# Simulation of Boiling Flow Experiments Close to CHF with  the Neptune_CFD Code

Authors: Boštjan Končar; Borut Mavko
Journal: Science and Technology of Nuclear Installations
 (2008)

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## Abstract

A three-dimensional two-fluid code Neptune_CFD has been validated against the Arizona State University (ASU) and DEBORA boiling flow experiments. Two-phase flow processes in the subcooled flow boiling regime have been studied on ASU experiments. Within this scope a new wall function has been implemented in the Neptune_CFD code aiming to improve the prediction of flow parameters in the near-wall region. The capability of the code to predict the boiling flow regime close to critical heat flux (CHF) conditions has been verified on selected DEBORA experiments. To predict the onset of CHF regime, a simplified model based on the near-wall values of gas volume fraction was used. The results have shown that the code is able to predict the wall temperature increase and the sharp void fraction peak near the heated wall, which are characteristic phenomena for CHF conditions.


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## Body

## 1. Introduction

In the case of offnormal
operation of the pressurized water reactor (increase of coolant inlet
temperature at full power and full pressure), a nucleate flow boiling on the
surface of the fuel rods may occur, which influences the operating and accident
conditions in several ways. The increase of vapour content due to the boiling
in narrow flow passages between the fuel rods increases the pressure drop
through the reactor core and reduces the moderation ability of the coolant
(effect on the core reactivity). When the applied heat flux reaches the CHF
value, the departure from nucleate boiling (DNB) may be observed, resulting in
rapid reduction of the heat removal ability. Overheating and consequently
damaging of the fuel rods may occur. A better understanding of this phenomenon
is a basis for optimization of fuel elements and for planning of appropriate
safety measures in the case of fuel rods overheating.In this study, the
capability of the three-dimensional code Neptune_CFD to simulate the local
boiling flow processes over a wide range of operating conditions, including
those close to CHF, has been assessed. This work has been carried out within
the scope of NURESIM project (NUclear REactor SIMulations, 6th EURATOM FP). The
main objective of the NURESIM activity related to CHF is to use two-phase computational
fluid dynamics (CFD) as a tool for understanding boiling flow processes. Numerical
simulations of boiling flows up to CHF conditions should help new fuel assembly
design and contribute to better local predictions of CHF phenomenon [1].The three-dimensional
two-fluid code Neptune_CFD [2] is developed within the framework of the Neptune project, financially supported by Commissariat à
l'Énergie Atomique (CEA), Électricité de France (EDF), Institut de
Radioprotection et de Sûreté Nucléaire (IRSN) and AREVA-NP. It has been more
specifically designed for simulation of transients in nuclear power plants and
it is currently used and further developed within the NURESIM project. To
validate the code, relevant benchmark experiments have to be used, which
provide useful local information about distributions of flow parameters (e.g.,
cross-sectional profiles of void fraction, phase velocities, temperature, bubbles
size, etc.). Nucleate boiling processes in the subcooled boiling regime were
studied on ASU experiments. Boiling flow close to CHF conditions was
investigated on the selected experiments performed in DEBORA facility located
at Commissariat à l'Énergie Atomique (CEA), Grenoble.


## 2. Experimental Data

The ASU and DEBORA
boiling flow experiments were used to validate the boiling model of the
Neptune_CFD code. Considered experimental facilities differ in the geometry of
the test channel (annulus, pipe) and also in working fluids. In ASU experiments
the refrigerant R-113 is used, while DEBORA facility uses the refrigerant R-12
as a working fluid. Density ratios and other scaling numbers are therefore
different.The measurement
section of the ASU experimental facility [3] consists of a vertical annular
channel with the heated inner tube with outer diameter of 15.8 mm and insulated
outer tube with inner diameter of 38.02 mm. The total length of the annulus is
3.66 m and the 2.75 m long upper part of the inner tube is heated by the direct
current. The 0.91 m long lower part of the annulus is not heated. The local
measurements of transversal profiles of void fraction, phase velocities,
velocity fluctuations, and liquid temperature were performed at a single axial
location located 1.99 m downstream from the beginning of the heated section.
The measurement probes and measurement techniques used in ASU experiments are
described in the original paper of Roy et al. [3].The DEBORA experiments (performed at CEA [4, 5]) were selected to analyze boiling processes close to CHF. The refrigerant
R-12 at the pressure conditions of about 30 bar has been used as the working
fluid to simulate steam-water flow at  pressurized
water reactor (PWR) conditions. The test section consists of a vertical pipe
with internal diameter of 19.2 mm, divided into three axial parts: the
adiabatic inlet section (1 m length), the heated section (3.5 m length), and the
adiabatic outlet section (≈0.5 m length). At
the end of the heated section, the radial profiles of void fraction, gas
velocity, and bubble diameter were measured by the optical probe. ASU and DEBORA experimental conditions are presented in Table 1.Table 1
ASU [3] and DEBORA [4, 5] experimental conditions.
Exp. No.pm.p. (bar)qw (kW/m2)G (kg/m2s)Tsat (°C)Tinlet (°C)ASU12.699556880.542.7ASU22.699578480.550.2ASU32.6911678480.550.2DEB1 [4]26.1573.89206486.6568.52DEB2 [5]30.0658.26994.994.1472.65DEB3 [5]30.0658.261007.494.1458.39


