Guidotti Roberto, Chmielewski Hana, Unnikrishnan Vipin, Gardoni Paolo, McAllister Therese, van de Lindt John
Department of Civil and Environmental Engineering, MAE Center, University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA.
NIST Center of Excellence for Risk-Based Community Resilience Planning, Colorado State University, Fort Collins, CO, USA.
Sustain Resilient Infrastruct. 2016;1(3-4):153-168. doi: 10.1080/23789689.2016.1254999. Epub 2016 Dec 22.
Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.
水和废水网络、电力网络、交通网络、通信网络以及信息技术网络是我们社区中的关键基础设施;在灾害事件期间及之后,这些网络的中断会极大地影响社区的福祉、经济安全、社会福利和公众健康。此外,一个网络的中断可能会导致其他网络中断,并使其功能下降。本文提出了一种统一的理论方法,用于对相关/相互依存的基础设施网络进行建模,并将其纳入一个六步概率程序中,以评估其恢复力。该方法和程序具有通用性,可应用于任何基础设施网络和灾害,并且可以对网络之间不同类型的相关性进行建模。作为示例,本文对地震事件对饮用水分配网络功能的直接影响以及电力网络(EPN)损坏对饮用水分配网络(WN)的级联影响进行了建模。结果量化了由于WN对EPN的依赖性而导致的功能丧失和恢复过程中的延迟。结果表明,在对关键基础设施的恢复力进行建模时,捕捉网络之间的依赖性非常重要。