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WP2.3: Boiling Water Reactor Thermal-gHydraulics
H. Anglart, D. Caraghiaur, D. Lakehal, J. Pérez, V. Tanskanen, M. Ilvonen
NURISP SEMINARApril2-3, Karlsruhe
BWR Thermal-hydraulic issues
CFD Eulerian/Eulerian approach (KTH)approach (KTH)
Subchannel code –
Annular flow /dryout
CATHARE-3 (VTT)
Core transient simulationsCore transient simulations using NEPTUNE_CFD
code (KIT)
Various simulation approaches: URANS using
Steam injection /condensation
NEPTUNE_CFD (LUT)
DNS, LES, VLES + ITM (ASCOMP & LUT)/condensation ( & )
NURISP SEMINARApril2-3, Karlsruhe
OBJECTIVES
1. Development of dryout modelling capability using CFD approach (KTH)– mechanistic deposition modelm chan st c pos t on mo– 3D formulation, – two-fluid formulation with liquid film capability
2 CATHARE 3 i l ti d lid ti (VTT)2. CATHARE-3 simulations and validation (VTT)– Validation of dryout predictions– Validation of film flow predictions against KTH data
3. Validation of the NEPTUNE_CFD code (KIT)– Validation against BFBT (turbine and pump trip)– Calculated void compared to measurements
C plin ith th m l s l S th s– Coupling with thermal solver Syrthes
4. Condensation modelling and validation against POOLEX (ASCOMP+LUT)– Low-Re, quasi-steady interface condensation
simulations – High-Re, chugging interface condensation
simulations
NURISP SEMINARApril2-3, Karlsruhe
simulations
WP2 3: Boiling Water Reactor Thermal-WP2.3: Boiling Water Reactor ThermalHydraulics
Towards CFD Euler/Euler dryout capability
D. Caraghiaur, KTHg
NURISP SEMINARApril2-3, Karlsruhe
Drops in annular flow (KTH)
∆t (∆s)
inertia
gravitygravity
tV )(ppp e
Vg
VtV ττ −
+=)0()0(
)(Discrete volume in CFDpp VV )0()0( sc ete o u e C
Semi-local deposition model for CFD calculations (KTH)
The drop deposits if:0.1
lltdi t
2'
≥pp vτwalltodistance
Drop turbulence is calculated: pf
Tv τ
+= 0.12'
2'
LpTv 2
046.02
* =RvTL Vames and Hanratty (1988)
4 kTL = Zaichik et al (2008)ε03 CL
Probability of deposition (KTH)
valuealexperimentvaluecalculatedvaluealexperimentyProbabilit =
Disperse turbulence model (KTH)
Inclusion of particle relaxation influence into the Reynolds stress equation
exp: Jepson et al. 1989: helium-water exp: Jepson et al. 1989: air-waterexp: Hewitt et al. 1969: steam-water, P=70 bar exp: Liu&Agarwal 1970: air-olive oilLPT-DRW: Liu&Agarwal LPT-DRW: Jepson helium-waterLPT-DRW: Jepson air-water LPT-DRW: Hewittpresent model: Liu&Agarwal present model: Jepson helium water
0,1
1
present model: Liu&Agarwal present model: Jepson helium-waterpresent model: Jepson air-water present model: Hewitt
test of 1D d l0 001
0,01
,
k D+
model0,0001
0,001
0,000010,1 1 10 100 1000 10000 100000
τp+
Conclusions on dryout CFD capability (KTH)
• A model for deposition applicable to CFD p ppcalculations has been formulated
• The model with post-processing of turbulence characteristics for drops has been compared to 4 sets of experimental data (including high pressure steam-water)
• It shows a good trend (better than L i t ki t t d i NURESIM)Lagrangian tracking tested in NURESIM)
WP2.3: Boiling Water Reactor Thermal-Hydraulics
Validation of CATHARE-3 code against KTH data
M. Ilvonen, VTT
NURISP SEMINARApril2-3, Karlsruhe
CATHARE-3 simulations and validation (VTT)
Description of the experiment:
• Liquid film flow studied by KTH• Published: Adamsson & Anglart 2006• Main feature: Effect of axial power
distribution (APD) on film flow• Vertical heated tube, length = 3.65 m, Din =
14 mm (see upper Figure)• Direct heating by electric current through the
t b APD i d b hi i th t btube; APD imposed by machining the tube• 1 uniform + 3 non-uniform axial profiles (inlet,
middle and outlet peaked; see lower Figure)U d b ili fl i BWR diti (70• Upward boiling flow in BWR conditions (70 bar, inlet mass flux 750…1750 kg/m2s)
• Liquid film was sucked through a porous section in wall and measuredsection in wall and measured
• Measured: film flow rates (21 experiments), or dryout power (12 experiments)
NURISP SEMINARApril2-3, Karlsruhe
CATHARE-3 simulations and validation (VTT)
CATHARE-3 (CEA Pilot Code) relevant features:
