Suscripción a Biblioteca: Guest
Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones
Atomization and Sprays
Factor de Impacto: 1.262 Factor de Impacto de 5 años: 1.518 SJR: 0.814 SNIP: 1.18 CiteScore™: 1.6

ISSN Imprimir: 1044-5110
ISSN En Línea: 1936-2684

Volumen 29, 2019 Volumen 28, 2018 Volumen 27, 2017 Volumen 26, 2016 Volumen 25, 2015 Volumen 24, 2014 Volumen 23, 2013 Volumen 22, 2012 Volumen 21, 2011 Volumen 20, 2010 Volumen 19, 2009 Volumen 18, 2008 Volumen 17, 2007 Volumen 16, 2006 Volumen 15, 2005 Volumen 14, 2004 Volumen 13, 2003 Volumen 12, 2002 Volumen 11, 2001 Volumen 10, 2000 Volumen 9, 1999 Volumen 8, 1998 Volumen 7, 1997 Volumen 6, 1996 Volumen 5, 1995 Volumen 4, 1994 Volumen 3, 1993 Volumen 2, 1992 Volumen 1, 1991

Atomization and Sprays

DOI: 10.1615/AtomizSpr.2015011556
pages 1063-1080


Baris Bicer
Graduate School of Maritime Sciences, Kobe University, 5-1-1, Fukaeminami, Higashinada, 658-0022 Kobe, Hyogo, Japan
Akira Sou
Graduate School of Maritime Sciences, Kobe University, Japan


This paper examines the applicability of the following three different combinations of cavitation models to simulate cavitating flows in a nozzle of liquid fuel injector for diesel engines. The first model in a house code consists of the Lagrangian bubble tracking method (BTM), the Rayleigh-Plesset (RP) equation, and large eddy simulation (LES). The second model is the combination of the homogeneous equilibrium model (HEM), a barotropic (Baro) equation, and the RANS turbulence model (k-ω SST). The last one utilizes HEM, RANS (k-ε, k-ω SST), and the mass transfer model (MTM), in which bubble dynamics is calculated by the simplified RP equation. OpenFOAM is used for the simulations with the second and third models. Unsteady cavitation in a rectangular injector nozzle is captured by a high-speed camera and the turbulent velocity in the nozzle is measured by laser Doppler velocimetry (LDV); they are compared with the numerical results. As a result, the following conclusions are obtained. The BTM/RP/LES model gives a good prediction for the cavitation length and thickness, as well as cavitation cloud shedding. However, it requires a fine grid and a long CPU time, and is applicable only to incipient cavitation. The HEM/Baro/RANS approach results in a wrong prediction for cavitation length and thickness, and underestimation of the turbulence velocity. It cannot reproduce unsteady cavitation behavior. The combination of HEM/MTM/RANS gives good prediction for the cavitation length and thickness with a relatively coarse grid, and therefore with a short CPU time.