## 3. Physical Modelling in the Neptune_CFD Code

The basic model of
Neptune_CFD is the classical six-equation two-fluid model together withk-ε transport equations used for
modelling of the liquid phase turbulence [2]. The version V.1.0.6 has been used
to perform numerical simulations. Only some most relevant models and new model
improvements used for the computations presented in this study are described.


### 3.1. Turbulence Modelling

The turbulent
stress tensor for the liquid phase is modelled using the Boussinesq
approximation(1)τ¯lturb=−ρl〈u⇀l'u⇀l'〉=μlturb(∇u⇀l+(∇u⇀l)T)−23I¯(ρlkl+μlturb∇⋅u⇀l), where u⇀l' is the fluctuating part of liquid velocity, u⇀l is the liquid velocity in axial direction, kl is the turbulent kinetic
energy of liquid phase kl=0.5〈u⇀l'u⇀l'〉, I¯ is identity tensor, and μlturb is the eddy viscosity(2)μlturb=Cμρlkl2εl. Eddy viscosity in (2) is defined by
the turbulent kinetic energy kl and its dissipation rate εl, both calculated from the two-equation k-ε model. Parameter Cμ is set to 0.09. The effect of wakes behind the
bubbles on the liquid turbulence is taken into account by additional terms in k-ε transport equations. These additional source
terms represent the turbulent contribution of the gas phase on liquid
and are modelled as follows [4]:(3)Slk=−(M⇀D+M⇀AM)⋅(u⇀g−u⇀l),Slε=Cε3Slkτ, where M⇀D and M⇀AM are interfacial drag and added mass volumetric
forces and τ is a
characteristic time for bubble induced turbulence, which depends on bubble
departure diameter db and
dissipation rate εl:(4)τ=(db2εl)1/3.


### 3.2. Interfacial Transfer Terms

The interfacial transfer
of momentum is modelled by interfacial forces per unit volume, which include drag
forceM⇀D, added mass force M⇀AM, lift force M⇀L, and turbulent dispersion force M⇀TD. The interfacial drag force is calculated according to the Ishii correlation [6]
and the added mass force is calculated by Zuber model [7]. Turbulent dispersion
force, which considers the diffusion of the vapour phase due to the liquid
phase turbulence, is calculated as(5)F⇀TD=−CTDρlkl∇α, where CTD is the turbulent dispersion coefficient.The bubble
diameter in the bulkdb determines the interfacial momentum transfer and interfacial heat and mass
transfer. In the present work, constant values for bubble diameter have been
used. The approximate values (1.2 mm for ASU and 0.3 mm for DEBORA experiments)
were estimated from the available experimental data. The interfacial heat and
mass transfer due to condensation in the subcooled bulk flow is modelled by
Ranz-Marshall correlation [8]. Description of mass and heat transfer models is
given in the code manual [2].


