Assessment of the CTF subchannel code for modeling a large-break loss-of-coolant accident reflood transient

Robert Salko, Aaron Wysocki, Belgacem Hizoum, Nathan Capps

Research output: Contribution to journalArticlepeer-review

Abstract

With increased industry interest in extending reactor operating cycles, the neams! (neams!) program has been investigating the behavior of high-burnup fuel during design basis accidents such as the lbloca! (lbloca!) with consideration for risk of ffrd! (ffrd!). As part of that activity, the neams! subchannel th! (th!) code, CTF, is being used for modeling of lbloca! and to determine the impact of subchannel resolution on results. Although CTF includes a wide range of models for lbloca! conditions, the code has not been used for this application while maintained at ornl! (ornl!) until now. Therefore, in this work, a preliminary assessment of several of these models was performed using openly available reflood experimental data from the feba! (feba!) tests. One coarse mesh and one fine mesh model were set up in CTF for high and low flooding rate tests performed in the unblocked feba! facility. A coarse TRACE model was set up to be as consistent as possible with the coarse CTF model to allow for code-to-code benchmarking. The assessment shows a tendency of the codes to over-predict pct! (pct!) near the top of the bundle and to quench early. Advanced spacer grid models were shown to improve upper bundle predictions in CTF. The resolved CTF model over-predicted pct! by a larger degree in the center channels in the low-flooding rate test, and it is believed that the radiative heat transfer model, which was not used in this study, may be needed to correct this over-prediction. Finally, this work demonstrates the importance of the droplet model in determining quench time and vapor temperature and pct! prediction, which necessitates a more in-depth validation of these models in the future.

Original languageEnglish
Article number110831
JournalAnnals of Nuclear Energy
Volume210
DOIs
StatePublished - Jan 2025

Keywords

  • CTF
  • FEBA
  • LOCA
  • ORNL

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