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The purpose of this paper is to present a novel approach that examines the vulnerability and interdependency of critical infrastructures using the network theory in geographic information system (GIS) setting in combination with literature and government reports. Specifically, the objectives of this study were to generate the network models of critical infrastructure systems (CISs), particularly electricity, roads and sewerage networks; to characterize the CISs’ interdependencies; and to outline the climate adaptation (CA) and flood mitigation measures of CIS.

An integrated approach was undertaken in assessing the vulnerability and interdependency of critical infrastructures. A single system model and system-of-systems model were operationalized to examine the vulnerability and interdependency of the identified critical infrastructures in GIS environment. Existing CA and flood mitigation measures from government reports were integrated in the above-mentioned findings to better understand and gain focus in the implementation of natural disaster risk reduction (DRR) policies, particularly during the 2010/2011 floods in Queensland, Australia.

Using the results from the above-mentioned approach, the spatially explicit framework was developed with four key operational dimensions: conceiving the climate risk environment; understanding the critical infrastructures’ common cause and cascade failures; modeling individual infrastructure system and system-of-systems level within GIS setting; and integrating the above-mentioned results with the government reports to increase CA and resilience measures of flood-affected critical infrastructures.

While natural DRR measures include preparation, response and recovery, this study focused on flood mitigation. Temporal analysis and application to other natural disasters were also not considered in the analysis.

By providing this information, government-owned corporations, CISs managers and other concerned stakeholders will allow to identify infrastructure assets that are highly critical, identify vulnerable infrastructures within areas of very high flood risk, examine the interdependency of critical infrastructures and the effects of cascaded failures, identify ways of reducing flood risk and extreme climate events and prioritize DRR measures and CA strategies.

The individualist or “pigeon-hole” approach has been the common method of analyzing infrastructures’ exposure to flood hazards and tends to separately examine the risk for different types of infrastructure (e.g. electricity, water, sewerage, roads and rails and stormwater). This study introduced an integrated approach of analyzing infrastructure risk to damage and cascade failure due to flooding. Aside from introducing the integrated approach, this study operationalized GIS-based vulnerability assessment and interdependency of critical infrastructures which had been unsubstantially considered in the past analytical frameworks. The authors considered this study of high significance, considering that floodplain planning schemes often lack the consideration of critical infrastructure interdependency.

As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).

The paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.

The digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.

This research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

Resource allocation is essential to infrastructure management. The purpose of this study is to develop a methodological framework for resource allocation that takes interdependencies among infrastructure systems into consideration to minimize the overall impact of infrastructure network disruptions due to extreme events.

Taking advantage of agent-based modeling techniques, the proposed methodology estimates the interdependent effects of a given infrastructure failure which are then used to optimize resource allocation such that the network-level resilience is maximized.

The findings of the study show that allocating resources with the proposed methodology, where optimal infrastructure reinforcement interventions are implemented, can improve the resilience of infrastructure networks with respect to both direct and interdependent risks of extreme events. These findings are also verified by the results of two case studies.

As the two case studies have shown, the proposed methodological framework can be applied to the resource allocation process in asset management practices.

The proposed methodology improves the resilience of the infrastructure network, which can alleviate the social and economic impact of extreme events on communities.

Capitalizing on the combination of agent-based modeling and simulation-based optimization techniques, this study fulfills a critical gap in infrastructure asset management by incorporating infrastructure interdependence and resilience concepts into the resource allocation process.

The purpose of this paper is to map the cascade effects of emergencies on critical infrastructure in a fast-growing city of a developing country. The paper specifically seeks to refocus the attention of decision makers and emergency managers towards a more effective way of reducing risk and costs associated with contingencies.

The study was based on a 2D representation of the three initiating events of fire, flood and automobile crashes. Detailed analysis was undertaken of the effects on the critical infrastructure, based on the probability of occurrence, frequency, spatial extent and degree of damage for the emergencies studied. Subsequently, a cascade matrix was generated to analyse the level of interaction or interdependencies between the participating critical infrastructures in the study area. A model of the cascade effects under a typical emergency was also generated using a software model of network trace functions.

The results show that while different levels of probability of occurrence, frequency and extent of damage was observed on the evaluated critical infrastructure under different emergency events, damage to the electricity distribution components of the critical infrastructure recorded the highest cascade effect for all emergency events.

This paper underlines the need to pay greater attention to providing protection to critical infrastructure in the rapidly growing cities, especially in developing countries. Findings from this study in Abeokuta, Nigeria, underscore the needs to expand the prevailing critical infrastructure protection beyond the current power and oil sectors in the national development plan. They also highlight the urgency for greater research attention to critical infrastructure inventories. More importantly, the results stress the need for concerted efforts towards proactive emergency management procedures, rather than maintaining the established “fire brigade, window dressing” approach to emergency management, at all levels of administration.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

The purpose of this paper is to identify the need for and develop a framework for research on the effects UN peace operation infrastructure has on a host nation. Mission infrastructure serves primarily to sustain a mission. As the mission terminates, infrastructure is often transferred to the host nation. The mission infrastructures could have both positive and negative implications for the host nation and for local communities.

Exploratory approach to develop a foundation for a research agenda in an area with little existing research. Identify theoretical contributions related to infrastructures, combine with primary data from one peace operation, secondary data from five other peace operations and from the UN repositories.

This study proposes a research agenda. As such our findings relate to the identification and classification of different infrastructures and their interdependencies.

