# Effects of the Ventilation System by Using Jet Fans during a Fire in Road Tunnels
## 3 Numerical Modelling of a Fire in a Road Tunnel  
Nowadays, numerical computational fluid dynamics (CFD) is often used to calculate air and fume velocities and temperature patterns in the event of a fire along a road tunnel [13; 21; 26; 27; 28]. The simulation of a tunnel fire through numerical modeling allows us to analyze in detail the air characteristic parameters. Although this may be true, back layering is challenging to study directly in the calculation due to the numerous factors that can play a decisive role in this phenomenon. It is, however, possible to evaluate the air velocity and temperature inside the tunnel during the fire evolution. From these results, it is then possible to estimate the back-layering length using Equations (9) and (10). Figure 4: Iterative procedure to evaluate the evolution of the back-layering length over time (\(L_{bl}=f(t)\)), starting from the start of the fire (\(t=0\)). The calculation of the air temperature downstream of the fire (\(T_{f}\)) is obtained by referring to the air velocity v evaluated in the previous cycle. To allow relatively short calculation times to be obtained, the tunnel is generally simulated by one-dimensional elements placed in series, each one representing a portion of the tunnel length for its entire cross-section (Figure 5). The main input data required by numerical models are:  
* Dimensional characteristics of the tunnel (shape of the cross-section and its area);
* Number of adopted elements and length of the tunnel represented in each element;
* Friction coefficients of air on the tunnel lateral surface;
* External temperature, specific mass, and specific heat of the air as its temperature and pressure vary;
* Coefficients that govern the heat transmissivity towards the lining and the ground/rock surrounding the tunnel;
* Location of the fire in the tunnel and hypothesized \(HRR\) evolution over time;
* Number and position of jet fans inside the tunnel;
* Operating parameters of the jet fans: more specifically the nominal absorbed power and the pressure-flow curve. In general, the most interesting results obtained from the numerical calculation concern:
* The air velocities upstream of the fire;
* The temperatures reached downstream of it and along the entire section of the tunnel between the fire and the air outlet section;
* The concentration of dangerous gases within the fumes and visibility in the areas of the tunnel occupied by the fumes;
* The operating modes of the fans inside the tunnel. Obviously, the results can be obtained over time during the entire evolution of the fire starting from its ignition. The effects of the fire on the air velocity upstream of the fire are able to permit the estimation of the length of back-layering over time and, therefore, the speed with which the fumes move against the fresh air towards the entrance of the tunnel. Several calculation programs are now available to be able to develop these sophisticated simulations. In particular, VentSim ([[https://ventsim.com/](https://ventsim.com/)]([https://ventsim.com/](https://ventsim.com/)), accessed on 1 March 2023) [29; 30] is a specific program to simulate underground ventilation circuits inside tunnels and mines. It is, therefore, particularly suitable for studying the airflow conditions during a fire inside a one-way tunnel in the presence of jet fans. The computer code has a specific module (VentFire module) capable of satisfactorily representing the fire inside the underground cavities, and for this reason, it will be adopted in this study. Researchers from all over the world have used the Ventsim program and the VentFIRE module for many years to study the issues with mine ventilation and, more recently, to investigate the impacts of fires in underground cavities [31; 32]. These calculation tools have been used in numerous studies that have allowed for the analysis of fire evolution and ventilation system circumstances. The validation of the calculation tool was made possible by the availability of the on-site data and the comparison with the modeling outcomes.