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Predicting fire suppression by water spray with numerical codes: model development and validation

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

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Predicting fire suppression by water spray with numerical codes: model development and validation

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  1. Predicting fire suppression by water spray with numerical codes: model development and validation Alexandre JENFT1, Armelle MULLER1, Grégoire PIANET1, Arnaud BRETON1 Pascal BOULET2, Anthony COLLIN2, 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

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

  4. Experimental setup • Metrology: • 18 thermocouples • Gas analyser for O2, CO2 and CO • Load cell • Video camera • Water mist characteristics: • Pressure = 10 bars • Flow rate = 6.3 l/min/nozzle • Injection angle = 130° • D32 = 112 µm

  5. Suppression observation

  6. Experimentalresults: fuel oil

  7. Numerical model • 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. 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. 8

  9. Fire suppression model 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. How does it work ? Simulate the part before water application with a specific interest in HRR (or pyrolysis rate) evolution and fuel surface temperature; Identify Bet Eon this part; Put optimal values for Band Ein simulation input file; Simulate the whole test. B = 0.00122 kg/m²/K0.5/s E = 3751 J/mol

  11. Results on suppression time • The new model predicts suppression by fuel cooling in every tests, just like in real tests; • Suppression time prediction still needs improvement.

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

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

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