AIAD_Hoehne (3)

Experiments and numerical simulations of horizontal two-phase flow regimes

using an interfacial area density model

Thomas Hhne, Christophe Valle Forschungszentrum Dresden-Rossendorf e.V.,

P.O. Box: 510119, 01314 Dresden, Germany

[Received date; Accepted date] to be inserted later

Abstract Stratified two-phase flow regimes can occur in the main cooling lines of Pressurized

Water Reactors, Chemical plants and Oil pipelines. A relevant problem occurring is

the development of wavy stratified flows, which can lead to slug generation. In the last

decade, stratified flows have increasingly been modelled with computational fluid

dynamics (CFD) codes. In CFD, closure models are required that must be validated.

Recent improvements of the multiphase flow modelling in the ANSYS CFX code,

now make it possible to simulate these mechanisms in detail. In order to validate

existing and further developed multiphase flow models, a high spatial and temporal

resolution of measurement data are required. For the experimental investigation of co-

current air/water flows, the HAWAC (Horizontal Air/Water Channel) was built. The

channel allows in particular the study of air/water slug flow under atmospheric

pressure. Parallel to the experiments, CFD calculations were carried out. The two-fluid

model was applied with a special turbulence damping procedure at the free surface. An

Algebraic Interfacial Area Density (AIAD) model based on the implemented mixture

model was introduced, which allows the detection of the morphological form of the

two-phase flow and the corresponding switching via a blending function of each

correlation from one object pair to another. As a result, this model can distinguish

between bubbles, droplets and the free surface using the local value of the volume

fraction of the liquid phase. The behaviour of slug generation and propagation was

qualitatively reproduced by the simulation, while local deviations require a

continuation of the work.

INTRODUCTION Stratified two-phase flows occur in many industrial applications. The effects of the flow on the

quantities (such as flow rate, pressure drop and flow regimes) have always been of engineering

interest. Wallis (1973) analysed the onset of slugging in horizontal and near horizontal gas-liquid

flows. A prediction of horizontal flow regime transitions in pipes was introduced by Taitel and

Dukler (1976). They explained the formation of slug flow by the Kelvin-Helmholtz instability.

They also proposed a model for the frequency of slug initiation (1977). The viscous Kelvin-

Helmholtz analysis proposed by Lin & Hanratty (1986) generally gives better predictions for the

onset of slug flow. A general overview of the phenomenological modelling of slug flow was given

by Hewitt (2003). Various multidimensional numerical models were developed to simulate

stratified flows: Marker and Cell (Harlow and Welch, 1965), Lagrangian grid methods (Hirt et al.,

1974), Volume of Fluid method (Hirt and Nichols, 1981) and Level set method (Osher and

Sethian, 1988). These methods can in principle capture accurately most of the physics of the

stratified flows. However, they cannot capture all the morphological formations such as small

bubbles and droplets, if the grid is not reasonably small enough. One of the first attempts to

simulate mixed flows was presented by erne et al. (2001) who coupled the VOF method with a two-fluid model in order to bring together the advantages of the both analytical formulations. Issa

Experiments and numerical simulations of horizontal two phase flow regimes using an interfacial area density model

The Journal of Computational Multiphase Flows

2

(2003) worked on multi-fluid simulation of slugging phenomena in horizontal channels and

showed a mechanistic approach to the prediction of hydrodynamic slug initiation, growth and

subsequent development into continuous slug flow in pipelines. A systematic study of numerical

simulation of slug flow in horizontal pipes using the two-fluid formulation was carried out by

Frank (2003). It was shown that the formation of the slug flow regime strongly depends on the

wall friction of the liquid phase. In simulations using inlet/outlet boundary conditions, it was

found that the formation of slug flow regimes strongly depends on the agitation or perturbation of

the inlet boundary conditions. Furthermore, Frank (2003) showed that the length of the

computational domain plays an important role in slug formation. However, direct comparisons

between CFD calculations and measurements of the slug generation mechanisms and its

propagation in horizontal pipes were not performed.

For the experimental investigation of air/water flows, the HAWAC (Horizontal Air/Water

Channel) with a rectangular cross-section was built at Forschungszentrum Dresden-Rossendorf

(FZD). Its inlet device provides defined inlet boundary conditions. The channel allows in

particular the study of air/water slug flow under atmospheric pressure. Parallel to the experiments,

CFD calculations were carried out (Valle and Hhne et al., 2008). The aim of the numerical

simulations presented in this paper is the validation of the prediction of slug flow with newly

developed and implemented multiphase flow models in the code ANSYS CFX.

