parameters Value N 5 n/r min -1 1490 Rotational axis vector (0,0,0) Pin/pa 101325 Qout/m 3 s -1 0.0867 Turbulent model Standard K-Epsilon Table 3. Working Fluid Parameters Parameters Working fluid Dynamic viscosity/pa-s Value Water 1.003e-03 Density/kg m 3 998 Liquid bulk modulus/pa 2.15e+09 Liquid reference pressure/pa 101325 Saturation pressure/pa 3610 2.3 COMPARISON OF PERFORMANCE By using the numerical simulations under 5 different flow rates, the predicted pump performance curve are obtained. To verify the accuracy of the simulation, the original pump, the size of which was scaled to 0.7, was tested in the open test rig. The rotating speed of the pump did not change. The performance of the model pump was obtained. The comparison of the performance between the experimental and the CFD is shown in Figure 5. The numerical results have a good agreement with the experimental results. At the design point, the head and net positive suction head required calculated by the PUMPLINX are 37.82m and 2.95m, respectively. While the experimental head and net positive suction head required are 37.9m and 2.93m. From the 80% to the 120% of the design conditions, the differences in the head are very small and the tendency of head from the numerical simulation is consistent with that of experimental data. It is clear that the numerical simulation can predict the (b) The Net Positive Suction Head Required Curve Figure 5. Comparison of the Pump Performance between the Experiment and CFD 3. ORTHOGONAL ARRAY EXPERIMENT To achieve the best performance characteristics of the radial diffuser pump, the main parameters should be selected carefully and exactly. According to the empirical design of the impeller and studies on cavitation performance ever done, three main impeller geometrical parameters are selected, namely impeller inlet diameter D1, inlet incidence angle Δβ, blade wrap angle φ. The geometry of the diffuser and volute remain the same. Table 4 shows the different parameters of the impeller. Trail No. Table 4. Parameters of the inlet diameter D1(mm) Inlet incidence angle Δβ( 0 ) Blade wrap angle φ (0 ) 1 260 3 110 2 260 5.5 120 3 260 8 130 4 270 3 120 5 270 5.5 130 6 270 8 110 7 280 3 130 8 280 5.5 110 9 280 8 120 4. RESULTS AND DISCUSSION 4.1 ORTHogonal experiment results based on the CFD
The 9 impellers were designed by the software CFturbo 9.0, whose function is fast to export the 3D computational domain of the impeller. Then, the mesh of the 9 impellers is generated with the approximate number of grids with the original pump, and calculated by using the PUMPLINX with the same settings of the original pump. Table 5 shows the predicted head, efficiency and net positive suction head required of the 9 schemes under the design condition. Range analysis method was applied to identify the influence of the main parameters on the objective. The sum values of each level for each factors are defined as Ki, and the average values ki are defined as, the Ki and ki are calculated by the Eq.(1) and (2). N K (1) i i y i, j i 1 1 ki Ki (2) N i Where i is number of level, j is number of factor, yi,j is the value of net positive suction head required, which is corresponding to the factor j in level i. N is the total number of levels. The analysis results for pump net positive suction head required under condition are shown in Table 6. To obtain the low net positive suction head required according to the Δ max-min values, the main parameters effect on the net positive suction head required is A>B>C, namely impeller inlet diameter is the most important factor of net positive suction head required, followed by inlet incidence angle, blade wrap angle. Thus, in this paper, mainly considering the lower net positive suction head required, the final optimal combination of the main parameter for low net positive suction head required is A3, B2 and C3, namely D1=280mm, Δβ=5.5 0, φ=130 0. Trail No. Table 5. Orthogonal Experimental Scheme A B C Head NPSHR Efficiency (m) (m) (%) 1 260 3 110 38.42 2.73 72.02 2 260 5.5 120 38.24 2.68 71.37 3 260 8 130 37.67 2.67 72.46 4 270 3 120 38.03 2.42 71.77 5 270 5.5 130 37.61 2.48 72.47 6 270 8 110 38.01 2.61 71.15 7 280 3 130 37.67 2.42 72.46 8 280 5.5 110 37.69 2.32 70.62 9 280 8 120 37.63 2.61 71.38 3 2.451 2.630 2.523 