Modeling sensitivity in prediction of interfacial area concentration in boiling flow

Longxiang Zhu, Zhiee Jhia Ooi, Caleb S. Brooks, Jianqiang Shan

Research output: Contribution to journalArticlepeer-review


A comprehensive review and validation of three approaches to predict interfacial area concentration in subcooled boiling flow are presented. The three methods are geometry-based semi-empirical correlations, empirical correlations, and the interfacial area transport equation (IATE). Extensive boiling experiment databases with the measurement of local interfacial area concentration and other local two-phase parameters are employed in the validation. The benchmark shows that the most suitable semi-empirical or empirical correlations chosen to predict the interfacial area concentration are different in the low void fraction region and high void fraction region. The closure model sensitivity in the IATE evaluation is analyzed for the bubble layer thickness models, point of net vapor generation (PNVG) determination approaches, and the presence of large cap and slug bubbles. The analysis of the bubble layer thickness model in IATE reveals that the model is necessary for subcooled boiling systems and the flat bubble layer thickness model is more appropriate than the triangle bubble layer thickness model. The result suggests a necessity of measuring the Point of Net Vapor Generation (PNVG) information in experiments for IATE calculation and the necessity of improvement to the PNVG models. The benchmark shows that the one-group IATE has exceptional performance in low group-2 void fraction region; while in high void fraction flows, the multi-group approach is needed to account for the different characteristics between small and large bubbles.

Original languageEnglish (US)
Article number103638
JournalProgress in Nuclear Energy
StatePublished - Mar 2021


  • Interfacial area concentration
  • Subcooled boiling
  • Two-fluid model
  • Two-phase flow
  • Validation

ASJC Scopus subject areas

  • Nuclear Energy and Engineering
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Waste Management and Disposal


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