HAWAC The Horizontal Air/Water Channel (HAWAC) (Fig. 1) is devoted to co-current flow experiments.

A special inlet device provides defined inlet boundary conditions by a separate injection of water

and air into the test-section. A blade separating the phases can be moved up and down to control

the free inlet cross-section for each phase, which influences the evolution of the two-phase flow

regime. The cross-section of this channel is smaller than the channel used in an earlier study

described in Valle and Hhne et al., 2008: its dimensions are 100 x 30 mm (height x width). The

test-section is about 8 m long, and therefore the length-to-height ratio L/h is 80. In terms of the

hydraulic diameter, the dimensionless length of the channel is L/Dh = 173.

Fig. 1: Schematic view of the horizontal channel with inlet device for a separate injection

of water and air into the test-section

pump

air outlet

inlet device

air inlet

8 m

GV

LV

wire mesh filters

Thomas Hhne, Christophe Valle

Volume 1 Number 1 2009

3

Fig. 2: The inlet device

The inlet device (Fig. 2) is designed for a separate injection of water and air into the channel. The

air flows through the upper part and the water through the lower part of this device. As the inlet

geometry introduces many perturbations into the flow (bends, transition from pipes to rectangular

cross-section), 4 wire-mesh filters are mounted in each part of the inlet device. The filters are

made of stainless steel wires with a diameter of 0.63 mm and have a mesh size of 1.06 mm. The

wire-mesh filters are used provide homogenous velocity profiles at the test-section inlet.

Moreover, the filters produce a pressure drop that attenuates the effect of the pressure surge

created by slug flow on the fluid supply systems.

Air and water come in contact at the final edge of a 500 mm long blade that divides both phases

downstream of the filter segment. The free inlet cross-section for each phase can be controlled by

inclining this blade up and down. In this way, the perturbation caused by the first contact between

gas and liquid can be either minimised or, if required, a perturbation can be introduced (e.g.

hydraulic jump). Both, filters and inclinable blade, provide well-defined inlet boundary conditions

for the CFD model and therefore offer very good validation possibilities. Optical measurements

were performed with a high-speed video camera.

FREE SURFACE MODELING The CFD simulation of free surface flows can be performed using the multi-fluid Euler-Euler

modelling approach available in ANSYS CFX. Detailed derivation of the two-fluid model can be

found in the book of Ishii and Hibiki (2006). However, it requires careful treatment of several

aspects of the model:

o The interfacial area density should satisfy the integral volume balance condition. In the

case of when surface waves are present, their contribution to the interfacial area density

should be taken into account.

o The turbulence model should address the damping of turbulence near the free surface.

o The interphase momentum models should take into account the surface morphology.

o Turbulence damping at the free surface must also be considered.

Algebraic Interfacial Area Density (AIAD) Model

Fig. 3 shows different morphologies at slug flow conditions. Separate models are necessary for

dispersed particles and separated continuous phases (interfacial drag etc.). Two approaches are

possible within the Euler-Euler methodology:

Fig. 3: Different morphologies at slug flow conditions

o Four phases: Bubble/Droplet generation and degassing have to be implemented as

sources and sinks

Droplets

Bubbles

Air (cont.)

Water(cont.)

inclinable blade

control rod

air inlet

water inlet



4

o Two phases: Momentum exchange coefficients depend on local morphology

For the second approach, Egorov (2004) proposed an Algebraic Interfacial Area Density (AIAD)

Model. The basic idea of the model is:

o The interfacial area density allows the detection of the morphological form and the

corresponding switching of each correlation from one object pair to another.

o It provides a law for the interfacial area density and the drag coefficient for full range

0r1 (Fig. 4). o The model improves the physical modelling in the asymptotic limits of bubbly and

droplet flows.

o The interfacial area density in the intermediate range is set to the interfacial area density

for free surface (Fig. 4).

Fig. 4: Air volume fraction and corresponding morphologies/ models

In an Euler-Euler simulation of horizontal slug,

the air entrainment below the water surface can

be caused by the drag force. The magnitude of

the force density for the drag is

2

2

1|| UACD D = (1)

where CD is the drag coefficient, A the interfacial area density and the density of the continuous phase (if the other phase is a dispersed phase). U is the relative velocity between the two phases.

