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International Journal of Fluid Mechanics Research
ESCI SJR: 0.206 SNIP: 0.446 CiteScore™: 0.5

ISSN Печать: 2152-5102
ISSN Онлайн: 2152-5110

Выпуски:
Том 46, 2019 Том 45, 2018 Том 44, 2017 Том 43, 2016 Том 42, 2015 Том 41, 2014 Том 40, 2013 Том 39, 2012 Том 38, 2011 Том 37, 2010 Том 36, 2009 Том 35, 2008 Том 34, 2007 Том 33, 2006 Том 32, 2005 Том 31, 2004 Том 30, 2003 Том 29, 2002 Том 28, 2001 Том 27, 2000 Том 26, 1999 Том 25, 1998 Том 24, 1997 Том 23, 1996 Том 22, 1995

International Journal of Fluid Mechanics Research

DOI: 10.1615/InterJFluidMechRes.v24.i4-6.200
pages 643-652

Theoretical Determination of Spray Drop Size Distributions
Part 1: Description of the Procedure

Jean Cousin
UMR 6614-CORIA, Technopole du Madrillet, B.P. 12 Avenue de l'Université 76801 Saint-Etienne du Rouvray Cedex, France
Christophe Dumouchel
Université et INSA de Rouen France

Краткое описание

The study presented in this paper reconsiders the use of the Maximum Entropy Formalism (M.E.F.) for the prediction of spray drop size distribution. This formalism is a statistical tool that allows the prediction of a probability distribution consistently with information related to the process studied. The study first shows that the formalism has to be adapted according to the distribution sought. Number and volume distributions are commonly used to describe a spray drop size distribution. However they do not contain similar information on the spray as the volume distribution is based on the relationship between the volume and the diameter of the drops and therefore always includes the knowledge of the shape of the particles. The difference between the two distributions is of paramount importance as far as the application of the Maximum Entropy Formalism is concerned and has to be taken into account when the entropy of the distribution is expressed. Furthermore, the precaution taken in the definition of the entropy leads to the prediction of distributions consistent with each other. Second, the tricky step of the writing of the constraints is tackled. The constraints must contain physical information specific to the problem studied. It is found that this could be achieved by using a single constraint based on the definition of a mean drop diameter of the Dqp series. Finally, an autonomous procedure for the prediction of drop size distributions is suggested in situations where the linear theory may be applied and leads to the prediction of a mean diameter of the distribution.


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