The structural design parameters of a plastic centrifugal pump were calculated and modeled, and flow field simulation analysis of the model was performed using CFD, in the framework of an orthogonal design method (or experiment). The inlet mounting angle β1, outlet mounting angle β2, wrap angle ϕ, and impeller inlet diameter D1 of the pump impeller were the four factors assumed for the application of the orthogonal experiment, using the efficiency and Net Positive Suction Head (NPSH) as evaluation indices. Moreover, taking the maximum efficiency and minimum NPSH of the plastic centrifugal pump as the evaluation factors, the parameters of the pump impeller were re-optimized through the Taguchi algorithm (leading to the following optimal combination: inlet diameter 35 mm, inlet angle 26°, outlet angle 27°, and wrap angle 110°). The minimum NPSH and the maximum efficiency have been found to be 0.957% and 61.5%, respectively.

Plastic centrifugal pumps are widely used because of their strong suction capacity, low working noise, and leak-proof construction. However, the unreasonable structural design of some areas may bring serious harm to pumps’ operation, which hinders the development of plastic centrifugal pumps. At present, the research on the structure of plastic centrifugal pumps in the world is relatively mature. Plastic centrifugal pumps produced by large pump factories generally have the advantages of high rotational speed, small size, and light weight, but their performance indicators still need to be further improved, which requires further improvements to the pump mechanical structure [_{9} (3^{4}) design table, the head and efficiency under the rated flow rate of the nine designed schemes are calculated and processed with the method of range analysis to obtain an optimized model.

In order to optimize the structure and performance of plastic centrifugal pumps, in this paper, CFD was used to analyze the flow field of a plastic centrifugal pump. Through the orthogonal experiment and range analysis, the combination parameters with efficiency and NPSH (net positive suction head) as evaluation indices were obtained. With the maximum efficiency and minimum NPSH as the evaluation indices of the combination parameters, the Taguchi algorithm was used to optimize the parameters of the analysis results; then, the optimal combination parameter with the maximum efficiency and minimum NPSH were obtained.

The basic parameters of the plastic centrifugal pump are as follows: design flow rate Q = 4.5 m^{3}/h, head H = 11 m, rotational speed n = 2840 r/min.

The impeller’s inlet diameter D_{1} can be calculated from

Q–flow rate (m^{3}/s);

n–rotational speed (r/min);

k_{0}–coefficient, which generally ranges from 3.5 to 4.0.

Considering cavitation and efficiency, k_{0} was taken as 4.5.

Then,

d_{h}--the thickness of the shaft hole after opening the keyway (mm); take

Then,

The impeller’s outlet diameter D_{2} can be calculated from

n_{s}--specific speed; n_{s} = 61.

Q--flow rate (m^{3}/s);

n--speed (r/min).

Then,

The impeller’s outlet width b_{2} can be calculated from

n_{s}--specific speed;

Q--flow rate in (m^{3}/s);

n–rotational speed (r/min).

Then,

The impeller’s inlet width b_{1} can be calculated from

H--head (m);

K_{0}--coefficient, which was set to 0.16.

Q--flow rate (m^{3}/s);

η_{v}--volume efficiency, which was set to 0.973;

D_{1}--blade’s inlet diameter (mm).

Then,

Then, the impeller inlet’s width b_{1} was taken as 5 mm.

Mounting angle of blade’s inlet and outlet

It is recommended to set the blade’s inlet angle _{1} to 20°∼25° and the attack angle Δ

The blade’s inlet angle β_{1} was set to 10^{o}∼40^{o}. In order to gradually reduce the blade’s mounting angle on the streamline, β_{1} can be increased to optimize the shape of the impeller flow channel so that a balanced pressure of each impeller blade can be achieved for a favorable operating condition.

_{1} = _{1} + Δ_{1} = 25°. The blade’s outlet angle β_{2} is usually 16°−40°, but here _{2} = 30°

The number of blades Z can be calculated from

D_{2}--the impeller’s outlet diameter (mm);

D_{1}--the impeller’s inlet diameter (mm);

β_{1}, β_{2}–the blade’s inlet and outlet angle.

Then, Z = 5.57; hence, the number of blades Z = 6.

