Improved Drift-Flux Correlation to Enhance the Prediction of Void Fraction in Nuclear Reactor Fuel Bundles at Low Flow and Elevated Pressure Conditions
The EPRI (1991) and the Clark et al. (2014) drift-flux correlations implemented in RELAP5/MOD3 code were benchmarked against the low-pressure void fraction data collected by Clark et al. (2014) at Purdue University and the high-pressure data collected by Anklam and Miller (1982) at ORNL. The Clark et al. correlation (2014) was found to perform best at low pressures of Clark et al. tests (2014), but the accuracy was deteriorated at higher pressures of Anklam and Miller tests (1982). To account for this effect, a pressure scaling factor has been added to the distribution parameter correlation to reduce the distribution parameter peaking at high pressures. This factor is dependent on the density ratio and it eliminates the distribution parameter enhancement effect for pressures over 0.5 MPa. It was confirmed that the new correlation with the correction improved the void fraction prediction performance at a higher pressure of Anklam and Miller tests (1982). The new correlation provides a transition between the Clark et al. correlation (2014) at low pressures and the correlation of Ozaki et al. (2013) and Ozaki and Hibiki (2015) at high pressures, which is excellent both in physical characteristics and scalability of two-phase flow in rod bundles.
I. Kinoshita et al., "Improved Drift-Flux Correlation to Enhance the Prediction of Void Fraction in Nuclear Reactor Fuel Bundles at Low Flow and Elevated Pressure Conditions," Journal of Nuclear Science and Technology, vol. 57, no. 5, pp. 553-572, Taylor and Francis Ltd., May 2020.
The definitive version is available at https://doi.org/10.1080/00223131.2019.1700843
Nuclear Engineering and Radiation Science
Center for Research in Energy and Environment (CREE)
Second Research Center/Lab
Center for High Performance Computing Research
Keywords and Phrases
Drift-Flux Model; RELAP5; Rod Bundle; Void Fraction
International Standard Serial Number (ISSN)
Article - Journal
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01 May 2020