Optimization analysis of evacuation facility parameters in interval tunnels under subway train fire accidents

Jiangtao Sun, Zhaijun Lu and Dan Zhou

Physica A: Statistical Mechanics and its Applications, 2024, vol. 651, issue C

Abstract: When a moving subway train catches fire in tunnels, high-temperature smoke spreads rapidly, posing a threat to the personnel evacuation process. Rational design parameters for evacuation facilities can mitigate the impact of high-temperature smoke on personnel evacuation. This study utilizes both the N−S equation and the fully buoyant corrected Renormalization-group (RNG) k−ε turbulence model to build a smoke spread model. Additionally, the study employs two-dimensional cellular automata to develop a personnel evacuation model in interval tunnels. Then determining the smoke spread and the influence of evacuation facility parameters on personnel evacuations. Furthermore, optimization algorithms are employed to optimize evacuation facility parameters. The results can be summarized as follows: (1) High-temperature smoke spreads to the downstream area after the train stops due to piston wind, severely limiting personnel evacuation. The efficiency of the downstream evacuation process determines overall efficiency of the evacuation process. (2) The width of evacuation walkways and the spacing of connecting bypasses significantly influence the total evacuation time, while the impact of the evacuation safety door width is minimal. (3) The spacing of connecting bypasses and the width of evacuation safety doors significantly influence evacuation exit congestion time, while the impact of evacuation walkway widths is small. (4) Evacuation facility parameters were optimized to minimize both the total evacuation time and exit congestion time. The Pareto frontier was analyzed, and optimization results were obtained. (5) After optimization, total evacuation time decreased by 72 %, and congestion time decreased by 85 %.

Keywords: Subway tunnel; Train fires; Smoke spread; Evacuation facility; Optimization analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:651:y:2024:i:c:s0378437124005296

DOI: 10.1016/j.physa.2024.130020

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