Heat-transfer characteristics of screw tube in one-side high heat load condition for fusion reactor divertor application

被引:0
|
作者
Lim J.H. [1 ]
Lee S.W. [1 ]
Oh H. [2 ]
Park M. [1 ]
Hwang D. [1 ]
Kim M.H. [1 ,2 ]
Jo H. [1 ,2 ]
机构
[1] Division of Advanced Nuclear Engineering, POSTECH, Hyoja-dong, Nam-gu, Kyung-buk, Pohang
[2] Department of Mechanical Engineering, POSTECH, Hyoja-dong, Nam-gu, Kyung-buk, Pohang
来源
International Journal of Advanced Nuclear Reactor Design and Technology | 2021年 / 3卷
关键词
Artificial intelligence technique; Divertor; Heat transfer; Screw tube; Subcooled flow boiling;
D O I
10.1016/j.jandt.2021.10.001
中图分类号
学科分类号
摘要
In this study, the heat transfer characteristics of one-side heated screw tubes were analyzed using subcooled flow boiling experiments. The experiments were performed until the critical heat flux was reached, while the applied heat flux was gradually increased. Subsequently, the boiling curves derived from the experimental results were divided into partial nucleate boiling (PDB) and fully developed nucleate boiling (FDB) regimes. As the flow rate increases, the forced convective heat transfer is enhanced, improving the single-phase heat transfer performance. However, as the FDB region is approached, most of the heat transfer proceeds via nucleate boiling heat transfer, so the heat transfer coefficient curve converges into the same straight line. The same trend was observed when analyzing the effect of the degree of subcooling. However, as the system pressure increased, and the liquid surface tension and latent heat decreased, a faster transition was observed from the single-phase regime to the PDB regime. From evaluating the prediction performance of the existing subcooled flow boiling heat transfer correlations, among the PDB regime; Liu and Winterton correlation, a kind of Chen-type correlation, showed the highest accuracy with mean absolute error (MAE) of 13.62% and root mean square error (RMSE) of 16.13%. However, most of the FDB correlations did not accurately predict the heat transfer performance of the one-side heated screw tube under a high heat flux load of several MW/m2. Therefore, a new screw tube FDB correlation was developed using Python code combined with artificial intelligence technology. The authors believe that the proposed correlation will be useful for not only predicting the heat transfer performance in the FDB region, but also establishing an operating map of the screw tube in the future. © 2021 Xi'an Jiaotong University
引用
收藏
页码:213 / 225
页数:12
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