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Atomization and Sprays
IF: 1.737 5-Year IF: 1.518 SJR: 0.814 SNIP: 1.18 CiteScore™: 2.2

ISSN Print: 1044-5110
ISSN Online: 1936-2684

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Atomization and Sprays

DOI: 10.1615/AtomizSpr.2020032620
pages 239-266

ATOMIZATION MODELING USING SURFACE DENSITY AND STOCHASTIC FIELDS

Aqeel Ahmed
CORIA-UMR 6614—Normandie University, CNRS-University and INSA of Rouen, 76800 Saint Etienne du Rouvray, France
G. Tretola
Department of Mechanical Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, UK
Salvador Navarro-Martinez
Department of Mechanical Engineering, Imperial College London, Exhibition Road, South Kensington, London SW7 2AZ, UK
K. Vogiatzaki
Advanced Engineering Centre, University of Brighton, Brighton, BN2 4AT, UK
B. Duret
CORIA-UMR 6614, Normandie University, CNRS-University and INSA of Rouen, Avenue de l'Université BP 12, Saint-Étienne-du-Rouvray 76800, France
Julien Reveillon
CORIA-UMR 6614 – Normandie Université, CNRS-Université et INSA de Rouen, Campus Universitaire du Madrillet, 76800 Saint Etienne du Rouvray, France
Francois-Xavier Demoulin
CORIA-UMR 6614 – Normandie Université, CNRS-Université et INSA de Rouen, Campus Universitaire du Madrillet, 76800 Saint Etienne du Rouvray, France

ABSTRACT

Correct prediction of the spray in automotive and aerospace engines remains a challenging task. In this work we present a numerical framework to characterize the spray, using both the large scale quantities, like mean liquid volume fractions, as well as small scale structures or liquid droplets. In the limit of high Reynolds and Weber number, the drop size is expected to be much smaller than can be resolved using first principles on a given mesh, thus a subgrid formulation is used to characterize the drop size. Using liquid gas interface surface density we have compared a standard formulation as well as a probability density function-based formulation. Using large eddy simulation we compared against the experimental database hosted by the engine combustion network for a single hole injector. Sauter mean diameter is predicted well using our formulation; at the same time use of the probability density function brings additional information regarding drop size distribution.

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