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Research Papers: Flows in Complex Systems

Computational Fluid Dynamics-Based Pump Redesign to Improve Efficiency and Decrease Unsteady Radial Forces

[+] Author and Article Information
Peng Yan

Institute of Process Equipment,
Zhejiang University,
Hangzhou 310027, China
e-mail: yanpeng@zju.edu.cn

Ning Chu

Engineering STI,
Swiss Federal Institute of Technology
in Lausanne,
Lausanne 1015, Switzerland
e-mail: chuning1983@sina.com

Dazhuan Wu

Institute of Process Equipment,
Zhejiang University,
Hangzhou 310027, China
e-mail: wudazhuan@zju.edu.cn

Linlin Cao

Institute of Process Equipment,
Zhejiang University,
Hangzhou 310027, China
e-mail: caolinlin@zju.edu.cn

Shuai Yang

Institute of Process Equipment,
Zhejiang University,
Hangzhou 310027, China
e-mail: 11228024@zju.edu.cn

Peng Wu

Institute of Process Equipment,
Zhejiang University,
Hangzhou 310027, China
e-mail: roc@zju.edu.cn

1Corresponding authors.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received January 6, 2016; final manuscript received July 21, 2016; published online October 10, 2016. Assoc. Editor: Bart van Esch.

J. Fluids Eng 139(1), 011101 (Oct 10, 2016) (11 pages) Paper No: FE-16-1013; doi: 10.1115/1.4034365 History: Received January 06, 2016; Revised July 21, 2016

In this study, a double volute centrifugal pump with relative low efficiency and high vibration is redesigned to improve the efficiency and reduce the unsteady radial forces with the aid of unsteady computational fluid dynamics (CFD) analysis. The concept of entropy generation rate is applied to evaluate the magnitude and distribution of the loss generation in pumps and it is proved to be a useful technique for loss identification and subsequent redesign process. The local Euler head distribution (LEHD) can represent the energy growth from the blade leading edge (LE) to its trailing edge (TE) on constant span stream surface in a viscous flow field, and the LEHD is proposed to evaluate the flow field on constant span stream surfaces from hub to shroud. To investigate the unsteady internal flow of the centrifugal pump, the unsteady Reynolds-Averaged Navier–Stokes equations (URANS) are solved with realizable k–ε turbulence model using the CFD code FLUENT. The impeller is redesigned with the same outlet diameter as the baseline pump. A two-step-form LEHD is recommended to suppress flow separation and secondary flow encountered in the baseline impeller in order to improve the efficiency. The splitter blades are added to improve the hydraulic performance and to reduce unsteady radial forces. The original double volute is substituted by a newly designed single volute one. The hydraulic efficiency of the centrifugal pump based on redesigned impeller with splitter blades and newly designed single volute is about 89.2%, a 3.2% higher than the baseline pump. The pressure fluctuation in the volute is significantly reduced, and the mean and maximum values of unsteady radial force are only 30% and 26.5% of the values for the baseline pump.

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Figures

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Fig. 1

geometry of centrifugal pump: (a) double volute, (b) single volute, (c) baseline impeller, (d) redesigned impeller without splitter blades, and (e) redesigned impeller with splitter blades

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Fig. 2

Comparisons of meridional profiles and axial cross section of volute between baseline and redesigned pumps

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Fig. 3

Schematic of splitter blade design

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Fig. 4

Computational domain and grid of centrifugal pump

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Fig. 5

Results of grid independence investigation

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Fig. 6

Combination of impeller and volute for CFD calculation

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Fig. 7

Comparison of CFD results with experimental data of geometry #1: (a) comparison in head and (b) comparison in efficiency

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Fig. 8

Calculated performance curves of different geometries: (a) head curve and (b) efficiency curve

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Fig. 9

Contours of entropy generation rate per unit volume on stream surface (span = 0.25) of impeller and midspan plane of volute: (a) geometry #1, (b) geometry #2, (c) geometry #3, and (d) geometry #4; Contours of entropy generation rate per unit volume on: (e) cross section A shown in Figs. 9(c) and 9(f) cross section B shown in Fig. 9(d)

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Fig. 10

Control volume in impeller

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Fig. 11

Local Euler head distribution: (a) geometry #1, (b) geometry #2, and (c) geometry #3

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Fig. 12

Relative streamline on blade to blade surface: (a) geometry #1, (b) geometry #2, and (c) geometry #3

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Fig. 13

Time-averaged blade loading of geometry #1–3: (a) span = 0.1, (b) span = 0.5, and (c) span = 0.9

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Fig. 14

Relative velocity vector on surface near blade pressure surface: (a) geometry #1, (b) geometry #2, and (c) geometry #3

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Fig. 15

Standard deviation of static pressure coefficient on midspan of volute: (a) geometry #1, (b) geometry #2, (c) geometry #3, and (d) geometry #4

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Fig. 16

Comparison of vector diagram of unsteady radial forces (a) at RF during one rotation period, (b) at main blade passing frequency during a main blade passing period, and (c) statistics of unsteady radial force in four geometries

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