A Mathematical Framework to Optimize Critical Infrastructure Resilience against Intentional Attacks

This article establishes a tri‐level decision‐making model supporting critical infrastructure (CI) resilience optimization against intentional attacks. A novel decomposition algorithm is proposed to exactly identify the best pre‐event defense strategy (protecting vulnerable components and building new lines), the worst‐case attack scenario, and the optimal postevent repair sequence of damaged components. As different types of CIs have different flow models, this article mainly considers the direct current power flow model and the maximal flow model for illustrative purposes. The proposed framework is illustrated by a simple but representative case system with nine nodes, and main results include: (1) the marginal value of extra defense investment under low defense budget is more considerable for mitigating system resilience loss, especially under large intentional attacks; (2) no defense strategy is always the best under different attack budgets; (3) increasing amount of repair resources can dramatically enhance CI resilience, but makes the pre‐event defense strategy less effective; (4) the use of maximal flow model can provide a lower bound estimation of the resilience loss from the power flow model; (5) the optimum defense strategy and the worst‐case attack identified by minimizing CI resilience loss largely differ from those by minimizing CI vulnerability, where the latter does not consider the recovery actions. Finally, the algorithm complexity is analyzed by comparing with the enumeration method and by testing two larger electric power systems.     

Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

This paper presents a Bayesian network model to assess the vulnerability of the flood control infrastructure and to simulate failure cascade based on the topological structure of flood control networks along with hydrological information gathered from sensors. Two measures are proposed to characterize the flood control network vulnerability and failure cascade: (a) node failure probability (NFP), which determines the failure likelihood of each network component under each scenario of rainfall event, and (b) failure cascade susceptibility, which captures the susceptibility of a network component to failure due to failure of other links. The proposed model was tested in both single watershed and multiple watershed scenarios in Harris County, Texas using historical data from three different flooding events, including Hurricane Harvey in 2017. The proposed model was able to identify the most vulnerable flood control network segments prone to flooding in the face of extreme rainfall. The framework and results furnish a new tool and insights to help decision‐makers to prioritize infrastructure enhancement investments and actions. The proposed Bayesian network modeling framework also enables simulation of failure cascades in flood control infrastructures, and thus could be used for scenario planning as well as near‐real‐time inundation forecasting to inform emergency response planning and operation, and hence improve the flood resilience of urban areas.     

What’s Critical about Critical Infrastructure?

Abstract

Critical infrastructure (CI) has received much attention in research, policy and political discussions in recent years, following concern over exposure of infrastructure to terrorist attack, disruption through disasters, rising awareness of the interdependent nature of infrastructure in modern urban systems, and changes in the ownership of and responsibility for infrastructure assets. In this paper, we explore the implications of different framings of both “critical” and “infrastructure”, through two questions: critical how and for whom; critical when and at what scale? Framings of CI, and their increasingly important manifestations in policy and law, have deep but too-often unexposed implications: the lines drawn between what is defined as critical and that which is not concerns not only the physical or informational assets, but the inclusion/exclusion of communities and their places and values as important aspects of modern urban governance. We argue that a better understanding of what is critical about urban infrastructure is not just recognition of their vulnerability and interconnectedness, but also of the key linkages between critical infrastructure and human and environmental system integrity and equity within the context of capitalist urbanisation.     

Protecting water and wastewater utilities from cyber‐physical threats

Recent events have highlighted the need to address cybersecurity threats to systems supporting critical infrastructure and federal information systems which are evolving and growing. These threats have become ubiquitous in the United States, and throughout the world. Many information and communications technology (ICT) devices and other components are interdependent so that disruption of one component may have a negative, cascading effect on others. In the United States, the Federal role in cyber‐security has been debated for more than a decade but creating a policy is complicated because in the United States, State and local governments are the major institutions responsible for providing services to their populations. It is important that critical infrastructure such as Publically Owned Treatment Works (POTWs) and Public Water Systems (PWSs) adopt suitable countermeasures to prevent or minimise the consequences of cyber‐attacks. This paper discusses both technological and procedural techniques that can be used to protect against cyber‐threats.     

