Regular Article
Numerical analysis of pressure fluctuation in a multiphase rotodynamic pump with air–water twophase flow
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
^{*} Corresponding author: yuzhiyi@bit.edu.cn
Received:
12
September
2018
Accepted:
12
December
2018
Pressure fluctuation in singlephase pumps has been studied widely, while less attention has been paid to research on multiphase pumps that are commonly used in the petroleum chemical industry. Therefore, this study investigates the pressure fluctuation for a multiphase rotodynamic pump handling air–water twophase flow. Simulations based on the Euler twofluid model were carried out using ANSYS_CFX16.0 at different Inlet Gas Void Fractions (IGVFs) and various flow rate values. Under conditions of IGVF = 0% (pure water) and IGVF = 15%, the accuracy of the numerical method was tested by comparing the experimental data. The results showed that the rotor–stator interaction was still the main generation driver of pressure fluctuation in gas–liquid twophase pumps. However, the fluctuation near the impeller outlet ascribe to the rotor–stator interaction was weakened by the complex gas–liquid flow. For the different IGVF, the variation trend of fluctuation was similar along the streamwise direction. That is, the fluctuation in the impeller increased before decreasing, while in the guide vane it decreased gradually. Also, the fluctuation in the guide vane was generally greater than for the impeller and the maximum amplitude appeared in the vicinity of guide vane inlet.
© W. Zhang et al., published by IFP Energies nouvelles, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Nomenclature
C_{p} : Pressure coefficient, dimensionless
IGVF : Inlet Gas Void Fraction, dimensionless
p_{i} : Static pressure at the pump inlet, Pa
p_{i}(t): Instantaneous static pressure, Pa
p_{o} : Static pressure at the pump outlet, Pa
Q_{d} : Designed flow rate, m^{3}/h
v_{i} : Velocity at pump inlet, m/s
v_{o} : Velocity at pump outlet, m/s
w_{ls} : Water superficial velocity, m/s
Greek symbols
α_{g} : Gas void fraction, dimensionless
η_{t} : Test pump efficiency, dimensionless
σ : Standard deviation of pressure, Pa
Subscripts
1 Introduction
Pressure fluctuation in pumps not only increases vibration of the unit, but can also increase noise levels and cavitation, seriously affecting the safety and stability of the pump (Chen et al., 2016; Hayashi and Kaneko, 2014; Nishida et al., 2016) and is therefore an important aspect for study. For singlephase pumps, many factors cause pressure fluctuation, including cavitation, flow separation, vortex hand, and rotor–stator interaction but the rotor–stator interaction is viewed as the major cause (Miorini et al., 2012). However, for gas–liquid twophase pumps, the flow is usually more disordered due to the phase interaction between the two phases effecting the fluctuation in such pumps (Liu et al., 2017a; Ma et al., 2018; Yu et al., 2014).
Many studies on the pressure fluctuation in singlephase pumps have been conducted or even carried out indepth cavitation analysis in recent years, including for centrifugal pumps (González et al., 2006; Liu et al., 2017b; Majidi, 2005), axial flow pumps (Feng et al., 2016; Shuai et al., 2014; Xie et al., 2018) and mixedflow pumps (Miyabe et al., 2006; Xu et al., 2017; Zhang et al., 2017b). González et al. (2006) investigated pressure fluctuation and radial forces for a centrifugal pump with an impeller to tongue gap variation and obtained the dynamic forces at the blade passing frequency. While Feng et al. (2016) found that the effect of clearance variation on the fluctuation in the impeller is larger than for the guide vane for an axial flow pump, which agreed with Zhang et al.’s (2017a) analysis for a mixedflow pump. Additionally, by exploring the pressure fluctuation in a mixedflow pump under cavitation condition, Xu et al. (2017) found a correlation between the dominant frequency and the variation of the cavitation regions. Thus, despite the type of singlephase pump, the rotor–stator interaction is always seen as the main generation driver of pressure fluctuation. In gas–liquid twophase pumps, due to the phase interaction, flow separation and the mixing of the two phases, the flow may become disordered and the flow pattern variable with the operating conditions of pump. However, research on such pumps has been focused primarily on design optimization (Cao et al., 2005; Kim et al., 2015; Suh et al., 2017) and transport properties (Minemura and Murakami, 1980; Minemura and Uchiyama, 1993). In terms of the pressure fluctuation, although Zhang et al. (2017c) and Tan and Zhang (2018) made a preliminary analysis, the relationship between the fluctuation and IGVF as well as the effect of flow rate was not discussed.
With the technological development of Computational Fluid Dynamics (CFD), CFD simulation has become a primary tool to investigate the internal flow in multiphase pumps (Caridad and Kenyery, 2004; Pineda et al., 2016). Also, the Euler twofluid model has been applied more widely in the related simulation because of its higher calculation precision than other twophase models such as mixture model and drift flow model, among others (Suh et al., 2018, Zhang et al., 2018a). In this model, each medium has its own governing equations, that is, each medium has its own velocity field but share the same pressure field and the phase interaction between the two phases is considered (Lane et al., 2005; Zhang et al., 2018b; Yan et al., 2017; Yu et al., 2015). Based on the Euler twofluid model, the biphasic characterization of a centrifugal pump was investigated by Caridad et al. (2008), and they showed that an increase in bubble diameter will be detrimental to the pump head. While based on the Euler twofluid model and a developed mechanistic model, Zhu and Zhang (2016) predicted the insitu GVF in an electrical submersible pump impeller and obtained that with the increase of bubble diameter and the decrease of gas density and rotation speed, the insitu GVF increased.
