When a fire occurs in a tunnel in the absence of sufficient air supply, large quantities of smoke are generated, filling the vehicles and any space available around them. Hot gases and smoke produced by fire form layers flowing towards extremities of the tunnel which may interfere with person’s evacuation and firefighter’s intervention. This paper carries out a numerical simulation of an unexpected fire occurring in a one-way tunnel in order to investigate for the critical velocity of the ventilation airflow; this one is defined as the minimum velocity able to maintain the combustion products in the downstream side of tunnel. The computation is performed successively with two types of fuels representing a large and a small heat release rate, owing to an open source CFD code called ISIS, which is specific to fires in confined and nonconfined environments. It is indicated that, after several computations of full-scale fires of 43.103 and 19.103 kJ/kg as heat release rate, the velocities satisfying the criterion of healthy environment in the upstream side of the tunnel are 1.34 m/s and 1.12 m/s, respectively.
Fires in tunnels, in underground mine roadways, and in building corridors have generally a very complex flow structure because of their geometry and the found ventilation system which can be natural or forced; that is the reason why fires occurring in these places often cause important damage in terms of human being life and material losses. The most remaining case of large-scale tunnel fire is the one of the Mont Blanc in 1999 caused by an accident of a cargo truck carrying margarine and flour. This incident has caused 39 deaths and left 30 people injured [
As a result of the above situations, the interest in fire safety science of tunnels has, however, increased mainly due to the increasing number of catastrophic tunnel fires and the increasing number of tunnels built. Numerous universities, research institutes, and large engineering companies have become involved in many tunnel fires studies. In order to understand the basic tunnel fire phenomena, several studies carried out by authors were focused on both reduced scale [
The most recent technique to study behavior of tunnel fires is by using Computational Fluid Dynamics (CFD). This approach is capable of modeling the multidimensional, time-dependent nature of fire in both obstructed and unobstructed tunnels of arbitrary geometry. However, the accuracy of the CFD modeling depends on the accuracy of the physical models employed in the CFD codes [
Illustration of the back-layer velocity (
After a validation test elaborated by developers of the used CFD code in order to demonstrate its accuracy to represent reality by comparing experiment and simulation, this paper presents a numerical investigations carried out on a small scale tunnel model to study the spread of smoke and hot gases during tunnel fire. Then, from which velocity of the longitudinal ventilation systems will the back layer be deleted? This question will be answered by assuming the heat release rate of fire constant in the small scale tunnel. Results will therefore be extrapolated in full-scale dimensions.
The contribution of the present paper is firstly to put numerically in evidence the complexity of fire in particular geometries, especially in tunnels. Secondly, this paper set a way for ventilation system design by introducing a manner to investigate critical velocity in a given fire incident.
The basic CFD framework used for the present study is ISIS. This open source code covers a wide range of applications including laminar or turbulent, reactive, incompressible, and low Mach flows governed by Navier-Stokes equations such as continuity and momentum equations coupled with equations of energy and species concentrations [
PELICANS environment.
CFD simulation is now a practical tool in fire engineering for simulating buoyancy-induced flows [
Turbulence methods commonly used in CFD are based on the Reynolds Averaging Navier-Stokes (RANS) equation method, Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS). In this study, the RANS method is used, more precisely, the standard Equation of mass: Equation of momentum: Equation of enthalpy: Equation of radiative intensity: Equation of mixture fraction: Equation of fuel mass fraction: Equation of turbulent kinetic energy: Equation of rate of turbulent kinetic energy
with
Constants of standard
| | | | | | | | | |
---|---|---|---|---|---|---|---|---|---|
4 | 0.09 | 1.44 | 1.92 | 1.44 | 1.0 | 1.3 | 0.7 | 0.7 | 0.7 |
The Froude number is a dimensionless number which represents the ratio between inertia forces and gravity forces. Its formula is defined as follows, where
The validation consists in assessing the credibility of numerical simulation by determining the accuracy of the computational solution as compared to a real situation; therefore, several integral tests conducted at the IRSN Fire Test Laboratory and consisting of large-scale fire scenarios in confined and mechanically ventilated compartments have enabled progress to be made in the validation process of the ISIS code. One of these experiments was the one carried out by Pretrel and coworkers [
Configuration of validation test.