Cognitive infrastructure - a modern concept for resilient performance under extreme events

The increasing frequency and intensity of natural disasters, as well as escalation of manmade threats, are posing significant threats to the built environment. Further, much of civil infrastructure in developed countries, built after World War II, is experiencing age-related deterioration and thus are vulnerable to damage under extreme events. This vulnerability of infrastructure under severe loading conditions can be assessed through a coupled sensing-structural framework that extends principles of the recently developed “Internet of Things” (IoT) technology into civil infrastructure. This concept aims at monitoring key response parameters (i.e. temperature, strain, deformation, vibration levels etc.) by incorporating cognitive abilities into a structure through interaction of various sensing devices and socio-environmental factors. These response parameters can be utilized to trace performance of critical infrastructure during the course of a disaster so as to predict signs of imminent failure and to provide first responders and occupants with much needed situational awareness. The practicality of the proposed concept in enhancing resilience of new and existing infrastructure is illustrated through two case studies.     

A cross‐scale refined damage evolution analysis of large commercial aircraft crashing into a nuclear power plant

Since the 9/11 attacks, whether nuclear power plants (NPPs) can withstand the malicious impact of large commercial aircraft has become a question that must be considered in the design phase. Refined model and fine‐scale element reflect more accurately the failure procedure and behaviour. However, due to the exceedingly complex structure of NPP, the traditional meshing method requires a substantial number of geometric operations involving point, line, area, and volume, leading to a tedious modelling process and very high computational costs, as well as making it difficult to modify and optimize the model. This paper combines the scaled boundary finite element method with the octree technique to refine nuclear engineering damage evolution analysis and establish a refined numerical model of the Generation III⁺ NPP, considering the detailed equipment hatch, air intake, and internal steel containment vessel structures. Subsequently, the refined damage evolution analysis of a large commercial aircraft crashing into an NPP was developed. The mesh size sensitivity, impact region shape comparison, and the influence of different impact heights were discussed. The results indicate that the cross‐scale refined meshing and analysis method provides a high‐quality discrete grid with fewer elements. Furthermore, this method is highly flexible, more accurately simulating the damage evolution and gradual destruction process. We recommend future structural optimization for the air intake and conducting detailed analyses at this location. The cross‐scale analysis method presented in this paper enables a rapid, refined simulation of a malicious impact by a large commercial aircraft. Additionally, it provides technical support for future studies of the responses of NPPs' internal structures, systems, and equipment under extreme earthquake and other disaster conditions.     

双向耦合剪切条件下饱和松砂的液化特性试验研究

为了模拟海床及海洋建筑物遭受波浪荷载时所引起的循环应力,进行了一系列均等固结条件下的应力控制式轴向–扭转双向耦合循环剪切试验。加载路径在σd/2-τ应力空间内为椭圆。试验在保证椭圆面积不变的情况下,分别变化竖向和扭转向的荷载分量幅值,以此来探讨双向耦合剪切试验中各个分量的变化对饱和松砂的循环强度特性的影响。试验结果表明砂土在双向耦合荷载作用下,其液化强度与加载椭圆路径的面积和两个荷载分量比值密切相关。当轴向应力与剪应力幅值的比值保持不变时,砂土液化强度随着椭圆面积的增大而降低。而在椭圆面积保持不变时,当竖向与扭转向荷载分量的比值小于某一临界值0.6～0.75时,砂土液化强度随着比值的增加而增大,当竖向与扭转向荷载分量的比值大于某一临界值0.6～0.75时,砂土的液化强度随着比值的增加而减小,在临界值0.6～0.75之间表现出最高的强度。另外,在一个周期内孔隙水压力的循环变化与轴向应力相位一致,与循环剪应力相位相差90。     

A simulation-based generalized framework to model vulnerability of interdependent critical infrastructure systems under incomplete information

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.     

