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Proceedings of the 10th International Symposium on Cavitation (CAV2018)
Editor
Joseph Katz
Joseph Katz
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ISBN:
9780791861851
No. of Pages:
1108
Publisher:
ASME Press
Publication date:
2018

An explicit density-based solver for the compressible Navier-Stokes equations able to simulate cavitating flows has been developed and utilised for the simulation of collapsing vapour bubbles. Phase-change is considered by employing the homogeneous equilibrium model (HEM). The wide variation of Mach numbers between the liquid, vapour and mixture regimes is tackled by a Mach consistent numerical flux, suitable for subsonic up to supersonic flow conditions. Time discretisation is performed using a second order low storage Runge-Kutta scheme. Thermodynamic closure is achieved by utilising the Helmholtz energy equation of state (EoS), making feasible simulation of conditions at subcritical and supercritical regions considering the variations of liquid and vapour temperatures during bubble collapse. In order to reduce the computational cost associated with the solution of the Helmholtz EoS at each time step, a tabulated data technique has been followed. The unstructured thermodynamic table, containing the thermodynamic properties derived from the Helmholtz EoS, has been constructed for n-dodecane, which has been the considered as the working fluid. The efficiency of the method is enhanced by a static linked-list algorithm for searching among the elements of the table. In addition, a finite element bilinear interpolation is used for approximating the unknown thermodynamic properties. After validating the numerical method, parametric studies considering 2-D axisymmetric vaporous bubble collapse in the proximity of a wall have been performed at conditions realised in micro-orifice flow passages. The temperature and pressure changes on the wall are estimated as function of the surrounding liquid pressure, the initial bubble radius and the location of the wall from the center of the initial bubble, revealing the expected range of variation as function on the set parameters.

Introduction
Numerical Method
Results
Conclusions
Acknowledgements
References
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