The thickness of blades s can be calculated from

A--coefficient, related to the specific speed and material chosen; set A = 0.025;

D_{2}--impeller’s outer diameter (mm);

Z--the number of blades;

H--the single stage head (m).

The selection of the blade wrap angle

In general. The wrap angle can be taken as 90°∼120°. It should be taken slightly larger when the specific is relative low. Herein, the wrap angle was taken 110°.

The base circle D_{3} tangential to the volute tongue should be slightly larger than the outer diameter D_{2} of the impeller to leave a proper gap between the tongue and the impeller. If the gap is too small, it may cause noise, vibration, and even cavitation in the tongue due to the blockage of liquid flow. Appropriately increasing the gap can lessen the flow blockage around the impeller, reduce noise and vibration, and improve efficiency. Herein, D_{3} was set to 131 mm; the volute’s inlet width b_{3} is usually larger than the impeller’s outlet width b_{2} so that the impeller’s front and rear covers can smoothly send the liquid into the pumping chamber and save part of the disk’s friction power to improve the pump’s efficiency. b_{3} was set to 10.9 mm; the mounting angle of the volute tongue Ψ_{0} should ensure the spiral session to be smoothly connected to the diffuser, and the radial dimension should be minimized as much as possible. Ψ_{0} was set to 15°.

The physical model of the impeller and volute flow channel was established based on the parameters above (see

The boundary condition settings consist of the fluid medium’s basic properties [

Parameter | Value |
---|---|

Fluid medium | Water |

Density | 980 kg/m^{3} |

Reference temperature | 300 K |

Vapor density | 0.2 |

Gas content | 9 × 10^{−5} (mass fraction) |

Saturated vapor pressure | 13.3 KPa |

Bulk modulus | 1 × 10^{9} |

The software defaults to the rotor being rotating and the volute and inlet being stationary. Therefore, the boundary condition settings should include the inlet, the rotor, and the interaction area between the rotor and the volute flow channel (see

As only the k-ε model is suitable for processing the highly-bent streamline flow, it was selected as the calculation model for simulation. The continuity equation of incompressible fluid, the Reynolds time-averaged N-S equation and standard k-ε model were used to simulate the three-dimensional turbulent flow inside the impeller of the plastic centrifugal pump [

The standard k-ε model introduces the turbulent dissipation rate ε [

where,

_{k}

_{b}

_{t}

In

In the numerical calculation process, the fluid flow follows the law of conservation of mass, the law of conservation of momentum, and the law of conservation of energy. In this study, the medium of the model was water, which can be regarded as incompressible viscous fluid. The study was conducted at constant temperature, without considering the effect of temperature changes in the medium; hence the continuity equation and momentum equation is used to obtain solutions:

continuity equation

where,

_{m}—Density of the mixed phase (kg/m^{3});

_{k}—Density of the k phase (kg/m^{3});

_{m}—Average mass;

_{k}—Relative velocity.

Momentum equation

where,

F—Volumetric force (N);

_{m}—Viscosity coefficient of the mixed phase (Pa.s);

_{k}—Viscosity coefficient of the k phase (Pa.s);

_{k}—Volume fraction of the k phase;

_{dr,k}—Drift velocity of the k phase.

With the calculation accuracy and computer’s performance taken into consideration, the total number of mesh units was finally determined to be 181123. The results of mesh independence check are shown in

Number of mesh units | Computational efficiency (%) | Steam volume fraction |
---|---|---|

143597 | 56.7 | 0.955 |

165743 | 57.4 | 0.961 |

181123 | 58.3 | 0.985 |

201674 | 58.3 | 0.987 |

Meshing is the basis of numerical dispersion of flow control equations. The mesh quality directly affects the convergence and accuracy of results. As illustrated in

The volute outlet pressure was monitored. When the outlet pressure was stable, it was considered as converged (see

In the calculation, the SIMPLEC algorithm was used for the pressure-velocity coupling; the momentum equation, turbulent kinetic energy, and dissipative transport equation were in the second-order windward scheme. In the steady calculation, it converged when the total outlet pressure fluctuated steadily; the unsteady calculation converged when the monitoring results displayed a periodically stable distribution.