### 3.3. Wall to Fluid Transfer Model at Conditions Close to CHF

To take into account the phenomenon of temperature excursion at CHF conditions, the standard
heat flux partitioning model of Kurul and Podowski [9] is extended by
additional heat transfer to the gas phase. To distribute the wall heat flux
between different phases, a phenomenological function fα1 is introduced. The function fα1 depends on liquid volume fraction α1 and takes care of the numerically smooth
transition between nucleate boiling regime and DNB regime. In the Neptune_CFD,
the transition to DNB regime is determined by an arbitrary value for liquid
volume fraction in the near-wall cell, set to α1cr=0.2(6)fα1=1−0.5⋅exp[−20(α1−α1cr)]forα1≥α1cr,fα1=0.5⋅(α1α1cr)20⋅α1crforα1<α1cr. The wall heat flux is then split into four different components(7)Φw=fα1(ΦC1+ΦQ+ΦE)+(1−fα1)ΦC2, where ΦC1 denotes the single-phase convection heat flux
to the liquid,  ΦQ denotes quenching heat flux that transfers
cold liquid from the bulk flow to the wall periodically, ΦE is the heat flux component needed to generate
vapor bubbles, and ΦC2 denotes the heat flux used to preheat the
vapor phase in the DNB regime. The first three heat flux components are
extensively described in the code manual [2] and in our previous references
[10, 11]. The convective heat flux to the vapor phase ΦC2 is modelled by a single-phase heat transfer at
the wall:(8)ΦC2=hlogg(Tw−Tg), where hlogg is the convective heat transfer coefficient in
the laminar regime [2], Tw is the wall temperature, and Tg is the temperature of the vapor phase. In the
case of standard nucleate boiling model the function fα1 is equal to one, leading to zero value of ΦC2. The proposed approach does not have the ambition to predict the CHF triggering
mechanism, but it is a promising attempt how to model the transition to DNB
conditions. Local CHF triggering mechanisms are much more complex and depend on
the microscale conditions, which cannot be resolved by CFD codes. Recently, Le
Corre and Yao [12]
have proposed a high resolution CHF model based on local wall hot spot
mechanism, which has a potential to bridge the gap between local modelling of
CHF mechanisms and implementation in the CFD codes.


### 3.4. Two-Phase Wall Law for Boiling Flows

At nucleate flow
boiling, the liquid velocity profile in the boiling boundary layer is
significantly disturbed by the bubble formation and detachment mechanisms on
the heated wall. The use of single-phase log law for boiling flow calculations
may lead to significant overprediction of liquid and gas velocities in the
boundary region near the heated wall [10, 13, 14]. In our previous work, [10] a
modified wall law following the formulation of Ramstorfer et al. [15] has been
proposed. The main idea of the new wall function is that nucleating bubbles on
the wall disturb the boundary layer flow in a similar way as the surface
roughness. As a basis, a logarithmic law for turbulent flows over rough walls
is used:(9)u+=1κln(y+)+B−Δu+, where velocity u+=ut/uw and distance from the wall y+=ρluwΔy/μl are written in nondimensional wall units
scaled by wall friction velocity uw=τw/ρl (τw is the wall shear stress). Here ut is the known velocity tangential to the wall and Δy is the distance from the wall. Coefficients κ and B are standard single-phase constants
with the values of 0.41 and 5.3, respectively. The last term in (9)
represents the offset of u+ due to the wall roughness:(10)Δu+={1κln(1+Ckrkr+),kr+>11.3,0,kr+≤11.3, where Ckr is a
roughness constant, which depends on the type of roughness (Cr=0.5
for sand-grain roughness) and kr+ is the roughness Reynolds number:(11)kr+=ρlkruτμl. The quantity kr represents the physical roughness height of
the surface. For kr+>11.3, the wall is considered to be smooth, otherwise the wall is rough. Although
Ramstorfer et al. [15] have studied the flow boiling in a horizontal channel this type of log-law may be applied to all
boiling flows where the flow motion along the wall is dominant. The
model assumes that the roughness height can be represented by a functional
dependence on the bubble departure diameter dbw and by the
contribution of nucleate boiling heat flux qnb to the total
heat flux qw:
(12)kr=ηdbw(qnbqw)ς=ηdbw(1−q1ϕqw)ς.In this study,
bubble departure diameter is calculated according to extended Unal model
[14].
The ratio of the nucleate boiling component to the total heat flux Φnb/Φ takes into account the thickening of the
boiling boundary layer with increasing boiling activity. The coefficients η and ζ in (12) are empirical parameters set to the
values η=0.5
and ζ=0.174 for the considered experimental cases.
The proposed “boiling” law of the wall is implemented in the Neptune_CFD code
in the form of blended linear-logarithmic wall function as follows:(13)u+=min(y+,1κln(y+)+B−Δu+). From this wall law the wall friction
velocity is computed, which is used as a “near-wall” boundary condition for the
liquid momentum equations.