On the whole, few studies on the pressure fluctuation in multiphase pumps have been carried out, thus the main cause of pressure fluctuation and its change rules in such pumps need further exploration. In this study, an experimental system of the multiphase pump handling air–water twophase flow was described firstly; secondly, the reliability of the numerical methods was discussed in terms of turbulence models, structured mesh, steady and unsteady simulations; then the unsteady simulations based on the Euler twofluid model were carried out using ANSYS_CFX16.0 at IGVF = 15%. In addition, because of the complexity of the operation conditions, the multiphase pumps may operate at different Inlet Gas Void Fractions (IGVFs) and various flow rates. Therefore, the influences of IGVF and flow rate were investigated. The objective of this research is to obtain the mechanism of fluctuation and determine the change rules.
2 Experimental system of the multiphase pump
2.1 Experimental design
An experimental system diagram of the gas–liquid twophase pump is shown in Figure 1. To ensure the safety of experiment and the reusability of equipment, as well as to observe the bubble diameter and the internal flow in the pump more conveniently, air and water were therefore selected. Meanwhile, before entry into the multiphase pump, they were mixed evenly in a mixer to provide a bubbly flow in the inlet pipe. The central perforated tube is the most important component of the mixer. The gas breaks and mixes uniformly with the liquid in the central perforated tube and the bubble size is adjusted by the openings in it. The mixer, multiphase pump, and water tank are labelled 4, 5, and 1 respectively in Figure 1. A schematic diagram of the test system has been present as Figure 2 to provide a better understanding of the real diagram. In addition, to observe the internal flow of the multiphase pump, the casing of impeller and guide vane was made from Plexiglas and the maximum pressure available on it is 0.6 MPa, as shown in Figure 3.
Fig. 1 Experimental system diagram of the multiphase pump. 1. Tank; 2. Rotameter; 3. Turbine flowmeter; 4. Mixer; 5. Multiphase rotodynamic pump; 6. Electric motor; 7, 8. Pressure gauges; 9. Collecting system; 10. Highspeed camera and lighting. 
Fig. 2 Schematic diagram of the test system. 
Fig. 3 Experimental pump model. 
The test pump head is obtained by equations (1)–(3), where β is the mass fraction of gas; p_{i} and p_{o} are the pressure at inlet and outlet of the pump respectively measured by the pressure gauge with an accuracy of ±0.25%; v_{i} and v_{o} are the velocities at the pump inlet and outlet respectively. The velocities of air and water are calculated based on the flow rates, which are measured by the rotameter and the turbine flowmeter respectively, with an accuracy grade of ±0.5%:(1) (2) (3)
The test pump efficiency is computed by equations (4)–(5), where Q denotes the total void flow rate of the two phases; P is the shaft power of the pump and is measured by a torque power meter with an accuracy of ±0.2%. In addition, according to the calculation method used in the Zhang et al. (2015), the measurement error of pump head and efficiency can be determined to be about 0.8%:(4) (5)here, the density ρ is the mixture density defined by:(6)
2.2 Parameter specifications
The multiphase pump in this study includes four components, i.e. the inlet and outlet pipes, impeller, and guide vane. Its designed rotational speed n is 2950 r/min; designed flow rate Q_{d} is 50 m^{3}/h; and designed head H_{d} is 15 m. The lengths of the inlet and outlet pipes are 300 mm and 400 mm, respectively. The number of blades of the impeller and guide vane is four and eleven respectively and other design parameter specifications for the impeller and guide vane passages are shown in Figure 4.
Fig. 4 Parameter specifications for the impeller and guide vane passages. 
3 Numerical methods
3.1 Governing equations
Twofluid model was adopted in this study to predict the internal flow of the multiphase pump. Furthermore, the drag model considered to be the most important phase interaction model was modified using the secondary development technology of ANSYS_CFX16.0, which has been introduced in the published literature (Zhang et al., 2019). In addition, the basic governing equations for incompressible flow in the multiphase rotodynamic pump have been detailed in previous studies (Yan et al., 2017; Yu et al., 2015; Zhang et al., 2017c). Significantly, as a result of a lack of an indepth understanding of the internal flow mechanisms in gas–liquid twophase pumps, no one turbulence model has been applied widely and accurately to predict the complex flows in such pumps (Franke, 2009).
Usually, twoequation turbulence models, such as standard kε (Ding et al., 2011; Kocaaslan et al., 2017), Renormalization Group (RNG) kε (Qu et al., 2016; Tan et al., 2014), kω (Feng et al., 2010; Menter, 1994), and Shear Stress Transport (SST) kω (Kim et al., 2015; Stel et al., 2015; Yan et al., 2017; Yu et al., 2015; Zhang et al., 2017c), have been used as they have a better compromise in terms of numerical effort and computational accuracy. Here, the SST kω model is a blending model between the kω model near the wall and the kε model in the outer region. Therefore, the SST kω model can account for the transport of the turbulent shear stress and give a highly accurate prediction of flow separation under adverse pressure gradients (Zhang, 2000).
