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Extension of GeN-Foam to departure from nucleate boiling prediction and validation against the OECD/NRC PSBT benchmark.

Authors :
Niu, Yuhang
Alessandro, Scolaro
Fiorina, Carlo
Qin, Hao
Lazare, Gauthier
Wu, Yingwei
Tian, Wenxi
Su, G.H.
Source :
Nuclear Engineering & Design. Jan2024, Vol. 416, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• GeN-Foam has been extended to predict the occurrence of DNB. • CHF look-up table and post-CHF flow and heat transfer models have been developed. • OECD/NRC PSBT benchmark (Phase II) is used to preliminarily validate the new solver. • Fluid temperatures in each sub-channel resulted within ±10 °C with respect to experimental values. • The predicted DNB power and time of occurrence fell within a ±10 % error range of the experimental values for all cases considered in this paper. The prediction of departure from nucleate boiling (DNB) has always been a crucial aspect of thermal-hydraulic codes for the analysis of Light Water Reactors. In this paper, GeN-Foam, a multi-physics code developed based on OpenFOAM, has been enhanced to incorporate DNB prediction using a CHF look-up table as well as post-CHF flow and heat transfer models. To assess GeN-Foam's accuracy in modeling DNB conditions in typical pressurized water reactors (PWRs), a preliminary validation was conducted utilizing Phase II of the PSBT benchmark, including the steady-state fluid temperature (Test Series 1), steady-state DNB (Test Series 4), and transient DNB (Test Series 11T) benchmarks. This paper presents the closure correlations implemented in GeN-Foam, provides a description of the PSBT benchmarks, and includes a comparison between GeN-Foam's predictions and experimental data, as well as code-to-code verification with other participants. The results demonstrate that GeN-Foam exhibits good performance in simulating two-phase flow boiling conditions. Furthermore, GeN-Foam accurately predicts the DNB power and time of occurrence within a ±10 % error range compared to measured values, preliminarily indicating its effectiveness in predicting DNB occurrence and two-phase flow boiling phenomena. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00295493
Volume :
416
Database :
Academic Search Index
Journal :
Nuclear Engineering & Design
Publication Type :
Academic Journal
Accession number :
174318385
Full Text :
https://doi.org/10.1016/j.nucengdes.2023.112748