A simple drought risk analysis procedure to supplement water resources management planning in England and Wales

The current ‘Deployable Output’ approach for assessing water resources system performance in England and Wales is a practical, communicable means for assessing the adequacy of a water supply system and determining the relative benefits of proposed system enhancements. A recognised flaw with this approach is that it fails to characterise the severity of potential supply shortfalls, leading to mischaracterisation of risks and benefits associated with alternative candidate investments. Here, we propose a Monte Carlo procedure that could supplement the existing process by exposing the magnitude (% water demand unserved) and duration (number of days) of supply curtailments under a range of drought scenarios. The method is demonstrated using a realistic, stylised water resources system and a discrete number of infrastructure investments. Results demonstrate that vulnerability assessments can expose previously unidentified risks that might radically alter a planner’s estimate of the cost‐effectiveness of a particular investment.     

Continuous and multidimensional assessment of resilience based on functionality analysis for interconnected systems

The increasing number of disruptions to critical infrastructure, like natural disasters, terrorist attacks or internal failure is today a major problem of society. Concern is even greater when considering the interconnected nature of critical infrastructure, which might lead to failure propagation, causing domino and cascade effects. To mitigate such outcomes, critical infrastructure must recover its capacity to function with regard to several criteria. Stakeholders must therefore analyse and improve the resilience of critical infrastructure before any disruption occurs, and base this analysis on different models so as to guarantee society’s vital needs. Current resilience assessment methods are mainly oriented toward the context of a single system, thus narrowing their criteria metrics, limiting flexibility and adaptation to other contexts and overlooking the interconnected nature of systems. This article introduces a new tool-equipped approach that makes it possible to define a model to evaluate the functionalities of interconnected systems. The model is then used to assess the resilience of these systems based on simple and generic criteria that can be extended and adapted. Several assertions related to the concept of resilience and some resilience indicators are also introduced. A case study provides the validation performed by experts from several domains.     

基础设施PPP项目脆弱性影响因素研究

以基础设施 PPP 项目为对象,借助网络模型,对其进行脆弱性影响因素的研究。基础设施 PPP 项目作为一个系统,其脆弱性往往由脆弱性影响因素诱发。将影响因素作为网络中的节点,因素间的关联关系及强度作为边和权重,在此基础上构建无向加权网络。通过对网络模型参数的计算,可以按照重要程度对脆弱性影响因素进行排序,从而为基础设施 PPP 项目的风险管理提供理论依据和实践指导。     

The Interdependent Network Design Problem for Optimal Infrastructure System Restoration

This study introduces the Interdependent Network Design Problem (INDP), concerned with defining the minimum‐cost reconstruction strategy of a partially destroyed system of infrastructure networks, subject to budget, resources, and operational constraints, while considering interdependencies between them. To solve the INDP, the authors develop an efficient Mixed Integer Programming (MIP) model, which considers different types of interdependency while exploiting efficiencies from joint restoration due to colocation for the first time. The authors also propose heuristic methodologies based on simulation and the iterative use of the INDP model, to enable studying problems with additional complexity, such as accounting for uncertainty from possible disaster scenarios, or determining not only what to reconstruct but the order of reconstruction. Such methodologies enable the analysis of expected costs and performance associated to reconstruction of the system of networks, providing an effective tool for infrastructure decision makers. To exemplify the capabilities of the presented INDP‐based methodologies, the authors study the process of restoration of a set of interdependent networks after hypothetical earthquakes in Shelby County, TN, United States. Results show that the INDP‐based approaches that account for time‐dependent recovery converge to quasi‐optimal solutions in all 16 configurations studied, considering four different resource levels and four different earthquake magnitudes. Similarly, as desired in emergency response scenarios, the rate of performance recovery is high in the early reconstruction stages, recovering more than 85% of performance in the first stage in a worst‐case scenario.     