The AIAD model applies three different drag coefficients, CD,B for bubbles, CD,D for the droplets

and CD,FS for free surface. Non-drag forces (e.g. lift force and turbulent dispersion force) are

neglected. The interfacial area density A also depends on the morphology of the phases. For

bubbles it is

B

G

d

rA

6= (2)

where dB is the bubble diameter and rG is the gas void fraction. For a free surface the interfacial

area density is

(3)

is applied as an average density is applied, i.e.

(4)

where rL and rG are the liquid and the gas phase density respectively. In the bubbly regime, where

rG is low, the average density is close to the liquid phase density L. According to the flow regime (bubbly flow, droplet flow or stratified flow with a free surface) the corresponding drag

coefficients and interfacial area densities have to be applied (Fig. 4).

n

rrA LLFS

==

LLGG rr +=

1=G

0=G

Free surface region

Bubble region

BBD AC ;,

FSFSD AC ;,

Droplet region DDD AC ;,



5

The simplest switching procedure for the interfacial area density uses the blending function f. Such

functions introduce void fraction limits, the weights for flow regimes and length scales for bubbly

and droplet flow (dB, dD), which are defined in the following equations:

(5)

(6)

(7)

(8)

(9)

Fig. 7 shows different blending functions f for different volume fraction limits and blending

coefficients.

For the simulation of slug flow the void fraction limits of rB,limit=0.3 resp. rD,limit=0.3 and blending

coefficients of aB=aD=70 were used.

Modelling the free surface drag

In simulations of free surface flows, eq. (1) does not represent a realistic physical model. It is

reasonable to expect that the velocities of both fluids in the vicinity of the interface are rather

similar. To achieve this result, it is assumed that the shear stress near the surface behaves like a

wall shear stress on both sides of the interface in order to reduce the velocity differences of both

phases.

A viscous fluid moving along a solid like boundary will incur a shear stress, the no-slip

condition. It is assumed that the morphology region free surface is acting like a wall and a wall

like shear stress is introduced at the free surface which influences the loss of gas velocity shown in

Fig. 5:

. (10)

Figure 5: Air velocity near the free surface dependent on the normal vectors

The components of the Normal vector at the free surface are taken from the gradients of the void

fraction in all directions. As a result, the modified drag coefficient is dependent on the viscosities

of both phases, the local gradients of gas/liquid velocities normal to the free surface, the liquid

density and the slip velocity between the phases:

( ),limit1

1 B G Ba r r

Bf e

= +

( ),limit1

1 D L Da r r

Df e

= +

1FS B Df f f=

, , ,FS FS B B D DA f A f A f A = + +

, , ,D FS D FS B D B D D DC f C f C f C= + +

0=

=

yW y

u

Normal vectors at the free surface



6

[ ]

2

,,2

U

rrC

L

GWGLWL

D

+=

(11)

Turbulence Damping

As the goal of the CFD calculation was to induce surface instabilities, which generate waves and

slugs, the interfacial momentum exchange and the turbulence parameters had to be modelled

correctly. Without any special treatment of the free surface, the high velocity gradients at the free

surface, especially in the gaseous phase, generate levels of turbulence that are too high throughout

the two-phase flow when using the differential eddy viscosity models like the k- or the k- model. Therefore, a certain amount of damping of turbulence is necessary in the region of the

interface, because the mesh is too coarse to resolve the velocity gradient in the gas phase at the

interface. A few empirical models have been suggested, which address the turbulence anisotropy

at the free surface, see among others Celik and Rodi (1984). However, no model is applicable for a

wide range of flow conditions, and all of them are non-local: they require for example explicit

specification of the liquid layer thickness, of the amplitude and period of surface waves, etc.

Direct and Large-Eddy Simulation of turbulent multi-material flow have been applied to model

surface waves. Specifically, the work of Reboux, Sagaut and Lakehal (2006) used DNS to quantify

the damping of turbulence approaching the interface and incorporated this knowledge into the

damping of LES turbulence models. Nourgaliev, Liou and Theofanous (2008), Boeck and Zaleski

(2005), Coward, Renardy and Renardy (1997) reported representations of surface instabilities that

were obtained by DNS.