In the steady calculation, the “Frozen Rotor” model was used for the two interfaces between the inlet pipe and the impeller and between the impeller and the volute; the General Connection model was used for the interface between the volute and the outlet pipe for they were both stationary. In the unsteady calculation, the “Transient Rotor Stator” model was used for the two interfaces between the inlet pipe and the impeller and between the impeller and the volute, which can capture the interaction between the transient and the stationary state of the rotor in relative motion and take the steady calculation results as the initial conditions for the unsteady calculation [

The non-steady time step size Δ

n--impeller’s rotational speed (r/min);

x--the rotational angle of the impeller in each time step.

With the computer memory and data integrity taken into consideration, x = 3°; that is, the impeller rotated once every 120 steps. The rated speed of the centrifugal pump n = 2840 r/min; then Δ^{−5}, and the maximum number of the iterations was 1000.

Convergence can be determined by monitoring the change in a physical quantity (such as pressure, power, etc.) at a specific position. When the physical quantity does not change as the iterations continue, or fluctuate slightly, convergence is reached. As the boundary conditions at the initial stage of the simulation were not unified, they were unstable. Therefore, the monitoring curve in the graph fluctuated in the beginning and stabilized later.

The fluid in the flow channel can only flow under pressure. As shown in

The pressure increased gradually from the impeller’s inlet to its outlet without any noticeable sudden hike. The pressure was equally and reasonably distributed in each flow channel; hence, the design of the impeller was feasible.

Cavitation simulation involves multi-phase integrated simulation of a fluid medium. The bubbles are formed when the partial pressure is less than the vapor pressure of the medium. However, for different pumps and different media, the process is different. Herein, the Pumplinnx software was used to solve the momentum equation and volume ratio equation after the gas and liquid phases were mixed, and the cavitation was simulated.

As shown in

The orthogonal experiment is a design scheme for multi-factor experiments by means of the normalized orthogonal tables in mathematical statistics. The basic steps are as follows:

Selecting experimental objectives and indices

When the selected parameters were applied to the orthogonal experiment, the experimental indices and quality evaluation indices were decided.

Selecting experimental factors and their levels

In the experiment, the factors were represented by English alphabets such as A, B, C. In selecting the factors, the factors that had more significant impacts on the experiment evaluation indices were prioritized. Then, the level of each factor was determined based on relevant information. In order to ensure experimental efficiency, 2 to 4 factor level values were chosen. The spacing of the factor level values was determined based on the existing reference data and professional information with the best effort to make the values at each level within the appropriate range.

Several factors may affect the efficiency and vapor volume fraction in the experiment. It is not feasible to include all of them into the orthogonal experiment. According to the relative theories and practices, the impeller’s inlet angles, outlet angles, wrap angles, and inlet diameters were selected as the four major factors. The selected factors and levels are listed in _{1}, inlet angle β_{1}, outlet angle β_{2}, and warp angle, respectively.

Factor | _{1} |
_{1} |
Wrap angle | |
---|---|---|---|---|

Level | ||||

1 | 18° | 19° | 35 | 100^{o} |

2 | 20° | 21° | 38 | 105^{o} |

3 | 22° | 23° | 41 | 110^{o} |

4 | 24° | 25° | 44 | 115^{o} |

5 | 26° | 27° | 47 | 120^{o} |

The orthogonal table of four factors and five levels was L_{25} (5^{4}). Orthogonal experiment results of the plastic centrifugal pump are presented in

In this experiment, the efficiency and vapor volume fraction were the indices.

By calculating the

With cavitation, that is, vapor volume fraction as the evaluation index, results are displayed in

With efficiency as the evaluation index, results are shown in

Number | _{1} (A) |
_{1} (B) |
_{2} (C) |
Wrap number (D) | Efficiency (%) | Vapor volume fraction |
---|---|---|---|---|---|---|

