Optimization of influence factors for water cooling of high temperature plate by accelerated control cooling process
- Authors
- Lim, Hwan Suk; Kang, Yong Tae
- Issue Date
- 1월-2019
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Accelerated control cooling; Heat transfer coefficient; Plate water cooling optimization; Precise plate cooling; Water temperature effect
- Citation
- INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, v.128, pp.526 - 535
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
- Volume
- 128
- Start Page
- 526
- End Page
- 535
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/68482
- DOI
- 10.1016/j.ijheatmasstransfer.2018.09.024
- ISSN
- 0017-9310
- Abstract
- The accelerated control cooling is considered to be one of the most practical technologies in the high tensile strength steel manufacturing industry. In order to achieve a high precision required for the cooling process, the system modeling should be done and optimized by considering the heat transfer mechanism as much as possible. For the system optimization, the parametric analysis for the influence factors such as feed water temperature, plate speed, plate width and specific heat should be carried out. In this study, we focus on optimizing the influence factors during water cooling of high temeperature plate by the accelerated control cooling process. The scale analysis with Reynolds and Prandtl numbers is made to optimize the effect of feed water temperature, and then the water flow density is determined during the water cooling process. The cooling efficiency is calculated in order to optimize the plate speed and plate width. Finally, start cooling temperature(SCT) and finish cooling temperature(FCT) are optimized by comparing the specific heat of standard references about low carbon steel such as NIST-JANAF, Eurocode, ISIJ. It is concluded that the accuracy of the predicted finish cooling temperature and the stability of the cooling process are significantly improved after the optimization of influence factors. (C) 2018 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > Department of Mechanical Engineering > 1. Journal Articles
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