Homogeneous multiphase CFD modeling of large scale cavities

Jules W. Lindau, Robert F. Kunz, Venkateswaran Sankaran, David R. Stinebring

Research output: Contribution to conferencePaperpeer-review

10 Scopus citations

Abstract

Recent progress in the development and application of homogenous multiphase CFD methods for large-scale gas cavities in liquid flows are presented. The focus of the presentation is on work in n-species transport approaches applied to developed and supercavitation. Numerical formulation, physical modeling, and applications are included. Numerical issues to be discussed include: preconditioning in the context of incompressible through supersonic Mach numbers, arbitrary numbers of species, high density ratios, and large gas volume/mass fractions; computational grid requirements; dual-time formulation; and general large-scale high-performance computing. Physical modeling issues to be discussed include: homogeneous mixture compressibility; mass-transfer modeling; condensable and non-condensable gas species; turbulence modeling; and 6-degree-of freedom [6DOF] flowfield/rigid-body interaction. The applications to be presented range from naturally cavitating modeled flow on simple configurations (ogives, nozzles, airfoils/wedges) to more industrially relevant, complex-geometry applications including turbomachinery (cavitation breakdown), and super-cavitation (underwater rockets, hypervelocity darts, condensable and non-condensable cavities, gas-on/off transients, twin-vortex regime). Recent applications including Detached Eddy Simulation [DES] of natural cavities, and 6DOF analysis of a propelled notional super-cavitating vehicle are presented.

Original languageEnglish (US)
StatePublished - 2004
EventEuropean Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2004 - Jyvaskyla, Finland
Duration: Jul 24 2004Jul 28 2004

Other

OtherEuropean Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2004
Country/TerritoryFinland
CityJyvaskyla
Period7/24/047/28/04

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Applied Mathematics

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