Nonuniform heat transfer of supercritical water in a tight rod bundle – Assessment of correlations. (December 2017)

• Record Type: Journal Article
• Authors: Wang, Han; Bi, Qincheng; Wang, Linchuan; Leung, Laurence K.H.
• Is Part Of: Annals of nuclear energy. Volume 110(2017:Dec.)
• Page Start: 570
• Page End: 583
• Publication Date: 2017-12
• Subjects: Supercritical water -- Nonuniform heat transfer -- 2 × 2 rod bundle -- Empirical correlation; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2017.07.011
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Heat transfer experiment of supercritical water in a rod bundle was performed. Circumferential wall temperature and heat transfer coefficient were obtained. Extensive heat transfer correlations were assessed against the test data. Abstract: The heat transfer coefficient of supercritical water in a rod bundle is essential for the fuel design of the Supercritical Water-Cooled Reactor (SCWR). Although numerous correlations have been proposed over the past few decades to predict the heat transfer coefficient, the conclusions are inconsistent due to the limited experimental data obtained in fuel bundle. In the present paper, 20 correlations were assessed against the experimental data obtained in a tight 2 × 2 rod bundle. Circumferential maximum wall temperature and minimum heat transfer coefficient were selected as the benchmark data to get a conservative conclusion in support of the fuel design and safety analysis. The assessments showed that the performances of these correlations vary greatly depending on the mass flux and heat flux. Most correlations give reasonable Nusselt numbers at normal and enhanced heat transfer regimes, but become worse when the heat transfer is impaired. Comparison of these correlations against the total of 714 data indicated that the correlation proposed by Chen-Fang is the best with an average error of −0.44% and a standard deviation of 6.4%. All of the experimental Nusselt numbers were successfully predicted within ±20% error band.