1 | 35 | 18 | 19 | 100 | 61.3 | 0.978 |

2 | 35 | 20 | 21 | 105 | 61.7 | 0.973 |

3 | 35 | 22 | 23 | 110 | 60.5 | 0.962 |

4 | 35 | 24 | 25 | 115 | 59.1 | 0.988 |

5 | 35 | 26 | 27 | 120 | 61.9 | 0.960 |

6 | 38 | 18 | 21 | 110 | 62.2 | 0.971 |

7 | 38 | 20 | 23 | 115 | 58.3 | 0.961 |

8 | 38 | 22 | 25 | 120 | 60.7 | 0.967 |

9 | 38 | 24 | 27 | 100 | 57.2 | 0.959 |

10 | 38 | 26 | 19 | 105 | 59.5 | 0.980 |

11 | 41 | 18 | 23 | 120 | 59.7 | 0.991 |

12 | 41 | 20 | 25 | 100 | 58.3 | 0.980 |

13 | 41 | 22 | 27 | 105 | 60.0 | 0.961 |

14 | 41 | 24 | 19 | 110 | 58.7 | 0.955 |

15 | 41 | 26 | 21 | 115 | 59.6 | 0.971 |

16 | 44 | 18 | 25 | 105 | 56.1 | 0.963 |

17 | 44 | 20 | 27 | 110 | 57.3 | 0.988 |

18 | 44 | 22 | 19 | 115 | 57.9 | 0.973 |

19 | 44 | 24 | 21 | 120 | 58.6 | 0.969 |

20 | 44 | 26 | 23 | 100 | 58.5 | 0.960 |

21 | 47 | 18 | 27 | 115 | 56.0 | 0.964 |

22 | 47 | 20 | 19 | 120 | 57.3 | 0.977 |

23 | 47 | 22 | 21 | 100 | 57.1 | 0.979 |

24 | 47 | 24 | 23 | 105 | 58.2 | 0.965 |

25 | 47 | 26 | 25 | 110 | 58.6 | 0.955 |

A | B | C | D | |
---|---|---|---|---|

K1 | 4.861 | 4.857 | 4.863 | 4.865 |

K2 | 4.838 | 4.879 | 4.863 | 4.832 |

K3 | 4.858 | 4.842 | 4.839 | 4.831 |

K4 | 4.843 | 4.866 | 4.843 | 4.857 |

K5 | 4.840 | 4.826 | 4.832 | 4.864 |

k1 | 0.9722 | 0.9714 | 0.9726 | 0.9730 |

k2 | 0.9676 | 0.9758 | 0.9726 | 0.9664 |

k3 | 0.9716 | 0.9684 | 0.9678 | 0.9662 |

k4 | 0.9686 | 0.9732 | 0.9686 | 0.9714 |

k5 | 0.9680 | 0.9652 | 0.9664 | 0.9728 |

R | 0.0046 | 0.0106 | 0.0062 | 0.0068 |

Order | 4 | 1 | 3 | 2 |

Analysis of vapor volume fraction

As per _{1}, K_{2}, K_{3}, K_{4}, K_{5} refer to the sum of vapor volume fraction of each factor under the levels of 1, 2, 3, 4, and 5, respectively, while k_{1}, k_{2}, k_{3}, k_{4}, and k_{5} represent the average value of vapor volume fraction of each factor. The range value R reflects the influence of each factor. According to the evaluation index, the optimal combination was A_{2}B_{5}C_{5}D_{3}, wherein the outlet diameter was 38 mm, inlet angle 26°, outlet angle 27°, and wrap angle 110°, and the vapor volume fraction reached its minimum. The optimized process parameters were not available in the existing experiment. The steam mass fraction of this set of data was 0.957, which was verified using Pumplinx simulation software. Comparing the size and location of the vapor volume fraction with the existing 25 sets of experimental results, the vapor volume fraction was close to the minimum value in the experiment, and the cavitation was significantly improved. The experimental results are presented in

By analyzing the results of the orthogonal experiment with the range method, the influence of each factor on each evaluation index was obtained: inlet angle > wrap angle > inlet angle > inlet diameter.

Analysis of efficiency

As per _{1}, K_{2}, K_{3}, K_{4}, K_{5} respectively stand for the sum of the efficiency of each factor under the levels of 1, 2, 3, 4, and 5, while k_{1}, k_{2}, k_{3}, k_{4}, and k_{5} represent the average value of efficiency of each factor. The range value R reflects the vapor volume effects of each factor. According to the evaluation index, the optimal combination was A_{2}B_{5}C_{5}D_{3}, wherein the outlet diameter was 35 mm, inlet angle 26°, outlet angle 21°, and wrap angle 120°; also, the vapor volume fraction reached its maximum. The optimized process parameters were not existing in the existing experiment. The efficiency of the data was 61.4% using Pumplinx simulation software. By comparing the existing 25 groups of experiment results, it can be found that the efficiency was close to the maximum in the experiment. The experimental results are shown in

By analyzing the result of the orthogonal experiment with the range method, the influence trend of each factor on each evaluation index was obtained as inlet diameter > wrap angle > outlet angle > inlet angle.

