文献类型：期刊文献

英文题名：An integrated emergency response model for toxic gas release accidents based on cellular automata

作者：Cao, Huan[1,2];Li, Tian[1,2];Li, Shuxia[1,2];Fan, Tijun[1,2]

机构：[1]East China Univ Sci & Technol, Inst Operat & Supply Chain Management, Sch Business, 130 Meilong Rd, Shanghai, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Virtual Business, 130 Meilong Rd, Shanghai, Peoples R China

年份：2017

卷号：255

期号：1-2

起止页码：617

外文期刊名：ANNALS OF OPERATIONS RESEARCH

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000406401200029)】；

基金：The authors wish to acknowledge the helpful comments provided by anonymous referees. This work was supported by the National Natural Science Foundation of China (71431004, 71171082, 71001039 and 71301050), National Key Technology R&D Program (2013BAH11F03) and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Energy and chemical industry; Toxic gas release; Emergency response; Integrated model; Cellular automata

摘要：An integrated emergency response model based on cellular automata (CA) is proposed for the toxic gas release accidents that happen in the energy and chemical industry. This integrated emergency response model consists of three sub-models: a toxic gas dispersion model, a dynamic evaluation model for accident consequences, and an evacuation route selection model. When a toxic gas release accident happens, the dispersion model predicts the distribution of toxic gas concentration, the evaluation model estimates the consequences in terms of probability of death, expected fatalities and impact scope caused by the accident, and the route selection model provides the safest evacuation route for evacuees. The three sub-models run simultaneously and present real-time results. The proposed model is applied to an ammonia gas release accident in an energy and chemical enterprise, and the corresponding model results are discussed. The efficiency of emergency response for toxic gas release accidents can be further improved through the proposed integrated emergency response model based on CA.