Turbulence Modelling of High-Pressure Convective Boiling Two-Phase Flows
NURETH-14 - 2011 September 25-30


Presented at:
NURETH-14
2011 September 25-30
Location:
Toronto, Canada
Session Title:
A2-1 Multifield Two-Phase Flow and Flow Regimes Identification and

Authors:
Jil Gueguen (CEA/Grenoble/Division for Nuclear Energy)
Fabrice Francois (CEA/Grenoble/Division for Nuclear Energy)
Hervé Lemonnier (CEA/Grenoble/Division for Nuclear Energy)
  

Abstract

This article is a contribution to the modelling of multidimensional high-pressure convective

boiling two-phase flows relative to PWR’s thermal hydraulics conditions.

Postulating that the turbulence is one possible physical mechanism for heat removal from the

wall towards the two-phase flow core, this work focuses on modelling turbulent transport terms

in the momentum and energy balance equations.

Using the pioneering work of Sato

et al.,

[1], [2], the momentum and the energy balance

equations are derived for a two-phase mixture. Such a system can be expressed as a combination

 

of parameters, which include the local void fraction as well as the fluid velocity profile, the wall

 

shear stress and the eddy diffusivity. By specifying a closure relation for this last parameter, a

 

numerical solution can be obtained. As a preliminary step towards a numerical solution, the

 

turbulent structure of the two-phase flow is expressed as a linear superposition of an inherent

 

liquid turbulence and an additional one due to the bubble agitation. On the basis of this theory,

 

the mixture velocity and temperature profiles can be predicted provided that the local void

 

fraction and the wall shear stress are known.

 

The model is then tested against the experimental data bank DEBORA (Garnier

 

 

et al.

, [3]) which

is devoted to the study of high pressure boiling flows. The first results are encouraging for the

 

mechanical part but some discrepancies are observed on temperature profiles for boiling tests.

 

This work should be continued in order to (i) improve the model especially for the thermal

 

aspects and (ii) identify the key parameters responsible for the heat flux limitation (DNB).

 

 

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