CFD for Two-Phase Flows - KTG e.V. · PDF file17. Is Two-Phase CFD a Predictive Method ? for Nuclear Reactor Applications. Can a two-phase flow in a nuclear reactor be predicted from

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Eckart Lauriena and Dirk Lucasb

aInstitute for Nuclear Technology and Energy Systems (IKE) Universität Stuttgart, Germany

bHelmholtz-Zentrum Dresden-Rossendorf Institute of Safety Research

Annual Meeting on Nuclear Technology, Jahrestagung KerntechnikMay 17-19, 2011, Berlin, Germany

CFD for Two-Phase Flows - Recent Developments, Status and Further Requirements -

CFD for Two-Phase Flows - Recent Developments, Status and Further Requirements -

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Outline

1 Introduction, why CFD ?

2 Recent Developmentsa. Countercurrent Stratified Flows in Horizontal Pipesb. Bubbly or Slug Flows in Vertical Pipes

3 Statusa. predictive ?b. is model validation efficient ?c. can support understanding ?

4 Further Requirements

5 Conclusion

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Computational Fluid Dynamics (CFD)

Preprocessing3D Integration domainGeometry

Grid generationDiscretization

Postprocesserinterpretation

Solver„general“ conservation equations

- mass, momentum, energy conservation- turbulence model

initial and boundary conditions

E. Laurien and H. Oertel: Numerische Strömungsmechanik, 4. Auflage, 2011

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On the Definition of CFDSeparation of Numerical and Model Errors

3D turbulent flow3D multiphase flow

3D model equations (PDE)boundary and initial conditions

CFD model used foranalysis, opimization

understanding

numerical integration on a grid:FDM, FVM, FEM + time stepping

first principles + turbulence/multiphase model

Model error iscontrolled byvalidation

Numerical error iscontrolled byverification

ERCOFTAC Best-Practice GuidelinesECORA Best-Practice Guidelines

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CFD for Nuclear-Reactor Technologythe `potential` of CFD for both single- and two-phase flow is:

Predict Two-Phase Flows

– in complex geometries with pronounced 3D flow phenomena

– which cannot be predicted by lumped-parameter Models

Transferable models make model Validation efficient

– using experiments in downscaled faclities

– using experiments with simplified geometries

Support the understanding of Complex Flows

– three-dimensional, unsteady, turbulent, multicale

– multiphysics, coupled with neutronics, solid wall materials, etc.

Nuclear Reactor Safety analysis has to reflect the actual state of the art

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Outline





5 Conclusion

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Teschendorff, Sonnenburg, Scheuerer: Projektvorschlag für eine konzertierte Aktion zur Integration von CFD-Codes bzw. deren Module in den Systemcode ATHLET zur physikalisch fundierten und sicher skalierbaren Simulation mehrdimensionaler Zweiphasenströmungen, 1998

Multidimensional Two-Phase FlowsExample: Contercurrent Stratified Flow

steam generator

here: primary circuitother applications: containment

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Counter-current stratified flowExperiments at the TOPFLOW test facility of HZDR

constant water flow rate injected into the steam generator simulator (at pressure up to 5 MPa)

stepwise increase/decrease of the gas flow rate (flooding/deflooding)

gas inlet

water inlet

steam generator (SG) inlet chamber

gas outlet

RPV simulator

SG

sep

arat

or

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Counter-current stratified flowUse of the data for model validation

Algebraic Interfacial Area Density Model

0,00 0,05 0,10 0,150,4

0,5

0,6

0,7

0,8

(JG

* )1/2

[-]

(JL*)1/2 [-]

Run Exp. CFD30-05 30-09 11-01

New modelling approach for momentum transfer at the interface

left: typical flow structures are well reflected

right: comparison of experimental and simulated flooding curves

figures from Deendarlianto et al. (submitted to NED)

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Contercurrent Stratified FlowTest Facility WENKA at Karlsruhe IT

Stäbler, Meier, Schulenberg, Laurien (NED)

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0

0,5

1

1,5

2

-2,0 -1,0 0,0 1,0 2,0

u* [-]

y* [-

]

(a) EXP

(b) EXP

y

1,25

0

Pos. (a) Pos. (b)y

0

1,25

9 mm inlet height

0

0,5

1

1,5

2

-2,0 0,0 2,0 4,0u* [-]

y* [-

]

