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Prediction of interfacial area transport in a coupled two-fluid model computation

  • Joshua P. Schlegel*
  • , Takashi Hibiki
  • , Xiuzhong Shen
  • , Santosh Appathurai
  • , Hariprasad Subramani
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

A computer code has been written to predict interfacial area transport within the framework of the two-fluid model. The suitability of various constitutive models was evaluated from a scientific and numerical standpoint, and selected models were used to close the two-fluid model. The resulting system was then used to optimize the empirical constants in the interfacial area transport equation for large diameter pipes. The optimized model was evaluated based on comparison with the data of Shen et al. and Schlegel et al. The optimization shows agreement with previous research conducted by Dave et al. and Talley et al. using TRACE-T, and reduced the RMS error in the interfacial area concentration prediction for the large diameter pipe data from 52.3% to 34.9%. The results also highlight a need for additional high-resolution data at multiple axial locations to provide a more detailed picture of the axial development of the flow. The results also indicate a need for improved modeling of the interfacial drag, especially for Taylor cap bubbles under relatively low void fraction conditions.
Original languageEnglish
Pages (from-to)58-73
JournalJournal of Nuclear Science and Technology
Volume54
Issue number1
DOIs
Publication statusPublished - 2 Jan 2017
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • computer code
  • fluid flow
  • interfacial area transport
  • light water reactor
  • optimization
  • Two-fluid model

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