In light of the influence of pump efficiency and cavitation factors and the efficiency required for the plastic centrifugal pump in this work, the efficiency and cavitation were taken as evaluation indices to inspect the comprehensive performance of the plastic centrifugal pump. The proportion of cavitation was set to be 30% and the efficiency 70%.

Comprehensively considering the efficiency of the plastic centrifugal plump and the cavitation, the four structural sizes: the impeller’s inlet diameter, inlet angle, outlet angle, and the wrap angle, were selected as the experimental factors. The factors were set at five levels, and the controllable factors and their levels were determined as shown in

The orthogonal internal table L_{25} (5^{4}) was selected as shown in

Calculation of SN ratios

A | B | C | D | |
---|---|---|---|---|

K_{1} |
304.5 | 295.3 | 294.7 | 292.4 |

K_{2} |
297.9 | 292.9 | 299.2 | 295.5 |

K_{3} |
296.3 | 296.2 | 295.2 | 297.3 |

K_{4} |
288.4 | 291.8 | 292.8 | 290.9 |

K_{5} |
287.2 | 298.1 | 292.4 | 298.2 |

k_{1} |
60.9 | 59.06 | 58.94 | 58.48 |

k_{2} |
59.58 | 58.58 | 59.84 | 59.1 |

k_{3} |
59.26 | 59.24 | 59.04 | 59.46 |

k_{4} |
57.68 | 58.36 | 58.56 | 58.18 |

k_{5} |
57.44 | 59.62 | 58.48 | 59.64 |

R | 3.46 | 1.26 | 1.36 | 1.46 |

Order | 1 | 4 | 3 | 2 |

The NPSH index in the software was the volume fraction of steam. In practice, a smaller or even zero value is better. In the Taguchi method, it is called the smaller-the-better type characteristic Y_{i}, and its SN ratio can be calculated from

Higher efficiency is better. In the Taguchi method, it is called the larger-the-better characteristic Y_{j}, and its SN ratio can be calculated from

Synthetic signal to noise ratio SN:

The result of SNR calculations is presented in

Number | _{1} (A) |
_{1} (B) |
_{2} (C) |
Wrap angle (D) |
---|---|---|---|---|

1 | 35 | 18 | 19 | 100 |

2 | 35 | 20 | 21 | 105 |

3 | 35 | 22 | 23 | 110 |

4 | 35 | 24 | 25 | 115 |

5 | 35 | 26 | 27 | 120 |

6 | 38 | 18 | 21 | 110 |

7 | 38 | 20 | 23 | 115 |

8 | 38 | 22 | 25 | 120 |

9 | 38 | 24 | 27 | 100 |

10 | 38 | 26 | 19 | 105 |

11 | 41 | 18 | 23 | 120 |

12 | 41 | 20 | 25 | 100 |

13 | 41 | 22 | 27 | 105 |

14 | 41 | 24 | 19 | 110 |

15 | 41 | 26 | 21 | 115 |

16 | 44 | 18 | 25 | 105 |

17 | 44 | 20 | 27 | 110 |

18 | 44 | 22 | 19 | 115 |

19 | 44 | 24 | 21 | 120 |

20 | 44 | 26 | 23 | 100 |

21 | 47 | 18 | 27 | 115 |

22 | 47 | 20 | 19 | 120 |

23 | 47 | 22 | 21 | 100 |

24 | 47 | 24 | 23 | 105 |

25 | 47 | 26 | 25 | 110 |

According to direct analysis of _{1}B_{5}C_{5}D_{5}.