The values of numerical efficiency and head at these four turbulence models along with the experimental results are listed in Table 1. It shows that the results for the standard kε model are furthest from the experiment, which may ascribe to the inaccurate ε equation, especially for the flow with large strain rate. In fact, this is also why Yakhot et al. (1992) developed the RNG kε model. From Table 1, although the results for the RNG kε and SST kω models are close to the experimental results, the SST kω model was chosen for the present study as a result of the complex gas–liquid flow and the existence of adverse pressure gradient in the multiphase pump.
Comparison of the efficiency and head between simulation and experiment (Q = Q_{d}).
3.2 Structured mesh
Figure 5 shows the threedimensional numerical pump model with a full flow passage and the structured mesh adopted for each component. In order to ensure the mesh qualities of the impeller and guide vane, an Automatic Topology and Meshing (ATM) optimized topology was applied in ANSYS TurboGrid (SAS IP, Inc., 2013). This topology type creates highquality meshes by adjusting the global size factor as well as the distribution parameters in the hub and shroud layers. The meshes for the impeller and guide vane, as well as the partial enlarged view, are shown in Figure 6.
Fig. 5 Computational pump model. 
Fig. 6 Meshes for the (a) impeller and (b) guide vane. 
The pump head and efficiency are compared with four mesh numbers under pure water conditions (Q = 49.3 m^{3}/h) to efficiently utilize the computer resources and to improve the computational efficiency as shown in Figure 7. This shows that the differences in head and efficiency are smaller between 3.68 million and 4.82 million mesh numbers, thus the total mesh number of 3.68 million was adopted finally.
Fig. 7 Values of efficiency and head at different mesh numbers. 
The detailed mesh information for the impeller and guide vane, such as elements, nodes, orthogonality, expansion factors, Aspect ratios, and y+ is extracted and listed in Table 2. The orthogonality angle range is 0°–90° with larger values indicating better orthogonality. Expansion involves the ratio of the maximum to minimum distance between the control volume node and the control volume boundaries with an acceptable range of 1–20 (SAS IP, Inc, 2013). Aspect ratio relates to the ratio of the maximum to minimum integration point surface areas in all elements adjacent to a node with an acceptable range of 1–100 (SAS IP, Inc, 2013). The y+ value is a nondimensional parameter representing the distance from the wall to the first node away from the wall (SAS IP, Inc, 2013). Thus, according to the analysis shown in Table 2, it can be concluded that the mesh qualities in this study can meet the requirements of unsteady simulation.
Detailed mesh information for the impeller and guide vane.
3.3 Simulations and validations
3.3.1 Steady simulation
Because of its computational efficiency and acceptable computational accuracy for steady simulation, the external characteristics of pumps, such as efficiency and head, are predicted by steady simulation (Kim et al., 2015; Tan et al., 2014; Zhang et al., 2014). To verify the reliability of the numerical methods adopted in this study, the inlet of computational domain was set as total mass flow rate and corresponding void fraction of the medium; the diameter of gas bubble in twophase flow was given 0.4 mm according to the experimental value; while at the outlet, the static pressure was specified. The model used for the tip clearance of the rotor is General Connection interface model, which is a powerful way to connect regions together. In terms of the numerical solution, a frozenstator method was given for the rotor–stator interfaces and the second order upwind scheme was used to solve the terms of advection and turbulence numerics. The total iterative step was set as 1000 and the RMS residual was set as 1 × 10^{−4}. Based on ANSYS_CFX16.0 code, the steady simulations for a gas–liquid twophase pump with a full flow passage were carried out at conditions of pure water and four IGVFs, and compared with the experimental data, as shown in Figures 8 and 9.
Fig. 8 Performance curves of efficiency and head for simulation and experiment at IGVF = 0%. 
Fig. 9 Values of head for simulation and experiment at different IGVFs (Q = Q_{d}). 
As shown in Figure 8, the numerical efficiency and head at pure water conditions are in good agreement with the experimental results, especially the relative errors of efficiency and head which are only 0.94% and 2.97% at the nominal flow rate, respectively. While, as can be seen in Figure 9, the numerical heads at these four IGVF conditions have small errors compared to the experimental results, that is, errors of 3.00%, 2.07%, 3.30%, and 1.57% for IGVFs of 3%, 9%, 15%, and 21%, respectively. Therefore, it can be concluded that the numerical methods applied in the present study are reliable.
3.3.2 Unsteady simulation
To get the convergence results more readily, the steady results were taken as the initial values of the unsteady simulations. The method for rotor–stator interfaces was modified to “transient rotor–stator method”, and it truly reflects the transient effect and gives highly accurate predictions for the flow between rotor and stator.
