Elements of Critical Infrastructure Resilience

This Article points to key elements of Critical Infrastructure Resilience (CIR) and how they differ from Critical Infrastructure Protection (CIP). CIP is still very important and one of the key systems that the society relies upon to ensure the continuity of operation of CI. However, CIP cannot predict an adequate number of major threats that would allow to conduct the preparedness and response at the level which would ensure the sufficient operation of CI in all cases. In that sense CIR sets a new paradigm with a quality that reduces vulnerability, minimizes the consequences of threats, accelerates response and recovery, and facilitates adaptation to a disruptive event. Some selected concepts of CIR with examples are presented in the Article that should assist in further development and enhancement of resilience of subsystems and infrastructures as a whole, resulting in more secure CI

A General Algorithm for Assessing Product Architecture Performance Considering Architecture Extension in Cyber Manufacturing

In modern manufacturing, the product architecture design options are usually restricted to those that can be produced with 100% confidence using those proven technologies to satisfy the existing customer requirement. As a result, the inefficiencies of architecture design are considerable due to such limitations. This issue is of particular interests in cyber manufacturing when exploring the tradeoff between generality and feasibility in product design and manufacturing. It can be expected that the improvement and extension of the existing product architecture may be required to meet new customer requirement when new technologies become available. An effective system performance assessment algorithm is necessary to facilitate the extension of existing product architecture. Though there has been a lot of research on architecture assessment, there is no well-defined model for level by level architecture assessment considering architecture extension. In this paper, we propose a general architecture assessment model considering the integration of additional functionality requirements and performance metrics to evaluate the architecture performance along its value pathway to meet stakeholder\u27s requirements. A numerical case study focusing on a hypothetical auto cooling system is used to validate the effectiveness of the proposed model

Methodology for the evaluation of resilience of ICT systems for smart distribution grids

Ensuring resilient operation and control of smart grids is fundamental for empowering their deployment, but challenging at the same time. Accordingly, this study proposes a novel methodology for evaluating resilience of Information and Communication Technology (ICT) systems for smart distribution grids. Analysing how the system behaves under changing operating conditions a power system perspective allows to understand how resilient the smart distribution grid is, but the resilience of the ICT system in charge of its operation affects the overall performance of the system and does, therefore, condition its resilience. With the aim of systematising the evaluation of ICT systems’ resilience, this study proposes to combine a standardized modelling of Smart Grids, the Smart Grid Architecture Model (SGAM), with a data structured diagram, the Entity Relationship Model (ERM). The architecture of smart distribution grids is analysed through SGAM. Then, their technical characteristics and functionalities are defined and represented in a ERM diagram. Finally, the attributes or properties of the system components are used to formulate resilience indicators against different types of disturbances. This methodology is then applied to analyse the resilience of a ICT platform being developed in EMPOWER H2020 project.Postprint (published version

Development of a tool to assess the resilience of Canterbury lifelines

This project was undertaken as part of the ongoing Risk and Resilience study by the Canterbury Lifeline Utilities Group. The purpose of this project was to create a tool to assess the resilience of lifeline utilities. The goal of the tool was to help the utilities make better decisions around improving resilience. The tool was initially built as an adaptation of a resilience assessment built for the New Zealand Transport Agency (NZTA), and evolved through multiple iterations and feedback from a variety of potential users. It is based around the definition of resilience as the ability to "withstand disruption, absorb disturbance, act effectively in a crisis, adapt to changing conditions, including climate change, and grow over time" (New Zealand Government, 2011). This definition was related to the principles of absorptive, adaptive, restorative and cohesive ability to attempt to measure resilience. The final tool assesses resilience by taking the user through 17 measures posed as questions to be scored on a 1-4 scale. The tool has a number of potential uses including as investment justification and as a communication tool

Modeling and Measuring Resilience: Applications in Supplier Selection and Critical Infrastructure

Nowadays, infrastructure systems such as transportation, telecommunications, water supply, and electrical grids, are considerably facing the exposure of disruptive events such as natural disasters, manmade accidents, malevolent attacks, and common failures due to their size, complexity, and interconnectedness nature. For example fragile design of supply chain infrastructure might collapses because the consequences of a failure can propagate easily through the layers of supply chains, especially for large interconnected networks. Previously, owners and operators of infrastructure systems focused to design cost-efficient, competitive and sustainable ones; however the need for design of resilient infrastructure systems is inevitable. Infrastructure systems must be designed in such a way so that they are resistant enough to withstand and recover quickly from disruptions. The consequences of disruptive events on infrastructures ranging from energy systems (e.g., electrical power network, natural gas pipeline) to transportation systems (e.g., food supply chain, public transportation) cannot only impacted on individuals, but also on communities, governments and economics. The goal of this dissertation is to (i) identify the resilience capacities of infrastructure systems; in particular inland waterway ports, and supply chain systems, (ii) quantify and analyze the resilience value of critical infrastructure systems (CIs), (iii) improve the resilience of CIs by simulating different disruptive scenarios, and (iv) recommend managerial implications to help owners and operators of CIs for timely response, preparedness, and quick recovery against disruptive events. This research first identifies the resilience capacity of CIs, in particular, inland waterway, supply chain and electrical power plant. The resilience capacity of CIs is modeled in terms of their absorptive capacity, adaptive capacity and restorative capacity. A new resilience metric is developed to quantify the resilience of CIs. The metric captures the causal relationship among the characteristics of CIs and characteristics of disruptive events including intensity and detection of disruption likelihood of disruptive events. The proposed resilience metric is generic, meaning that can be applied across variety of CIs. The proposed metric measures the system resilience as the sum of degree of achieving successful mitigation and contingency strategies. The resilience metric accounts for subjectivity aspect of disruptive events (e.g., late disruption detection, very intense disruption, etc.). Additionally, the proposed resilience metric is capable of modeling multiple disruptive events occurring simultaneously. This research study further explores how to model the resilience of CIs using graphical probabilistic approach, known as Bayesian Networks (BN). BN model is developed to not only quantify the resilience of CIs but also to predict the behavior of CIs against different disruptive scenarios using special case of inference analysis called forward propagation analysis (FPA), and improvement scenarios on resilience of CIs are examined through backward propagation analysis (BPA), a unique features of BN that cannot be implemented by any other methods such as classical regression analysis, optimization, etc. Of interest in this work are inland waterway ports, suppliers and electrical power plant. Examples of CIs are inland waterway ports, which are critical elements of global supply chain as well as civil infrastructure. They facilitate a cost-effective flow of roughly $150 billion worth of freights annually across different industries and locations. Stoppage of inland waterway ports can poses huge disruption costs to the nation’s economic. Hence, a series of questions arise in the context of resilience of inland waterway ports. How the resilience of inland waterway ports can be modeled and quantified? How to simulate impact of potential disruptive events on the resilience of inland waterway ports? What are the factors contributing to the resilience capacity of inland waterway ports? How the resilience of inland waterway can be improved