Statistics of the internal table [

①The sum of the SN ratios T can be calculated from:

Then,

②Under each factor lever, the sums of the SN ratios _{i}, the mean values of the SN ratios _{i}, and the ranges of each column _{i} were calculated, wherein

③The sum of squared total fluctuations of the SN ratios S_{T} can be calculated from

④The sums of squared total fluctuations of the SN ratios for each factor S_{1}, S_{2}, S_{3}, and S_{4} [

Number | _{s} (A) |
_{1} (B) |
_{2} (C) |
Wrap angle (D) | SNR _{i} |
SNR _{j} |
Synthetic SNR |
---|---|---|---|---|---|---|---|

1 | 35 | 18 | 19 | 100 | −4.25 | 0.193 | −2.9171 |

2 | 35 | 20 | 21 | 105 | −4.19 | 0.238 | −2.8616 |

3 | 35 | 22 | 23 | 110 | −4.36 | 0.336 | −2.9512 |

4 | 35 | 24 | 25 | 115 | −4.57 | 0.104 | −3.1678 |

5 | 35 | 26 | 27 | 120 | −4.16 | 0.355 | −2.8055 |

6 | 38 | 18 | 21 | 110 | −4.12 | 0.026 | −2.8762 |

7 | 38 | 20 | 23 | 115 | −4.69 | 0.346 | −3.1792 |

8 | 38 | 22 | 25 | 120 | −4.34 | 0.291 | −2.9507 |

9 | 38 | 24 | 27 | 100 | −4.85 | 0.364 | −3.2858 |

10 | 38 | 26 | 19 | 105 | −4.5 | 0.175 | −3.0975 |

11 | 41 | 18 | 23 | 120 | −4.48 | 0.078 | −3.1126 |

12 | 41 | 20 | 25 | 100 | −4.69 | 0.175 | −3.2305 |

13 | 41 | 22 | 27 | 105 | −4.44 | 0.346 | −3.0042 |

14 | 41 | 24 | 19 | 110 | −4.63 | 0.4 | −3.121 |

15 | 41 | 26 | 21 | 115 | −4.5 | 0.256 | −3.0732 |

16 | 44 | 18 | 25 | 105 | −5.02 | 0.327 | −3.4159 |

17 | 44 | 20 | 27 | 110 | −4.84 | 0.105 | −3.3565 |

18 | 44 | 22 | 19 | 115 | −4.75 | 0.238 | −3.2536 |

19 | 44 | 24 | 21 | 120 | −4.64 | 0.274 | −3.1658 |

20 | 44 | 26 | 23 | 100 | −4.66 | 0.355 | −3.1555 |

21 | 47 | 18 | 27 | 115 | −5.04 | 0.318 | −3.4326 |

22 | 47 | 20 | 19 | 120 | −4.84 | 0.202 | −3.3274 |

23 | 47 | 22 | 21 | 100 | −4.87 | 0.184 | −3.3538 |

24 | 47 | 24 | 23 | 105 | −4.7 | 0.309 | −3.1973 |

25 | 47 | 26 | 25 | 110 | −4.64 | 0.4 | −3.128 |

Then,

Range analysis

As there was no empty column in this experiment [_{3} was taken as the sum of squared error fluctuations S_{e}. Then,

The range analysis is shown in

A | B | C | D | |
---|---|---|---|---|

T1 | −14.7032 | −15.7544 | −15.7166 | −15.9427 |

T2 | −15.3894 | −15.9552 | −15.3306 | −15.5765 |

T3 | −15.5415 | −15.5135 | −15.5958 | −15.4329 |

T4 | −16.3473 | −15.9377 | −15.8929 | −16.1064 |

T5 | −16.4391 | −15.2597 | −15.8846 | −15.362 |

t1 | −2.9106 | −3.1508 | −3.1433 | −3.1885 |

t2 | −3.0788 | −3.191 | −3.0661 | −3.1553 |

t3 | −3.108 | −3.1027 | −3.1191 | −3.0867 |

t4 | −3.2695 | −3.1875 | −3.1786 | −3.2213 |

t5 | −3.2878 | −3.1509 | −3.17 | −3.0724 |

R | 0.3718 | 0.0848 | 0.1176 | 0.1489 |

As per the range analysis of the signal-to-noise ratios, factor A has a significant effect on the quality fluctuation characteristics. Factor A can be considered a stable factor, while factors B, C, and D adjustable factors. For the stable factor, the level of factor A is A_{1}. The vapor volume fraction signal-to-noise ratio η_{j} of factors B, C, and D are listed in

