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FIRE SUPPRESSION USING WATER MISTS - A NUMERICAL MODEL

DOI: 10.1615/ICHMT.2000.TherSieProcVol2TherSieProcVol1.300
pages 219-229

George V. Hadjisophocleous
Fire Risk Management, Institute for Research in Construction - NRC, Ottawa, ON, Canada K1A 0R6

Mingwang An
Atlantic Nuclear Services Ltd., Fredericton, N.B., Canada E3B 5C8

Vitor Costa
Universidade de Aveiro

Antonio C. M. Sousa
Departamento de Engenharia Mecânica; Universidade de Aveiro;Campus Universitário de Santiago; 3810-193 Aveiro-Portugal; and Department of Mechanical Engineering; University of New Brunswick; Fredericton, NB, Canada E3B 5A3

Abstract

The modeling of fire suppression using fine watersprays is described within the context of an engineering computer model. A Lagrangian formulation was selected for the liquid droplet phase, while the gas phase uses an Eulerian formulation based on the RANS equations with a two-equation turbulence model. The fire is assumed to be a turbulent diffusion flame with its behavior dependent upon the supply of hydrocarbon fuel and the air accessing the fire. A feedback mechanism is also implemented, which dictates the rate of fuel evaporation. The flammability limits of the fuel vapor are taken into account, and the concentrations of fuel vapor, air, combustion products and steam evaporated from the droplets in the gas mixture are calculated by solving the equations for the mixture mass fractions. The droplets/gas phase interaction is described through source terms in the gas-phase equations.
The time-dependent equations governing the gas phase are solved in primitive variable form by using a segregated technique. The ordinary differential equations for droplet motion, heating and evaporation are solved by an explicit forward time integration, which starts at the injection point. The droplet time step is determined by considering the turbulence dispersion of the droplets. The predictions produced by the model for the three different cases examined are physically realistic, notwithstanding the uncertainties associated with the experimental data and the input parameters.

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