Flows in Complex Systems

Analysis and Optimization of a Vaned Diffuser in a Mixed Flow Pump to Improve Hydrodynamic Performance

[+] Author and Article Information
Jin-Hyuk Kim

Department of Mechanical Engineering,Graduate School,  Inha University, 253 Yonghyun-Dong, Nam-Gu, Incheon 402-751, South Korea

Kwang-Yong Kim1

Department of Mechanical Engineering,  Inha University, 253 Yonghyun-Dong, Nam-Gu, Incheon 402-751, South Koreakykim@inha.ac.kr


Corresponding author.

J. Fluids Eng 134(7), 071104 (Jun 21, 2012) (10 pages) doi:10.1115/1.4006820 History: Received January 30, 2012; Revised April 30, 2012; Published June 21, 2012; Online June 21, 2012

Hydrodynamic analysis and an optimization of a vaned diffuser in a mixed-flow pump are performed in this work. Numerical analysis is carried out by solving three-dimensional Reynolds-averaged Navier-Stokes equations using the shear stress transport turbulence model. A validation of numerical results is conducted by comparison with experimental data for the head, power, and efficiency. An optimization process based on a radial basis neural network model is performed with four design variables that define the straight vane length ratio, the diffusion area ratio, the angle at the diffuser vane tip, and the distance ratio between the impeller blade trailing edge and the diffuser vane leading edge. Efficiency as a hydrodynamic performance parameter is selected as the objective function for optimization. The objective function is numerically assessed at design points selected by Latin hypercube sampling in the design space. The optimization yielded a maximum increase in efficiency of 9.75% at the design flow coefficient compared to a reference design. The performance curve for efficiency was also enhanced in the high flow rate region. Detailed internal flow fields between the reference and optimum designs are analyzed and discussed.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 1

Mixed flow pump model and computational domain. (a) Mixed flow pump model. (b) Computational domain and grids.

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Figure 2

Results of grid dependency test. (a) Head and power. (b) Static pressure distributions at each TE of the impeller blade and diffuser vane.

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Figure 3

Optimization procedure

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Figure 4

Definition of design variables. (a) Straight vane length ratio (SVLR). (b) Diffusion area ratio (DAR). (c) β distribution at vane tip. (d) Example of a changed vane shape with variation of β at vane tip. (e) Distance between impeller blade TE and diffuser vane LE.

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Figure 5

Radial basis neural network architecture (single neuron) [26]

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Figure 6

Validation of the numerical results [5]

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Figure 7

Results of sensitivity test

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Figure 8

Performance characteristic curves

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Figure 9

Distributions of total and static pressures at 50% span of the vaned diffuser along the meridional length

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Figure 10

Static pressure distributions on blade surfaces of diffuser vanes. (a) At 20% span. (b) At 50% span. (c) At 80% span.

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Figure 11

Velocity vectors at three spanwise locations. (a) At 20% span. (b) At 50% span. (c) At 80% span.

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Figure 12

Velocity contours at 50% chord of the diffuser vane (units: m/s). (a) Location of observation. (b) Reference design. (c) Optimum design.

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Figure 13

Velocity contours at TE of the diffuser vane (units: m/s): (a) Location of observation. (b) Reference design. (c) Optimum design.

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Figure 14

Isosurfaces with low velocity of 1 m/s. (a) Reference design. (b) Optimum design.




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