A Methodology for Assessing Transportation Network Terrorism Risk with Attacker and Defender Interactions

Abstract: In an adversarial setting, a transportation network's capacity is influenced by both the defender's protective measures and the attacker's actions, which include substituting targets and attack methods in response to security measures. Decision makers need a methodology that can capture the complex attacker–defender interactions and help them understand the overall effects on the transportation system, as well as the consequences of asset failure. This article presents such a methodology, which uses probabilities of target–attack method combinations that are degree of belief based and updated using Bayes' Theorem after evidence of the attack is obtained. Monte Carlo simulation generates the probability of link capacity effects by sampling from distributions of capacity reductions due to preevent security measures, substitutions, target failure, and postevent security measures. The average capacity reduction for a particular target–attack method combination serves as an input to the traffic assignment–simulation package DYNASMART‐P to determine travel time effects. The methodology is applied to a sample network based on the northern Virginia area. Results based on notional data indicated that preevent security measures reduced attack probabilities, but in some cases increased the mobility consequences. Thus, decision makers must carefully evaluate the effects of their decisions.     

Quantifizierung der Schadenspotentiale infolge Erdbeben – Teil 2: Modellstudie Baden‐Württemberg

Assessment of damage and loss potentials due to earthquake (2): Model study Baden Wuerttemberg. For the study area of Baden‐Wuerttemberg an intensity‐oriented and thus empirical approach of seismic risk analysis is taken. Explaining the essential work steps, the proximity to reality and the scatter of the results are discussed. Regional differences in the building substance and consequences for the damage expectation to be derived thereof are illustrated. A regionalisation factor is suggested, which reflects the vulnerability of building types and leads to a modification of damage functions; it is derived from extensive data surveys from the model region. The procedures and the processing levels implemented in the model are structured transparently and presented in the paper. The scenarios refer to historical earthquakes with remarkable detailing of the available regional shake maps. For these events it can be proven that losses corresponding to the intensity are calculated if the most important influence factors from soil and building vulnerability are considered. Losses from maximum events are determined by simply increasing the intensity; for worst‐case‐scenarios the respectively strongest shake effects for all communities are superimposed summarily. By applying the gross domestic capital and other statistical property values a relative loss can be derived. The communities are differentiated regarding inhabitant numbers in order to illustrate differences in how heavily affected they are. The calculated scenarios confirm that in the model region, small and medium‐sized towns deserve more attention regarding earthquake preparation than large city centres.     

A graph‐based method for social sensing of infrastructure disruptions in disasters

Damages in critical infrastructure occur abruptly, and disruptions evolve with time dynamically. Understanding the situation of critical infrastructure disruptions is essential to effective disaster response and recovery of communities. Although the potential of social media data for situation awareness during disasters has been investigated in recent studies, the application of social sensing in detecting disruptions and analyzing evolutions of the situation about critical infrastructure is limited. To address this limitation, this study developed a graph‐based method for detecting credible situation information related to infrastructure disruptions in disasters. The proposed method was composed of data filtering, burst time‐frame detection, content similarity calculation, graph analysis, and situation evolution analysis. The application of the proposed method was demonstrated in a case study of Hurricane Harvey in 2017 in Houston. The findings highlighted the capability of the proposed method in detecting credible situational information and capturing the temporal and spatial patterns of critical infrastructure events that occurred in Harvey, including disruptive events and their adverse impacts on communities. The proposed methodology can improve the ability of community members, volunteer responders, and decision makers to detect and respond to infrastructure disruptions in disasters.     

Multiagent Simulation for Complex Adaptive Modeling of Road Infrastructure Resilience to Sea‐Level Rise

Infrastructure systems in coastal areas are exposed to episodic flooding exacerbated by sea‐level rise stressors. To enable assessing the long‐term resilience of infrastructure to such chronic impacts of sea‐level rise, the present study created a novel complex system modeling framework that integrates: (i) stochastic simulation of sea‐level rise stressors, based on the data obtained from downscaled climate studies pertaining to future projections of sea level and precipitation; (ii) dynamic modeling of infrastructure conditions by considering regular decay of infrastructure, as well as structural damages caused by flooding; and (iii) a decision‐theoretic modeling of infrastructure management and adaptation processes based on bounded rationality and regret theories. Using the proposed framework and data collected from a road network in Miami, a multiagent computational simulation model was created to assess the long‐term cost and performance of the road network under various sea‐level rise scenarios, adaptation approaches, and network degradation effects. The results showed the capabilities of the proposed computational model for robust planning and scenario analysis to enhance the resilience of infrastructure systems to sea‐level rise impacts.     