Yang et al. 2006:
• 3-field (9-equation) model: continuous liquid, continuous gas, liquid droplets
• Frictions between the fields wall friction• Frictions between the fields, wall friction, interfacial & wall heat transfers and phase changes, mass transfers by entrainment and depositionp
• Only the OAF (Onset of Annular Flow) transition is explicit in CATHARE-3
• Entrainment in the Pilot Code:– Hewitt & Govan tearing off from wave tops– Ueda film bursting by bubbles due to boiling
• Deposition in the Pilot Code:– Hewitt & Govan transverse droplet diffusion– Hoyer inhibition by steam diffusion from film
interface
NURISP SEMINARApril2-3, Karlsruhe
CATHARE-3 simulations and validation (VTT)Case 6: uni 1750 kg/m2s 1.22 MW/m2.f07; L,G,D
Simulation results for dryout experiments:
0 2
0.25
0.3
0.35
, kg/
s
• Example: Case 6, with dryout observed at outlet 0.05
0.1
0.15
0.2
mas
s flo
w ra
te
• Uniform APD, 1.22 MW/m2
• Inflow 1750 kg/m2s• Upper Figure: Mass flow rates of 3 fields
0 0.5 1 1.5 2 2.5 3 3.50
ZV (height along the heated tube, m)
• Green = continuous liquid film flow• Red = liquid droplets flow• Black = continuous vapour core flowUpper Figure: Mass flow rates of 3 fields
• Dryout was not yet reached in simulation with given parameters of experiment
• Lower Figure:
• Black = continuous vapour core flow• Black circles = total mass flow rate
Lower Figure:– Entrainment E starts consuming the film
at 0.5 m; minimum E at 3 m height– Deposition D only starts at 3 m heighty g– Net entrainment E – D turns negative
after 3 m height
NURISP SEMINARApril2-3, Karlsruhe
• Blue = entrainment rate E• Magenta = deposition rate D• Black = E - D• Red = difference of droplet field flow rate
CATHARE-3 simulations and validation (VTT)Case 15: out 1750 kg/m2s 1.00 MW/m2.f07; L,G,D
Simulation results for film flow rate measurements:
E l C 15 ith d fil 0 15
0.2
0.25
0.3
, kg/
s
• Example: Case 15, with measured film flow rate (appr. 20 g/s)
• Outlet peaked APD, 1.00 MW/m2
I fl 1750 k / 20
0.05
0.1
0.15
mas
s flo
w ra
te
• Inflow 1750 kg/m2s• Upper Figure: Mass flow rates• Simulated film flow rate is reasonably
d b t l th d ’
• Green = continuous liquid film• Red = liquid droplets• Black = continuous vapour core
0 0.5 1 1.5 2 2.5 3 3.5-0.05
ZV (height along the heated tube, m)
good, but leaves the measured ’error channel’ around 3.5 m of tube height
• Lower Figure:E t i t E t t i th fil
• Black = continuous vapour core• Black circles = total mass flow rate• Blue = measured film flow rate
– Entrainment E starts consuming the film at 1.0 m; minimum E at tube outlet
– Deposition D only starts at 3.3 m height– Net entrainment E – D turns negativeNet entrainment E D turns negative
only after 3.5 m height
NURISP SEMINARApril2-3, Karlsruhe
• Blue = entrainment rate E• Magenta = deposition rate D• Black = E - D• Red = difference of droplet field flow rate
CATHARE-3 simulations and validation (VTT)
Summary of findings:
• Dryout experiments:– Low mass inflow rates are hardest to simulate.– Middle and inlet peaked APDs are hardest.
• Film flow rate measurements:– Most simulated cases have a non-monotonic film flow rate
(decrease followed by increase), but measured film flow was always monotonic decreasing.
– Low power >> large prediction error– Low power >> large prediction error– High power >> very small errors
• Deposition rate has discontinuities and sharp peaks.• Correlations particularly deposition should be studied in detail• Correlations, particularly deposition, should be studied in detail.• Ultimately, one should gradually move away from use of
empirical correlations and towards a more mechanistic modeling of the entrainment and deposition processes.of the entrainment and deposition processes.
NURISP SEMINARApril2-3, Karlsruhe
WP2.3: Boiling Water Reactor Thermal-Hydraulics
Validation of NEPTUNE_CFD code against BFBT data
J. Pérez, KIT
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Validation of the NEPTUNE_CFD code
BFBT benchmark is used to validate two phase flow models of Neptune CFD 1.0.8. two scenarios are simulated: A turbine trip without bypass and a recirculation pump trip.