An Ecosystem Called University

This book is dedicated to the university as a protagonist of change. Its purpose is to see the university as a place where the lines between organization and system are fluid, where the whole is more than the sum of its parts, and the product is knowledge as an end, a means and a way of developing the individual (critical sense) and its interaction with the environment (instrumental reason). The book seeks throughout to foster the image of the Ecosystem University as being a producer of novelty, where the only certainty is uncertainty. The university undergoes a process of permanent spiral growth - the spiral of knowledge without any control of causality - and creating, through its environment, responsible citizens, and free-thinking persons. The Ecosystem University is undeTTast that is assumed in the present. Our work to rediscover the natural feel of an ecosystem embedded in the university and the rich experience of community will take us by the hand and lead us, proud professors, to the purest origin of human knowledge with a flair of joie de vivre: the refreshing purity of the new and the authentic value of ingenuity that will allow us to be ourselves in that very moment: a community that self-organizes, builds projects of life and culture, and determines its own destiny

The resilience of road transport networks redundancy, vulnerability and mobility characteristics

This thesis is concerned with the development of a composite resilience index for road transport networks. The index employs three characteristics, namely redundancy, vulnerability and mobility, measuring resilience at network junction, link and origin-destination levels, respectively. Various techniques have been adopted to quantify each characteristic and the composite resilience index as summarised below. The redundancy indicator for road transport network junctions is based on the entropy concept, due to its ability to measure the system configuration in addition to being able to model the inherent uncertainty in road transport network conditions. Various system parameters based on different combinations of link flow, relative link spare capacity and relative link speed were examined. The developed redundancy indicator covers the static aspect of redundancy, i.e. alternative paths, and the dynamic feature of redundancy reflected by the availability of spare capacity under different network loading and service level. The vulnerability indicator for road transport network links is developed by combining vulnerability attributes (e.g. link capacity, flow, length, free flow and traffic congestion density) with different weights using a new methodology based on fuzzy logic and exhaustive search optimisation techniques. Furthermore, the network vulnerability indicators are calculated using two different aggregations: an aggregated vulnerability indicator based on physical characteristics and the other based on operational characteristics. The mobility indicator for road transport networks is formulated from two mobility attributes reflecting the physical connectivity and level of service. The combination of the two mobility attributes into a single mobility indicator is achieved by a fuzzy logic approach. Finally, the interdependence of the proposed characteristics is explored and the composite resilience index is estimated from the aggregation of the three characteristics indicators using two different approaches, namely equal weighting and principal component analysis methods. Moreover, the impact of real-time travel information on the proposed resilience characteristics and the composite resilience index has been investigated. The application of the proposed methodology on a synthetic road transport network of Delft city (Netherlands) and other real life case studies shows that the developed indicators for the three characteristics and the composite resilience index responded well to traffic load change and supply variations. The developed composite resilience index will be of use in various ways; first, helping decision makers in understanding the dynamic nature of resilience under different disruptive events, highlighting weaknesses in the network and future planning to mitigate the impact of disruptive events. Furthermore, each developed indicator for the three characteristics considered can be used as a tool to assess the effectiveness of different management policies or technologies to improve the overall network performance or the daily operation of road transport networks

Análisis multidimensional de la resiliencia en zonas de desastre. Factores críticos de adaptabilidad en Baños de Agua Santa - Ecuador

Esta tesis analiza el efecto multidimensional de la resiliencia en zonas afectadas por desastres de origen natural. Considera los sistemas adaptativos complejos y el modelo heurístico de panarquía como la base teórica para identificar los factores críticos de la resiliencia y su comportamiento dinámico sobre los sistemas socio–ecológicos. Se identifica ocho dimensiones que agrupan a 56 criterios (factores) que son tratados a través de un modelo de decisión discreta Fuzzy AHP, obteniéndose una estructura ponderada que describe de forma jerárquica los componentes del sistema socio-ecológico que inciden en la capacidad dinámica de aprendizaje, auto–organización y adaptabilidad de las poblaciones o regiones que han sufrido el impacto de un evento extremo de origen natural. El modelo permite establecer procesos de gobernanza adaptativa a través del diseño de una matriz cualitativa de doble entrada. La aplicación empírica de esta investigación se desarrolla en la ciudad de Baños de Agua Santa (Ecuador), población que durante 16 años ha sido afectada por la erupción del volcán Tungurahua, demostrando altos niveles de resiliencia