Study on pool boiling and flow boiling with artificial neural networks

Rong Hua Chen, Guang Hui Su, Sui Zheng Qiu

研究成果: Article査読

抄録

In this paper, two artificial neural networks (ANNs) are trained successfully to predict the CHF of thermosyphon and heat transfer coefficient of pool nucleate boiling respectively. The root mean square of predicated value are 16.43% and 19.57%, respectively. The analysis results indicate that CHF would be improved by inserting an inner tube in the thermosyphon. CHF increases initially as inner tube diameter increases and then decreases with the further increase of inner tube diameter. The heat transfer coefficient of pool nucleate boiling increases linearly as pressure increases, and when the pressure is close to the critical pressure, the increasing rate increases.

本文言語English
ページ(範囲)49-52
ページ数4
ジャーナルHedongli Gongcheng/Nuclear Power Engineering
31
SUPPL. 1
出版ステータスPublished - 2010 5

ASJC Scopus subject areas

  • Nuclear Energy and Engineering

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