To explore the pressure fluctuation in the impeller and guide vane passage, eight monitoring points denoted as R1C–R4C, S1C–S4C were evenly arranged along the flow direction and located at midheight in the radial direction, as shown in Figure 10. Meanwhile, at the unsteady simulation stage, the timescale plays a very important role in determining the numerical results and the computational speed. Therefore, at pure water design conditions, two time steps were analyzed – first Δt_{1} = 1.69 × 10^{−4} s and then Δt_{2} = 1.13 × 10^{−4} s, corresponding to the time for the impeller rotation of 3° and 2° respectively, as presented in Table 3 and Figure 11. There is little difference in both the external characteristics of the pump (efficiency and head) and the pressure variation of monitoring points R4C, S1C, S4C at these two time steps. However, the efficiency and head of the pump in unsteady simulation are a bit larger than the steady results shown in Figure 7. This is because the unsteady simulation results given in Table 3 are extracted at a certain time, rather than the average values in the stable period. Compared to the singlephase flow, the flow with two phases is usually more disordered due to the phase interaction as well as the separation and the mixing. Therefore, Δt_{2} = 1.13 × 10^{−4} s was chosen for the unsteady simulation at different IGVFs. The total time was set as 0.203 s, namely, the time that the impeller rotates 10 cycles.
Fig. 10 Locations of monitoring points in the impeller and guide vane passages. 
Fig. 11 Time domain characteristics of monitoring points R4C, S1C, S4C at two time steps. 
Values of efficiency and head of the pump at two time steps (Q = Q_{d}).
4 Results and discussion
4.1 Pressure fluctuation at condition of IGVF = 15%
Under conditions of IGVF = 15% and Q = Q_{d}, the time domain characteristics of all points during one cycle are shown in Figure 12. The pressure fluctuations of points R1C–R4C in the impeller are smaller than that of points S1C–S4C in the guide vane. Also, an obvious cyclical fluctuation occurs for the points R2C–R3C and points S1C–S4C, that is, there are eleven and four peaks and valleys respectively during one cycle which corresponds to the number of blades of guide vane and impeller, respectively.
Fig. 12 Time domain characteristics of points (a) R1C–R4C and (b) S1C–S4C at IGVF = 15% and Q = Q_{d}. 
Using the Fast Fourier Transform (FFT) method, the frequency domain characteristics of points R1C–R4C, S1C–S4C are obtained, as shown in Figure 13. Along the streamwise direction, the fluctuation in the impeller increases firstly and then decreases, while there is a gradual decrease for the fluctuation in the guide vane and the maximum fluctuation amplitude for all points appears near the guide vane inlet (point S1C). The fluctuation near the rotor–stator interaction region, that is, from the impeller outlet to guide vane inlet regions is relatively large and the rotor–stator interaction region is usually taken as the main reason for the pressure fluctuation in single phase pumps. However, as can be seen in Figure 13, the fluctuation of points R4C located near the impeller outlet is relatively small, which should go hand in hand with the gas–liquid twophase flow therein. As there is a difference in density between the gas and liquid phases, the gas phase will gather at the outlet of the impeller (Fig. 14a) and form a gas vortex in the corresponding regions (Fig. 14b), which have been described in detail previously (Zhang et al., 2018b). Therefore, it can be drawn that the complex gas–liquid twophase flow will weaken the pressure fluctuation in the vicinity of the impeller outlet that has been attributed to the rotor–stator interaction.
Fig. 13 Frequency domain characteristics of points (a) R1C–R4C and (b) S1C–S4C (IGVF = 15%, Q = Q_{d}). 
Fig. 14 Field characteristics for the blade to blade of the impeller and guide vane (IGVF = 15%, Q = Q_{d}, span = 0.5). (a) Distribution of gas void fraction, (b) distribution of gas streamlines. 
It can be also seen from Figure 13 that, aside from the dominant frequency, there are more chaotic frequencies for the points in the impeller. This is associated with the complex gas–liquid twophase flow caused by the rotation of the impeller. Additionally, the fluctuation in impeller was generally less than that in the guide vane, which shows that the rotor–stator interaction has a greater effect on the fluctuation in guide vane at IGVF = 15%.
4.2 Influence of Inlet Gas Void Fractions (IGVFs)
The information about the dominant frequency of monitoring points at different IGVF conditions are listed in Table 4, where, fn is the rotating frequency of impeller with a computed value of about 49 Hz based on the rotational speed of the pump. Overall, the dominant frequencies of all points are 11fn and 4fn respectively which corresponds to the blade numbers of guide vane and impeller. Therefore, it can be illustrated that the rotor–stator interaction is still responsible of the pressure fluctuation in the multiphase rotodynamic pump handling gas–liquid twophase flow. The rotor–stator interaction is the interactions between the cyclical rotating impeller and the stationary guide vane. The forces acting on the impeller blades will change periodically when each blade rotates through one guide vane spacing.
Information about the dominant frequency of points at different IGVFs (Q = Q_{d}).
From Table 4, the dominant frequency for the points in the impeller includes 0.5fn except 11fn, which is believed to relate to the flow separation and the vortex shedding frequency in the corresponding area (Ni et al., 2018; Xu et al., 2017; Zhang et al., 2017b). The point R1C is located at the impeller inlet and is subjected to a weaker rotor–stator interaction, thus the fluctuation caused by vortex separation will play a leading role at some conditions. However, where IGVF = 21%, besides point R1C, the dominant frequency of point R4C is also 0.5fn which is related to the accumulated gas in the impeller outlet and that increases significantly at IGVF = 21%. This then results in a turbulent gas–liquid flow, which can be verified by the distributions of water superficial velocity and gas void fraction, as shown in Figures 15 and 16c, respectively.
