Analysis and simulation verification of key factors affecting safe rescue in building fire scenarios
Xinzhe Zhao
Wuxi Big Bridge Academy
Yunqi Jing
Wuxi Big Bridge Academy
Huixin Dai
Wuxi Big Bridge Academy
Yuming Kuang
Wuxi Big Bridge Academy
Chongtian Wan
Wuxi Big Bridge Academy
DOI: https://doi.org/10.59429/esta.v13i1.13393
Keywords: building fire; safety rescue; simulation
Abstract
To address the issues of low efficiency, prominent safety risks, significant congestion interference, and communication disruption in building fire rescue operations, this paper proposes a rescue optimization model that integrates multiple constraints. The model takes "efficiency-safety-balance" as its core objective, incorporates the Two-in-Two-out safety rule, congestion coefficient, and the Bernoulli distribution of communication failure, quantifying the trade-offs among multiple objectives. Through Monte Carlo simulation and multi-scenario parameter analysis, the robustness of the model in 3-15 story building scenarios is verified, revealing the coupling influence mechanism of communication failure rate and risk threshold on rescue performance. The results show that the model can significantly reduce the total rescue time and safety violation rate, providing quantitative decision support and practical solutions for emergency dispatch in high-rise buildings.
References
[1] Li Xia, Guo Mengting, Wang Haipeng, et al. Research on the Probability of Evacuation in Road Tunnel Fires Based on the Randomness of Vehicle Parking [J]. Journal of Safety and Environmental Sciences, 2023, 23(05): 1689-
1698.
[2] Xue Guanghui, Liu Shuang, Li Yuan, et al. Research on Path Planning in Closed and Narrow Spaces Based on
Obstacle Scale [J]. Mining Safety and Environmental Protection, 2023, 50(03): 62-67.
[3] Zhang Huazhou, Xing Hongyan, Li Haoqi, et al. Fire Escape Path Planning Method Based on Fusion of LSTM
and Improved A* Algorithm [J]. Journal of Electronic Measurement and Instrumentation, 2023, 37(04): 69-79.
[4] GAO P, ZHOU L, ZHAO X, et al. Research on Ship Collision Avoidance Path Planning Based on Modified
Potential Field Ant Colony Algorithm [J]. Ocean and Coastal Management, 2023, 235(3): 106482.
[5] Zheng Xinyi. Research and Application of Improved Ant Colony Algorithm in Fire Evacuation System of
Underground Commercial Street [D]. Shenyang: Liaoning University, 2023.
[6] WANG J L, WEI G F, DONG X F. A dynamic fire escape path planning method with BIM[J]. Journal of
ambient intelligence and humanized computing, 2021, 12(11): 10253-10256.
[7] PENG Y, LI S W, HU Z Z. A self-learning dynamic path planning method for evacuation in large public
buildings based on neural networks [J]. Neurocomputing, 2019, 365(11): 71-85.