## 3.1. Turbulence Modelling

The turbulent
stress tensor for the liquid phase is modelled using the Boussinesq
approximation(1)τ¯lturb=−ρl〈u⇀l'u⇀l'〉=μlturb(∇u⇀l+(∇u⇀l)T)−23I¯(ρlkl+μlturb∇⋅u⇀l), where u⇀l' is the fluctuating part of liquid velocity, u⇀l is the liquid velocity in axial direction, kl is the turbulent kinetic
energy of liquid phase kl=0.5〈u⇀l'u⇀l'〉, I¯ is identity tensor, and μlturb is the eddy viscosity(2)μlturb=Cμρlkl2εl. Eddy viscosity in (2) is defined by
the turbulent kinetic energy kl and its dissipation rate εl, both calculated from the two-equation k-ε model. Parameter Cμ is set to 0.09. The effect of wakes behind the
bubbles on the liquid turbulence is taken into account by additional terms in k-ε transport equations. These additional source
terms represent the turbulent contribution of the gas phase on liquid
and are modelled as follows [4]:(3)Slk=−(M⇀D+M⇀AM)⋅(u⇀g−u⇀l),Slε=Cε3Slkτ, where M⇀D and M⇀AM are interfacial drag and added mass volumetric
forces and τ is a
characteristic time for bubble induced turbulence, which depends on bubble
departure diameter db and
dissipation rate εl:(4)τ=(db2εl)1/3.


## 3.2. Interfacial Transfer Terms

The interfacial transfer
of momentum is modelled by interfacial forces per unit volume, which include drag
forceM⇀D, added mass force M⇀AM, lift force M⇀L, and turbulent dispersion force M⇀TD. The interfacial drag force is calculated according to the Ishii correlation [6]
and the added mass force is calculated by Zuber model [7]. Turbulent dispersion
force, which considers the diffusion of the vapour phase due to the liquid
phase turbulence, is calculated as(5)F⇀TD=−CTDρlkl∇α, where CTD is the turbulent dispersion coefficient.The bubble
diameter in the bulkdb determines the interfacial momentum transfer and interfacial heat and mass
transfer. In the present work, constant values for bubble diameter have been
used. The approximate values (1.2 mm for ASU and 0.3 mm for DEBORA experiments)
were estimated from the available experimental data. The interfacial heat and
mass transfer due to condensation in the subcooled bulk flow is modelled by
Ranz-Marshall correlation [8]. Description of mass and heat transfer models is
given in the code manual [2].


## 3.3. Wall to Fluid Transfer Model at Conditions Close to CHF

To take into account the phenomenon of temperature excursion at CHF conditions, the standard
heat flux partitioning model of Kurul and Podowski [9] is extended by
additional heat transfer to the gas phase. To distribute the wall heat flux
between different phases, a phenomenological function fα1 is introduced. The function fα1 depends on liquid volume fraction α1 and takes care of the numerically smooth
transition between nucleate boiling regime and DNB regime. In the Neptune_CFD,
the transition to DNB regime is determined by an arbitrary value for liquid
volume fraction in the near-wall cell, set to α1cr=0.2(6)fα1=1−0.5⋅exp[−20(α1−α1cr)]forα1≥α1cr,fα1=0.5⋅(α1α1cr)20⋅α1crforα1<α1cr. The wall heat flux is then split into four different components(7)Φw=fα1(ΦC1+ΦQ+ΦE)+(1−fα1)ΦC2, where ΦC1 denotes the single-phase convection heat flux
to the liquid,  ΦQ denotes quenching heat flux that transfers
cold liquid from the bulk flow to the wall periodically, ΦE is the heat flux component needed to generate
vapor bubbles, and ΦC2 denotes the heat flux used to preheat the
vapor phase in the DNB regime. The first three heat flux components are
extensively described in the code manual [2] and in our previous references
[10, 11]. The convective heat flux to the vapor phase ΦC2 is modelled by a single-phase heat transfer at
the wall:(8)ΦC2=hlogg(Tw−Tg), where hlogg is the convective heat transfer coefficient in
the laminar regime [2], Tw is the wall temperature, and Tg is the temperature of the vapor phase. In the
case of standard nucleate boiling model the function fα1 is equal to one, leading to zero value of ΦC2. The proposed approach does not have the ambition to predict the CHF triggering
mechanism, but it is a promising attempt how to model the transition to DNB
conditions. Local CHF triggering mechanisms are much more complex and depend on
the microscale conditions, which cannot be resolved by CFD codes. Recently, Le
Corre and Yao [12]
have proposed a high resolution CHF model based on local wall hot spot
mechanism, which has a potential to bridge the gap between local modelling of
CHF mechanisms and implementation in the CFD codes.


