SYSTEMS RESILIENCE: DEFINITION, MODELING AND ITS QUANTITATIVE ANALYSIS

Ph.DDOCTOR OF PHILOSOPHY (FOE

InfraRisk: An open-source simulation platform for resilience analysis in interconnected power–water–transport networks

Integrated simulation models are emerging as an alternative for analyzing large-scale interdependent infrastructure networks due to their modeling advantages over traditional interdependency models. This paper presents an open-source integrated simulation package for the component-level analysis of interdependent power-, water-, transport networks. The simulation platform, named ’InfraRisk’ and developed in Python, can simulate network-wide effects of disaster-induced infrastructure failures and subsequent post-disaster restoration. InfraRisk consists of an infrastructure module, a hazard module, a recovery module, a simulation module, and a resilience quantification module. The infrastructure module integrates existing infrastructure network packages (wntr for water distribution systems, pandapower for power systems, and a static traffic assignment model for road transport systems) through an interface that facilitates the network-level simulation of infrastructure failures. The hazard module generates infrastructure component failures based on various disaster characteristics. The recovery module determines repair sequences and assigns repair crews based on predefined heuristics-based recovery strategies or model predictive control (MPC) based optimization. Based on the schedule, the simulation module simulates the consequences of the disaster impacts and the recovery actions on the performance of the interdependent network. The resilience quantification module offers system-level and consumer-level metrics to quantify both the risks and resilience of the integrated infrastructure networks against disaster events. InfraRisk provides a virtual platform for decision-makers to experiment and develop region-specific pre-disaster and post-disaster policies to enhance the overall resilience of interdependent urban infrastructure networks.ISSN:2210-670

Application of Clustering Algorithms for Dimensionality Reduction in Infrastructure Resilience Prediction Models

Recent studies increasingly adopt simulation-based machine learning (ML) models to analyze critical infrastructure system resilience. For realistic applications, these ML models consider the component-level characteristics that influence the network response during emergencies. However, such an approach could result in a large number of features and cause ML models to suffer from the `curse of dimensionality'. We present a clustering-based method that simultaneously minimizes the problem of high-dimensionality and improves the prediction accuracy of ML models developed for resilience analysis in large-scale interdependent infrastructure networks. The methodology has three parts: (a) generation of simulation dataset, (b) network component clustering, and (c) dimensionality reduction and development of prediction models. First, an interdependent infrastructure simulation model simulates the network-wide consequences of various disruptive events. The component-level features are extracted from the simulated data. Next, clustering algorithms are used to derive the cluster-level features by grouping component-level features based on their topological and functional characteristics. Finally, ML algorithms are used to develop models that predict the network-wide impacts of disruptive events using the cluster-level features. The applicability of the method is demonstrated using an interdependent power-water-transport testbed. The proposed method can be used to develop decision-support tools for post-disaster recovery of infrastructure networks

Designing resilient and economically viable water distribution systems: A Multi-dimensional approach

Enhancing the resilience of critical infrastructure systems requires substantial investment and entails trade-offs between environmental and economic benefits. To this aim, we propose a methodological framework that combines resilience and economic analyses and assesses the economic viability of alternative resilience designs for a Water Distribution System (WDS) and its interdependent power and transportation systems. Flow-based network models simulate the interdependent infrastructure systems and Global Resilience Analysis (GRA) quantifies three resilience metrics under various disruption scenarios. The economic analysis monetizes the three metrics and compares two resilience strategies involving the installation of remotely controlled shutoff valves. Using the Micropolis synthetic interdependent water-transportation network as an example, we demonstrate how our framework can guide infrastructure stakeholders and utility operators in measuring the value of resilience investments. Overall, our approach highlights the importance of economic analysis in designing resilient infrastructure systems

Urbanscope: A Lens to Observe Language Mix in Cities

Cities of the 21st century are places where various actors interact, where physical systems, that are sometime geographically distant, are strictly dependent, where relational mechanisms become crucial, and where the boundaries between individual and collective, local and global, real and digital become more and more blurred. In this context, social media can be used as a digital lens to analyze the space and the territory of cities. In fact, they offer a great opportunity to individualize and understand the connections that might exist between different spheres. In this article, we use Twitter to analyze the language mix of the city and to detect language communities within the city neighborhoods. We then compare these â\u80\u9cdigitalâ\u80\u9d communities, discovered through Twitter, with the â\u80\u9crealâ\u80\u9d communities identified by the traditional census data. Milan, a city which is increasingly becoming an international melting pot, is chosen as a case study for this work