Δmax-min 0.245 0.318 0.048 Rank 1 2 3 Δ max-min=difference between maximum and the minimum values of the NPSHR 4.2 FINAL OPTIMIZATION According to the best combination of the main parameters (D 1=280mm, Δ β =5.5 0, φ =130 0 ), the optimized impeller is designed and simulated by using the same method. And the predicted performance is compared with the original one, as illustrated in Figure 6. Under the design condition, the net positive suction head required and head of the optimized pump is 2.32m and 72.39%. The net positive suction head required decreases 0.61m, which significantly improves the cavitation performance. Meanwhile, compared with the simulation results of the original impeller, the efficiency of the optimized impeller increases 0.6%, which meets the requirements. Figure 6. Comparison of the Pump Cavitation Performance between the Optimization and Original 4.3 COMPARISON WITH THE INNER FLOW Turbulent kinetic energy is used to describe the turbulent fluctuation. Its value and spatial non-uniformity identify the intensity of fluctuation diffusion and viscous dissipation. The Figure 7 illustrates the distributions of the turbulent kinetic energy. The biggest turbulence kinetic energy occurs at the outlet of the impeller and the inlet of the diffuser, the area of the high values is smaller in the optimal impeller and the optimization has improved the inner flow characteristics. Table6. Range Analysis of Net Positive Suction Head Required Net positive suction head Levels required (A) (B) (C) D1(mm) Δβ( 0 ) φ( 0 ) 1 2.696 2.572 2.554 2 2.503 2.492 2.571 (a) the Turbulence Kinetic Energy Distribution in the Original
Figure 8. Comparison of Vapor Volume Fraction Distribution in the (b) the Turbulence Kinetic Energy Distribution in the Original Figure 7. Comparison of turbulence kinetic energy Net positive suction head required is a very important parameter of the pump performance. There is on accurate calculation method for NPSHR at present except to cavitation experiments. In this paper, numerical simulation of the cavitation experiment had been done by changing the inlet total pressure, and the vapor volume fraction distributions are compared between the optimal impeller and original impeller. Figure 8 shows when the inlet pressure of pump dropped to 32.5kp, the vapor volume fraction of optimal impeller was better than the original impeller, in which serious cavitation occurred, and it is more intuitive to use total volume fraction to do comparison, as shown in Figure 9. From the above numerical simulation results, it can be significantly seen that cavitation is distributed in the back of the blade inlet and the optimal impeller better the cavitation performance. (a) the Vapor Volume Fraction Distribution in the Original (b) the Vapor Volume Fraction Distribution in the Optimal (a) the Total Volume Fraction Distribution in the Original (b) the Total Volume Fraction Distribution in the Optimal Figure 9. Comparison of Total Volume Fraction Distribution in the 5 CONCLUSIONS An L9 (3*3) orthogonal array was designed with the above three factors by using Orthogonal Experimental Method (OEM). The performances of the residual heat removal pump were predicted with PUMPLINX, and the best program for pump cavitation was obtained. In the above numerical simulations, cavitation is distributed in the back of the blade inlet, which meets the actual phenomenon. Under the design condition, the net positive suction head required decreases 0.61m, which significantly improves the cavitation performance. Meanwhile, compared with the simulation results of the original impeller, the efficiency of the optimized impeller increases 0.6%, which meets the requirements. The flow distribution in the optimized impeller is more regular. The area of the high turbulence kinetic energy is smaller in the optimal impeller and the optimization has improved the inner flow characteristics. ACKNOWLEDGMENTS This study is supported by National Science & Technology Pillar Program (Grant NO. 2011BAF14B04), State Key Program of National Natural Science of China (Grant NO. 51239005) and National Natural Science Foundation of China (Grant NO. 51409123). Many thanks are given to the 4Cpump research group.
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