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Atomization and Sprays

Publicado 12 números por año

ISSN Imprimir: 1044-5110

ISSN En Línea: 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 NOVEL SPRAY MODEL VALIDATION METHODOLOGY USING LIQUID-PHASE EXTINCTION MEASUREMENTS

Volumen 25, Edición 5, 2015, pp. 397-424
DOI: 10.1615/AtomizSpr.2014010377
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SINOPSIS

Physical spray models employed in engine computational fluid dynamics (CFD) simulations are not yet fully predictive; therefore, the breadth of conditions under which these simulations yield valid predictions depends strongly on the "tuning" of these models against available spray measurements. Often, these models are validated and calibrated against spray images based on the elastic scattering of light, or Mie scattering, from liquid structures and droplet clouds. However, these measurements do not typically detect the absolute liquid boundary, so employed computational metrics used to define the liquid boundary in the modeled spray can be physically inconsistent with that detected in Mie-scatter images. To more robustly validate fuel spray model predictions against light scattering measurements, direct comparisons can be made between predicted and measured light scattering intensity signals. Such a comparison provides a more quantitative validation of the liquid phase fuel boundary and further offers the potential to validate local spray structure. In this work, we apply the Lorentz−Mie solution to Maxwell's equations to predict extinction signals due to elastic light scattering, informed by droplet diameter and number density distributions, within a predicted diesel spray. The predicted extinction is compared to experimental results from diffused back-illumination and single line-of-sight extinction measurements to generate a calibrated model of the Engine Combustion Network "Spray A" condition that replicates the measured centerline extinction profile. This spray model is used to inform liquid volume fraction thresholds to similarly define the detected liquid boundary from Mie-scatter images.

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