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International Journal of Fluid Mechanics Research

Publication de 6  numéros par an

ISSN Imprimer: 2152-5102

ISSN En ligne: 2152-5110

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.1 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0002 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.33 SJR: 0.256 SNIP: 0.49 CiteScore™:: 2.4 H-Index: 23

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

Volume 24, Numéro 4-6, 1997, pp. 643-652
DOI: 10.1615/InterJFluidMechRes.v24.i4-6.200
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RÉSUMÉ

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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