Component importance measures for interdependent infrastructure network resilience

被引:57
|
作者
Almoghathawi, Yasser [1 ]
Barker, Kash [2 ]
机构
[1] King Fand Univ Petr & Minerals, Syst Engn Dept, Dhahran, Saudi Arabia
[2] Univ Oklahoma, Sch Ind & Syst Engn, 202 W Boyd St, Norman, OK 73019 USA
基金
美国国家科学基金会;
关键词
Importance measures; Interdependent networks; Recoverability; Resilience; Vulnerability; VULNERABILITY ANALYSIS; STOCHASTIC-MEASURES; SEISMIC RESILIENCE; FLOW MODEL; SYSTEMS; RESTORATION; IDENTIFICATION; DESIGN; FAILURE; IMPACTS;
D O I
10.1016/j.cie.2019.05.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Critical infrastructure networks such as transportation, telecommunications, electric power, natural gas and oil, and water distribution rely on one another for their proper functionality. Hence, they are increasingly interdependent, making them highly vulnerable, where the occurrence of even a small disruption in one infrastructure network could propagate to affect other dependent infrastructure networks leading to a more significant adverse impact on society. Therefore, a key aspect of preparedness planning in infrastructure networks is identifying the critical network components that influence not only (i) the performance of their networks the most when disrupted and restored but also (ii) the performance of other networks due to their interdependent nature. This work offers a means to study the importance of interdependent network components with a resilience-focused performance measure in mind. We propose two component importance measures, (i) the first of which quantifies the effect of disrupted components on the resilience of the interdependent infrastructure networks once they are recovered, while (ii) the second measures the potential impact on the resilience of the interdependent infrastructure networks caused by a specific disrupted network element. The proposed measures are illustrated through generated interdependent power-water networks and compared with two other common network centrality measures. The use of such measures could identify components that are candidates for the allocation of resources to reduce their vulnerability or to expedite their recovery.
引用
收藏
页码:153 / 164
页数:12
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