摘要
为给我国隧道火灾安全的科学应急提供参考依据,对公路隧道火灾烟气行为特征、隧道火灾预测技术、隧道火灾探测与预警技术以及隧道火灾控制技术四方面的研究现状与进展进行系统阐述,并提出未来发展方向:探明复杂因素耦合驱动下公路隧道多火源燃烧行为和烟气蔓延特性;基于深度学习、AI数据和大数据分析等先进算法与技术,开发数字化与智慧化隧道火灾预测技术;采用互联网、物联网和云计算等新一代信息技术,实现隧道火灾快速实时监测与智能感知提前预警;研制集火烟消灭材料、智慧应急装置、多功能通风防排烟技术和智能疏散为一体的隧道火灾综合控制技术;建立公路隧道火灾全过程全面-高效-协同的应急技术体系。
To provide a scientific basis for emergency responses to tunnel fire safety in our country,a systematic exposition has been conducted on the current status and progress of research in four areas:the characteristics of smoke behavior in highway tunnel fires,tunnel fire prediction technologies,tunnel fire detection and early warning technologies,and tunnel fire control technologies.To ascertain the combustion behavior and smoke spread characteristics of multiple fire sources in highway tunnels under the influence of complex coupled factors;to develop digital and intelligent tunnel fire prediction technologies based on advanced algorithms and techniques such as deep learning,AI data,and big data analytics;to employ next-generation information technologies like the internet,Internet of Things,and cloud computing to achieve rapid,real-time monitoring and intelligent early warning for tunnel fires;to develop integrated tunnel fire control technologies that combine fire extinguishing materials,smart emergency devices,multifunctional ventilation smoke exhaust technology,and intelligent evacuation systems;to establish a"comprehensive-efficient-collaborative"emergency technology system for the entire process of highway tunnel fires.
作者
郭志国
李益锌
周令剑
张一恒
叶瑀伋
GUO Zhiguo;LI Yixin;ZHOU Lingjian;ZHANG Yiheng;YE Yuji(School of Emergency Management and Safety Engineering,Jiangxi University of Science and Technology,Ganzhou 341099,Jiangxi,China;School of Safety Engineering,China University of Mining and Technology,Xuzhou 221116,Jiangsu,China;Ganzhou Key Laboratory of Industrial Safety and Emergency Technology,Ganzhou 341099,Jiangxi,China)
出处
《隧道与地下工程灾害防治》
2024年第2期13-24,65,共13页
Hazard Control in Tunnelling and Underground Engineering
基金
江西省大学生创新创业训练计划资助项目(S202310407106)
江西省教育厅科学技术资助项目(GJJ210825)
关键词
公路隧道
火灾烟气
复杂因素耦合
智能感知
应急技术体系
数字预测
highway tunnel
fire smoke
complex factors coupling
intellisense
emergency technology system
numerical prediction
作者简介
郭志国(1988—),男,江西都昌人,副教授,硕士生导师,博士,主要研究方向为火灾科学与应急技术。E-mail:gzg2016@ustc.edu.cn