Source | S | f | V | F-value |
---|---|---|---|---|

A | 0.41 | 4 | 0.1025 | 10* |

B | 0.061 | 4 | 0.01525 | 1.14 |

C | 0.041 | 4 | ||

D | 0.071 | 4 | 0.01775 | 1.21 |

(e) | (0.041) | (4) | 0.01025 | |

T | 0.583 | 16 |

Note: * indicates the significance level

As factors B, C, and D have little influence on the quality fluctuation characteristics, it is possible to neglect the efficiency and then adjust them until the vapor volume fraction reaches the minimum. As shown in _{5}C_{5}D_{3}.

Factor | Wrap angle (D) | |||
---|---|---|---|---|

Level | ||||

1 | 0.942 | 1.208 | 1.271 | |

2 | 1.066 | 0.978 | 1.267 | |

3 | 1.395 | 1.424 | 1.395 | |

4 | 1.451 | 1.297 | 1.262 | |

5 | 1.504 | 1.488 | 1.2 |

The optimal combination is A_{1}B_{5}C_{5}D_{3}, which is almost the same as the results from the direct analysis.

The impeller model was set to the following parameters:

Inlet diameter 35 mm, inlet angle 26°, outlet angle 27°, and wrap angle 110°.

After these parameters were imported into pumplinx, the simulation was performed thrice. The results are displayed in

Number | Vapor volume fraction | Efficiency | Vapor volume fraction SN ratio | Efficiency SN ratio | Synthetic SN ratio |
---|---|---|---|---|---|

1 | 0.959 | 61.3% | 0.363 | −4.251 | −2.8668 |

2 | 0.960 | 61.6% | 0.355 | −4.208 | −2.8391 |

3 | 0.957 | 61.5% | 0.382 | −4.222 | −2.8408 |

The synthetic signal-to-noise ratio obtained by the simulation with the optimized parameters was rather close to the synthetic signal-to-noise ratio of the fifth group, suggesting that the optimized parameters were reasonable.

The molding process parameters were optimized by the orthogonal experiment and the Taguchi algorithm, respectively. Results were compared in

It can be seen from

Index | Influencing factor | Combination of structural parameters | Steam volume fraction | Efficiency |
---|---|---|---|---|

Cavitation analysis based on the orthogonal experiment | B > D > C > A | A_{2}B_{5}C_{5}D_{3} |
0.957 | 59.3% |

Efficiency analysis based on the orthogonal experiment | A > D > C > B | A_{1}B_{5}C_{2}D_{5} |
0.934 | 61.4% |

Taguchi algorithm analysis | A > D>C > B | A_{1}B_{5}C_{5}D_{3} |
0.959 | 61.5% |

In this paper, CFD simulations were used to analyze the flow field of a plastic centrifugal pump. Through an orthogonal experiment and range analysis, the optimized parameters were obtained with efficiency and NPSH as the evaluation indices. With the maximum efficiency and minimum NPSH as evaluation indices for combination parameters, the Taguchi algorithm was employed to optimize the parameters of the plastic centrifugal pump to obtain the optimal combination parameters of the maximum efficiency and minimum NPSH.

The structural parameters of the plastic centrifugal pump were calculated, modeled, and the flow field simulation analysis of the model was performed by CFD.

Herein, an orthogonal experiment was designed and performed. Each factor affected the efficiency of the plastic centrifugal pump orderly by the impeller’s inlet diameter D_{1}, wrap angle φ, outlet angle β_{2}, and inlet angles β_{1}. Each factor affected the cavitation of the centrifugal pump orderly by the impeller’s inlet angle β1, wrap angle φ, outlet angle β_{2}, and inlet diameter D_{1}.

With the efficiency and cavitation of the plastic centrifugal pump as the evaluation indices, with the help of the Taguchi algorithm, the parameters of the impeller of the plastic centrifugal pump were optimized. The optimal combination parameters with the maximum efficiency and minimum cavitation were obtained as follows: The impeller’s inlet diameter D_{1} was 35 mm, inlet angle β_{1} 26°, outlet angle was 27°, and wrap angle φ 110°. Then, the efficiency of the plastic centrifugal pump was highest, and cavitation lowest.