For the two-fluid formulation, Egorov (2004) proposed a symmetric damping procedure. This

procedure provides a solid wall-like damping of turbulence in both gas and liquid phases. It is

based on the standard -equation, formulated by Wilcox (1994) as follows:

( ) ( ) ( )[ ]++=+

t

2

t Sk

Ut

(12)

where = 0.52 and = 0.075 are the k- model closure coefficients of the generation and the destruction terms in the -equation, = 0.5 is the inverse of the turbulent Prandtl number for , t is the Reynolds stress tensor, and S is the strain-rate tensor. In order to mimic the turbulence damping near the free surface, a source term is introduced on the right hand side of the gas and

liquid phase -equations. The factor A activates this source term only at the free surface, where it cancels the standard -destruction term of the -equation ( )2iiir and enforces the required high value of i and thus the turbulence damping.

BOUNDARY CONDITIONS The HAWAC channel with rectangular cross-section was modelled using ANSYS CFX. The

model dimensions are 8000 x 100 x 30 mm (length x height x width) (Fig. 6a). The grid consists

of 1.2x106 hexahedral elements. A slug flow experiment at a superficial water velocity of 1.0 m/s

and a superficial air velocity of 5.0 m/s was chosen for the CFD calculations. In the experiment,

the inlet blade was in horizontal position. Accordingly, the model inlet was divided into two parts:

in the lower half of the inlet cross-section, water was injected and air in the upper half. The inlet

blade was modelled (Fig. 6a). An initial water level of y0 = 50 mm was assumed for the entire

model length (Fig. 6b). In the simulation, both phases have been treated as isothermal and

incompressible, at 25C and at a reference pressure of 1 bar. A hydrostatic pressure was assumed

for the liquid phase. Buoyancy effects between the two phases are taken into account by the

directed gravity term. At the inlet, the turbulence properties were set using the Medium intensity

and Eddy viscosity ratio option of the flow solver. This is equivalent to a turbulence intensity of

5% in both phases. The inner surface of the channel walls has been defined as hydraulically

smooth with a non-slip boundary condition applied to both gaseous and liquid phases. The channel

outlet was modelled with a pressure controlled outlet boundary condition. The parallel transient

calculation of 15.0 s of simulation time on 4 processors took 10 CPU days. A high-resolution



7

discretization scheme was used. For time integration, the fully implicit second order backward

Euler method was applied with a constant time step of dt = 0.001 s and a maximum of 15

coefficient loops. Convergence was defined in terms of the RMS values of the residuals, which

could assured to be less then 10-4

most of the time. The implementation of the AIAD model and

turbulence damping functions into CFX was done via the command language CCL.

a) Fluid domain (channel with inlet

blade in horizontal position)

b) Air volume fraction, initial state (Zoom) [-]

Fig. 6: Model and initial conditions of the volume fractions

RESULTS: COMPARISON BETWEEN SIMULATION AND EXPERIMENT A simulated free surface at the HAWAC channel (Fig. 6) with small surface instabilities is shown

in Fig. 8. Fig. 9 shows the resulting interfacial area density variable. The AIAD model uses the

following three different drag coefficients: CD,B = 0.44 for bubbles, CD,D = 0.44 for the droplets

and CD,S according to eq. 11 for the free surface (see Fig. 10).

In the picture sequences (Fig. 11 and 12), a comparison is presented between a CFD calculation

and an experiment: the calculated phase distribution is visualized and comparable camera frames

are shown. In both cases, a slug is generated. The sequences show that the qualitative behaviour of

the creation and propagation of the slug is similar in both the experiment and the CFD calculation.

!"

!"#

# !"#

Figure 7: Blending functions fB blending

coeff.

Figure 8: Air volume fraction [-]



8

Figure 9: Interfacial area density variable

[m-1

]

Figure 10: Drag coefficient [-]

Fig. 11: Measured picture sequence at JL = 1.0 m/s and JG = 5.0 m/s with t = 50 ms

(depicted part of the channel: 0 to 3.2 m after the inlet)

Fig. 12: Calculated picture sequence at JL = 1.0 m/s and JG = 5.0 m/s (depicted part of the

channel: 1.4 to 6 m after the inlet)

In this CFD calculation the inlet device was not modelled. Fig. 12 shows the development of the

slug. These slugs are induced only by instabilities. These single effects leading to slug flow that

can be simulated here are:

o Instabilities and small waves randomly generated by the interfacial momentum transfer.

As a result, bigger waves are generated.

o The waves can have different velocities and can merge together.

o Bigger waves roll over smaller waves and can close the channel cross-section.



9

In order to extract quantitative information from the calculation as well as from the measurements,

interface capture methods were developed. Moreover, a statistical treatment of the data is proposed

for the comparison between both results.

