Experimental investigation and prediction of post-dryout heat transfer for steam-water flow in helical coils

被引:20
|
作者
Xiao, Yao [1 ]
Hu, Zhenxiao [1 ]
Chen, Shuo [1 ]
Gu, Hanyang [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China
关键词
Helical coil; Secondary flow; Post-dryout heat transfer; Redeposition rate; Direct contact heat transfer; LOW-MASS FLUX; TRANSFER MODEL; PRESSURE-DROP; TUBES; NONEQUILIBRIUM; REGIME; GENERATOR; DIAMETERS;
D O I
10.1016/j.ijheatmasstransfer.2018.07.026
中图分类号
O414.1 [热力学];
学科分类号
摘要
Post-dryout heat transfer for steam-water flow in helical coils is experimentally investigated. The inner diameters of the helical coils are 12.5 mm and 14.5 mm, and the coil diameters range from 180 mm to 380 mm. The experimental system pressure covers the range 2-8 MP. The results indicate that the centrifugal force induced secondary flow has a great influence on post-dryout heat transfer in helical coils. In the low quality post-dryout region, because of the high redeposition rate induced by secondary flow, the heat transfer coefficient of helical coils is significantly higher than that of straight tubes. As the total droplet mass decreases with increasing quality, the heat transfer performance of helical coils decreases and continuously approaches that of straight tubes. In high quality post-dryout region, the bulk fluid in helical coils is closer to thermodynamic equilibrium state due to the secondary flow, and the heat transfer coefficient may be exceeded by straight tubes. For the effects of flow parameters, the post-dryout heat transfer performance decreases in heat flux and increases in mass flux. For system pressure, due to the change of the dominant heat transfer mechanism, the post-dryout heat transfer decreases in the low quality region but increases in the high quality region with increasing system pressure. Based on a detailed analysis of the effects of various dimensionless parameters, a new correlation containing a quality correction is proposed and provides good prediction accuracy. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:515 / 525
页数:11
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