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COMPUTATIONAL MULTISCALE FRAMEWORK FOR PREDICTING DIFFERENT FLOW REGIMES IN BUBBLY FLOW

DOI: 10.1615/ICHMT.2000.TherSieProcVol2.160
pages 80-81

Iztok Zun
Laboratory for Fluid Dynamics and Thermodynamics, Faculty of Mechanical Engineering, University of Ljubljana, Askerceva 6, 1000 Ljubljana, Slovenia

Abstract

Many modern engineering systems utilize two-phase flow with phase change because of its excellent heat transfer characteristics and high thermodynamic efficiency for energy conversion. Examples include: heat exchangers, steam generators, evaporators, boilers, condensers, nuclear reactors, chemical reactors, refrigeration cycles, air conditioners, electronic cooling units, combustion engines and cooling systems, and space craft propulsion and attitude control systems. However, available models for diabatic two-phase channel flow, including current generation computational models, are often inadequate for detailed analysis of multiphase flow and phase change heat transfer phenomena (Theofanous et al 2000). The difficulties stem from interfacial area evolution during boiling and condensation. Furthermore, the flow structure is almost always changing in both the lateral and axial directions. As a consequence, it is inherently multidimensional. Both the wall-to-fluid and phase-to-phase energy transfers affect the generation of interfacial area. From a practical point of view, one of the most urgent needs is the development of an accurate predictive method for boiling heat transfer and the associated thermal limits; in particular, critical heat flux (CHF) (Theofanous et al 2000).
The essence of two-phase flow with phase changes is the understanding of flow regime transitions. Indicators of flow regime transition depend upon the scale of observation. The five-step approach that we have followed for many years allows us to build up knowledge in a logical order and facilitates prioritization (Zun 1998, Zun 1999). A proposal is given to disassemble the complex diabatic bubbly flow process in a pipe into two frames, each including four steps that comprise different scales. The four steps are: (1) Identify structures that are known to exist, (2) Determine the spatial relationships between the various structures, (3) Study the spatio-temporal relationships between the structures, (4) Determine the statistical significance of the various structures, their apparent generation mechanism and any interaction events. The first frame considers disassembling the core flow structures that behave similarly to adiabatic conditions while the second frame considers initial conditions inside the heated layer that are rooted in microscale. To reassemble the complex process in numerical simulation, the cascade modeling is proposed under step (5) utilizing higher spatial resolution simulations to support lower spatial resolution modeling. At least six essentially different viewpoints can be used in reassembling the key processes on different scales: (a) Two-fluid four field (Lahey 1999), interfacial area transport (Ishii et al 1998), N+1 fluid (Tomiyama 1998), (b) Bubble tracking method on mesoscale 1 (Zun et al. 1993), (Tomiyama et al 1997), (c) Bubble interface tracking on mesoscale 2 (Tomiyama et al. 1994), (Tomiyama et al. 2000) (d) DNS of near-interface turbulence on microscale 1 (Banarjee et al. 1997) and (e) lattice-Boltzmann method on microscale 2 (Sehgal et al. 1999). Each method is applicable to the corresponding scale at a frozen time step for the environment that is defined by other scales. A way to model the complex process of diabatic bubble flow is shown based on these methods with a particular emphasis on bubble wake entrainment characteristics.

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