The second configuration used in this study is inspired from the work of Roh and coworkers [
Configuration of reduced tunnel.
Meshing often influences numerical results when grid sensitivity test is not performed. The test consists of varying number of nodes by inspecting the variation of one parameter; so, starting from coarse grid of 3,000 nodes to fine grid of 4,800 nodes, temperature above the source fire precisely at a height of 0.24 m near the ceiling is observed. In Figure
Influence of meshing on the variation of temperature.
Concerning the validation test, only a part of their results has been plotted over 1,500 seconds; Figures
Temperatures at the center domain above the fire source with different height.
When a fire is started on the floor of a straight tunnel without a ventilation flow, a hot plume rises above the fire and involves the surrounding cold air into the plume, which, by reaching the ceiling, forms two layers of hot gases concentration flowing in opposite directions along the ceiling (Figure
Streams of smoke and hot gases flowing in opposite directions along the ceiling.
In this simulation study, it is assumed that fire is initialized; then, it grows till reaching its full developed stage with constant heat release rate. A longitudinal flow of air, provided by the ventilation system, is sent inside the tunnel in fire in order to reduce the aggressiveness of fire and maintain the upstream side of tunnel exempt of smoke and hot gases. Starting by a weak velocity in the entrance of tunnel in fire and varying it progressively, the computation is repeated until the conditions of critical velocity are reached.
The first value of velocity injected inside the tunnel by the ventilation system is 0.05 m/s. At this velocity, many phenomena are observed in the upstream side, precisely at 3 m of fire source. From 0 to 10 seconds, fire is still at stage of ignition, and there is no change in measure point about the ambient parameters (Figure
Upstream conditions for
Velocity
Temperature
Mass fraction
From 10 to 20 seconds, after its ignition, it is stage of growth which leads directly to the full developed fire stage. The overpressure due to this generalization of fire generates a stratified layer flowing against the ventilation direction, the reason why the value of velocity falls suddenly to the negative side till reaching a peak of −0.39 m/s and stabilizes around −0.15 m/s during fire (Figure
When computation is run using a ventilation velocity of 0.15 m/s, the velocity curve is still in the negative side (Figure
Upstream conditions for
Velocity
Temperature
Mass fraction
For velocity
Upstream conditions for
Velocity
Temperature
Mass fraction
Starting from ventilation velocity
Upstream conditions for
Velocity
Temperature
Mass fraction
At these velocities, all the measured parameters are in normal values; by consequence, the tunnel upstream is free of smoke and combustion products while the tunnel downstream is full of flames, smoke, and hot and toxic gases (Figure
Visualization of upstream free of fire products at
Starting from this minimum velocity (
By repeating the computation progressively with the methanol as combustion’s fuel, the ventilation’s velocity sets the velocity of the layer to zero (Figure
Upstream conditions for
Velocity
Temperature
Tunnel fire situation is in principle different from the one where fire plume impinges on a ceiling, in which buoyancy force in the ceiling flow is function of ceiling height. In tunnel fire, buoyancy force in the back layer is due to the whole fire plume. Numerical study carried out in this work was in relation to tunnel fire, precisely its behavior over time depending of ventilation system operated. Intervention of firefighters in tunnel fire case often needs control of combustions gases and smoke, in order to reset visibility inside the upstream tunnel. In this numerical study, two computations with different HRR have been done and it came out that critical velocity is a function of thermic power released by the fire; so for simulation with HRR of 43.103 kJ/kg, the minimum velocity is 1.12 m/s; as for 19.103 kJ/kg, the minimum velocity is 1.34 m/s, both in full-scale conditions. So, ISIS is more useful for fire simulations in complex geometries as mine and road tunnels. In the next future work, it will be about the experimental work using the same small scale tunnel with the same conditions in order to validate actual numerical results.
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors are grateful to the staff of IRSN, for the open access code and for the available online documentations. They would like to thank Mr. Babik Fabrice, Engineer Researcher at IRSN, for his kind support in ISIS code.