2014
DOI: 10.3801/iafss.fss.11-499
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Numerical Simulations of a Mechanically-Ventilated Multi- Compartment Fire

Abstract: The objective of this work was to evaluate the capabilities of a widely used Computational Fluid Dynamics (CFD) code in the fire community, namely the Fire Dynamics Simulator (FDS 5.5.3), in the simulation of a large-scale, well-confined and mechanically ventilated multi-room fire scenario. The CFD analysis focuses on the effect of pressure build-up induced by the fire on the ventilation network. The measured heat release rate (HRR) was therefore prescribed as input in the simulations. Computational results we… Show more

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Cited by 9 publications
(6 citation statements)
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References 13 publications
(28 reference statements)
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“…Numerical results reported by Brohez et al [9][10][11] also validated the using of CFAST and FDS in modeling fire-induced pressure. Beji et al [14] evaluated the capability of FDS, version 5.5.3, in the simulation of a large scale, well-confined and mechanically ventilated multi-room fire scenario. Their results showed that FDS can give a good first basis for a fire hazard analysis in forced-ventilated enclosure fires, provided that the HRR (heat release rate) is known from experiments or design calculation requirements.…”
Section: Introductionmentioning
confidence: 99%
“…Numerical results reported by Brohez et al [9][10][11] also validated the using of CFAST and FDS in modeling fire-induced pressure. Beji et al [14] evaluated the capability of FDS, version 5.5.3, in the simulation of a large scale, well-confined and mechanically ventilated multi-room fire scenario. Their results showed that FDS can give a good first basis for a fire hazard analysis in forced-ventilated enclosure fires, provided that the HRR (heat release rate) is known from experiments or design calculation requirements.…”
Section: Introductionmentioning
confidence: 99%
“…In addition to the large scale fire tests, extra support tests for the characterization of fire sources, in open atmosphere, were performed to provide additional data for validation purposes. As in the previous PRISME project, the analytical working group evaluated the capabilities of various fire modelling codes to simulate fire scenarios based on the PRISME 2 results . The output of the PRISME 2 project has been summarized in the OECD/NEA application report…”
mentioning
confidence: 99%
“…FDS predictions of fuel burning rates for three of these tests, one for each pool size, are compared to the experimental fuel mass loss rate data. 1 Numerous authors, including Suard et al (2011Suard et al ( , 2013, van Hees (2013, 2016), Beji et al (2013Beji et al ( , 2014, van Hees et al (2014), Sikanen and Hostikka (2017), Stewart and Kelsey (2017), have used data from the PRISME or PRISME-2 experiments for the purposes of model evaluation. Thomas et al (2007) performed open atmosphere and compartment fire tests using one or more steel fuel trays 0.81 m x 0.70 m x 0.05 m in size each containing 5 l, 10 l or 20 l of methylated spirit (97% ethanol, 3% water).…”
Section: Tablementioning
confidence: 99%
“…For such applications significant assumptions are often made about the fire source with fuel mass loss rates imposed as boundary conditions in the models. Numerical modelling studies of this type have typically focussed on assessing other aspects of the models, such as the performance of heat, ventilation and air conditioning (HVAC) sub-models (Wahlqvist and van Hees, 2013;Beji et al, 2013Beji et al, , 2014, the choice of gas-phase combustion model (Wen et al, 2007;Stewart and Kelsey, 2017), or the turbulence closure model used in combination with the hydrodynamic solver (Vasanth et al, 2013). Where studies have considered the capability of models to predict fuel vaporisation rates for pool fires, the work has often been limited to fuel mass loss rates during the quasi-steady burning regime (Hostikka et al, 2002;Rengel et al, 2018).…”
Section: Introductionmentioning
confidence: 99%