Conference Proceedings Paper
Dynamic Modeling Strategy for Flow Regime Transition in Gas-Liquid Two-Phase Flows
NURETH-14 - 2011 September 25-30
Xia Wang (The Ohio State University)
Xiaodong Sun (The Ohio State University)
Ben Doup (The Ohio State University)
Haihua Zhao (Idaho National Laboratory)
In modeling gas-liquid two-phase flows, the concept of flow regime has been widely used to characterize
the global interfacial structure of the flows. Nearly all constitutive relations that provide closures to the
interfacial transfers in two-phase flow models, such as the two-fluid model, are often flow regime
dependent. Currently, the determination of the flow regimes is primarily based on flow regime maps or
transition criteria, which were developed for steady-state, fully-developed flows and have been widely
applied in nuclear reactor system safety analysis codes. As two-phase flows are dynamic in nature (fullydeveloped
two-phase flows generally do not exist in real applications), it is of importance to model the
flow regime transition dynamically to be able to predict two-phase flows more accurately.
The present work aims to develop a dynamic modeling strategy to determine flow regimes in gas-liquid
two-phase flows through introduction of interfacial area transport equations (IATEs) within the
framework of a two-fluid model. The IATE is a transport equation that models the interfacial area
concentration by considering the creation and destruction of the interfacial area, such as the fluid particle
(bubble or liquid droplet) disintegration, boiling and evaporation; and fluid particle coalescence and
condensation, respectively. For the flow regimes beyond bubbly flows, a two-group IATE has been
proposed, in which bubbles are divided into two groups based on their size and shapes, namely group-1
and group-2 bubbles. A preliminary approach to dynamically identify the flow regimes is discussed, in
which discriminators are based on the predicted information, such as the void fraction and interfacial
area concentration. The flow regime predicted with this method shows good agreement with the
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