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Atomization and Sprays

Published 12 issues per year

ISSN Print: 1044-5110

ISSN Online: 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

SIMULATION OF WATER AND OTHER NON-FUEL SPRAYS USING A NEW SPRAY MODEL

Volume 13, Issue 1, 2003, 26 pages
DOI: 10.1615/AtomizSpr.v13.i1.10
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ABSTRACT

Hitherto, all polydisperse spray models have been based on discretizing the liquid flow field into groups of equally sized droplets. The work assessed here involves the implementation of a spray model [1-3] that captures the full polydisperse nature of the spray flow without using droplet size classes. The parameters used to describe the distribution of droplet sizes are the first four moments of the droplet number distribution function. Transport equations are written for the two moments which represent, per unit volume, the liquid mass and surface area, and two more moments representing the sum of the droplet radii and droplet number are approximated via use of a presumed distribution function which is allowed to vary in space and time. The velocities to be used in the two transport equations are obtained by defining moment-average quantities and constructing further transport equations for the relevant moment-average velocities. An equation for the energy of the liquid phase and standard gas-phase equations, including a k-e turbulence model, are also solved. All the equations are solved in a Eulerian framework using the finite-volume approach, and the phases are coupled through source terms. Effects such as droplet breakup and droplet—droplet collisions are also included through the use of source terms, and all the source terms are expressed in terms of the four moments of the droplet size distribution in order to find the net effect on the whole spray flow field.
In previous journal publications, the model has been qualitatively assessed by examining the predicted structures of narrow-cone, wide-angle full-cone and hollow-cone sprays, and the dependence of the results on parametric changes. Quantitative verification using experimental data has largely been confined to macro features of the sprays, such as penetration rates.
In this article the model is further assessed by examining the microstructure of the predicted sprays. Comparisons are made with experimental data on local values of drop sizes, mass fluxes, and drop velocities for wide-angle full-cone, hollow-cone, and evaporating sprays. In most cases, good agreement is achieved. The one exception to this is the mass flux distributions predicted for wide-angle full-cone water sprays. Suggestions for improvement are made to the modeling for this, and for other features of sprays.

CITED BY
  1. Scott Stephen J., Shrimpton John S., Experimental investigation of a maximum entropy assumption for acceleration terms within a poly-disperse moment framework, International Journal for Numerical Methods in Fluids, 60, 6, 2009. Crossref

  2. SAKAGUCHI Daisaku, YAMAMOTO Shohei, UEKI Hironobu, ISHDIA Masahiro, Study of Heterogeneous Structure in Diesel Fuel Spray by Using Micro-Probe L2F, Journal of Fluid Science and Technology, 5, 1, 2010. Crossref

  3. Beck J. C., Watkins A. P., The simulation of fuel sprays using the moments of the drop number size distribution, International Journal of Engine Research, 5, 1, 2004. Crossref

  4. Dhuchakallaya I., Watkins A.P., Development and application of the drop number size moment modelling to spray combustion simulations, Applied Thermal Engineering, 30, 10, 2010. Crossref

  5. Pougatch K., Salcudean M., Chan E., Knapper B., A two-fluid model of gas-assisted atomization including flow through the nozzle, phase inversion, and spray dispersion, International Journal of Multiphase Flow, 35, 7, 2009. Crossref

  6. Watkins A.P., Modelling the mean temperatures used for calculating heat and mass transfer in sprays, International Journal of Heat and Fluid Flow, 28, 3, 2007. Crossref

  7. Dhuchakallaya Isares, Rattanadecho Phadungsak, Watkins Paul, Auto-ignition and combustion of diesel spray using unsteady laminar flamelet model, Applied Thermal Engineering, 52, 2, 2013. Crossref

  8. Nave Ophir, Lehavi Yaron, Ajadi Suraju, Gol’dshtein Vladimir, Analysis of polydisperse fuel spray flame, Heat and Mass Transfer, 53, 2, 2017. Crossref

  9. Petranović Zvonimir, Edelbauer Wilfried, Vujanović Milan, Duić Neven, Modelling of spray and combustion processes by using the Eulerian multiphase approach and detailed chemical kinetics, Fuel, 191, 2017. Crossref

  10. Petranovic Zvonimir, Edelbauer Wilfried, Vujanović Milan, Priesching Peter, Tatschl Reinhard, Duić Neven, Modeling of Reactive Spray Processes in DI Diesel Engines, SAE Technical Paper Series, 1, 2017. Crossref

  11. Shrimpton J. S., Haeri S., Scott Stephen J., Eulerian–Eulerian Field Equations, in Statistical Treatment of Turbulent Polydisperse Particle Systems, 2014. Crossref

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