(1. Research Center for Urban Fire Safety Engineering, Zhejiang University, Hangzhou 310058, Zhejiang, China;
2. Research Center of Balance Architecture, Zhejiang University, Hangzhou 310007, Zhejiang, China;
3. College of Energy Environment and Safety Engineering, China Jiliang University, Hangzhou 310018, Zhejiang,China;
4. Zhejiang University Urban - Rural Planning & Design Institute Co, Ltd. , Hangzhou 310010, Zhejiang, China;
5. China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, Hubei, China)
Abstract: Addressing the unpredictability of tunnel fire accidents, this paper presented a dynamic quantification approach to ascertain the probabilistic metrics of traffic tunnel fires, complemented by a statistical case study analysis. Causal analysis of tunnel fires identified vehicles as the principal disaster-inducing factors. Taking into account the conditions of the vehicles and the environmental impact within the tunnel, the individual fire frequency for each vehicle type was corrected. Then synthesizing above modification value with the number of vehicles inside the tunnel could obtain the tunnel's vehicle fire probability, which was amalgamated with the statistical probabilities of other incendiary events to construct a probabilistic quantification model for tunnel fires. Two empirical case studies analysis were conducted on a specific tunnel, resulting in the fire probability distribution within a 24-hour period. This achieved a dynamic quantification of the potential for fire occurrence, which provided a basis for real-time risk identification and accident prevention of tunnel fires.
吴珂, 周倩, 陈茗, 曹颖, 孙峰, 朱凯. 交通隧道火灾概率的动态量化研究[J]. 隧道与地下工程灾害防治, .
WU Ke, ZHOU Qian, CHEN Ming, CAO Ying, SUN Feng, ZHU Kai. Research on dynamic quantification method for the fire probability in traffic tunnel. Hazard Control in Tunnelling and Underground Engineering, 0, (): 1-.