## 3.4. Two-Phase Wall Law for Boiling Flows

At nucleate flow
boiling, the liquid velocity profile in the boiling boundary layer is
significantly disturbed by the bubble formation and detachment mechanisms on
the heated wall. The use of single-phase log law for boiling flow calculations
may lead to significant overprediction of liquid and gas velocities in the
boundary region near the heated wall [10, 13, 14]. In our previous work, [10] a
modified wall law following the formulation of Ramstorfer et al. [15] has been
proposed. The main idea of the new wall function is that nucleating bubbles on
the wall disturb the boundary layer flow in a similar way as the surface
roughness. As a basis, a logarithmic law for turbulent flows over rough walls
is used:(9)u+=1κln(y+)+B−Δu+, where velocity u+=ut/uw and distance from the wall y+=ρluwΔy/μl are written in nondimensional wall units
scaled by wall friction velocity uw=τw/ρl (τw is the wall shear stress). Here ut is the known velocity tangential to the wall and Δy is the distance from the wall. Coefficients κ and B are standard single-phase constants
with the values of 0.41 and 5.3, respectively. The last term in (9)
represents the offset of u+ due to the wall roughness:(10)Δu+={1κln(1+Ckrkr+),kr+>11.3,0,kr+≤11.3, where Ckr is a
roughness constant, which depends on the type of roughness (Cr=0.5
for sand-grain roughness) and kr+ is the roughness Reynolds number:(11)kr+=ρlkruτμl. The quantity kr represents the physical roughness height of
the surface. For kr+>11.3, the wall is considered to be smooth, otherwise the wall is rough. Although
Ramstorfer et al. [15] have studied the flow boiling in a horizontal channel this type of log-law may be applied to all
boiling flows where the flow motion along the wall is dominant. The
model assumes that the roughness height can be represented by a functional
dependence on the bubble departure diameter dbw and by the
contribution of nucleate boiling heat flux qnb to the total
heat flux qw:
(12)kr=ηdbw(qnbqw)ς=ηdbw(1−q1ϕqw)ς.In this study,
bubble departure diameter is calculated according to extended Unal model
[14].
The ratio of the nucleate boiling component to the total heat flux Φnb/Φ takes into account the thickening of the
boiling boundary layer with increasing boiling activity. The coefficients η and ζ in (12) are empirical parameters set to the
values η=0.5
and ζ=0.174 for the considered experimental cases.
The proposed “boiling” law of the wall is implemented in the Neptune_CFD code
in the form of blended linear-logarithmic wall function as follows:(13)u+=min(y+,1κln(y+)+B−Δu+). From this wall law the wall friction
velocity is computed, which is used as a “near-wall” boundary condition for the
liquid momentum equations.