Interface capture in the high-speed video observations

To capture the gas-liquid interface in the camera frames, an image-processing algorithm was

developed. The capture method illustrated in Fig. 13 consists of the following steps:

1. the synthesis of a background from the picture sequence by filtering out its dynamic

component (Fig. 13-b);

2. a background subtraction with the image generated in step 1 (Fig. 13-c);

3. a pixel detection in each vertical line:

a. of the darkest pixel;

b. of the minimum of a grey-level time variation;

4. selection of the pixels detected in step 3 that best fit onto a continuous interface line (Fig.

13-d).

The capture method allows the representation of the interface by a water level as function of the

duct length z and the time t. The accuracy of the interface detection algorithm depends on the

thickness of the interface in the images. In the stratified flow regions, the interface thickness is

quite thin with at most 3 pixels. Therefore, the accuracy of the water level measurement is there

about 1.5 pixels. This corresponds to 3.9 mm for a picture resolution of about 2.6 mm/pixel in

this experiment. The accuracy is worse in the region of the slug front, where a two-phase mixture

is generated (red circle in Fig. 13-c). This makes a definition of the water level difficult and

sometimes induces unphysical fluctuations in the detected interface. In particular, at the end of the

visualised region (further than 2.5 m from the inlet), where the slugs are developed the

interpretation of the water level measurement is sometimes quite delicate.

Interface capture in the CFD simulation

Contrary to the interface tracking methods, the two-fluid model does not reproduce a sharp

interface between air and water. Nevertheless, for the comparison between the CFD calculation

and experimental results, a surface similar to the interface observed in the

a

b

c

d

Fig. 13: Original picture (a), background picture (b), picture with subtracted background

(c) and detected interface during slug flow (d)

camera pictures should be defined. Therefore, an isosurface with a void fraction of 50% was

chosen (Fig. 14) and the coordinates of its intersection with the vertical mid-plane was exported

from ANSYS-CFX. With this simplification, the three-dimensional shape of the isosurface is not

taken into account.

For each time step, the exported data set was treated in order to determine the minimum and

maximum water levels in each vertical cross-section. As shown in Fig. 15, this data set is

composed of several domains representing the free surface, bubbles or droplets.



10

At first, the free surface has to be recomposed. The domains representing bubbles and droplets are

recognised and separated from the domains corresponding to the free surface. Then, free surface

domains are unified to a single one by connecting them in the empty spaces left by slugs on top of

the channel. In the next step, the droplet and bubble domains are treated. In order to obtain similar

results to the interface capture method used for the experimental data, only the bigger structures

with a circumference longer than approximately 20 mm are selected. The small formations are also

mostly excluded in the experiment because they do not fit into a continuous interface line (step 4

of the method described in the previous section). Furthermore, droplets attached to the top of the

channel are not taken into account. Finally, the minimum and maximum water levels are

determined from the coordinates of the free surface domain as well as the selected bubble/droplet

domains. This is done in each vertical cross-section with a resolution of 1 cm in the horizontal axis

(Fig. 16).

Statistical treatment of the measured water levels for comparison with CFD

Since a direct comparison of the measured

water levels with CFD results is difficult, a

statistical approach is proposed. Therefore,

a time-averaged water level was calculated

and bounded by the standard deviation in

each cross-section (Fig. 17). This results in

a mean water level profile along the

channel, which reflects the structure of the

interface. Furthermore, the standard

deviation quantifies the spread of the measured values, which originates from the

dynamic change of the free surface. In the

first part of Fig. 17, a slight increase of the

mean water level from 50 mm at the inlet to 58 mm is observed as well as a low standard

deviation. Both are characteristic for the supercritical flow (Fr 1) obtained at the test-section inlet. In fact, in a supercritical flow the pressure drop due to wall friction results in an increase of

the water level. Furthermore, only small supercritical waves can propagate in such a flow. Around

the maximum of the mean water level reached at about 0.9 m from the inlet, the standard deviation

increases quickly up to about 18 mm. This data points out the rapid wave growth induced by the

high air velocity in this zone. In the downstream region, where the slugs are generated and

propagate the mean water level decreases to an asymptotic value of about 30 mm. It shows that

there is an acceleration of the water flow, which can be attributed to the exchange of momentum

between the phases.

