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Research Papers: Flows in Complex Systems

Numerical and Experimental Investigation of the Cavitating Flow Within Venturi Tube

[+] Author and Article Information
Jiří Kozák

Kaplan Department of Fluid Engineering,
Faculty of Mechanical Engineering,
Brno University of Technology,
Technická 2896/2,
Brno CZ-61669, Czech Republic
e-mail: jiri.kozak1@gmail.com

Pavel Rudolf

Kaplan Department of Fluid Engineering,
Faculty of Mechanical Engineering,
Brno University of Technology,
Technická 2896/2,
Brno CZ-61669, Czech Republic
e-mail: rudolf@fme.vutbr.cz

Martin Hudec

Kaplan Department of Fluid Engineering,
Faculty of Mechanical Engineering,
Brno University of Technology,
Technická 2896/2,
Brno CZ-61669, Czech Republic
e-mail: hudec@fme.vutbr.cz

David Štefan

Kaplan Department of Fluid Engineering,
Faculty of Mechanical Engineering,
Brno University of Technology,
Technická 2896/2,
Brno CZ-61669, Czech Republic
e-mail: david.steffan@gmail.com

Matěj Forman

ESI-Group,
Technicka 15,
Brno CZ-61600, Czech Republic
e-mail: matej.forman@esi-group.com

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received February 15, 2018; final manuscript received September 13, 2018; published online November 8, 2018. Assoc. Editor: Olivier Coutier-Delgosha.

J. Fluids Eng 141(4), 041101 (Nov 08, 2018) (11 pages) Paper No: FE-18-1103; doi: 10.1115/1.4041729 History: Received February 15, 2018; Revised September 13, 2018

Hydrodynamic cavitation represents complex physical phenomenon undesirably affecting operation as well as lifespan of many hydraulic machines from small valves to the large hydro power plants. On the other hand, the same phenomenon and its concomitants such as pressure pulsations can be exploited in many positive ways. One of them which seems to be very promising and perspective is the cavitation utilization for reduction of the microorganisms such as cyanobacteria within large bulks of water. Mutual effect of the swirl induced by the upstream mounted generator and flow constriction in converging–diverging nozzle has been experimentally investigated. The analysis of the hydraulic losses in the wide range of the cavitation regimes has been done as well as the investigation of the pipe wall acceleration induced by the fluctuations of the cavitating structures. The dynamics of the cavitation was studied using the proper orthogonal decomposition (POD) of the captured video records. The main scope of this paper is numerical investigation complementing the experimental results. The multiphase simulations were carried out using the OpenFOAM 1606+ and its interPhaseChangeFoam solver. The present study focuses on computational fluid dynamics results of the cavitating velocity field within the nozzle and analysis of the loss coefficient within the nozzle. The results of the numerical analysis were utilized for the further discussion of the experimental results.

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References

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Figures

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Fig. 4

Hydraulic loss coefficient versus cavitation number (measurement uncertainty for selected operating points)

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Fig. 5

Analysis of test rig vibrations induced by cavitation

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Fig. 3

Model of the swirl generator with the fixed blades exploited during the investigation

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Fig. 2

Main dimensions of the exploited Venturi tube (dimensions in mm)

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Fig. 1

Scheme of cavitation circuit equipped with the transducers (list of transducers is provided in Table 1)

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Fig. 6

Set of images capturing cavitating structures and influence of the induced swirl over a wide range of σ (the flow is from right to left)

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Fig. 9

Dominant frequencies obtained by analysis of the most important dynamic POD modes. The analyses of 6 l/s are complemented by the correlation with the results of the pressure fluctuations analysis.

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Fig. 10

Relative significance of the most important dynamic POD modes contributions

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Fig. 7

Detail of the straight cavitating vortex within the throat of the nozzle

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Fig. 8

Spatial coefficients of the most significant POD modes white–max values, black–min values

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Fig. 11

Computational domain

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Fig. 12

Comparison of the coarse (CG1) with the refined (CG2) computational grid—throat of the nozzle

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Fig. 13

Size of the computational grids including the number of hexahedral cells within the grids

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Fig. 15

Correction of the hydraulic loss coefficient using the energy correction factor

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Fig. 16

Pipe wall acceleration magnitude versus cavitation number corrected using αcorr

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Fig. 17

Pipe wall acceleration magnitude versus σpres

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Fig. 14

Hydraulic loss coefficient in the case of 6 l/s flow rate and SG presence—influence of the computational grid

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Fig. 18

Cavitating vortex filament downstream the SG (7 l/s, σvel = 0.017)

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Fig. 19

Flaws of the numerical simulation: absence of the cavitating vortex filament and significant cavitation of the boundary layer downstream the throat of the nozzle (6 l/s, SG, σvel = 0.48)

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Fig. 20

Cavitating vortex captured using the CFD (6 l/s, SG, σvel = 0.71)

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Fig. 21

Helical vortex breakdown captured using the CFD (6 l/s, SG, σvel = 0.98)

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Fig. 22

The images captured using high-speed camera in comparison with the numerical results

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Fig. 23

Detail of the cavitation closure region with velocity vectors colored by the axial velocity magnitude (ms−1)

Tables

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