A preconditioned navier-stokes method for two-phase flows with application to Cavitation prediction

Robert F. Kunz, Dairid A. Boger, David R. Stinebring, Thomas S. Chyczewski, Howard J. Gibeling, Sankararn Venkateswaran, T. R. Govindan

Research output: Contribution to conferencePaperpeer-review

7 Scopus citations

Abstract

An implicit algorithm for the computation of viscous two-phase flows is presented. The baseline differential equation system is the multi-phase Navier-Stokes equations, comprised of the mixture volume, mixture momentum and constituent volume fraction equations. Though further generalization is straightforward, a three species formulation is pursued here, which separately accounts for the liquid and vapor (which exchange mass) as well as a non-condensable gas field. The implicit method developed here employs a dual-time, preconditioned, three-dimensional algorithm, with multi-block and parallel execution capabilities. Time-derivative preconditioning is employed to ensure well-conditioned eigenvalues, which is important for the computational efficiency of the method. Special care is taken to ensure that the resulting eigensystem is independent of the density ratio and the local volume fraction, which renders the scheme wellsuited to high density ratio, phase-separated two-fluid flows characteristic of many cavitating and boiling systems. To demonstrate the capabilities of the scheme, several two-dimensional and three-dimensional examples are presented.

Original languageEnglish (US)
Pages676-688
Number of pages13
StatePublished - 1999
Event14th Computational Fluid Dynamics Conference, 1999 - Norfolk, United States
Duration: Nov 1 1999Nov 5 1999

Other

Other14th Computational Fluid Dynamics Conference, 1999
Country/TerritoryUnited States
CityNorfolk
Period11/1/9911/5/99

All Science Journal Classification (ASJC) codes

  • General Engineering

Fingerprint

Dive into the research topics of 'A preconditioned navier-stokes method for two-phase flows with application to Cavitation prediction'. Together they form a unique fingerprint.

Cite this