Fig. 15 Distribution of water superficial velocity in the impeller at IGVF = 21% (span = 0.5). 
Fig. 16 Distribution of GVF in impeller and guide vane at different IGVFs (span = 0.5, Q = Q_{d}). (a) IGVF = 3%, (b) IGVF = 9%, (c) IGVF = 21%. 
Table 5 lists the fluctuation coefficients of points where the fluctuation coefficient C_{p} is defined as follows:(7) (8)where H_{d} is the designed pump head; ρ_{l} is the density of water; and p_{i}(t) and represent the values of the instantaneous and average pressure, respectively.
Pressure fluctuation coefficients of points at different IGVFs (%, Q = Q_{d}).
From Table 5, the variation trend of fluctuation is similar at different IGVFs along the streamwise direction, that is, (1) the fluctuation in the impeller increases firstly and then decreases, while it decreases gradually in the guide vane; (2) the fluctuation in the guide vane is greater than that in the impeller and the maximum fluctuation amplitude for all points appears near the inlet of the guide vane (point S1C); (3) on the whole, the fluctuation of point R4C in the vicinity of impeller outlet is relatively small among all eight points. The characteristics of the frequency domains for points R4C and S1C are shown in Figure 17. It can be seen that with the increase of IGVF, the influence of frequencies (except the dominant frequency) increases and more chaotic frequencies appear. This is closely related to the increase of the accumulated gas as the IGVF increases, shown in Figure 17. The accumulated gas will block the passage and the flow will be more disordered.
Fig. 17 Frequency domain characteristics of points (a) R4C and (b) S1C at different IGVFs (Q = Q_{d}). 
Further, as the IGVF increases, the fluctuation of the corresponding points shown in Table 5 overall first increases before decreasing, which illustrates that as the IGVF increases within limits, a more disordered flow and enhanced gas–liquid phase interaction will occur, and resulting in greater pressure fluctuation. However, when the IGVF is outside of the limit, the degree of gas accumulation will be clearly enhanced and thus the gas mass forms, as shown in Figure 16c, thus decreasing the collision probabilities between the gas–liquid molecules. According to the research of Konno et al. (2001), part of the energy released from the molecular collision may be absorbed by the gas mass, thus leading to the decrease of pressure fluctuation.
4.3 Influence of flow rates
Figure 18 shows the pressure fluctuation of points at different flow rates (0.75Q_{d}, Q_{d}, 1.25Q_{d}) and an IGVF of 15%. Overall, the fluctuation in the impeller along the streamwise direction first increases and then decreases at Q = Q_{d}, and increases gradually under 0.75Q_{d} and 1.25Q_{d} conditions, while the fluctuation in the guide vane decreases gradually at these three flow rates. Furthermore, the influence of flow rate on the fluctuation is not consistent in the vicinity of the interaction region (points R3C, R4C, S1C, S2C). For points S1C, S2C, the fluctuations generally decrease with increasing flow rate due to the entrainment capacity of the liquid which is enhanced as the flow rate increases, thus decreasing the degree of the accumulation of gas and the flow separation between the gas–liquid phases. But for points R3C, R4C, due to the inconsistency between the inflow angle and the blade angle at offdesign condition, the fluctuations at conditions of Q = 0.75Q_{d} and Q = 1.25Q_{d} are greater than the condition of Q = Q_{d}. The same phenomenon can be observed at the trailing edge of the guide vane (points S3C, S4C), this can also be attributed to the offdesign effect at the guide vane inlet. However, a strong flow separation occurs at the trailing edge of the guide vane (shown in Fig. 19), thus the impact of the effect is weak and the difference of fluctuation at the three flow rates is relatively small.
Fig. 18 Fluctuation coefficient of points at different flow rates (IGVF = 15%). 
Fig. 19 Distributions of GVF and gas streamlines in guide vane at different flow rates (IGVF = 15%, span = 0.5). (a) Q = 0.75Q_{d}, (b) Q = Q_{d}, (c) Q = 1.25Q_{d}. 
The analysis shown in Figure 18 also shows that the fluctuation in the guide vane is greater than for the impeller at these three flow rates and the greatest degree of fluctuation occurs at point S1C. Therefore, the characteristics of the time and frequency domains for point S1C were analyzed and are shown in Figure 20. Four peaks and valleys occur in one cycle and the dominant frequency and second dominant frequency are 4fn and 8fn respectively, which corresponds to the blade number of the impeller or its integer multiple.
Fig. 20 Characteristics of (a) time and (b) frequency domains for point S1C at different flow rates (IGVF = 15%). 
Figure 20a shows that the phenomenon of the second peak and valley occurs at Q = 1.25Q_{d}, marked with a red circle, which is attributed to the rotor–stator interaction. That is, the pressure wave generated by the rotation of the impeller propagates along the flow direction and then generates the refraction and the reflection after colliding with the pressure surface of the guide vane blades. Therefore, the gas–liquid twophase flow near the pressure surface (PS) at the inlet of the guide vane will be more disordered, as shown in Figure 19c, and the accumulation of gas and the flow separation occur therein.
5 Conclusion
