Improvement of Gas Entrainment Prediction Method-Introduction of Surface Tension Effect

A gas entrainment (GE) prediction method has been developed to establish design criteria for the largescale sodium-cooled fast reactor (JSFR) systems. The prototype of the GE prediction method was already confirmed to give reasonable gas core lengths by simple calculation procedures. However, for si...

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Bibliographic Details
Published inJournal of nuclear science and technology Vol. 47; no. 9; pp. 771 - 778
Main Authors ITO, Kei, SAKAI, Takaaki, EGUCHI, Yuzuru, MONJI, Hideaki, OHSHIMA, Hiroyuki, UCHIBORI, Akihiro, XU, Yongze
Format Journal Article Conference Proceeding
LanguageEnglish
Published Tokyo Taylor & Francis Group 01.09.2010
Atomic Energy Society of Japan
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Summary:A gas entrainment (GE) prediction method has been developed to establish design criteria for the largescale sodium-cooled fast reactor (JSFR) systems. The prototype of the GE prediction method was already confirmed to give reasonable gas core lengths by simple calculation procedures. However, for simplification, the surface tension effects were neglected. In this paper, the evaluation accuracy of gas core lengths is improved by introducing the surface tension effects into the prototype GE prediction method. First, the mechanical balance between gravitational, centrifugal, and surface tension forces is considered. Then, the shape of a gas core tip is approximated by a quadratic function. Finally, using the approximated gas core shape, the authors determine the gas core length satisfying the mechanical balance. This improved GE prediction method is validated by analyzing the gas core lengths observed in simple experiments. Results show that the analytical gas core lengths calculated by the improved GE prediction method become shorter in comparison to the prototype GE prediction method, and are in good agreement with the experimental data. In addition, the experimental data under different temperature and surfactant concentration conditions are reproduced by the improved GE prediction method.
ISSN:0022-3131
1881-1248
DOI:10.1080/18811248.2010.9711653