Abstract

The critical heat flux (CHF) is essential to the operational safety of nuclear power plants (NPP), and it plays a vital role in the thermal-hydraulic and structural design of a fuel assembly. In this study, the commercial computational fluid dynamics package STAR-CCM+ was used to predict the departure from the nucleate boiling (DNB) phenomenon. Based on the Eulerian two-fluid model and the extended Rensselaer Polytechnic Institute (RPI) wall boiling model combined with the Weisman-Pei bubble crowding model, the DNB phenomenon was investigated for two coolants (water and R134a) with different geometric structures and working conditions. The results demonstrated that one set of Eulerian two-fluid models could accurately predict the CHF within a certain range of working conditions. The CHF value calculated in this study show good agreement with the experimental measured CHF data, which indicated that the Eulerian two-fluid model had a good application prospect for CHF prediction. The observed mean error was less than 10%. The results of this study may contribute to an advanced boiling model development for CHF prediction in complex geometric structures such as fuel assembly. In addition, these results demonstrated that it was feasible to use the refrigerant R134a, which had a low critical pressure and low latent heat of vaporization, as the modeling fluid to replace water, which had a high latent heat of vaporization and a high critical pressure in the experimental study.

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