A Boolean Networks Approach to Modeling and Resilience Analysis of Interdependent Critical Infrastructures

Abstract

In this article, we propose a dynamic Boolean network‐type mathematical representation of networked critical infrastructures under stress. Our formulation is obtained as a threshold‐based approximation of a discrete‐time switched system meant to describe failure and recovery phases that may span considerably different time periods. The formalism can incorporate mitigating factors, resource constraints, and allocation strategies affecting the response of the system and the unfolding of restoration processes. As such, the tool may inform both contingency planning and consequence assessment. We also discuss an illustrative case study concerning the recovery process of selected infrastructures of the Thessaloniki Port in an earthquake scenario. Simulations are performed for assigned parameter distributions associated with the different operational modes. Finally, a performance loss indicator is computed to assess the overall service perturbation affecting the system. For the needs of this analysis, fragility curves have been selected from the literature, whereas restoration curves, recovery priorities, classification of components, and other modeling variables have been defined in collaboration with the local Port Authority.

Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets

“…The available restoration models correlate the recovery time with the functionality reached for a given damage level, e.g. Gidaris et al (2017) for bridges, Galbusera et al (2018) for port facilities, Castillo et al (2014) for electric power systems, Luna et al, (2011) for water distribution systems and HAZUS-MH (2011) for various infrastructure assets. They are typically based on expert judgments, following a linear, e.g.…”

The Resilience of Critical Infrastructure Systems: A Systematic Literature Review

“…Some studies described resilience as the "system's joint ability to resist (prevent and withstand) any possible hazards, absorb the initial damage, and recover to normal operation" [109][110][111][112]. The US National Academies of Science (NAS) defined system's resilience as the "system's ability to prepare and plan for, absorb, recover from, and successfully adapt to disruptive events" [77,113,114]. According to the US Presidential Policy Directive (PPD), resilience can be defined as the "system's ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptive events" [88,115].…”

The Effect of Time-Varying Value on Infrastructure Resilience Assessments

“…1). Units of time vary, with examples adopting minutes [85], [86], hours [87], days [15], [20], and weeks [88]. Without loss of generality, this manuscript scales time, , to the control interval such ∈ [0,1].…”

“…Specific definitions vary across domains and analysis techniques. Examples include: connected electrical generation capacity [19], functional cranes at a seaport [20], volume of gas supplied [21], average vehicle speed [22], and travel time in a transportation network [23]. In most cases, measures are normalized relative to a performance target or baseline (e.g., percent of customers with utility service [24], [25] or satisfied demand [26], [27]).…”