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Journal of Flow Visualization and Image Processing

年間 4 号発行

ISSN 印刷: 1065-3090

ISSN オンライン: 1940-4336

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: 0.6 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: 0.6 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: 0.00013 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: 0.14 SJR: 0.201 SNIP: 0.313 CiteScore™:: 1.2 H-Index: 13

Indexed in

OPTIMAL WATER DISTRIBUTION IN THE COOLING TOWER

巻 16, 発行 4, 2009, pp. 367-375
DOI: 10.1615/JFlowVisImageProc.v16.i4.70
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要約

The objective of this work is to provide a method and data for engineers dealing with cooling tower design. A cooling tower is a heat rejection device, which distributes wasted heat to the atmosphere through the cooling of water by air. In this case, low-pressure nozzles usually distribute water from the pipelines onto the fill. Cooling tower nozzle characteristics such as water distribution around the nozzle, flow rate, distance between nozzles, and distance between pipelines are important for the cooling tower water distribution design. Parameters such as water distribution around the nozzle and flow rate were simply obtained from measurements. The distance between nozzles and the distance between pipelines were obtained from the superposition of water distribution around every single nozzle determined by optimal water distribution onto the fill. We got this optimal water distribution from optimization of parameters (the distance between nozzles and the distance between pipelines) by means of the simplex method.

参考
  1. S. C. Kranc, Optimal spray patterns for counterflow cooling towers with structured packing.

  2. V. Syrovatka, P. Vitkovic, and J. Nozicka, The comparing between two methods of measurement of splashing characteristic of spray nozzle RT 240.

  3. V. Syrovatka, P. Vitkovic, and J. Nozicka, The Measurement of Mass Flow Characteristic of Splashing Nozzle RT 240-22 mm, 25 mm, 28 mm, 30 mm.

  4. P. Vitkovic, V. Syrovatka, and J. Nozicka, Measurement of Splashing Characteristic on One Square Meter of Spray Nozzles RT 240.

によって引用された
  1. Stodůlka Jiří, Vitkovičová Rut, Dančová Petra, Vít Tomáš, Design and CFD Simulation of the Drift Eliminators in Comparison with PIV Results, EPJ Web of Conferences, 92, 2015. Crossref

  2. Stodůlka Jiří, Vitkovičová Rut, Dančová P., Veselý M., Estimation of the drift eliminator efficiency using numerical and experimental methods, EPJ Web of Conferences, 114, 2016. Crossref

  3. He Yu, Sun Zhibin, Shen Baojun, Guo Fang, Yang Yili, Zhan Xiaobin, Li Xiwen, CFD study on the flow distribution of an annular multi‐hole nozzle, The Canadian Journal of Chemical Engineering, 98, 2, 2020. Crossref

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