Title: Simplified Methodology to Predict Polyurethane Foam Mass Loss Rate in the Cone Calorimeter // Proceedings of the Ninth International Seminar on Fire and Explosion Hazards. Vol. 2: 21-26 April 2019, Saint Petersburg, Russia
Creators: Leroy A.; Erez G.; Suzanne M.; Thiry-Muller A.; Collin A.; Boulet P.
Organization: Laboratoire Central de la Préfecture de Police; École Nationale Supérieure de Techniques Avancées Bretagne; Laboratoire Énergies
Imprint: Saint Petersburg, 2019
Collection: Общая коллекция
Document type: Article, report
File type: PDF
Language: English
DOI: 10.18720/SPBPU/2/k19-43
Rights: Свободный доступ из сети Интернет (чтение, печать, копирование)

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The work presented here is the first step of a larger study aiming at improving the description of fuel mass loss rate (MLR) in fire simulations, through multi-scale experimentation and model development. The final model, based on cone calorimeter scale measurements and on heat transfer modelling, is developed to predict full-scale fire spread over polyurethane foam slabs. In the present paper, small-scale tests performed in cone calorimeter are described, as well as a model predicting the material mass loss rate as a function of heat flux from the cone heater. Several irradiance levels were tested (from 20 to 70 kW/m2), and two simple mathematical functions were chosen to describe experimental curves of mass loss rate. Correlations between the functions parameters and cone calorimeter heat fluxes were computed, thus producing a model able to predict MLR as a function of time and irradiance level. The numerical results are in accordance with experimental data for intermediate heat fluxes (approximately 40 to 70 kW/m2). For lower heat fluxes, the model fails (by construction) to reproduce the combustion decay. This is not considered to be a problem, as the range of heat fluxes for which the correlations are valid can be easily estimated from the results. In conclusion, the proposed methodology allows to predict MLR results in cone calorimeter conditions (e.g. only for 5 cmthick samples) for various heat fluxes. After adding other sub-routines, it will be coupled to a heat transfer model in order to predict fire spread over polyurethane foam slabs.

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