Journal Published Online: 22 April 2011
Volume 8, Issue 4

Modeling Vertical Subcooled Boiling Flows at Low Pressures

CODEN: JAIOAD

Abstract

An improved wall heat flux partitioning model at the heated surface was developed by Yeoh This model, coupled with a three-dimensional two-fluid model and Multiple Size Group model, has led to satisfactory agreement being achieved between the model predictions and experimental measurements. Nevertheless, one shortcoming is the reliance on empirical correlations for the active nucleation site density in the wall heat flux partitioning model. This discrepancy brings about uncertainties, especially in appropriately evaluating the vapor generation rate, which greatly influences the model prediction on the axial and radial void fraction profiles within the bulk fluid flow. By considering the fractal model with the aforementioned subcooled boiling flow model in the absence of empirical correlations for the active nucleation site density, a comprehensive mechanistic model to predict vertically oriented subcooled boiling flows is developed. The proposed model is assessed against the experimental data of axial measurements of Zeitoun and Shoukri and the radial measurements of Yun and Lee for vertical subcooled boiling flows within annular channels. Improved model predictions are obtained when the model is compared against typically applied empirical correlations for active nucleation site density. Discussions on the agreement of other two-phase flow parameters are also presented.

Author Information

Yeoh, G.
Australian Nuclear Science and Technology Organisation (ANSTO), Kirrawee DC, New South Wales, Australia School of Mechanical and Manufacturing Engineering, Univ. of NSW, New South Wales, Australia
Cheung, S.
School of Aerospace, Mechanical and Manufacturing Engineering, RMIT Univ., Victoria, Australia
Tu, J.
School of Aerospace, Mechanical and Manufacturing Engineering, RMIT Univ., Victoria, Australia
Ho, M.
Australian Nuclear Science and Technology Organisation (ANSTO), Kirrawee DC, New South Wales, Australia
Pages: 20
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Stock #: JAI103374
ISSN: 1546-962X
DOI: 10.1520/JAI103374