OPTIMIZATION OF TWO-PHASE FLOW MODELS AND ESTIMATION OF CROSS-FLOW IN FUEL ASSEMBLIES USING DATA ASSIMILATION

Atsushi Ui*, Tetsuhiro Ozaki, Takahiro Arai, Masahiro Furuya, Riichiro Okawa, Tsugumasa Iiyama, Shota Ueda

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Several model parameters affecting void fraction distribution of the subchannel analysis code CTF (previously called COBRA-TF) were selected, and a global sensitivity analysis was performed for the CRIEPI 5 × 5 fuel bundle void tests. Using the sensitivity analysis results as training data, a metamodel was developed with the Kriging method. The response variables such as bundle-averaged void fraction difference and residual void fraction deviation to the prior distributions of the model parameters were estimated from this metamodel, and the posterior distributions of the parameters were obtained so that the response variables would be close to the target distributions. It was confirmed that the bundle-averaged void fraction difference and residual void fraction deviation calculated by CTF could be improved with the parameter set optimized by the data assimilation. Furthermore, using the data assimilation method, the flow characteristics of the cross-flow between subchannels corresponding to the space between fuel rods were back-calculated to reproduce the measured void fraction.

Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalMultiphase Science and Technology
Volume34
Issue number2
DOIs
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • cross-flow
  • data assimilation
  • subchannel analysis
  • two-phase flow

ASJC Scopus subject areas

  • Modelling and Simulation
  • Condensed Matter Physics
  • Engineering(all)

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