基于网络云模型的尾矿库溃坝安全评估  

Safety assessment of tailings reservoir dam break based on network cloud model

作　　者：戴剑勇 王雯雯 黄晓庆 DAI Jian-yong;WANG Wen-wen;HUANG Xiao-qing(Schoolof Resource Environment and Safety Engineering,University of South China,Hengyang 421001,Hunan,China;Hunan Province Key Laboratory of Emergency Safety Technology and Equipment for Nuclear Facilities,Hengyang 421001,Hunan,China)

机构地区：[1]南华大学资源环境与安全工程学院,湖南衡阳421001 [2]核设施应急安全作业技术与装备湖南省重点实验室,湖南衡阳421001

出　　处：《安全与环境学报》2022年第1期1-7,共7页Journal of Safety and Environment

基　　金：湖南省教育厅重点资助科研项目(18A235);铀矿冶放射性控制技术湖南省工程研究中心、湖南省铀尾矿库退役治理技术工程技术研究中心联合开放重点课题(2018YKZX1001)。

摘　　要：为了分析尾矿库溃坝事故中的关键隐患,降低溃坝风险,提出了基于网络云模型的关键节点分析方法。首先确定尾矿库溃坝安全风险指标,构建尾矿库溃坝安全风险评价指标体系,应用云模型理论判断各指标的风险等级;然后结合指标体系关联关系构建复杂网络模型,运用TOPSIS算法,将融合后的中心性作为网络节点的重要度评估依据,得到节点重要度排序结果;最后分析得到较高风险等级下的关键风险指标,包括地震烈度、浸润线高度、日常管理和平均粒径。This paper intends to make an exploration of the key factors in the tailings dam failure accident so as to reduce the probability of tailings dam failure.For this purpose,we put forward a key node analysis method based on the network cloud model.This method combines qualitative index with quantitative value,in view of the correlation of the factors affecting the dam failure of the tailings reservoir and the uncertainty of the factor information.First of all,we constructed a risk evaluation index system for tailings dam failure,including 5 first-level indicators and 16 secondary indicators.According to the risk index classification criteria,the three digital characteristic values of Expected Ex,Entropy En and Hyper-Entropy He were determined,the cloud model of tailings dam failure was generated,and the conversion between qualitative language description and quantitative value was achieved.Besides,the risk level of the first-level indicator was determined by calculating the comprehensive determination.Then,in order to further analyze the risk level of the secondary index,we constructed a complex network model based on the correlation between the secondary indicators,and got the value of the network characteristic parameters.Next,the TOPSIS algorithm was used to fuse the parameter values of network characteristics,and the centrality of fusion was used as the basis for evaluating the importance of network nodes,obtaining node importance sorting.Then,according to the results of the sorting of secondary indicators,the key risk indicators under higher risk level were analyzed,including seismic intensity,immersion line height,average particle size and daily management.In order to run the tailings depot safely,we should strengthen the monitoring and management of these four risk indicators.Furthermore,we also compared it with traditional analytic hierarchy process.

关 键 词：安全工程 云模型 复杂网络 尾矿库 

分 类 号：X93[环境科学与工程—安全科学]