Using Micro-Level Data to Evaluate Infrastructure of the Walking Environment Around Bus Rapid Transit Stations:A Case Study of Xiamen,China

China has experienced rapid car-oriented suburbanization during the past decades and is facing emerging challenges such as traffic congestion,air pollution,and even health threats.Learning from North American cities,Chinese cities have started adopting and implementing a Transit-Oriented Development(TOD) strategy,which encourages the transit ridership and walking trips by creating a pedestrian-friendly urban environment.Although much research has examined the walking environment in various neighborhoods or communities,few existing studies have examined the walking environment around transit stations,especially using micro-level data,such as walking infrastructure variables.This research chooses several infrastructure variables that are critical for pedestrians to investigate the walking environment around stations of the Bus Rapid Transit(BRT) No.1 Line in Xiamen City,China.This study defines a half mile buffer centered on each station as the spatial unit of analysis.The Geographic Information System(GIS) and field audits are employed to measure the characteristics of the infrastructure for pedestrians in each spatial unit of analysis.The results of this analysis can help assess the existing conditions of the infrastructure for pedestrians in each station area,which might need to be added or improved.The findings will not only provide empirical support for improving TODs in Xiamen,but also offer a lesson on how areas around transit stations could be retrofitted to improve the pedestrian environment.     

Inter-agency governance risk in managing hospital responses to extreme weather events in New South Wales,Australia: a facilities management perspective of shared situational awareness

Extreme weather is predicted to become more frequent and severe into the future. While our understanding of hospital infrastructure vulnerability to such events has advanced considerably in recent years, current approaches to healthcare facilities management treat hospitals in isolation from their surrounding governance infrastructure. However, recent research indicates that if hospital resilience is to be properly understood, health infrastructure must be managed holistically, as part of a much larger governance system of interdependent organizations. The inter-agency governance risks associated with this system are currently ignored in the facilities management literature. To explore these risks, an in-depth case study of 24 agencies in the state of New South Wales, Australia is presented. The results show that facilities managers are embedded in a highly complex and dynamic array of governance boundaries which are largely unresolved and misunderstood. A number of practical strategies are presented which could be adopted to significantly improve facilities manager’s integration into this system. These include: mapping hospital dependency on other agencies to build surge capacity; resolving overlapping operational boundaries with other agencies; proactive risk reduction for critical external support infrastructure; understanding potential conflicts with the objectives external agencies in responding to an extreme weather event.     

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

The connected vehicle can be easily attacked by cyber threats due to its communication through the wireless network in an open‐access environment. But very few studies have paid attention to the spreading of malicious information such as denial of service, message delay/replay, and eavesdropping generated by cyberattacks. To this end, this article introduces an analytical model, named vehicular malicious information propagation (VMIP), which integrates a classical epidemic model through two‐layer system structure, in which the upper layer describes the malicious information spreading and the lower describes the traffic flow dynamics. The proposed VMIP model is designated for platooned (one‐lane, particularly) traffic. Numerical experiments show the proposed model can efficiently describe the interactions between traffic dynamics and malicious information spreading; and the information propagation highly depends on traffic flow patterns. This article is expected to contribute to a better understanding of the impacts of cyberattacks on traffic and lays a foundation for future development of control strategies on mitigating the disastrous effects of cyberattacks.     

Securing water and wastewater systems: global perspectives

There has been long‐standing concern that water systems are vulnerable to man‐made and natural threats. In the United States, after the events of 11 September 2001, government planners focused on the possibility that the nation's critical infrastructure may be vulnerable to terrorist attacks. However, as demonstrated in this paper, there are many other factors that influence water supply security including lack of water resource availability, threats from point and nonpoint source pollution to water‐related ecosystems, and impact of climate change. In order to meet water security threats, there is a need to balance human and environmental water needs while at the same time safeguarding essential ecosystem services and biodiversity. Integrated water resources management may help achieve this balance. Examples are presented, which illustrate the diversity of water security throughout the world.