skip to main content


Title: A simulation‐based generalized framework to model vulnerability of interdependent critical infrastructure systems under incomplete information
Abstract

This paper proposes a novel simulation‐based hybrid approach coupled with time‐dependent Bayesian network analysis to model multi‐infrastructure vulnerability over time under physical, spatial, and informational uncertainties while considering cascading failures within and across infrastructure networks. Unlike existing studies that unrealistically assume that infrastructure managers have full knowledge of all the infrastructure systems, the proposed approach considers a realistic scenario where complete information about the infrastructure network topology or the supply–demand flow characteristics is not available while estimating multi‐infrastructure vulnerability. A novel heuristic algorithm is proposed to construct a dynamic fault tree to abstract the network topology of any infrastructure. In addition, to account for the unavailability of exact supply–demand flow characteristics, the proposed approach constructs the interdependence links across infrastructure network systems using different simulated parameters considering the physical, logical, and geographical dependencies. Finally, using parameters for geographical proximity, infrastructure managers' risk perception, and the relative importance of one infrastructure on another, the multi‐infrastructure vulnerability over time is estimated. Results from the numerical experiment show that for an opportunistic risk perception, the interdependencies attribute to redundancies, and with an increase in redundancy, the vulnerability decreases. On the other hand, from a conservative risk perspective, the interdependencies attribute to deficiencies/liabilities, and the vulnerability increases with an increase in the number of such interdependencies.

