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雾化与喷雾

每年出版 12 

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

APPLICATION OF ARTIFICIAL NEURAL NETWORKS MODELING TO SPRAYS AND SPRAY IMPINGEMENT HEAT TRANSFER

卷 12, 册 4, 2002, pp. 359-386
DOI: 10.1615/AtomizSpr.v12.i4.10
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摘要

Artificial neural networks (ANN) models have been developed and applied to free propane sprays and to water spray cooling heat flux predictions. For the propane spray conditions the ANN model is trained against the computational fluid dynamics (CFD) results and verified against experimental data for drop diameter at the centreline 95 mm from the nozzle. It is shown that an ANN model trained on CFD gives results comparable to the CFD predictions and that it can therefore be employed online in industry to investigate and limit the consequences of a depressurization accident. When enough experimental data are present, as in the spray cooling case, the ANN model can be welt trained and proves to be an alternative numerical modeling technique to CFD, with the numerical predictions comparable to the CFD predictions, but in real-time mode.

对本文的引用
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  5. Guo Han, Zhou Jun, Liu Fei, He Yong, Huang He, Wang Hongyan, Application of Machine Learning Method to Quantitatively Evaluate the Droplet Size and Deposition Distribution of the UAV Spray Nozzle, Applied Sciences, 10, 5, 2020. Crossref

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