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Journal of Hydrodynamics

, Volume 18, Issue 1, pp 476–480 | Cite as

Stochastic study of cavitation bubbles near boundary wall

  • S. Li
  • Z. G. Zuo
  • S. C. Li
Session A8

Abstract

A proposed Markov stochastic model for the random behavior of cavitation bubble(s) near compliant walls is introduced. Also for verification of the model a versatile facility for observing the effects of wall compliance on the stochastic behavior of single/multi-bubbles has been designed and built purposely at the Fluid Dynamics Research Centre, the University of Warwick (UK). This paper briefly introduces the previous work and the testing facility as well as current on going work.

Key words

cavitation bubble behavior bubble boundary interaction Markov model 

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References

  1. [1]
    Shima A et al. 1989 J. Fluid Mech. 203, pp199–214.CrossRefGoogle Scholar
  2. [2]
    Zhang S and Duncan J H 1993 FED 153, ASME, pp137–142.Google Scholar
  3. [3]
    Li S C and Carpenter P W 2000 ‘Note on an Markov Model for Cavitation Bubble(s) Near Compliant Walls’ ASME Fluids Engineering Conference June 11–15, 2000, Boston, Massachussetts, USAGoogle Scholar
  4. [4]
    Li S C and Carpenter PW 1999 ‘A Device for Studying the Stochastic Behaviour of Bubble Interacting with Compliant Wall’, The Eighth Asian Congress of Fluid Mechanics, Shenzhen, ChinaGoogle Scholar
  5. [5]
    Li S C 2000, ’3.7 ‘Origins of bubble statistics’ Cavitation of Hydraulic Machinery. ICP LondonGoogle Scholar
  6. [6]
    Z. G. Zuo, P. Dunkley, P. W. Carpenter, P. Bryanston-Cross, S. C. Li 2005, ‘Visualization Method for Acquiring Statistical Characteristics of Cavitation Bubbles’ The 8th International Symposium on Fluid Control, Measurement and Visualization, Chengdu, China.Google Scholar

Copyright information

© China Ship Scientific Research Center 2006

Authors and Affiliations

  1. 1.School of EngineeringWarwick UniversityCoventryUK

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