Purdue University Graduate School
Ph.D Dissertation Guanyi Wang_Final.pdf (7.2 MB)


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posted on 2021-10-12, 13:16 authored by Guanyi WangGuanyi Wang

To fully realize the advantages of the two-fluid model, the interfacial area concentration (IAC) should be properly given by a constitutive model. The conventional flow-regime-based IAC correlations intrinsically cannot predict the dynamic flow structure change and would introduce a discontinuity and numerical instability to system codes. As a promising alternative, the interfacial area transport equation (IATE) is developed to model the interface structure mechanistically. Progress has been achieved for IATE modeling in bubbly, slug, and churn-turbulent flow during the past two decades. Aiming at a comprehensive flow structure predictor for all flow regimes, further development in two directions is highly desirable. First is extending the current experiment and modeling capability from churn-turbulent to annular flow. In this study, an advanced four-sensor droplet capable conductivity probe (DCCP-4) is developed to capture all interfaces in churn-turbulent and annular flow, including liquid film, liquid droplet, gas core, and gas bubble. A first of a kind experimental database in churn-turbulent, annular, and wispy annular flow with two-dimensional spatial distributions is established, which provides the experimental basis for the multi-field two-phase flow model development. The measured parameters include local time-averaged volume faction, IAC, and velocity for various fields of annular flow. In addition, a new constitutive model to quantify the interfacial area between the gas core and liquid film of annular flow is developed, which fills the last theoretical gap of interfacial area modeling. The other important direction is improving the current IATE model to fulfill the dynamic prediction of developing flow, especially the bubbly to slug transition flow. Vertical-upward air-water two-phase flow experiments are performed. The state-of-the-art IATE model is evaluated against the newly collected data at bubbly and slug flow, and the result shows unsatisfactory performance in predicting the developing flow with intensive bubble coalescence. A new bubble coalescence model is derived by using the log-normal bubble size distribution, which significantly improves the model prediction capability.


Naval Nuclear Laboratory (Bettis Atomic Power Laboratory)


Degree Type

  • Doctor of Philosophy


  • Nuclear Engineering

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Mamoru Ishii

Additional Committee Member 2

Seungjin Kim

Additional Committee Member 3

Martin Lopez-De-Bertodano

Additional Committee Member 4

Steven T. Wereley