0,00

0,05

0,10

4,00 4,25 4,50 4,75 5,00 5,25 5,50

Length [m]

Wate

r le

vel [m

]

Fig. 15: Example of data set exported from ANSYS-CFX (in red: domains of the free

surface; in blue: a bubble domain)

Comparison with the CFD calculation

The time-averaged water level profiles were calculated for the CFD results from the minimum and

maximum water levels determined as described previously. These are shown in Fig. 18 for t =

Fig. 1 Side view of the calculated void fraction and structure of the 50% isosurface (in green)



11

17.25020.250 s (i.e. from the passage of the first slug clearing the channel to the end of the

calculation time) and are bounded by the standard deviation.

Qualitatively, Fig. 18 shows that the trend obtained for the simulation is similar to the

measurement (Fig. 17). Like in the experiment, the mean water level profile increases after being

injected over a height of 50 mm at the inlet. Further downstream, the water levels decrease

simultaneously with an increase of the standard deviation. Furthermore, a difference between

minimum and maximum appears which is due to the development of waves that roll over smaller

waves and slugs or the presence of bigger bubbles or droplets structures in the flow. In the last part

of the channel, the mean water levels converge slightly together, probably due to collapsing slugs.

The water levels tend to about 24 mm and 30 mm for the minimum and maximum water levels

respectively.

However, a detailed comparison shows quantitative deviations between simulation and

measurement. In the interface rising region, the water level reaches a maximum of 68 mm, which

is 10 mm more than in the experiment. This region is followed by a plateau between 2 and 3 m,

which is only observed in the calculation. Furthermore, wave growth starts downstream of the 3 m

mark, revealed by a rapid increase of the standard deviation, compared to about 0.9 m in the

experiment.

These quantitative differences can be explained with the flow regimes observed at the test-section

inlet. In fact, the flow pattern has an import influence on the momentum exchange between the gas

and liquid, especially with high velocity differences between the phases. Small disturbances of the

interface provide a more efficient momentum transfer from the air to the water than in a stratified

smooth flow. A high momentum transfer induces a rapid wave growth and therefore slug

generation. In this case, the very low standard deviation ( 0.5 mm) observed over the 3 first meters in the simulation reveals a smooth interface, whereas in the experiment the flow is wavy

from the inlet of the channel. This means that the boundary conditions chosen for the CFD model

do not reproduce the small disturbances observed in the experiment. In the end, a quite long

channel length is needed before waves appear spontaneously in the simulation, deferring

accordingly the instable wave growth to slugs. This occurs downstream of the 3 m mark, inducing

an increase of the standard deviation up to about 18 mm (at 4.00 m) and 23 mm (at 5.20 m) for the

minimum and maximum water levels respectively. These values correspond to the order of

magnitude measured about 3 m after the inlet.

Finally, the quantitative differences noticed between simulation and experiment concern in

particular the inlet boundary conditions. As the conditions have an important influence on the

generation of the two-phase flow, future work should focus on the proper modelling of the small

instabilities observed at the channel inlet.

0

20

40

60

80

100

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5

Distance from the inlet blade [m]

Wate

r le

ve

l [m

m]

Fig. 16: Time-averaged water level bounded by the standard deviation



12

0,00

0,02

0,04

0,06

0,08

0,10

0 1 2 3 4 5 6 7 8

Length [m]

Wa

ter

level [m

]

Min

Max

Fig. 17: Comparison between the mean water level profiles (ANSYS-CFX calculation)

Legend: dark colours: average ; light colours: average standard deviation

SUMMARY In the HAWAC test facility, a special inlet device provides well defined as well as variable

boundary conditions, which allow very good CFD-code validation possibilities. A picture

sequence recorded during slug flow was compared with the equivalent CFD simulation made with

the code ANSYS CFX. The two-fluid model was applied with a special turbulence damping

procedure at the free surface. An Algebraic Interfacial Area Density (AIAD) model on the basis of

the implemented mixture model was introduced and implemented. It improves the physical

modelling, detection of the morphological form and the corresponding switching of each

correlation is now possible. The behaviour of slug generation and propagation at the experimental

setup was reproduced, while deviations require a continuation of the work. Experiments are

planned that include pressure and velocity measurements that will allow quantitative comparisons.

The formation of waves and slugs at other superficial velocities will also be studied.

ACKNOWLEDGEMENTS This work was carried out in the frame of a research project funded by the German Federal

Ministry of Economics and Labour, project number 150 1329. Thanks to Yuri Egorov and Thomas

Frank from ANSYS CFX for their fruitful cooperation.

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