ERMSAR 2012, Cologne March 21 – 23, 2012

Validation of the FCI codes against DEFOR-A data on the mass fraction of agglomerated debris

Session 2, paper 2-9

ERMSAR 2012, Cologne March 21 – 23, 2012

The issue of debris bed formation Interaction of corium melt with water yields melt

fragmentation and deposition to form a debris bed

The characteristics of debris bed drive the heat transfer from the melt to surrounding

Vessel retention and MCCI kinetics are dependent on debris bed characteristics.

Only few tools available for this analysis, and lack of specific modeling

Only few experimental data, mainly from FCI integral tests

The DEFOR experiment (KTH) was designed for this purpose

2

ERMSAR 2012, Cologne March 21 – 23, 2012

Experimental database with corium : FARO FARO : intermediate scale FCI

premixing program at JRC ISPRA

Only integral results with high uncertainty on mechanisms (complete jet breakup ?)

Data mostly with saturated water so OK for in-vessel but limited for ex-vessel situation

Selected FARO database (jet dia = 5 cm, one single melt composition):

– Melt mass and water subcooling as most influential parameters

There is a need for more data

3

mass (kg)

superheat (K)

coolant height

(m)Cool.temp.

agglomeration

L19 160 25O 1.1 m sat 50%

L20 100 350 2 sat 25%

L27 130 180 1.5 sat 20%

L28 180 220 1.5 sat 50%

L31 90 160 1.5 sub 0%

ERMSAR 2012, Cologne March 21 – 23, 2012

The DEFOR-A program

Part of the DEFOR (Debris Bed Formation) program initiated at KTH.

– The goal is to clarify the phenomena that govern formation of the debris bed and quantification of the bed properties.

Eutectic mixture of Bi2O3–WO3

– Tmelt ~ 1000 K– Djet < 25 mm

– Water height = 1.5 m– Subcooled water (~20 °C)– 3 intermediate melt catchers

4

200 cm

150 cm

20 cm

245 cm

ERMSAR 2012, Cologne March 21 – 23, 2012

Selected tests from DEFOR-A

A1, A2 and A8 behaves similarly

– Almost no cake after 1 m of fall

A7 with 100 K higher melt superheat : different behavior (confirmed with a reproducibility test A9)

– Strong delay for freezing– Larger particles

5

Parameters TestsA1 A2 A7 A8

Melt temperature, K 1253 1246 1349 1255Melt superheat, K 110 103 206 112Melt jet initial diameter, mm 10 20 25 25Mass average particle size, mm 4.0 3.7 4.8 3.9

ERMSAR 2012, Cologne March 21 – 23, 2012

Short analysis Debris size density distribution (fragmented part)

– Quite far from usual quasi log-normal distribution, with a “plateau” between 1.5 and 4 mm Larger mean mass diameter in A7 but

Similar mean Sauter diameters:

• A7 : 2.5 mm

• A8 : 2.4 mm

Impact of melt temperature mainly on the mass of agglomerated melt in catchers

Drops mostly “solid” at 2nd catcher in A8:

=> Breakup length L/D < 50 (D~1.5 cm at impact)

ERMSAR 2012, Cologne March 21 – 23, 2012

How interpreting the difference between A7 and A8 ?– The solidification process seems displaced by 2 catchers i.e. ~60 cm– supplementary energy in A7 = energy lost between catcher 1 and 3

– An energy balance can be done to obtain the mean heat transfer coefficient

– With d=2.5 mm, and v~1 m/s, this yields h ~150 W/K.m²– Which is very small, an order of magnitude higher is expected in film

boiling.

So strong non linear effects in agglomeration processes ?

Short analysis

ERMSAR 2012, Cologne March 21 – 23, 2012

Codes used for interpretation / validation Three models dedicated to FCI were used

– VAPEX-P : developed by EREC and used by KTH– JEMI : developed by IKE-Stuttgart– MC3D-PREMIX : developed by IRSN

VAPEX-P and JEMI : langrangian description of drops, eulerian for MC3D (one single drop field)

Lagrangian (vertical) jet as source of drops in JEMI

Eulerian continuous fuel (jet) field in MC3D (VOF-PLIC method)

JEMI and MC3D involved in SERENA pg

2D calculations with VAPEX and JEMI,

3D calculations with MC3D with account of debris catchers

ERMSAR 2012, Cologne March 21 – 23, 2012

Agglomeration modeling No specific modeling in VAPEX and JEMI

– Agglomeration as a post-treatment function of solidification state of drops at a given height and time