The purpose of this study was to investigate the main reason for the generation of pressure fluctuation, as well as their change rules, in a multiphase rotodynamic pump handling air–water twophase flow, which will help in the optimization design for such pumps. Based on the Euler twofluid model, the pressure fluctuations in the impeller and guide vane passages were analyzed at different IGVFs and various flow rates. The main conclusions were:
Along streamwise flow direction, the fluctuation in the impeller first increases and then decreases at different IGVFs, while it decreases gradually for that in the guide vane. Also, the complex gas–liquid flow in the vicinity of the impeller outlet weakens the fluctuation therein. Additionally, as IGVF increases, the fluctuation of the corresponding points overall first increases and then decreases.
When the IGVF is 15%, along the streamwise direction, the fluctuation in the impeller overall first increases and then decreases at Q = Q_{d}, and increases gradually under 0.75Q_{d} and 1.25Q_{d} conditions, while the fluctuation in the guide vane decreases gradually at these three flow rates. Also, the phenomenon of the second peak and valley for point SIC located near the inlet of the guide vane is seen when Q = 1.25Q_{d}.
Overall, the dominant frequency of points are respectively 11fn and 4fn, corresponding to the number of blades of the guide vane and impeller. This illustrates that the rotor–stator interaction can still be considered the main reason for the generation of fluctuation in gas–liquid twophase pumps. Furthermore, the effect of rotor–stator interaction on the fluctuation in the guide vane is greater than for the impeller and the maximum fluctuation amplitude appears in the vicinity of the guide vane inlet (point S1C).
Acknowledgments
This study was supported by the National Natural Science Foundation of China (grant number 51579006), the Basic Research Foundation of Beijing Institute of Technology (grant number 20150342012).
References
 Cao S.L., Peng G.Y., Yu Z.Y. (2005) Hydrodynamic design of rotodynamic pump impeller for multiphase pumping by combined approach of inverse design and CFD analysis, J. Fluids Eng. 127, 330–338. [Google Scholar]
 Caridad J., Kenyery F. (2004) CFD analysis of electric submersible pumps (ESP) handling twophase mixtures, J. Energy Resour. 126, 99–104. [CrossRef] [Google Scholar]
 Caridad J., Asuaje M., Kenyery F., Tremante A., Aguillon O. (2008) Characterization of a centrifugal pump impeller under twophase flow conditions, J. Pet. Sci. Eng. 63, 18–22. [Google Scholar]
 Chen E., et al. (2016) Numerical investigation on vibration and noise induced by unsteady flow in an axialflow pump, J. Mech. Sci. Technol. 30, 5397–5404. [CrossRef] [Google Scholar]
 Ding H., Visser F.C., Jiang Y., Furmanczyk M. (2011) Demonstration and validation of a 3D CFD simulation tool predicting pump performance and cavitation for industrial applications, J. Fluids Eng. 133, 1–13. [Google Scholar]
 Feng J.J., Benra F.K., Dohmen H.J. (2010) Application of different turbulence models in unsteady flow simulations of a radial diffuser pump, Forsch. Ingenieurwes. 74, 123–133. [CrossRef] [Google Scholar]
 Feng J.J., Luo X., Guo P., Wu G. (2016) Influence of tip clearance on pressure fluctuations in an axial flow pump, J. Mech. Sci. Technol. 30, 1603–1610. [CrossRef] [Google Scholar]
 Franke M. (2009) Aspects of numerical simulation of turbomachinery flowsEingeladener Vortrag am Institut für Technische und Angewandte Mechanik der TU Warschau, SAS IP Inc., Polen. [Google Scholar]
 González J., Parrondo J., Santolaria C., Blanco E. (2006) Steady and unsteady radial forces for a centrifugal pump with impeller to tongue gap variation, J. Fluids Eng. 128, 454–462. [Google Scholar]
 Hayashi I., Kaneko S. (2014) Pressure pulsations in piping system excited by a centrifugal turbomachinery taking the damping characteristics into consideration, J. Fluids Struct. 45, 216–234. [Google Scholar]
 Kim J.H., et al. (2015) Improvement of hydrodynamic performance of a multiphase pump using design of experiment techniques, J. Fluids Eng. 137, 1–15. [Google Scholar]
 Kocaaslan O., Ozgoren M., Babayigit O., Aksoy M.H. (2017) Numerical investigation of the effect of number of blades on centrifugal pump performance, American Institute of Physics Conference Series 1863, 1–4. [Google Scholar]
 Konno A., Kato H., Yamaguchi H., Maeda M. (2001) On the collapsing behavior of cavitation bubble clusters, JSME Int. J. 45, 631–637. [CrossRef] [Google Scholar]
 Lane G.L., Schwarz M.P., Evans G.M. (2005) Numerical modelling of gasliquid flow in stirred tanks, Chem. Eng. Sci. 60, 2203–2214. [Google Scholar]
 Liu X.B., Hu Q.Y., Shi G.T., Zeng Y.Z., Wang H.Y. (2017a) Research on transient dynamic characteristics of threestage axialflow multiphase pumps influenced by gas volume fractions, Adv. Mech. Eng. 9, 1–10. [Google Scholar]
 Liu Y., Tan L., Liu M., Hao Y., Xu Y. (2017b) Influence of prewhirl angle and axial distance on energy performance and pressure fluctuation for a centrifugal pump with inlet guide vanes, Energies 10, 1–14. [Google Scholar]
 Ma Y., Ni Y., Zhang H., Zhou S., Deng H. (2018) Influence of valve’s lag characteristic on pressure pulsation and performance of reciprocating multiphase pump, J. Pet. Sci. Eng. 164, 584–594. [Google Scholar]
 Majidi K. (2005) Numerical study of unsteady flow in a centrifugal pump, J. Turbomach. 127, 805–814. [Google Scholar]
 Menter F.R. (1994) 2equation eddyviscosity turbulence models for engineering applications, AIAA J. 32, 1598–1605. [Google Scholar]
 Minemura K., Murakami M. (1980) A theoreticalstudy on air bubble motion in a centrifugal pump impeller, J. Fluids Eng. 102, 446–455. [Google Scholar]
