Heat transfer characteristics during jet impingement on a high-temperature plate surface. (5th May 2016)

• Record Type: Journal Article
• Authors: Wang, Bingxing; Lin, Dong; Xie, Qian; Wang, Zhaodong; Wang, Guodong
• Is Part Of: Applied thermal engineering. Volume 100(2016:May)
• Page Start: 902
• Page End: 910
• Publication Date: 2016-05-05
• Subjects: Ultra-fast cooling -- Heat transfer -- Jet impingement -- Rewetting phenomenon; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2016.02.054
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: The influenced parameters of the impinging jet were systematically studied. The wetting characteristic along the radial direction was investigated. The rewetting temperature highly depended on the initial plate temperature. A regression equation was established to predict the maximum heat flux. Abstract: The heat transfer ability and cooling uniformity in ultra-fast cooling technology played a critical role in improving the microstructure and mechanical properties of hot rolling steel. However, the heat transfer characteristics and boiling phenomena during the cooling process of a water jet impinging on a hot plate surface approximate to the industrial conditions were rarely reported. Herein, we investigated the effect of the initial surface temperature, water temperature, and jet velocity on the heat transfer characteristics for the industrial applications. The results revealed that the rewetting front propagation was considerably affected by the growth and detachment of the bubbles in the rewetting front region. The wetting delay time was extended by the superheat increase, and the sub-cooling and jet velocity decrease, because the ability to condense the bubbles was weakened in the front rewetting region. Meanwhile, the wetting velocity varied with the distance from the stagnant point. Moreover, the maximum heat flux, qmax, was influenced by the initial surface temperature, water temperature, and jet velocity; finally, a regression equation was established to predict the qmax value. The information provided in this work would be beneficial for predicting and optimizing the industrial applications of ultra-fast cooling technology.