Experimental void fraction measurement are compared against the simulations at three different axial levels.
NEPTUNE_CFD is coupled with thermal solver Syrthes improving local temperatures prediction, specially in the near wall region.
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
NUPEC BWR full Size fine mesh bundle test benchmark
– Void distribution measurements. – Experiment number 4102/001-009– BWR full sized fuel assembly
Measurements of the averaged void at 3 different
– Flow rate 35 to 55 t/h– Power from 2.5 to 6.5 MW– Heated length 3.7(m), total 3.95(m)
C nst nt xi l p sh p
averaged vo d at 3 d fferent axial levels: 0.68 m, 1.7 m
and 2.73 m
– Constant axial power shape– Pressure 7-8 Mpa– Constant inlet temp, 552 (K) – External ø of rods: 12.2mm External ø of rods 12.2mm – Radial power shape distribution– Void fraction measured at 3 levels– Sampling frequency: 50 Hz
Local void Local void fraction
distribution in the domain:
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
NUPEC BWR full Size fine mesh bundle test benchmarkExperimental conditions (Turbine Trip + Pump Trip)
7 6
7,8
8,0
8,2
PumpTrip
Turbine Trip 40
50
60
6,8
7,0
7,2
7,4
7,6
0 20 40 60
MP
a
0
10
20
30
0 10 20 30 40 50 60
t/h
TurbineTrip PumpTrip
0 20 40 60Time (s).0 10 20 30 40 50 60
Time (s).
5 0
6,0
7,0PumpTrip
TurbineTrip
1,0
2,0
3,0
4,0
5,0
MW
TurbineTrip
0,00 20 40 60
Time (s).
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Neptune_CFD models
Generalities • Eulerian approach, 2 phases with 3
equations for each phase (momentum d ) RANS i l ti
Heat exchange models:• Wall heat exchange: Kurul and Podowski
extension (4 fluxes model by J.Lavieville).mass and energy) RANS simulation.
• First order upwind scheme for pressure and energy
• Second order scheme for velocities
y• Liquid properties controlled by Cathare tables• Heat transfer term for the liquid-interphase:
Ranz-Marshall / Astrid / Flashing• G s ph s t ll d b st t tim c n r r ch m f r c t
and volume fractions.• K-ε for the liquid phase • No turbulence model for the gas phase.
(Compressible)
• Gas phase energy controlled by a constant time scale returning to saturation.
• y+ = 250 for the liquid characteristics at the wall.
(Compressible) • SYRTHES code is applied to solve the conjugated heat transfer at the wall.
( )ksatlili TTCq −⋅= ( )TTC
Aq pvv ⋅⋅=
ρα
( ) ( ) veqcwall qfqqqfq ⋅−+++⋅= 11 1 αα3/12/1 PrRe6.02 ⋅+=Nu
dkNuC ll
ki⋅
=
( )2TTt
Aq satc
ivi −⋅=
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Neptune_CFD models
Bubbly flow regime• Interfacial area equation for bubble
diameters ( two different minimum l
( )
[ ]BRKCOANUC
vvNv
Cv
v
ivi
i
DtDAVA
tA
φφφα
ρααρ
⎟⎞
⎜⎛
⎥⎦⎤
⎢⎣⎡ ⋅
⋅−Γ+Γ⋅⋅=⋅⋅∇+∂∂
2
12
32
bubble ø, 0.15mm am 0.1 mm ) • Break up and coalescence from W.Yao
and C.Morel• Interfacial momentum transfer:
[ ]BRKn
COAn
NUCn
iAφφφπ ++⋅⎟⎟
⎠⎜⎜⎝⋅⋅+12
iAd α⋅=6 Sauter mean
diameterInterfacial momentum transfer:• Drag force: Ishii correlation• Lift force by Tomiyama• Wall lubrication by Antal WL
kTDk
Lk
AMk
Dkk MMMMMM ++++=
iA am t r
y• Turbulent dispersion force by
Lance & Lopez de Bertodano• Added mass force by Zuber
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Avg. void fraction at 3 axial levels (Turbine Trip) Selected results:
Neptune_CFD
Neptune_CFD / Syrthes
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Avg. void fraction at 3 axial levels (Pump Trip) Selected results:
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Local steam and water temperatures (Turbine Trip) Near wall region:
Selected results:
NURISP SEMINARApril2-3, Karlsruhe
Validation of the Neptune_CFD (KIT)
Local steam and water temperatures (Pump Trip) Selected results:
In the near wall region
The excesive steam overheat can be controled byIn the bulk
the water and steam temp. remain at saturation
wall region the steam is superheated
can be controled by decreasing the time scale returning to saturation
Water TempWater Temp. in the near wall region
NURISP SEMINARApril2-3, Karlsruhe
WP2.3: Boiling Water Reactor Thermal-Hydraulics
Condensation modelling and validation against POOLEX data
V. Tanskanen, LUTD. Lakehal, ASCOMP
NURISP SEMINARApril2-3, Karlsruhe
Condensation modelling in suppression pools (LUT/ASCOMP)
During the project, two condensation modes of suppression pools were simulated by using the direct contact condensation (DCC) models of separated flow. These models were the same as used within the PTS These models were the same as used within the PTS context of the NURISP project.
