# Development of a Fire Risk Assessment Program for Submerged Tunnels
## 3 Development of Quantitative Risk Assessment Program for Submerged Tunnels
### Main Considerations  
The Submerged Tunnel Quantitative Risk Assessment Program (SFT_QRA) is designed to conduct assessments separately for road and railway tunnels. In the case of road tunnels, an evacuation analysis is performed based on the number of people in vehicles inside the tunnel, while for railway tunnels, the analysis considers passengers aboard the traveling train. During the simulation, the program calculates the Fractional Effective Dose (FED) values based on the inhalation of hazardous gases such as high-temperature air, reduced visibility, and CO concentration. Upon the completion of the simulation, the program estimates the number of fatalities based on evacuation routes--for road tunnels, it assesses evacuation passageways or the main tunnel, and for railway tunnels, it assesses the main tunnel and nearby vertical shafts. By probabilistically analyzing different cases of hazardous gas exposure, the program allows for the estimation of fatalities and provides a quantitative assessment of evacuation scenarios. In the case of fire analysis, the program allows for the import of existing numerical simulation results from FDS (Fire Dynamics Simulator) and applies them by storing data on temperature, visibility, and CO concentration at breathing height in a database. For road tunnels, the frequency of fire scenarios is derived from statistical survey data compiled in accordance with current relevant standards. Specifically, Table 1 presents a summary of road tunnel fire incidents that occurred over a five-year period, providing the foundational data used to estimate scenario frequencies in the risk assessment. Fire scenarios are categorized into general road tunnels and small-vehicle-only road tunnels, and corresponding branching ratios are provided as default values. Users can modify these branching ratios according to their specific requirements for greater flexibility. Similarly, for railway tunnels, the program provides predefined fire scenarios. Users can input branching ratios based on the train type, operating direction, post-fire maneuverability, and initial fire suppression status. In particular, these values are calculated using railway tunnel fire incident data, as summarized in Table 2. This table compiles historical fire statistics from railway tunnels, allowing the program to generate realistic scenario frequencies that reflect actual incident trends. By integrating these data-driven calculations, the tool enhances the reliability of fire risk assessments for railway tunnel environments. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Category** & **Year** & **Car** & **Bus** & **Truck** & **Total** \\ \hline  & 2016 & 1940 & 386 & 1391 & 3717 \\ Cases of fire & 2017 & 1849 & 389 & 1386 & 3624 \\ incidents & 2018 & 1787 & 355 & 1379 & 3521 \\ (cases/year) & 2019 & 1739 & 351 & 1392 & 3482 \\  & 2020 & 1622 & 320 & 1374 & 3316 \\  & Total & 7906 & 1520 & 7067 & 16,493 \\ \hline  & 2016 & 194,705 & 18,355 & 59,682 & 272,742 \\  & 2017 & 194,281 & 21,564 & 61,570 & 277,415 \\ Traffic volume & 2018 & 205,518 & 20,737 & 60,472 & 286,727 \\ (\(10^{6}\) Veh\(\cdot\)km) & 2019 & 212,721 & 19,818 & 62,372 & 294,911 \\  & 2020 & 224,024 & 19,857 & 63,688 & 307,569 \\  & Total & 1,031,249 & 100,331 & 307,784 & 1,439,364 \\ \hline  & 2016 & 1.04 & 1.53 & 2.41 & 1.38 \\ Accident rate by & 2017 & 1.00 & 1.71 & 2.36 & 1.36 \\ vehicle type & 2018 & 0.97 & 1.62 & 2.47 & 1.35 \\ (cases/100 million & 2019 & 0.89 & 1.91 & 2.33 & 1.28 \\ km\(\cdot\)Veh) & 2020 & 0.83 & 1.48 & 2.23 & 1.20 \\  & Average & 0.95 & 1.64 & 2.36 & 1.31 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Road tunnel fire incident rate. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Train Operating Distance** & **Number of Fire Incidents** & **Fire Incident Rate** \\  & **(1,000,000 km)** & **(Cases)** & **(Cases/1,000,000 Train\(\cdot\)km)** \\ \hline
2012 & 113.8 & 2 & 0.0176 \\
2013 & 117.9 & 1 & 0.0085 \\
2014 & 118.3 & 3 & 0.0254 \\ \hline \hline \end{tabular}
\end{table}