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

Transcription

1 Validation of the FCI codes against DEFOR-A data on the mass fraction of agglomerated debris Session 2, paper 2-9

2 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

3 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?) mass (kg) superhea t (K) coolant height (m) Cool. temp. agglomer ation L O 1.1 m sat 50% L sat 25% L sat 20% Data mostly with saturated water so OK for in-vessel but limited for exvessel situation L sat 50% L sub 0% 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

4 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. 20 cm Eutectic mixture of Bi 2 O 3 WO cm Tmelt ~ 1000 K 200 cm Djet < 25 mm 150 cm Water height = 1.5 m Subcooled water (~20 C) 3 intermediate melt catchers 4

5 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 Parameters Tests A1 A2 A7 A8 Melt temperature, K Melt superheat, K Melt jet initial diameter, mm Mass average particle size, mm

6 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 2 nd catcher in A8: => Breakup length L/D < 50 (D~1.5 cm at impact)

7 Short analysis 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?

8 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

9 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)

10 KTH approach for agglomeration with VAPEX-P Combines code estimates of local solidification of drops and correlation of experimental data of the form m agglo = f(m liq ) 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) m liq = fraction of melt with crust < 0.1 drop radius Best Estimate approach using sub assumption m* liq = fraction of melt no crust

11 Fraction of Agglomerates (-) Fraction of Agglomerates (-) KTH approach for agglomeration with VAPEX-P The Best Estimate approach yields good estimate of DEFOR experimental data DEFOR A7 Sat+Formula(2) Sat+Formula(3) Sub+Formula(2) Sub+Formula(3) BE Formula DEFOR A8 Sat+Formula(2) Sat+Formula(3) Sub+Formula(2) Sub+Formula(3) BE Formula Water depth (m) Water depth (m)

12 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 d crust < 0.2 R drop

13 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

14 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 < E solidus is used (as for explosion) But better criterion should be found for debris bed formation

15 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

16 agglomeration (%) 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 Exp A7 Exp A8 Calc A7 Calc A8 0 0,5 0,75 1 1,25 1,5 pool depth (m)

17 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)

18 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.