Research Papers: Flows in Complex Systems

A Fast Method to Predict the Cavitation Volume on Two-Dimensional Sections

[+] Author and Article Information
Zhibo Zeng

National Key Laboratory on Ship
Vibration & Noise,
China Ship Scientific Research Center,
Wuxi 214082, China
e-mail: zbzeng80@163.com

Gert Kuiper

Bennekon 06721 XB, The Netherlands
e-mail: g.kuiper@cavitation.nl

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received November 5, 2018; final manuscript received April 10, 2019; published online May 8, 2019. Assoc. Editor: Shawn Aram.

J. Fluids Eng 141(11), 111102 (May 08, 2019) (9 pages) Paper No: FE-18-1743; doi: 10.1115/1.4043499 History: Received November 05, 2018; Revised April 10, 2019

The paper presents a simplified prediction method to estimate cavitation-induced pressure fluctuations by marine propellers in a nonuniform wake field. It is realized by a very fast calculation of the cavitation volume variation. The sheet cavitation volume is represented by the cavitation area in a two-dimensional section, which is the vapor area inside the cavity contour. The variation of the cavitation area on a two-dimensional blade section has been simplified to a relation in quasi-steady condition with only a limited number of nondimensional parameters. This results in a fast method to predict the cavitation area of a blade section passing a wake peak, using a precalculated database. Application of this method to the prediction of cavitation-induced pressure fluctuations shows to be effective. This makes optimization of propeller sections for minimum cavitation-induced pressure fluctuations feasible.

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Fig. 1

Pressure distributions on suction side of section using parametric variations

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Fig. 2

Two types of pressure distributions on suction side; With the fixed values of αm = 1.65 deg, −Cpm = 0.20 they are, respectively, generated by variation of Eppler parameters xpc = 0.017, ΔCpmi = −0.045 for the flat pressure distribution and xpc = 0.110, ΔCpmi = 0.048 for the triangular pressure distribution; and then with angle of attack changed, they have the same minus minimum pressure coefficient (0.6) in the leading edge

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Fig. 3

The sensitivity of the pressure variation: ΔC¯¯p(ϕ) to the parameter αm (It is relative to αm=1.65 deg with an increment of angle of attack Δα=0.5 deg)

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Fig. 4

The development of section cavitation area as a function of the combined cavitation parameter

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Fig. 5

The development of cavitation area of propeller section at 0.8 R for the 5600TEU container ship

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Fig. 6

The database of precalculated cavitation area characteristic of section related with a series of pressure distributions: (a) xpc=0.017, (b) xpc=0.067, and (c) xpc=0.110. (“■ and ★” denote a variation of σ with α unchanged; “◻ and ☆” denote a variation of α with σ constant; The curves are their fittings).

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Fig. 7

The comparison of the characteristic of cavitation area predicted by Eq. (12) and simulated by computational fluid dynamics method

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Fig. 8

The fast prediction procedure to predict cavitation area variation

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Fig. 9

The cavitation bucket and the operating curve of propeller section at 0.8 R for the 5600TEU container ship

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Fig. 10

The combined cavitation parameter σ∗ with the blade angle position at 0.8 R for the 5600TEU container ship

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Fig. 11

The cavity shape on the propeller section at 0.8 R for the 5600TEU container ship at the 12 o’clock blade angle position: (a) The NACA section and (b) The new section

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Fig. 12

The variation of cavitation area on the propeller section at 0.8 R for the 5600TEU container ship

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Fig. 13

The second derivative of cavitation area on the propeller section at 0.8 R for the 5600TEU container ship



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