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Research Papers: Multiphase Flows

Numerical and Experimental Study of a Ventilated Supercavitating Vehicle

[+] Author and Article Information
I. Rashidi, Ma. Pasandideh-Fard, Mo. Passandideh-Fard

Department of Mechanical Engineering,
Ferdowsi University of Mashhad,
Mashhad, Iran

N. M. Nouri

School of Mechanical Engineering,
Iran University of Science and Technology,
Narmak, Tehran 16846, Iran

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received May 2, 2013; final manuscript received January 23, 2014; published online July 24, 2014. Assoc. Editor: Edward M. Bennett.

J. Fluids Eng 136(10), 101301 (Jul 24, 2014) (7 pages) Paper No: FE-13-1289; doi: 10.1115/1.4027383 History: Received May 02, 2013; Revised January 23, 2014

In this paper, the ventilated supercavities are studied both numerically and experimentally. A slender rod is considered as the solid body which has a sharp edged disk at the nose as a cavitator and special ports for air ventilation. The experiments are conducted in a recirculating water tunnel. The simulations are provided for two different algorithms in free-surface treatment, both using the VOF method but one using Youngs' algorithm in the advection of the free-surface and the other without. The comparison between numerical simulations and experiments show that the numerical method using Youngs' algorithm accurately simulates the physics of ventilated cavitation phenomena such as the cavity shape, the gas leakage and the re-entrant jet.

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References

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Figures

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Fig. 1

The schematic of the water tunnel

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Fig. 2

The model used in the water tunnel

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Fig. 3

The computational domain and boundary conditions. The figure is not to scale.

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Fig. 4

The structure grid near the body

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Fig. 5

The shape of the ventilated cavity from (a) experiments, (b) simulations using Youngs' algorithm, and (c) simulations without Youngs' algorithm at an air entrainment coefficient of CQ = 0.092 and the Froude number of Fr = 17

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Fig. 6

The shape of the ventilated cavity from (a) experiments, (b) simulations using Youngs' algorithm, and (c) simulations without Youngs' algorithm at an air entrainment coefficient of CQ = 0.113 and the Froude number of Fr = 17

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Fig. 7

The variation of the air entrainment coefficient (CQ) versus the dimensionless cavity length (Lc/d) from the numerical method using Youngs' algorithm and experiments for Fr = 17

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Fig. 8

The variation of the air entrainment coefficient (CQ) versus the cavitation number from the numerical method using Youngs' algorithm and experiments for Fr = 17

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Fig. 9

The re-entrant jet in the ventilated cavitation from (a) experiments (where arrows point to the re-entrant jet) and (b) simulations using Youngs' algorithm (where a counter of the air volume fraction is shown)

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Fig. 10

The evacuation of the vortices at the rear end of the cavity from (a) experiments and (b) the simulations using Youngs' algorithm

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Fig. 11

The re-entrant jet inside the cavity

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Fig. 12

The pressure coefficient distributions from the numerical method using Youngs' algorithm for an air entrainment of 0.102 and Fr = 17. The cavity interface from the numerical method is also displayed in the figure.

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Fig. 13

The pressure coefficient distributions from the numerical method using Youngs' algorithm for an air entrainment of 0.113 and Fr = 17. The cavity interface from the numerical method is also displayed in the figure.

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Fig. 14

The time variation of cavitation number inside the cavity for CQ = 0.102 and Fr = 17. The mean value of the cavitation number is also shown.

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Fig. 15

The time variation of cavitation number inside the cavity for CQ = 0.113 and Fr = 17. The mean value of the cavitation number is also shown.

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Fig. 16

The unsteady behavior of the ventilated cavitation for CQ = 0.102. The time interval between successive images is 0.01 s.

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Fig. 17

The unsteady behavior of the ventilated cavitation for CQ = 0.113. The time interval between successive images is 0.01 s.

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