(a) EXP(b) EXP

k-w

k-ε

k-εk-ω

water inflow

air and water outflow air inflow

water outflow

aa

b b

a b

15 mm inlet heigth

Inletheight

Wintterle & Laurien, NED, 2007

Contercurrent Stratified FlowTwo-Fluid Model for Average Flow

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0,4

0,5

0,6

0,7

0,8

0,25 0,3 0,35 0,4 0,45

1,2 %

2,5 %

3,8 %

20,1%

12,5 %

5,1 %

4,4 %

2,3 %

2,1 %

18,9 %10,5 %

4,3 %

nondimensionalsuperficial velocity of the liquid

nond

imen

sion

alsu

perfi

cial

vel

ocity

of t

he g

as

UPTF flooding correlation

1,2% back-flow rate

2,5%

3,8%18,9%

4,3%10,5%

20,1%

2,1%2,3%

4,4%

5,5%

12,5%

liquid

gas

Contercurrent Stratified FlowComparison with the UPTF Flooding Correlation

Wintterle & Laurien, NED, 2007

isosurface of 50 %volumetric gas content

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wavy flow hydraulic jump

droplet entrainment flow reversal with droplet flow

Transition to Flow with DropletsWENKA facility of KIT with Modified Test Section

Gabriel, Meier, Schulenberg, Laurien

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Validation of the model for upward vertical pipe flow – TOPFLOW facility of HZDR

Wire-mesh sensor

Gas injection devices

Experiments for:

• Air-water flows

• Adiabatic steam- water flows

• Condensating steam in sub- cooled water

• Evaporation by pressure relief

• Flow around an obstacle

diameter: 200 mm

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Model Validation, upward vertical pipe flow Experiments: TOPFLOW facility of HZDR

0.000 0.020 0.040 0.060 0.080 0.100Radius [m]

0.00

0.10

0.20

0.30

0.40

Gas

vol

ume

fract

ion

[-]

R: 7.802 mExperimentCFX (total)dB<6 mmdB>6 mm

0 10 20 30 40 50 60 70 80 90DB [mm]

0.00

0.50

1.00

1.50

2.00

2.50

H [%

/mm

]

L12_118R: 7.802 m

ExpCFX

Radial volume fraction profilesand bubble size distributionsfor air-water flow

Separation of small and large bubbles

Bubble size distribution at the upperend of the pipe

0 10 20 30 40 50 60 70 80 90DB [mm]

0.00

0.20

0.40

0.60

0.80

1.00

H [%

/mm

]

level O: z = 4.531 m

ExperimentCFX

0.000 0.020 0.040 0.060 0.080 0.100Radius [m]

0.00

0.10

0.20

0.30

0.40

Gas

vol

ume

fract

ion

[-]

level O: z = 4.531 m

ExperimentCFX

482 483 484 485 486[K]

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

z [m

]

ExperimentTSAT

TSUBA=0.9 KTSUBA=1.6 KTSUBA=2.3 K

0 0.1 0.2 0.3 0.4 [-]

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

z [m

]

ExperimentTSUBA=0.9 KTSUBA=1.6 KTSUBA=2.3 K

Condensation and re-evaporation along the pipe

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Outline





5 Conclusion

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Is Two-Phase CFD a Predictive Method ?for Nuclear Reactor Applications

Can a two-phase flow in a nuclear reactor be predicted from given inflow and outflow conditions without any prior knowledge about the phase distribution or flow pattern?

MUSIG model for vertical upward pipe flow (TOPFLOW): results depend largely on inflow conditions, phase distribution, spectrum and distribution of bubble sizes, transition to slug flow not yet demonstrated

Two-fluid model for horizontal, countercurrent channel flow (WENKA): Validated for some special flow cases, deviations from these cases can be predicted, but model is not general, not very robust

Horizontal, countercurrent channel flow (TOPFLOW): algebraic interfacial density model can predict counter current flow limitation at low liquid flow rates

not predictive

not predictive

predictive

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Is Model Validation Efficient ?By using downscaled Exmeriments

Vertical upward pipe flow (TOPFLOW): the single-group bubbly flow model applied for the 50 mm pipe is a special case of the MUSIG model, developed for the 200 mm pipe

Two-fluid model for horizontal, countercurrent channel flow (WENKA): At higher mass fluxes new physical effects occur: droplet entrainment and deposition

Horizontal, countercurrent channel flow (TOPFLOW): algebraic inderfacial density model can be extended to 3D and larger geometries, but high computational effort

CFD is based on ´First Principles´, which do not depend on the size, flow rate or heating rate of a validation experiment

- use downscaled experiments for validation- apply validated models to reactor case

models must be `scalable´

scalable

not scalableextension underway

scalabilityto be determined

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Understanding of Complex Flowssuppored by two-phase CFD ?

