1. Predicting fire suppression by water spray with numerical codes: model development and validation Alexandre JENFT 1, Armelle MULLER 1, Grégoire PIANET 1, Arnaud BRETON 1 Pascal BOULET 2, Anthony COLLIN 2, 1 CNPP, Route de la Chapelle Réanville, BP 2265, F-27950 Saint Marcel - FRANCE 2 LEMTA, 2 Avenue de la Forêt de Haye - TSA 60604 - 54518 Vandoeuvre-lès-Nancy cedex – FRANCE

2. Contents Suppression mechanisms by water spray Experimental study Numerical results New suppression model writing New suppression model results Conclusions / current work 2

3. Suppression mechanisms Gas phase cooling; Oxygen displacement and fuel vapor dilution; Fuel surface cooling and wetting; Radiative transfer attenuation; Kinetic effects. 3

4. Experimental setup Metrology: 18 thermocouples Gas analyser for O 2, CO 2 and CO Load cell Video camera Water mist characteristics: Pressure = 10 bars Flow rate = 6.3 l/min/nozzle Injection angle = 130° D 32 = 112 µm 4

5. Suppression observation Test 14 t app = 1 min a) t 0 +10 sb) t app -1 s c) t app +5 sd) t app +10 se) t app +20 s 5 f) t app +30 sg) t app +60 sh) t app +65 s

6. Experimental results: fuel oil 6 N°D pool [cm] T 0 [°C] t app [s] HRR app [kW] T A2,290,app [°C] dt vid [s] dt gas [s] dt pool [s] 1335123828214035 143511644832656165 20357945242655878 213561265651705778 31251038717312935 32251064122330 62 3325109919296971104 342510128243399108126 352510186323910695126 3625103054047105103125 3725105444650126131156

7. Numerical model 7 Main parameters: Cell size : 5 cm x 5 cm x 5 cm; Power increase defined as a ramp following the actual measured curve until stationary regime; After mist activation, HRR guided toward a reduction through suppression model. Suppression model: with

8. 8 N°13142021 HRR app – [kW]28485256 a – [m²/kg/s]0.20.150.40.2 N°31323334353637 HRR app – [kW]7121924324046 a – [m²/kg/s]110.240.260.420.740.24 It is impossible to predict the value of ‘a’ for a test which has not been carried out prior to the simulation. This model does not allow predictive simulations.

9. Fire suppression model 9 Pyrolysis rate reduction during water application is linked to fuel surface temperature. The model is written: B and E are empirical coefficient which can be easily determined, even with no preliminary real test. The model is based on Arrhenius law:

10. 10 How does it work ? 1. Simulate the part before water application with a specific interest in HRR (or pyrolysis rate) evolution and fuel surface temperature; 2. Identify B et E on this part; 3. Put optimal values for B and E in simulation input file; 4. Simulate the whole test. 1. Simulate the part before water application with a specific interest in HRR (or pyrolysis rate) evolution and fuel surface temperature; 2. Identify B et E on this part; 3. Put optimal values for B and E in simulation input file; 4. Simulate the whole test. B = 0.00122 kg/m²/K 0.5 /s E = 3751 J/mol

11. Results on suppression time 11 N°1314202131323334353637 t sup,exp (s) 4065 7031306999106105129 t sup,num (s) 223950668173243577486 Gap (s) 182615423133756493143 Gap (%) 454023674435457463033 The new model predicts suppression by fuel cooling in every tests, just like in real tests; Suppression time prediction still needs improvement.

12. 12 Conclusions 1. An experimental study has been carried out to understand suppression mechanisms; 2. For the “fuel cooling” cases, a new suppression model has been developed and integrated to FDS; 3. This model allows predictive simulations for fire suppression by water spray.

13. 13 Current work 1. Improve model results by improving fuel temperature calculation through particles / fuel exchanges modeling; 2. Validate the model on other configurations; 3. Determine FDS capability to determine extinction by flame cooling and inerting effects in FDS 6.