The Influence of Tunnel Geometry and Ventilation on the Heat Release Rate of a Fire

Carvel, Richard; Beard, Alan N.; Jowitt, Paul; Drysdale, Dougal

doi:10.1023/b:fire.0000003313.97677.c5

Cited by 78 publications

(36 citation statements)

References 10 publications

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“…For illustration purposes, velocities of 1 m/s, 1.5 m/s and 3 m/s were performed similar to ventilation velocities that might be expected from a tunnel smoke control system and Figure 11d indicates there is an increase in the peak heat release rate as the air velocity in the tunnel increases similar to previous experimental observations [18,19]. The total simulated energy release at 3 m/s was found to be 257 GJ compared with the theoretical 247 GJ experimental value (Table 1).…”

Section: Simulation Results and Comparisonssupporting

confidence: 76%

“…Observations from the EUREKA [18] fire experiments and studies by Carvel et al [19] have shown that ventilation condition, tunnel geometry, fuel configuration and even the location of ignition can affect the burning characteristics of a fire. The effect on the simulated fire growth of these parameters and the FDS representation of the Runehamar tunnel experiment T1 were investigated as part of the computational analysis.…”

Section: Simulation Results and Comparisonsmentioning

confidence: 99%

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Calibrating an FDS Simulation of Goods-vehicle Fire Growth in a Tunnel Using the Runehamar Experiment

Cheong

Spearpoint

Fleischmann

2009

Journal of Fire Protection Engineering

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ABSTRACT:As with any complex fuel assembly configuration, modelling a goods vehicle fire using FDS to estimate the heat release rate in a tunnel is a challenging task. The work presented in this paper involves the use of heat release rate curve taken from the Runehamar tunnel fire experiment T1 to 'calibrate' the heat release rate curve predicted using FDS 4.0.7. The paper develops a simplified representation of burning wood and plastic pallets and illustrates that an FDS simulation is able to reproduce a reasonable estimate of the fire growth characteristics in the tunnel. The paper considers the effects of the assumptions made to calibrate the simulations and then investigates how the fire growth might change if conditions were varied.

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Section: Simulation Results and Comparisonssupporting

confidence: 76%

Section: Simulation Results and Comparisonsmentioning

confidence: 99%

Calibrating an FDS Simulation of Goods-vehicle Fire Growth in a Tunnel Using the Runehamar Experiment

Cheong

Spearpoint

Fleischmann

2009

Journal of Fire Protection Engineering

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“…Experimental data were used to produce a probability distribution of fire size for heavy goods vehicles (HGV), cars and a range of pool fire sizes [12]. The peak HRR in a tunnel is established from an equation in the form of [13]:…”

Section: Statistical Approachmentioning

confidence: 99%

“…j is presented as probability percentile graphs which vary depending on the type of fuel burning. According to Carvel et al [13], the probability distribution for j are categorised into HGVs, medium sized pool fires and large pool fires ( Figure 1). For example, 50% of all fires have a j value of 4 at 4 m/s for HGV fires.…”

Section: Statistical Approachmentioning

confidence: 99%

A Comparison of a Statistical and Computational Fluid Dynamics Approach to Estimate Heat Release Rate in Road Tunnel Fires

2009

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Computational tools such as one-dimensional models or Computational Fluid Dynamics (CFD) have been used for the fire safety design of road tunnels. However, most of these analyses are performed using a specified fire source where the heat release rate (HRR) in the tunnel is fixed by the user and the influences of ventilation conditions and tunnel geometry are not considered. For a more realistic estimate, models need to incorporate these factors in their input. This paper discusses the use of a statistical approach previously developed by other researchers (Carvel and Beard, The handbook of tunnel fire safety. Thomas Telford Publishing, pp [184][185][186][187][188][189][190][191][192][193][194][195][196][197] 2005) and the use of a CFD approach to estimate the HRR in a road tunnel fire. As an application example, fire scenarios in which a light goods vehicle carrying wooden pallets are used to compare the estimation of the HRR using these two methods.

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“…Domestic and foreign scholars have conducted a lot of research on the smoke flow characteristics of tunnel fire under different fire heat release rate and ventilation mode. Carvel, R. O. et al summarized the fire tests and simulated the influence of tunnel geometry and ventilation wind speed on the growth of fire heat release rate coefficient [2] . Li, Y Z et al researched the influence of the height and width of tunnel section and ventilation velocity on the heat release rate of liquid oil pool fire and solid fuel fire through model experiment [3] .…”

Section: Introductionmentioning

confidence: 99%

The Effect of Subway Tunnel Section Shape on the Moving Train Fire Smoke Flow Characteristics

Hui¹,

Zhou²

2017

dtetr

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Based on dynamic grid technology, established a full-size model of subway train and the tunnel, the influence of tunnel section shape (circle, rectangle and arch) on fire smoke flow characteristics during the braking and stop process of subway in tunnel after the fire broke out under the bottom of the vehicle while moving is simulated. The computational results show follows: The results show that the shape of the tunnel has a great influence on the flow velocity around the train under the piston wind and smoke characteristics. The range of high temperature smoke in the arch tunnel fire center upstream is smallest at stop instant. The lower bottom space of the rectangular section tunnel is not conducive to the initial high temperature smoke diffusion and even accelerates the combustion of the train. The narrow side waist of the rectangular section tunnel causes the smoke quickly encircling the train body and the piston wind would slow down faster, which will accelerate the smoke deposition, and is not conducive to the smoke flow downstream. The narrow upper space of the arch section tunnel is favorable for the smoke flow downstream, but the smoke flow back early at about 180s. At 360s, the total temperature and concentration of the arch section tunnel is the lowest, and the rectangle is the highest.

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The Influence of Tunnel Geometry and Ventilation on the Heat Release Rate of a Fire

Cited by 78 publications

References 10 publications

Calibrating an FDS Simulation of Goods-vehicle Fire Growth in a Tunnel Using the Runehamar Experiment

Calibrating an FDS Simulation of Goods-vehicle Fire Growth in a Tunnel Using the Runehamar Experiment

A Comparison of a Statistical and Computational Fluid Dynamics Approach to Estimate Heat Release Rate in Road Tunnel Fires

The Effect of Subway Tunnel Section Shape on the Moving Train Fire Smoke Flow Characteristics

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