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An Efficient 1-D Thermal Stratification Model for Pool-Type Sodium-Cooled Fast Reactors
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document.pdf
Description
Accepted version
Size
997.13 KB
Format
Adobe PDF
Checksum (MD5)
6b8980ef0eaf49b8fd08ad6cb1604f14
Author(s)
Lu, Cihang
Wu, Zeyun
Morgan, Sarah
Schneider, James
Anderson, Mark
Xu, Liangyu
Baglietto, Emilio
Bucknor, Matthew
Weathered, Matthew
Bilbao y Leon, Sama
Date Issued
2020
Journal
Nuclear Technology
Publisher
Informa UK Limited
Version
Author's final manuscript
Abstract
© 2020 American Nuclear Society. Investigating thermal stratification in the upper plenum of a sodium fast reactor (SFR) is currently a technology gap in SFR safety analysis. Understanding thermal stratification will promote safe operation of the SFR before its commercial deployment. Stratified layers of liquid sodium with a large vertical temperature gradient could be established in the upper plenum of an SFR during a down-power or a loss-of-flow transient. These stratified layers are unstable and could result in uncertainties for the core safety of an SFR. In order to predict the occurrence of the thermal stratification efficiently, we developed a one-dimensional (1-D) transport model to estimate the temperature profile of the ambient fluid in the upper plenum. This model demands much less computational effort than computational fluid dynamics (CFD) codes and provides calculations with higher fidelity than historical system-level codes. Two flow conditions were considered separately in the current study depending on if in-vessel components are presented in the upper plenum. For the condition where in-vessel components, specifically the upper internal structure, are presented, we assumed that the impinging sodium was evenly dispersed in the ambient fluid within the distance between the bottom of the in-vessel component and the jet inlet surface. For the condition where no in-vessel components are presented, we assumed that the impinging sodium was evenly dispersed in the ambient fluid within the jet length, which was determined through data-driven trainings. The newly developed 1-D model showed similar performance with the CFD model in both cases. However, due to the assumption of flat profiles of the impinging jet axial dispersion rate, nonnegligible discrepancies between the 1-D prediction and the measured data were observed.
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1080/00295450.2020.1719799