– Solidification as a function of solid crust thickness

Simplified modeling in MC3D : “liquid” drops coalesce to continuous melt depending on solidification

– Solidification as function of drop energy

(crust model not used)

ERMSAR 2012, Cologne March 21 – 23, 2012

KTH approach for agglomeration with VAPEX-P Combines code estimates of local solidification of drops and

correlation of experimental data of the form magglo = f(mliq)

Calculations done with two boundary assumptions :– “sub” : no vapor production or “sat”: no condensation

Conservative approach :conservative estimate for the fraction of agglomerated debris

Form (2) or Form (3)– mliq = fraction of melt with crust < 0.1 drop radius

Best Estimate approach using “sub” assumption

– m*liq = fraction of melt no crust

ERMSAR 2012, Cologne March 21 – 23, 2012

KTH approach for agglomeration with VAPEX-P

The Best Estimate approach yields good estimate of DEFOR experimental data.

0.4 0.6 0.8 1.0 1.2 1.4

0.0

0.2

0.4

0.6

0.8

1.0

DEFOR A7 Sat+Formula(2) Sat+Formula(3) Sub+Formula(2) Sub+Formula(3) BE Formula

Frac

tion

of A

gglo

mer

ates

(-)

Water depth (m)

0.6 0.8 1.0 1.2 1.4 1.6

0.0

0.2

0.4

0.6

0.8

1.0

DEFOR A8 Sat+Formula(2) Sat+Formula(3) Sub+Formula(2) Sub+Formula(3) BE Formula

Frac

tion

of A

gglo

mer

ates

(-)

Water depth (m)

ERMSAR 2012, Cologne March 21 – 23, 2012

IKE approach with JEMI

The modeling is similar in JEMI except additional model for the jet fragmentation.

The agglomerated fraction is simply the fraction of melt with crust thickness below a given threshold (or drop energy above a given value)

Based on comparison with FARO results, the agglomeration occurs if

crust < 0.2 Rdrop

ERMSAR 2012, Cologne March 21 – 23, 2012

IKE approach with JEMI

Correct qualitative results but unable to explain the difference between A7 and A8 : small impact of melt superheat on individual drop solidification

ERMSAR 2012, Cologne March 21 – 23, 2012

Approach with MC3D The debris bed is computed with assumptions related to solidified

state of the melt drops and debris bed itself– Agglomeration occurs if either the debris bed either the drop is “liquid”

Solidification is decided upon comparison of drop energy with a threshold

– E < Esolidus is used (as for explosion)

– But better criterion should be found

for debris bed formation

ERMSAR 2012, Cologne March 21 – 23, 2012

Approach with MC3D The calculation is done in 3D with modeling of the catchers

=> Negligible void production and breakup length at ~first catcher, as with JEMI

ERMSAR 2012, Cologne March 21 – 23, 2012

Approach with MC3D As for JEMI, qualitative correct results for first approach but unable to

explain the behavior of higher melt superheat in A7

Melt drop modeling with only one field is too rough and need to be improved : multi-size modeling is underway

Debris bed formation to be improved

0

20

40

60

80

100

120

0,5 0,75 1 1,25 1,5pool depth (m)

aggl

omer

atio

n (%

)

Exp A7Exp A8Calc A7Calc A8

ERMSAR 2012, Cologne March 21 – 23, 2012

Conclusions and perspectives DEFOR installation provides useful data for the analysis of the melt

solidification and debris bed formation.

First attempt of validation for JEMI and MC3D.

KTH uses a combination of code calculation and empirical fitting and is able to predict the agglomeration in DEFOR with formulae

– m*liq = fraction of melt no crust

Only MC3D computes the debris bed formation (need however improvements)

JEMI and MC3D yields similar correct qualitative results

But are unable to explain the difference between A7 and A8, consistently with short heat transfer analysis (slide 6)

ERMSAR 2012, Cologne March 21 – 23, 2012

Conclusions and perspectives Further efforts are necessary:

KTH approach: the formulae

should be explained and rationalized for an increased confidence in reactor applications

Beyond necessary improvements of fragmentation and solidification processes, mechanisms of melt deposition and agglomeration should be analyzed to provide a conceptual picture of the phenomenon and be able to compute a real debris bed

need for small scale experiments on melt deposition

Necessity to improve melt drop description in MC3D with a mutli-size (multi-field) modeling : currently underway.