 
more » « less
NSF-PAR ID:
10405408
Author(s) / Creator(s):
 ;  
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Computer-Aided Civil and Infrastructure Engineering
Volume:
38
Issue:
18
ISSN:
1093-9687
Format(s):
Medium: X Size: p. 2537-2559
Size(s):
["p. 2537-2559"]
Sponsoring Org:
National Science Foundation
More Like this
  1. Baraldi, P. ; null ; Zio, E. (Ed.)
    Critical infrastructure networks are becoming increasingly interdependent which adversely impacts their performance through the cascading effect of initial failures. Failing to account for these complex interactions could lead to an underestimation of the vulnerability of interdependent critical infrastructure (ICI). The goal of this research is to assess how important interdependent links are by evaluating the interdependency strength using a dynamic network flow redistribution model which accounts for the dynamic and uncertain aspects of interdependencies. Specifically, a vulnerability analysis is performed considering two scenarios, one with interdependent links and the other without interdependent links. The initial failure is set to be the same under both scenarios. Cascading failure is modeled through a flow redistribution until the entire system reaches a stable state in which cascading failure no longer occurs. The unmet demand of the networks at the stable state over the initial demand is defined as the vulnerability. The difference between the vulnerability of each network under these two scenarios is used as the metric to quantify interdependency strength. A case study of a real power-water-gas system subject to earthquake risk is conducted to illustrate the proposed method. Uncertainty is incorporated by considering failure probability using Monte Carlo simulation. By varying the location and magnitude of earthquake disruptions, we show that interdependency strength is determined not only by the topology and flow of ICIs but also the characteristics of the disruptions. This compound system-disruption effect on interdependency strength can inform the design, assessment, and restoration of ICIs. 
    more » « less
  2. d. Many of the infrastructure sectors that are considered to be crucial by the Department of Homeland Security include networked systems (physical and temporal) that function to move some commodity like electricity, people, or even communication from one location of importance to another. The costs associated with these flows make up the price of the network’s normal functionality. These networks have limited capacities, which cause the marginal cost of a unit of flow across an edge to increase as congestion builds. In order to limit the expense of a network’s normal demand we aim to increase the resilience of the system and specifically the resilience of the arc capacities. Divisions of critical infrastructure have faced difficulties in recent years as inadequate resources have been available for needed upgrades and repairs. Without being able to determine future factors that cause damage both minor and extreme to the networks, officials must decide how to best allocate the limited funds now so that these essential systems can withstand the heavy weight of society’s reliance. We model these resource allocation decisions using a two-stage stochastic program (SP) for the purpose of network protection. Starting with a general form for a basic two-stage SP, we enforce assumptions that specify characteristics key to this type of decision model. The second stage objective—which represents the price of the network’s routine functionality—is nonlinear, as it reflects the increasing marginal cost per unit of additional flow across an arc. After the model has been designed properly to reflect the network protection problem, we are left with a nonconvex, nonlinear, nonseparable risk-neutral program. This research focuses on key reformulation techniques that transform the problematic model into one that is convex, separable, and much more solvable. Our approach focuses on using perspective functions to convexify the feasibility set of the second stage and second order conic constraints to represent nonlinear constraints in a form that better allows the use of computational solvers. Once these methods have been applied to the risk-neutral model we introduce a risk measure into the first stage that allows us to control the balance between an efficient, solvable model and the need to hedge against extreme events. Using Benders cuts that exploit linear separability, we give a decomposition and solution algorithm for the general network model. The innovations included in this formulation are then implemented on a transportation network with given flow demand 
    more » « less
  3. Critical infrastructure networks, including water, power, communication, and transportation, among others, are necessary to society’s functionality. In recent years, the threat of different types of disruptions to such infrastructure networks has become an increasingly important problem to address. Due to existing interdependencies, damage to a small area of one of the networks could have far-reaching effects on the ability to meet demand across the entire system. Common disruption scenarios include, among others, intentional malevolent attacks, natural disasters, and random failures. Similar works have focused on only one type of scenario, but combining a variety of disruptions may lead to more realistic results. Additionally, the concept of social vulnerability, which describes an area’s ability to prepare for and respond to a disruption, must be included. This should promote not only the protection of the most at-risk components but also ensure that socially vulnerable communities are given adequate resources. This work provides a decision making framework to determine the allocation of defensive resources that accounts for all these factors. Accordingly, we propose a multi-objective mathematical model with the objectives of: (i) minimizing the vulnerability of a system of interdependent infrastructure networks, and (ii) minimizing the total cost of the resource allocation strategy. Moreover, to account for uncertainty in the proposed model, this paper incorporates a means to address robustness in finding the most adaptable network protection plan to reduce the vulnerability of the system of interdependent networks to a variety of disruption scenarios. The proposed work is illustrated with an application to social vulnerability and interdependent power, gas, and water networks in Shelby County, Tennessee. 
    more » « less
  4. Lankes, R.David (Ed.)
    Resilience is often treated as a single-dimension system attribute, or various dimensions of resilience are studied separately without considering multi-dimensionality. The increasing frequency of catastrophic natural or man-made disasters affecting rural areas demands holistic assessments of community vulnerability and assessment. Disproportionate effects of disasters on minorities, low-income, hard-to-reach, and vulnerable populations demand a community-oriented planning approach to address the “resilience divide.” Rural areas have many advantages, but low population density, coupled with dispersed infrastructures and community support networks, make these areas more affected by natural disasters. This paper will catalyze three key learnings from our current work in public librarians’ roles in disaster resiliency: 1) rural communities are composed of diverse sub-communities, each which experiences and responds to traumatic events differently, depending on micro-geographic and demographic drivers; 2) public libraries are central to rural life, providing a range of informational, educational, social, and personal services, especially in remote areas that lack reliable access to community resources during disasters; and 3) rural citizens tend to be very self-reliant and are committed to strengthening and sustaining community resiliency with local human capital and resources. Public libraries and their librarian leaders are often a “crown jewel” of rural areas’ community infrastructure and this paper will present a community-based design and assessment process for resiliency hubs located in and operated through rural public libraries. The core technical and social science research questions explored in the proposed paper are: 1) Who were the key beneficiaries and what did they need? 2) What was the process of designing a resiliency hub? 3) What did library resiliency hubs provide and how can they be sustained? This resiliency hub study will detail co-production of solutions and involves an inclusive collaboration among researchers, librarians, and community members to address the effects of cascading impacts of natural disasters. The novel co-design process detailed in the paper reflects 1) an in-depth understanding of the complex interactions among libraries, residents, governments, and other agencies by collecting sociotechnical hurricane-related data for Calhoun County, Florida, USA, a region devastated by Hurricane Michael (2018) and hard-hit by Covid-19; 2) analyzed data from newly-developed fusing algorithms and incorporating multiple communities; and 3) co-designed resiliency hubs sited in public libraries. This research leverages a unique opportunity for the co-development of integrated library-centered policies and technologies to establish a new paradigm for developing disaster resiliency in rural settings. Public libraries serve a diverse population who will directly benefit from practical support tailored to their needs. The project will inform efficient plans to ensure that high-need groups are not isolated in disasters. The knowledge and insight gained from disseminating the study’s results will not only improve our understanding of emergency response operations, but also will contribute to the development of new disaster-related policies and plans for public libraries, with a broader application to rural communities in many settings. 
    more » « less
  5. Lankes, R. David (Ed.)
    Resilience is often treated as a single-dimension system attribute, or various dimensions of resilience are studied separately without considering multi-dimensionality. The increasing frequency of catastrophic natural or man-made disasters affecting rural areas demands holistic assessments of community vulnerability and assessment. Disproportionate effects of disasters on minorities, low-income, hard-to-reach, and vulnerable populations demand a community-oriented planning approach to address the “resilience divide.” Rural areas have many advantages, but low population density, coupled with dispersed infrastructures and community support networks, make these areas more affected by natural disasters. This paper will catalyze three key learnings from our current work in public librarians’ roles in disaster resiliency: rural communities are composed of diverse sub-communities, each which experiences and responds to traumatic events differently, depending on micro-geographic and demographic drivers. Rural citizens tend to be very self-reliant and are committed to strengthening and sustaining community resiliency with local human capital and resources. Public libraries are central to rural life, providing a range of informational, educational, social, and personal services, especially in remote areas that lack reliable access to community resources during disasters. Public libraries and their librarian leaders are often a “crown jewel” of rural areas’ community infrastructure and this paper will present a community-based design and assessment process for resiliency hubs located in and operated through rural public libraries. The core technical and social science research questions explored in the proposed paper are: 1) Who were the key beneficiaries and what did they need? 2) What was the process of designing a resiliency hub? 3) What did library resiliency hubs provide and how can they be sustained? This resiliency hub study will detail co-production of solutions and involves an inclusive collaboration among researchers, librarians, and community members to address the effects of cascading impacts of natural disasters. The novel co-design process detailed in the paper reflects an in-depth understanding of the complex interactions among libraries, residents, governments, and other agencies by collecting sociotechnical hurricane-related data for Calhoun County, Florida, USA, a region devastated by Hurricane Michael (2018) and hard-hit by Covid-19. We analyzed data from newly developed fusing algorithms and incorporating multiple communities and developed a framework and process to co-design resiliency hubs sited in public libraries. This research leverages a unique opportunity to library-centered policies and technologies to establish a new paradigm for developing disaster resiliency in rural settings. Public libraries serve a diverse population who will directly benefit from practical support tailored to their needs. The project will inform efficient plans to ensure that high-need groups are not isolated in disasters. The knowledge and insight gained from the resiliency hub design process will not only improve our understanding of emergency response operations, but also will contribute to the development of new disaster related policies and plans for public libraries, with a broader application to rural communities in many settings. 
    more » « less