On the relevance of kinematics for cavitation implosion loads

Abstract

This study presents a novel physical model to convert the potential energy contained in vaporous cavitation into local surface impact power and an acoustic pressure signature caused by the violent collapse of these cavities in a liquid. The model builds on an analytical representation of the solid angle projection approach by Leclercq et al. ["Numerical cavitation intensity on a hydrofoil for 3D homogeneous unsteady viscous flows," Int. J. Fluid Mach. Syst. 10, 254-263 (2017)]. It is applied as a runtime post-processing tool in numerical simulations of cavitating flows. In the present study, the model is inspected in light of the time accurate energy balance during the cavity collapse. Analytical considerations show that the potential cavity energy is first converted into kinetic energy in the surrounding liquid [D. Obreschkow et al., "Cavitation bubble dynamics inside liquid drops in microgravity," Phys. Rev. Lett. 97, 094502 (2006)] and focused in space before the conversion into shock wave energy takes place. To this end, the physical model is complemented by an energy conservative transport function that can focus the potential cavity energy into the collapse center before it is converted into acoustic power. The formulation of the energy focusing equation is based on a Eulerian representation of the flow. The improved model is shown to provide physical results for the acoustic wall pressure obtained from the numerical simulation of a close-wall vapor bubble cloud collapse.

Assessment of RANS turbulence models and Zwart cavitation model empirical coefficients for the simulation of unsteady cloud cavitation

“…In addition, it can be observed that the optimal coefficients in Table 10 are significantly higher than the default empirical coefficients (50, 0.01) which underestimate the cavity vapor content and the intensity of the collapse process as discussed before. These results are in accordance with the recent works by Ghahramani, Arabnejad and Bensow (2019) and Schenke, Melissaris and van Terwisga (2019). Using different cavitation models, they found that the speed of the bubble collapse is significantly underestimated with low mass transfer coefficients.…”

A numerical study on the effect of cavitation erosion in a diesel injector

“…In cavitation erosive cases, pressure waves are created during the cavity collapse and impact the nearby walls, which can lead to material damage. Fast condensation rates can predict such high values in pressure at the end phase of cavities collapse [14,15]; simulations with compressible liquids can predict pressure wave propagation patterns. The maximum pressure peaks can then be recorded on the surfaces and associated with erosion risk.…”

“…The prediction of cavitation erosion has been the subject of a wide range of research [4,5,6,7,8,9,10,11,12,13,14,15]. Among them, experimental campaigns are of great importance to obtain a deeper understanding of the underlying physics and to allow the validation of numerical models.…”

Modelling and prediction of cavitation erosion in GDi injectors operated with E100 fuel

“…These models contain empirically calibrated constants that determine the mass transfer rate and have been shown to be equivalent if the constants are chosen appropriately [46]; typically, low values of the calibration constants are selected, which may results in non-physical negative pressures [47]. Moreover, this also results in a severe over-prediction of the collapse time of cavitation bubbles [47,48,49]. The error can be reduced by model calibration to match the critical cavitation point measurement (CCP) for different throttle configurations as it is reported in [50]; still this empirical approach is not efficient and reliable considering that all the model parameters need to be calibrated simultaneously.…”

“…Some studies rely on resolving the mechanical loads of cavitation collapses reaching the walls and recording the maximum pressure [15,34]. The drawback of this method is that the value of the recorded pressure peaks can be mesh and time resolution dependent [52,49]. In addition in fuel injectors due to the moving needle valve, the sac volume pressure presents variations of the order of the injection pressure, which can obscure pressure peaks arising during the different injection phases [62].…”