# Development of a Fire Risk Assessment Program for Submerged Tunnels
## 5 Conclusions  
This study developed a program (SFT_QRA) capable of quantitatively assessing fire risk in submerged tunnels (both road and railway types) and verified its reliability and validity through a comparison with commercial QRA programs. The main research findings are as follows:  
1. This study utilized the latest road and railway tunnel fire statistics to reflect fire occurrence probabilities and the proportion of vulnerable users, aiming to develop a realistic and practical assessment program. However, this program was developed for research purposes and is not a commercially developed product. It is currently based on Korean datasets and operates in the Korean language. Future studies are required to adapt the program for international data and to develop an English-based version for broader applicability.
2. The program was developed based on Excel VBA to ensure easy accessibility for operators and was designed to facilitate the preparation of input data. It is also structured to import analysis results from the Fire Dynamics Simulator (FDS) and store and apply data such as temperature, visibility, and CO concentration at human breathing height in a database format.
3. The program was applied to various tunnel types, including general road tunnels, small-vehicle-only road tunnels, railway tunnels, and rescue station scenarios. Its high reliability was verified through a comparison with commercial QRA programs (Road_QRA amd Rail_QRA), showing a maximum error margin within 0.4-5.0%.
4. The program developed through this study reflects the unique fire risk characteristics of submerged tunnels and is expected to have high applicability in practical settings. Furthermore, its flexibility in applying up-to-date statistical data makes it a valuable foundational tool for policy and standard improvements.
5. While the SFT_QRA program offers a practical and validated method for quantitative risk assessment, it heavily relies on numerical simulations and statistical inputs. This approach inevitably involves simplifications, particularly in modeling human behavior during evacuations, and lacks empirical field data for calibration. Future studies should consider incorporating real-world evacuation drills or sensor-based monitoring data to enhance model accuracy.  
Writing, original draft preparation, and numerical analysis, S.-M.K.; resources, H.-G.K.; data curation and numerical analysis, H.-H.L.; conceptualization, review, and editing, S.-WL. All authors have read and agreed to the published version of the manuscript.  
This research was conducted with support from the Smart Operation and Performance Improvement Technology Development Project for the Activation of Joint Utilities by the Korea Agency for Land and Infrastructure Technology Advancement (RS-2023-00245334). We express our gratitude for this support.  
Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** Authors [PERSON] and [PERSON] were employed by the company JuSeong GNB Inc. The remaining authors declare that the re-search was con-ducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.