 Minemura K., Uchiyama T. (1993) 3dimensional calculation of airwater 2phase flow in centrifugal pump impeller based on a bubbly flow model, J. Fluids Eng. 115, 766–771. [Google Scholar]
 Miorini R.L., Wu H., Katz J. (2012) The internal structure of the tip leakage vortex within the rotor of an axial waterjet pump, J. Turbomach. 134, 403–419. [Google Scholar]
 Miyabe M., Maeda H., Umeki I., Jittani Y. (2006) Unstable headflow characteristic generation mechanism of a low specific speed mixed flow pump, J. Therm. Sci. 15, 115–120. [CrossRef] [Google Scholar]
 Ni Y., Zhu R., Zhang X., Pan Z. (2018) Numerical investigation on radial impeller induced vortex rope in draft tube under partial load conditions, J. Mech. Sci. Technol. 32, 157–165. [CrossRef] [Google Scholar]
 Nishida M., et al. (2016) Longterm durability test of axialflow ventricular assist device under pulsatile flow, J. Artif. Organs 20, 1–8. [Google Scholar]
 Pineda H., et al. (2016) Phase distribution analysis in an Electrical Submersible Pump (ESP) inlet handling waterair twophase flow using Computational Fluid Dynamics (CFD), J. Pet. Sci. Eng. 139, 49–61. [Google Scholar]
 Qu W.S., Tan L., Cao S.L., Wang Y.C., Xu Y. (2016) Numerical investigation of clocking effect on a centrifugal pump with inlet guide vanes, Eng. Comput. 33, 465–481. [Google Scholar]
 SAS IP, Inc (2013) ANSYS TurboGrid Users Guide, Release 15.0, Pittsburgh, PA, USA. [Google Scholar]
 Shuai Z.J., Li W.Y., Zhang X.Y., Jiang C.X., Li F.C. (2014) Numerical study on the characteristics of pressure fluctuations in an axialFlow water pump, Adv. Mech. Eng. 2, 1–7. [Google Scholar]
 Stel H., Sirino T., Ponce F.J., Chiva S., Morales R.E.M. (2015) Numerical investigation of the flow in a multistage electric submersible pump, J. Pet. Sci. Eng. 136, 41–54. [Google Scholar]
 Suh J.W., et al. (2017) Multiobjective optimization of the hydrodynamic performance of the second stage of a multiphase pump, Energies 10, 1–21. [Google Scholar]
 Suh J.W., et al. (2018) Development of numerical EulerianEulerian models for simulating multiphase pumps, J. Pet. Sci. Eng. 162, 588–601. [Google Scholar]
 Tan L., Zhu B.S., Cao S.L., Wang Y.C., Wang B.B. (2014) Influence of prewhirl regulation by inlet guide vanes on cavitation performance of a centrifugal pump, Energies 7, 1050–1065. [Google Scholar]
 Tan L., Zhang J.S. (2018) Energy performance and pressure fluctuation of a multiphase pump with different gas volume fractions, Energies 11, 1–14. [Google Scholar]
 Xie C., et al. (2018) Numerical calculation of axialflow pump’s pressure fluctuation and model test analysis, Adv. Mech. Eng. 10, 1–13. [Google Scholar]
 Xu Y., Tan L., Liu Y., Cao S. (2017) Pressure fluctuation and flow pattern of a mixedflow pump with different blade tip clearances under cavitation condition, Adv. Mech. Eng. 9, 1–12. [Google Scholar]
 Yakhot V., Orszag S.A., Thangam S., Gatski T.B., Speziale C.G. (1992) Development of turbulence models for shear Flows by a double expansion technique, Phys. Fluids AFluid Dyn. 4, 1510–1520. [CrossRef] [MathSciNet] [Google Scholar]
 Yan D., Kovacevic A., Tang Q., Rane S., Zhang W.H. (2017) Numerical modelling of twinscrew pumps based on computational fluid dynamics, Proc. Inst. Mech. Eng., Part C: J. Mach. Eng. Sci. 231, 4617–4634. [CrossRef] [Google Scholar]
 Yu Z.Y., Zhu B.S., Cao S.L., Liu Y. (2014) Effect of virtual mass force on the mixed transport process in a multiphase rotodynamic pump, Adv. Mech. Eng. 2, 1–7. [Google Scholar]
 Yu Z.Y., Zhu B.S., Cao S.L. (2015) Interphase force analysis for airwater bubbly flow in a multiphase rotodynamic pump, Eng. Comput. 32, 2166–2180. [Google Scholar]
 Zhang K.W. (2000) Theory of fluid machinery, Vol. 1, China Machine Press, Beijing, China. [Google Scholar]
 Zhang Y., Zhang J., Zhu H., Cai S. (2014) 3D blade hydraulic design method of the rotodynamic multiphase pump impeller and performance research, Adv. Mech. Eng. 1, 1–10. [Google Scholar]
 Zhang J., Cai S., Zhu H., Zhang Y. (2015) Experimental investigation of the flow at the entrance of a rotodynamic multiphase pump by visualization, J. Pet. Sci. Eng. 126, 254–261. [Google Scholar]
 Zhang W., Yu Z., Zhu B. (2017a) Influence of tip clearance on pressure fluctuation in low specific speed mixedflow pump passage, Energies 10, 1–16. [Google Scholar]
 Zhang W., Zhu B., Yu Z., Yang C. (2017b) Numerical study of pressure fluctuation in the whole flow passage of a low specific speed mixedflow pump, Adv. Mech. Eng. 9, 1–11. [Google Scholar]
 Zhang W.W., Yu Z.Y., Zhu B.S. (2017c) Numerical study of pressure fluctuation in a gasliquid twophase mixedflow pump, Energies 10, 1–14. [Google Scholar]
 Zhang W.W., Yu Z.Y., Li Y.J. (2018a) Analysis of flow and phase interaction characteristics in a gasliquid twophase pump, Oil Gas Sci. Technol.  Rev. IFP Energies nouvelles 73, 69. [CrossRef] [Google Scholar]
 Zhang W.W., Yu Z.Y., Zahid M.N., Li Y.J. (2018b) Study of the gas distribution in a multiphase rotodynamic pump based on interphase force analysis, Energies 11, 1–16. [Google Scholar]
 Zhang W.W., Yu Z.Y., Li Y.J. (2019) Application of a nonuniform bubble model in a multiphase rotodynamic pump, J. Pet. Sci. Eng. 173, 1316–1322. [Google Scholar]
 Zhu J.J., Zhang H.Q. (2016) Mechanistic modeling and numerical simulation of insitu gas void fraction inside ESP impeller, J. Nat. Gas Sci. Eng. 36, 144–154. [Google Scholar]
All Tables
Comparison of the efficiency and head between simulation and experiment (Q = Q_{d}).
Information about the dominant frequency of points at different IGVFs (Q = Q_{d}).
All Figures
Fig. 1 Experimental system diagram of the multiphase pump. 1. Tank; 2. Rotameter; 3. Turbine flowmeter; 4. Mixer; 5. Multiphase rotodynamic pump; 6. Electric motor; 7, 8. Pressure gauges; 9. Collecting system; 10. Highspeed camera and lighting. 