Whan can two-phase CFD contribute to the understanding of the flow physics, phase distribution and turbulence of a complex flow in a nuclear reactor ?

Horizontal, countercurrent channel flow (TOPFLOW): algebraic inderfacial density model gives insight into instantaneous, local flow, structures, waves, frequencies

MUSIG model for vertical upward fipe flow (TOPFLOW): predicts bubble-size distribution, fragmentation and breakup precesses, forces on bubbles, evaporation and condensation

Two-fluid model for horizontal, countercurrent channel flow (WENKA): predicts the average phase distribution and average turbulence parameters in a complex, 3D geometry

contributesto understanding



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Outline





5 Conclusion

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Further Requirements (1)

Best Practice Guidelines for CFD (activities by OECD/NEA GAMA Writing Groups) including e.g.

– recommendations for closure models to be used in dependence on the involved flow phenomena (basing on PIRT)

– rules to explore grid and time step dependencies

Validation for broad ranges of flow conditions – needs detailed experimental data

Development of model approaches, which allow to simulate transitions between different flow pattern / morphologies

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Two-Phase Flow in vertical Pipesmeasurement method: ultrafast x-ray tomography

Hampel und Fischer, FZD

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Further Requirements (2)

Development/Validation of models for heat and mass transfer

– Heat and mass trasfer of bubbly flows with evaporation or condensation in a pool

– model for bubbles growing from nuclei in a pool or pipe (nucleation model)

– droplet entrainment and deposition model for horizontal channel flows

Evaluate the Scalability of Two-Phase CFD– using data from large-scale facilities (UPTF, ThAI, Karlstein, …)

– use available models to simulate ´reactor cases´

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Bubbly Flow, Boiling Re-CondensationPool experiment at IKE-Stuttgart

pool, H=2,75 m

lower wall heated

illumination

high-speed camera

data aquisition

ther

moc

oupl

es

pres

sure

tabs

Ben Hadj Ali, Kulenovic, Laurien, IKE

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New Fields of Two-Phase CFD ApplicationSevere Accidents

Debris-bed coolability in complex 3D-geometries

– two-phase flow with heat and mass transfer within a porous medium

– understanding of 3D phenomena and dryout

In-Vessel Melt Retention– natural convection and solidification in a corium pond

– investigation of heat transfer mechanisms (inside/outside vessel wall)

– coupling with reactor-pressure vessel structure

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1.) In-Vessel Debris 2.) Melt Poolif sump is flooded:3.) Ex-Vessel Debris

if uncoolable if uncoolable

two-phase flowboiling and drayout in a

porous debris bed

free convectionsolidification

crust formationrelocation

corium jetfragmentationformation of

porous debris bed

if uncoolable maximumdesasterscenario

two-phase flowmodels areavailable in 2D

3D is possiblewith CFD !

Containment sump

Two-Phase CFD Application to Severe AccidentsSequence of (coolable ?) states after Core Damage

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Conclusions

Two-Phase CFD in the Primary Circuit– can qualtitatively predict deviations from a reference case

– should be developed towards a quantitative method

Model Validation using downscaled Experiments– sholuld be continued

– should be supported by scalability investigations (experimental, numerical)

Two-Phase CFD supports the understanding of complex flows– can be extendended to different flows / other flows

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This research has been partially supported by the

German Ministry of Economy (BMWi)

under the contract numbers

150 1329

1501292, 1501364, 1501375,

in the framework of the German CFD Network on Nuclear Reactor Safety Research and Alliance for Competence in Nuclear Technology, Germany.

Documents

CFD for Two-Phase Flows - KTG e.V. · PDF file17. Is Two-Phase CFD a Predictive Method ? for Nuclear Reactor Applications. Can a two-phase flow in a nuclear reactor be predicted from