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Journal of Enhanced Heat Transfer

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ISSN Druckformat: 1065-5131

ISSN Online: 1563-5074

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: 2.3 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: 0.2 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: 0.00037 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: 0.6 SJR: 0.433 SNIP: 0.593 CiteScore™:: 4.3 H-Index: 35

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EXPERIMENTAL STUDY AND OPTIMIZATION OF AIR ATOMIZED SPRAY WITH SURFACTANT ADDED WATER TO PRODUCE HIGH COOLING RATE

Volumen 19, Ausgabe 5, 2012, pp. 397-408
DOI: 10.1615/JEnhHeatTransf.2012004285
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ABSTRAKT

The current research deals with the heat transfer study using air atomized spray with surfactant added water for cooling a hot steel plate (6 mm thick) at high initial surface temperature (~900°C). Experiments were conducted with an air atomized spray at a fixed nozzle-to-plate distance and at different impingement density, air flow rate, and surfactant concentration. An inverse heat conduction model has been developed for the estimation of surface heat flux and surface temperature from the experimentally recorded temperature profile. From the experimental data, response surface methodology (RSM) has been used to derive statistical correlations for cooling rate and surface heat flux. Analysis shows that the predicted values obtained from the statistical model are in close agreement with the experimental data. In addition to the above, the interaction behavior and the optimal values of different process variables (impingement density, air flow rate, and surfactant concentration) are also determined. The achieved cooling rate and the developed correlations can be useful in the steel industry to produce high strength steel.

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