– Low-Re, quasi-steady interface condensation simulations were carried out by using the DCC models simulations were carried out by using the DCC models of Hughes & Duffey (1991), Lakehal (2008), Coste-Laviéville (2009), and Coste (2004).
Hi h R h i i t f
STB-31 exp.
STB-28 exp. Pattern recognition- High-Re, chugging interface
condensation simulations were carried out by using the DCC models of Hughes & Duffey (1991), Lakehal (2008) and Coste-Laviéville (2009)
recognition
(2008), and Coste Laviéville (2009).
- NEPTUNE_CFD and TransAT CFD codes were used as solvers.
- A Pattern recognition procedure was employed to obtain comparable quantitative data from the chugging experiments.
NURISP SEMINARApril2-3, Karlsruhe
DCC on the quasi-steady steam/water interface (LUT/ASCOMP)
NEPTUNE_CFD TransAT
Light grey envelope:Light grey envelope:Measurement uncertainty due to possible non-condensable gases
In the low-Re condensation case, the DCC model of Lakehal 2008 gives a gcondensation rate prediction which is near to the measured values. Other models tend to overestimate the DCC
Grey envelope: Base measurement uncertainty
rate.
The results of NEPTUNE_CFD and
NURISP SEMINARApril2-3, Karlsruhe
TransAT are similar.
DCC during chugging steam/water interface (LUT/ASCOMP)
In the high-Re condensation case, the DCC
3D,Hughes-Duffey, Nept.Exp. STB-28-4
case, the DCC model of Hughes & Duffey yields realistic bubble
Bubble size distribution Exp.
STB- 2D-axi
Chugging frequency
0.63 Hz
size distribution and chugging frequency.
2D axi
Experiment STB-28-4
STB-28-4
2D axi.Hughes-Duffey, Nept.1.07 HzChugging cases
have been 2D-axi. Hughes-Duffey, Nept.
simulated by using the NEPTUNE_CFD
d A fcode. A few TransAT simulations have been started
NURISP SEMINARApril2-3, Karlsruhe
been started.
DCC during chugging steam/water interface (LUT/ASCOMP)
Turbulence kinetic energy 3D NEPTUNE CFDThe NEPTUNE_CFD and TransAT simulations of the chugging condensation mode have revealed
Turbulence kinetic energy, 3D, NEPTUNE_CFD
condensation mode have revealed new information of the significant effect of the pool turbulence (mixing) on the condensation rate i.e. on the violence of chugging.
It is likely that LEIS simulations, long
High shear High
bulk turbulence
3D URANS simulations, and experiments with turbulence and/or velocity field Turbulence kinetic energy, 2D-axi,TransATmeasurements could provide crucial results for the best-estimate-
2D-axi,TransAT
solution of this challenging condensation
bl
High shear
NURISP SEMINARApril2-3, Karlsruhe
problem.
CONCLUSIONS
1. A new deposition model for Eulerian/Eulerial framework has been developed, allowing for:– 3D, general formulationD, g n ra formu at on– development towards mechanistic dryout capability in CFD
Eulerian/Eulerian codes
2 CATHARE 3 annular flow predictions has been validated against KTH film 2. CATHARE-3 annular flow predictions has been validated against KTH film measurement data– Reasonable agreement for high powers; difficulties for low flows– Areas for further improvements of predictions have been identified
3. Validation of the NEPTUNE_CFD code against BFBT has been performed– Calculated void compared to measurements and good agreement has been
found– Coupling with thermal solver Syrthes tested to improve wall temperature
predictions
4 Condensation modelling and validation against POOLEX4. Condensation modelling and validation against POOLEX– Low-Re, quasi-steady interface condensation best predicted with the
Lakehal model– High-Re, chugging frequency and bubble size best predicted with the
H h &D ff d lNURISP SEMINARApril2-3, Karlsruhe
g gg g q y pHughes&Duffey model.