Effects of topology on water distribution systems resilience

Water Distribution Systems (WDSs) are critical infrastructures for providing water to sustain life and human activities. Some recent trends, such as climate change, urbanization, and increasing system interdependence, have led to more frequent threats, with detrimental effects on WDSs. In recent years, resilience has been considered an effective approach to address those threats, for which it is difficult to estimate the likelihood and consequences (Henry and Ramirez-Marquez, 2012). In the literature, two approaches were used to assess WDS resilience. On the one hand, performance-based metrics were used to quantify the impacts of disruptions on the WDS. Specifically, recovery functions were developed to model the time-continuous system response following a disruption, during periods of loss and restoration of performance (Cassottana et al., 2019). On the other hand, indexes based on system attributes were developed to classify WDSs and identify structural vulnerabilities. For example, algebraic connectivity, clustering coefficient, and average path length were used as proxies for robustness, redundancy, and efficiency, respectively (Yazdani et al., 2011). However, those approaches were applied separately, and the relationship between the performance of WDSs and their attributes is still unknown. Hence, the question arises from the above analysis on how to identify the key structural factors determining the resilience of a WDS. The goal of this research is to understand how and to what extent different network topologies determine different performance losses and recovery behaviors given increasing magnitude of disruption, i.e., pipe breakdown. To this end, we consider different network topologies as case studies and vary their structural attributes, e.g., water source head and tank capacity. We then simulate disruption scenarios of increasing magnitude and model the resulting system performance by means of recovery functions for the assessment of resilience. The estimated parameters of these functions are useful for characterizing different system responses, including severe or limited performance losses and fast or slow recoveries. By systematically varying the network topologies and the structural attributes, the function parameters could be in turn associated with key structural factors. We find that, while increasing the WDS supply capacity results in limited performance loss in terms of satisfied demand for water, increasing the reserve capacity improves the robustness of the system by delaying the loss of performance. This analysis will inform the design of resilient water networks based on their topology and unique attributes.System Engineerin

Resilience analysis of cyber‐physical systems: A review of models and methods

Cyber-physical systems (CPSs) are monitored and controlled by a computing andcommunicating core. This cyber layer enables better management of the controlledsubsystem, but it also introduces threats to the security and protection of CPSs, asdemonstrated by recent cyberattacks. The resulting governance and policy emphasison cybersecurity is reflected in the academia by a vast body of literature. In this arti-cle, we systematize existing knowledge on CPS analysis. Specifically, we focus onthe quantitative assessment of CPSs before and after the occurrence of a disruption.Through the systematic analysis of the models and methods adopted in the literature,we develop a CPS resilience assessment framework consisting of three steps, namely,(1) CPS description, (2) disruption scenario identification, and (3) resilience strategyselection. For each step of the framework, we suggest established methods for CPSanalysis and suggest four criteria for method selection. The framework proposes a stan-dardized workflow to assess the resilience of CPSs before and after the occurrence of adisruption. The application of the proposed framework is exemplified with reference toa power substation and associated communication network.The case study shows thatthe proposed framework supports resilience decision making by quantifying the effectsof the implementation of resilience strategies.ISSN:0272-4332ISSN:1539-692

Designing resilient and economically viable water distribution systems: A Multi-dimensional approach

Enhancing the resilience of critical infrastructure systems requires substantial investment and entails trade-offs between environmental and economic benefits. To this aim, we propose a methodological framework that combines resilience and economic analyses and assesses the economic viability of alternative resilience designs for a Water Distribution System (WDS) and its interdependent power and transportation systems. Flow-based network models simulate the interdependent infrastructure systems and Global Resilience Analysis (GRA) quantifies three resilience metrics under various disruption scenarios. The economic analysis monetizes the three metrics and compares two resilience strategies involving the installation of remotely controlled shutoff valves. Using the Micropolis synthetic interdependent water-transportation network as an example, we demonstrate how our framework can guide infrastructure stakeholders and utility operators in measuring the value of resilience investments. Overall, our approach highlights the importance of economic analysis in designing resilient infrastructure systems

Quantitative Assessment of System Response during Disruptions: An Application to Water Distribution Systems

The resilience of water distribution systems (WDSs) has gained increasing attention in recent years. Various performance loss and recovery behaviors have been observed for WDSs subject to disruptions. However, a model for their characterization, which could provide further insight for resilience assessment and enhancement, is still lacking. Here, the authors develop a recovery function to model WDS performance over time following a disruption. This function is useful to compare system responses under different disruption and recovery scenarios and supports the identification of areas for improvement within various aspects of the resilience of a WDS. The proposed model was applied to two benchmark networks. Different scenarios were analyzed in which one node at a time was disrupted and two recovery strategies were implemented. It was found that the developed model supports the implementation of tailored strategies to improve WDS resilience according to the location of the disruption, therefore enhancing the efficient allocation of resources. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.System Engineerin