This framework would contribute to new ways of exploring and analysing both the effectiveness of peace operations and the impact a mission has on the development in the host nation.

This study proposes a framework for research. As such, it will have implications primarily for researchers.

Understanding the interdependencies between mission infrastructures and the material and social infrastructures of a host nation would help understanding what value mission infrastructure brings to a host nation and the local communities.

Analysing the logistics in peace support operations as networks of infrastructures bring new perspectives into humanitarian logistics.

This paper applies the theory of cascading, interconnected and compound risk to the practice of preparing for, managing, and responding to threats and hazards. Our goal is to propose a consistent approach for managing major risk in urban systems by bringing together emergency management, organisational resilience, and climate change adaptation.

We develop a theory-building process using an example from the work of the Greater London Authority in the United Kingdom. First, we explore how emergency management approaches systemic risk, including examples from of exercises, contingency plans and responses to complex incidents. Secondly, we analyse how systemic risk is integrated into strategies and practices of climate change adaptation. Thirdly, we consider organisational resilience as a cross cutting element between the approaches.

London has long been a champion of resilience strategies for dealing with systemic risk. However, this paper highlights a potential for integrating better the understanding of common points of failure in society and organisations, especially where they relate to interconnected domains and where they are driven by climate change.

The paper suggests shifting toward the concept of operational continuity to address systemic risk and gaps between Emergency Management, Organizational Resilience and Climate Change Adaptation.

The purpose of this paper is to present a coherence analysis to evaluate the resilience for a critical infrastructure (CI). This is the new way to evaluate the CI and demonstrate that the authors need to pass from the protection towards resilience.

The authors use two approaches for this research. First is a consequence-based approach to evaluate the resilience. This approach has been used many times for evaluating the interdependencies between CIs. The second is a systemic approach to characterize the system and doing the coherence analysis.

This paper presents a methodology to evaluate the coherence in a context of CIs protection. The coherence analysis in resilience is a new concept and the first result to the application seems very good for the user of the research.

The originality of this paper is the coherence analysis applied to a resilience evaluation. The criteria for coherence analysis is innovative and it is a new way to consider the resilience and the relation between an organization and it is partners. Another value is the need for a wider scope in the analysis of hazards and how to address them that includes the infrastructure system itself, but also other related organizations and infrastructure systems.

City is an artificial dynamic open giant complex system, whose multifunctional and interdisciplinary characteristics leads to significant complexity. While challenges arising from individual urban functions have been the focus of urban studies, major urban challenges such as traffic congestion and inefficiency of resource usages may originate from the “interface” where different urban functions interact. Previous research has revealed the potential that regarding city as a system-of-systems (SoS) may shed light on solutions to various urban challenges. The paper aims to discuss these issues.

To examine this research potential, this paper begins with an overview of challenges in urbanization and current approaches which lack systematic solutions. The idea of applying SoS approach is then inspired by existing studies on urban metabolism where city is regarded as an entire system. This idea is followed by definition and characteristics of SoS, as well as comprehensive overview of the state of the art on SoS-based solutions to urban challenges. This paper then discusses the merits and limitations of current studies on SoS for urbanization, followed by a case study which precedes research visions.

The paper finds that regarding city as SoS is a potentially effective approach for urban studies. This is highlighted by original research visions on how to advance this line of research. These research visions point out a few ideas for future research. It particularly highlights the role of human and information in the establishment, management and evolution of various urban functions.

The originality of this paper lies in the use of the conception of “SoS” to emphasize the importance of properly modeling human and information in an urban system so as to better reveal the intra-SoS mechanism.

The purpose of this paper is to assess the severity of social and economic impact of floods on the communities and industries with respect to their reliance on the flood impacted critical infrastructure. This paper illustrates a severity assessment tool to determine the reduced serviceability level of critical infrastructure after a disaster, how the change in serviceability impacts activities of associated communities and industries, and the resulting social and economic impact.

The results presented in this paper are a part of a larger research designed to develop a decision support system for disaster impact mitigation. This research evaluated the impact of floods as a natural hazard on infrastructure and the related industries and communities in terms of criticality and vulnerability of infrastructure and the severity of social and economic impact if the critical infrastructure were to be affected. The overall research focused on the 2008 Midwest floods for the required data collection (including the cities of Cedar Rapids, Iowa, Terre Haute, Indiana, St Louis, Missouri, Gulfport and Des Plaines, Illinois). Relevant data were collected through questionnaire surveys, personal interviews, and site visits.

The data collected through this research highlighted the importance of relationship between infrastructure, communities and industries with respect to technical, social and economic aspects. While the overall research resulted in a Decision Support System with three modules, to assess criticality, vulnerability and severity, this paper only elaborates the Severity Assessment Tool (SAT). Serviceability of an infrastructure plays an important role in post disaster recovery and response. Reduction in the serviceability of an infrastructure also affects the functionality of the activities that depend on the affected infrastructure resulting in social and economic impact. The tool presented in this paper determines the severity of social and economic impact by evaluating the reduction in the functionality of the affected activities.

The model (SAT) presented in this paper determines the social and economic impact on communities and industries due to natural disaster when the serviceability of disaster impacted critical infrastructure is impaired. This tool can be effectively used by city managers as well as emergency planners for industries and communities in developing mitigation strategies based on the severity of social and economic impact due to the affected critical infrastructure. The results would also help the decision makers in arriving at more effective investment decisions to repair/rehabilitate certain critical infrastructure.