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雾化与喷雾

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ISSN 打印: 1044-5110

ISSN 在线: 1936-2684

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: 1.2 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: 1.8 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.3 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: 0.00095 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: 0.28 SJR: 0.341 SNIP: 0.536 CiteScore™:: 1.9 H-Index: 57

Indexed in

A MAXIMUM ENTROPY APPROACH TO MODELING THE DYNAMICS OF A VAPORIZING SPRAY

卷 20, 册 12, 2010, pp. 1017-1031
DOI: 10.1615/AtomizSpr.v20.i12.10
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摘要

Conventional particle tracking techniques used to predict the dynamics and statistics of spray flows can be prohibitively expensive, requiring large computation times and significant data storage. Moreover, because of the discontinuous nature of the spray drops, data from a simulation of the flow do not produce smooth statistics unless the results from many simulations have been averaged. A new model has been presented previously that computes spray statistics directly, without simulating the flow, by closing a set of transport equations for the low-order moments of the droplet probability density function. The model is now extended to include nonlinear drag, heating, and vaporization effects. The Ranz-Marshall correlation and d 2 law are used for droplet heating and vaporization; however, any other correlation could be used without significant change to the overall spray model. Both nonvaporizing and vaporizing test cases with a quasi-one-dimensional flow geometry show very good agreement in comparison with a conventional Lagrangian simulation. With three notable exceptions, the vaporizing and nonvaporizing results are very similar.

对本文的引用
  1. Sazhin Sergei, Heating and Evaporation of Monocomponent Droplets, in Droplets and Sprays, 2014. Crossref

  2. Sazhin Sergei S., Heating and Evaporation of Mono-component Droplets, in Droplets and Sprays: Simple Models of Complex Processes, 2022. Crossref

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