## 4. Results

Experiments
presented in Table1 were simulated. The calculations for ASU and DEBORA experiments
were performed on 2D numerical meshes (19×220 for ASU and 20×220 for DEBORA),
where the lower number denotes the number of cells in radial direction. These
meshes were selected as a reasonable compromise between the numerical accuracy
and the computational effort [4, 10].The heat transfer
regime in ASU experiments is subcooled nucleate boiling, significantly below
the CHF conditions. In this regime local nucleate boiling processes governing
the lateral distribution of flow parameters were studied. In Figures1 to 5 two
different Neptune_CFD calculations are validated against ASU experiments. The
calculations differ in wall function models. The “base” calculation uses
standard single-phase law of the wall, whereas “wall func” calculation uses
modified wall function model as described in Section 3.4. Other models,
described in Section 3, are the same for both calculations.ASU experiments: void fraction profile.
(a)(b)(c)Radial void
fraction profiles are shown in Figure1. The “wall func” simulation predicts
somewhat wider boiling region comparing to the base calculation. The
calculation of the axial gas velocity depends on the model for interfacial drag
and interfacial area density (e.g., bubble size) whereas the axial liquid
velocity profile in the wall boundary layer mainly depends on the wall friction,
determined by the velocity wall function. Other influencing parameters are
nondrag forces. The liquid and gas axial velocities are compared in Figures 2
and 3. The “base” calculation significantly overpredicts measured phase
velocities for all experimental cases. In the calculation with the new wall
function model, the liquid velocity adjacent to the wall is significantly
decreased and is closer to the measured data, but overprediction somewhat away
from the wall is still notable. Due to the coupling through the interfacial
drag, a similar trend of decreased velocity near the heated wall may be
observed also for the gas phase (Figure 3). In this case, the agreement between
the “wall func” calculation and experiments is significantly improved over the
entire gas velocity profile.ASU experiments: liquid velocity profile.
(a)(b)(c)ASU experiments: gas velocity profile.
(a)(b)(c)Turbulent kinetic
energy profiles are presented in Figure4. The measurements showed that
turbulent kinetic energy is the highest in the boiling region near the inner
wall and then rapidly decreases towards centre of the channel. This trend was
not adequately reproduced by the “base” calculation, whose kl profile tends to be more gradual. The “base”
calculation also significantly overpredicts the kl values for ASU3 experiment. The “wall func”
calculation gives improved prediction of the kl profile for the experiment ASU3 over the entire
channel cross-section but still overestimates measured data for the other two experiments.
Due to the new wall function model, the calculated values of kl are
very high near the wall. In spite of discrepancies between
the measured and simulated results, “wall func” calculations and measurements
show similar trend-most of the turbulent kinetic energy
production occurs in the boiling region close to the inner wall.ASU experiments: turbulent kinetic energy profile.
(a)(b)(c)ASU experiments: liquid temperature.
(a)(b)(c)The liquid
temperature profiles are compared in Figure5. For both calculations, a
reasonable agreement with experiments may be observed for all cases. The
temperature profile is somewhat steeper in the case of “wall func” calculation.The simulation
results for DEBORA experiments are presented in Figures6, 7, 8, and 9. The calculation
denoted as “base” includes the models described in Section 3; the wall function
is standard single-phase log law. In the calculation “CTD=2,” the turbulent
dispersion coefficient CTD in (4) is increased to the value of 2. Three different experimental cases (see
Table 1) with significantly different operating conditions are simulated.
According to the measured void fraction profile, the experiment DEB2 is
supposed to be close to DNB, since a sharp increase of void fraction is
observed near the heated wall. Radial void fraction profiles in Figure 6 are
best predicted by the modified calculation with turbulent dispersion
coefficient, though the profiles are smoother and underpredict the near-wall
values. Especially in the case of DEB1 experiment, the “base” calculation
strongly overpredicts measured void fraction on the heated wall, whereas the
calculated void fraction in the centre of the pipe is too low. Both
calculations are able to predict a void fraction jump near the wall at DEB2
experiment.DEBORA experiments: void fraction profile.
(a)(b)(c)DEBORA experiments: gas velocity profile.
(a)(b)(c)DEBORA experiments: liquid temperature profile.
(a)(b)(c)Figure 9
DEBORA experiments: distribution of heat flux components.Gas velocity
profiles are presented in Figure7. In general, both calculations tend to
overpredict the measured gas velocities in the near-wall region. A better
agreement can be observed in for DEB1 experiment, which has a higher mass flow
rate and heat flux than the other two experiments. The experiments DEB2 and DEB3
differ only in the inlet temperature. The simulations with increased CTD
give profiles closer to measured data. The measured liquid temperature profile is available only for
DEB1 experiment. Like in the case of other flow
parameters, the calculation with increased CTD predicts smoother
temperature profiles closer to experimental data.Distribution of heat flux components for DEB2 case is presented in
Figure9. Heat fluxes are multiplied by function fα1 according to (6). The liquid single-phase convection component ΦC1 decreases
with increasing evaporation heat flux ΦE. Towards the end of the heated channel the
convective heat flux to the gas phase ΦC2 is
activated, which denotes the onset of CHF conditions. According to (6), the
incipience of CHF is defined by function fα1 and predefined near-wall void fraction value 0.8 (Figure 10). Although the wall
temperature shows fluctuating behavior along the wall after the onset of CHF,
the temperature excursion at CHF is fair predicted (Figure 10).Figure 10
DEBORA experiments: axial distribution of near-wall void fraction,fα1, wall temperature, saturation temperature.


## 5. Conclusions

The set of ASU and
DEBORA boiling flow experiments have been calculated with the version V1.0.6 of
the Neptune_CFD code. The distribution of flow parameters in the subcooled
boiling regime was studied on ASU experiments. Within this scope, a new wall
function model based on the surface roughness analogy has been implemented,
leading to improved agreement of flow parameters with measured data.The capability of
the code to predict boiling flow phenomena close to CHF conditions was tested
on the selected DEBORA experiment. Though the simplified model for the onset of
CHF was used, it was demonstrated that the code is able to predict the wall
temperature increase and the sharp void fraction peak characteristic for CHF
conditions. However, it should be emphasized that more generic CHF criteria
based on physical mechanisms need to be developed. Further investigations of critical
heat flux mechanisms are therefore necessary, both experimentally and numerically.



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*Source: 732158-2008-10-27.xml*