Identifying Critical Regions in Industry Infrastructure: A Case Study of a Pipeline Network in Kansas, USA

doi:10.1109/ACCESS.2020.2985595

CSpace

	Identifying Critical Regions in Industry Infrastructure: A Case Study of a Pipeline Network in Kansas, USA
	Hou, Peng 1; Yi, Xiaojian 1,2; Dong, Haiping 1
	2020
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	8 页码:71093-71105
摘要	In the face of the budget cuts and increased size of industry infrastructure, one of the top priorities for industry infrastructure protection is to identify critical regions by vulnerability analysis. Then, limited resources can be allocated to those critical regions. Unfortunately, difficulties can be observed in existing approaches of vulnerability analysis. Some of them are unavailable due to the insufficient data. Others are susceptible to human biases. Here, we propose an approach to overcome these difficulties based on the location data of failure events. The critical geographic regions are determined by the risk ranking of different candidate regions. Risk is calculated by integrating the probability of the failure event occurring (risk uncertainty) and total failure cost (the severity of failure consequences) in each candidate region. By changing the modeled object from the components to the region where the whole industry infrastructure is located, it collects the rarely failure events which are dispersed in different positions of the industry infrastructure to provide sufficient data, then the probability can be obtained by using a Poisson point process and kernel density estimation. Meanwhile, the application of hypothesis testing avoids the susceptibility of the approach to human biases by verifying the correctness of the assumptions used in the approach. Finally, a case study of this approach is performed on a pipeline network in Kansas, USA. In addition to the validation of the feasibility of our approach, risk uncertainty is proven to be less instructive for identifying critical regions than the severity of failure consequences.
关键词	Industries Hazards Pipelines Data models Object recognition Uncertainty Accidents Critical region critical industry infrastructure Poisson point process risk assessment vulnerability analysis
DOI	10.1109/ACCESS.2020.2985595
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[71801196]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000530809000031
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/51443
专题	中国科学院数学与系统科学研究院
通讯作者	Yi, Xiaojian; Dong, Haiping
作者单位	1.Beijing Inst Technol, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Hou, Peng,Yi, Xiaojian,Dong, Haiping. Identifying Critical Regions in Industry Infrastructure: A Case Study of a Pipeline Network in Kansas, USA[J]. IEEE ACCESS,2020,8:71093-71105.
APA	Hou, Peng,Yi, Xiaojian,&Dong, Haiping.(2020).Identifying Critical Regions in Industry Infrastructure: A Case Study of a Pipeline Network in Kansas, USA.IEEE ACCESS,8,71093-71105.
MLA	Hou, Peng,et al."Identifying Critical Regions in Industry Infrastructure: A Case Study of a Pipeline Network in Kansas, USA".IEEE ACCESS 8(2020):71093-71105.