Cavitating flows entail phase change and hence very large and steep density variations in the low pressure regions. These are also very sensitive to: (a) the formation and transport of vapor bubbles, (b) the turbulent fluctuations of pressure and velocity, and (c) the magnitude of noncondensible gases, which are dissolved or ingested in the operating liquid. The presented cavitation model accounts for all these first-order effects, and thus is named as the full cavitation model. The phase-change rate expressions are derived from a reduced form of Rayleigh-Plesset equation for bubble dynamics. These rates depend upon local flow conditions (pressure, velocities, turbulence) as well as fluid properties (saturation pressure, densities, and surface tension). The rate expressions employ two empirical constants, which have been calibrated with experimental data covering a very wide range of flow conditions, and do not require adjustments for different problems. The model has been implemented in an advanced, commercial, general-purpose CFD code, CFD-ACE+

Mathematical Basis and Validation of the Full Cavitation Model

The structure

Physics of shock waves and high-temperature hydrodynamic phenomena - Ya.B. Zeldovich and Yu.P. Raizer (translated from the Russian and then edited by Wallace D. Hayes and Ronald F. Probstein); Dover Publications, New York, 2002, 944 pp., $34.

流体力学用語集 非線形音響学(Nonlinear acoustics)

Cavitation and Bubble Dynamics: Preface

Modeling of surface cleaning by cavitation bubble dynamics and collapse.

Material pitting from cavitation bubble collapse is investigated numerically including two-way fluid–structure interaction (FSI). A hybrid numerical approach which links an incompressible boundary element method (BEM) solver and a compressible finite difference flow solver is applied to capture non-spherical bubble dynamics efficiently and accurately. The flow codes solve the fluid dynamics while intimately coupling the solution with a finite element structure code to enable simulation of the full FSI. During bubble collapse high impulsive pressures result from the impact of the bubble re-entrant jet on the material surface and from the collapse of the remaining bubble ring. A pit forms on the material surface when the impulsive pressure is large enough to result in high equivalent stresses exceeding the material yield stress. The results depend on bubble dynamics parameters such as the size of the bubble at its maximum volume, the bubble standoff distance from the material wall, and the pressure driving the bubble collapse. The effects of these parameters on the re-entrant jet, the following bubble ring collapse pressure, and the generated material pit characteristics are investigated.

Modelling of material pitting from cavitation bubble collapse

Multiscale tow-phase flow modeling of sheet and cloud cavitation

The acoustic pressure generated by cavitation inception in a tip vortex flow was simulated in water containing a realistic bubble nuclei size distribution using a surface-averaged pressure (SAP) spherical bubble dynamics model. The flow field was obtained by the Reynolds-averaged Navier-Stokes computations for three geometrically similar scales of a finite-span elliptic hydrofoil. An acoustic criterion, which defines cavitation inception as the flow condition at which the number of acoustical peaks above a pre-selected pressure level exceeds a reference number per unit time, was applied to the three scales. It was found that the scaling of cavitation inception depended on the reference values (pressure amplitude and number of peaks) selected. Scaling effects (i.e., deviation from the classical σ i R 0.4 e ) increase as the reference inception criteria become more stringent (lower threshold pressures and less number of peaks). Larger scales tend to detect more cavitation inception events per unit time than obtained by classical scaling because a relatively larger number of nuclei are excited by the tip vortex at the larger scale due to simultaneous increase of the nuclei capture area and of the size of the vortex core. The average nuclei size in the nuclei distribution was also found to have an important impact on cavitation inception number. Scaling effects (i.e., deviation from classical expressions) become more important as the average nuclei size decreases.

Scaling of Tip Vortex Cavitation Inception Noise With a Bubble Dynamics Model Accounting for Nuclei Size Distribution

The current study considers the prediction of tip vortex cavitation inception at a fundamental physics based level. Starting form the observation that cavitation inception detection is based on the monitoring of the interaction between bubble nuclei and the flow field, the bubble dynamics is investigated in detail. A spherical model coupled with a bubble motion equation is used to study numerically the dynamics of a nucleus in an imposed flow field. The code provides bubble size and position versus time as well as the resulting pressure at any selected monitoring position. This model is used to conduct a parametric study. Bubble size and emitted sound versus time are presented for various nuclei sizes and flow field scales in the case of an ideal Rankine vortex to which a longitudinal viscous core size diffusion model is imposed. Based on the results, one can deduce cavitation inception with the help of either an optical inception criterion (maximum bubble size larger than a given value) or an acoustical inception criterion (maximum detected noise higher than a given background value)

Chao-Tsung Hsiao

Papers

Modeling of surface cleaning by cavitation bubble dynamics and collapse.

Modelling of material pitting from cavitation bubble collapse

Multiscale tow-phase flow modeling of sheet and cloud cavitation

Scaling of Tip Vortex Cavitation Inception Noise With a Bubble Dynamics Model Accounting for Nuclei Size Distribution

Scaling Effect on Prediction of Cavitation Inception in a Line Vortex Flow