In the text 
Fig. 2 Schematic diagram of the test system. 

In the text 
Fig. 3 Experimental pump model. 

In the text 
Fig. 4 Parameter specifications for the impeller and guide vane passages. 

In the text 
Fig. 5 Computational pump model. 

In the text 
Fig. 6 Meshes for the (a) impeller and (b) guide vane. 

In the text 
Fig. 7 Values of efficiency and head at different mesh numbers. 

In the text 
Fig. 8 Performance curves of efficiency and head for simulation and experiment at IGVF = 0%. 

In the text 
Fig. 9 Values of head for simulation and experiment at different IGVFs (Q = Q_{d}). 

In the text 
Fig. 10 Locations of monitoring points in the impeller and guide vane passages. 

In the text 
Fig. 11 Time domain characteristics of monitoring points R4C, S1C, S4C at two time steps. 

In the text 
Fig. 12 Time domain characteristics of points (a) R1C–R4C and (b) S1C–S4C at IGVF = 15% and Q = Q_{d}. 

In the text 
Fig. 13 Frequency domain characteristics of points (a) R1C–R4C and (b) S1C–S4C (IGVF = 15%, Q = Q_{d}). 

In the text 
Fig. 14 Field characteristics for the blade to blade of the impeller and guide vane (IGVF = 15%, Q = Q_{d}, span = 0.5). (a) Distribution of gas void fraction, (b) distribution of gas streamlines. 

In the text 
Fig. 15 Distribution of water superficial velocity in the impeller at IGVF = 21% (span = 0.5). 

In the text 
Fig. 16 Distribution of GVF in impeller and guide vane at different IGVFs (span = 0.5, Q = Q_{d}). (a) IGVF = 3%, (b) IGVF = 9%, (c) IGVF = 21%. 

In the text 
Fig. 17 Frequency domain characteristics of points (a) R4C and (b) S1C at different IGVFs (Q = Q_{d}). 

In the text 
Fig. 18 Fluctuation coefficient of points at different flow rates (IGVF = 15%). 

In the text 
Fig. 19 Distributions of GVF and gas streamlines in guide vane at different flow rates (IGVF = 15%, span = 0.5). (a) Q = 0.75Q_{d}, (b) Q = Q_{d}, (c) Q = 1.25Q_{d}. 

In the text 
Fig. 20 Characteristics of (a) time and (b) frequency domains for point S1C at different flow rates (IGVF = 15%). 

In the text 