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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A wide range of fire incidents can occur in a road tunnel, e.g. a fire in the cargo compartment of a goods vehicle, carelessness due to discarded smoker's materials or loss of vehicle control, and a crash resulting in a multiple-vehicle fire. The number of possible fire scenarios is numerous and so, for design applications, rather than attempting to analyse every possible event using a deterministic approach, a preliminary analysis using a quantitative risk assessment approach should be considered. This paper presents a risk assessment methodology to identify the possible fire scenarios that can occur in a road tunnel in order to specify design fire requirements for smoke control systems. The analysis considers factors such as legislation, vehicle fuel load, traffic mix in the tunnel, vehicle accident rate, and causes of vehicle ignition.

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.