Analysis of Resilience Situations for Complex Engineered Systems – the Resilience Holon

Improving the resilience of complex engineered and engineering systems (CES) includes planning for complex resilience situations, in which there may be multiple threats, interactions, and disruptions. One challenge in the modeling of CES is the identification of how interactions in a complex situation occur and their combined influence on CES resilience. This article presents a resilience holon that can be used to analyze complex resilience situations. It is made up of 24 elements (defining types of resilience, threats, interactions, and disruptions), which have varying importance to specific situations. Holons can be linked together hierarchically or in a network. An application of the resilience holon to a documented real-world resilience situation, widespread flooding in a city, illustrates its use. Pathways taken by threats and disruptions, as the flood effects cascaded through the city, are shown as connections between holons. The resilience holon could be used to decompose diverse resilience situations involving CES, to identify where critical vulnerability points are and how the whole resilience situation could be improved. The visual nature of the resilience holon could be used in an interactive way, allowing stakeholders to better understand the full resilience picture of CES that they use or operate

System importance measures: A new approach to resilient systems-of-systems

Resilience is the ability to withstand and recover rapidly from disruptions. While this attribute has been the focus of research in several fields, in the case of system-of-systems (SoSs), addressing resilience is particularly interesting and challenging. As infrastructure SoSs, such as power, transportation, and communication networks, grow in complexity and interconnectivity, measuring and improving the resilience of these SoSs is vital in terms of safety and providing uninterrupted services. ^ The characteristics of systems-of-systems make analysis and design of resilience challenging. However, these features also offer opportunities to make SoSs resilient using unconventional methods. In this research, we present a new approach to the process of resilience design. The core idea behind the proposed design process is a set of system importance measures (SIMs) that identify systems crucial to overall resilience. Using the results from the SIMs, we determine appropriate strategies from a list of design principles to improve SoS resilience. The main contribution of this research is the development of an aid to design that provides specific guidance on where and how resources need to be targeted. Based on the needs of an SoS, decision-makers can iterate through the design process to identify a set of practical and effective design improvements. ^ We use two case studies to demonstrate how the SIM-based design process can inform decision-making in the context of SoS resilience. The first case study focuses on a naval warfare SoS and describes how the resilience framework can leverage existing simulation models to support end-to-end design. We proceed through stages of the design approach using an agent-based model (ABM) that enables us to demonstrate how simulation tools and analytical models help determine the necessary inputs for the design process and, subsequently, inform decision-making regarding SoS resilience. ^ The second case study considers the urban transportation network in Boston. This case study focuses on interpreting the results of the resilience framework and on describing how they can be used to guide design choices in large infrastructure networks. We use different resilience maps to highlight the range of design-related information that can be obtained from the framework. ^ Specific advantages of the SIM-based resilience design include: (1) incorporates SoS- specific features within existing risk-based design processes - the SIMs determine the relative importance of different systems based on their impacts on SoS-level performance, and suggestions for resilience improvement draw from design options that leverage SoS- specific characteristics, such as the ability to adapt quickly (such as add new systems or re-task existing ones) and to provide partial recovery of performance in the aftermath of a disruption; (2) allows rapid understanding of different areas of concern within the SoS - the visual nature of the resilience map (a key outcome of the SIM analysis) provides a useful way to summarize the current resilience of the SoS as well as point to key systems of concern; and (3) provides a platform for multiple analysts and decision- makers to study, modify, discuss and documentoptions for SoS

Protection, interlocks and diagnostics

When designing any power converter it is essential to assess and incorporate adequate protection. The main objective is to offer a solution which is safe, reliable and repairable and that achieves its specification within budget. The level of protection found within each converter varies widely and will depend on the topology employed, its application and rating. This document is a guide to the types of protection engineers should consider mainly when designing power converters, as protection added during construction or after installation will always be expensive

Methodologies for Simplified Lifeline System Risk Assessments

Natural hazards are a growing risk across the globe. As regions have urbanized, single events impact greater proportions of the population, and the populations within those regions have become more dependent on infrastructure systems. Regional resilience has become closely tied to the performance of infrastructure. For a comprehensive risk assessment losses caused by lifeline outage must be considered alongside structural and nonstructural risks. Many well developed techniques quantify structural and nonstructural risk; however, there are insufficient procedures to determine the likelihood of lifeline outages. Including lifelines in seismic assessments will provide a comprehensive risk, improving a decision maker’s capacity to efficiently balance mitigation against the full spectrum of risks. An ideal lifeline risk assessment is infeasible due to the large geographic scale of lifeline systems and their system structure; these same characteristics also make them vulnerable to disruption in hazard events. Probabilistic methods provide solutions for their analysis, but many of the necessary analysis variables remain unknown. Continued research and increased collection of infrastructure data may improve the ability of advanced probabilistic methods to study and forecast performance of lifelines, but many inputs for a complete probabilistic model are likely to remain unknown. This thesis recognizes these barriers to assessment and proposes a methodology that uses consequences to simplify analysis of lifeline systems. Risk is often defined as the product of probability of failure and consequence. Many assessments study the probability of failure and then consider the consequence. This thesis proposes the opposite, studying consequence first. In a theoretical model where all information is available the difference in approach is irrelevant; the results are the same regardless of order. In the real world however, studying consequence first provides an opportunity to simplify the system assessment. The proposed methodology starts with stakeholders defining consequences that constitute ruin, and then the lifeline system is examined and simplified to components that can produce such consequences. Previously large and expansive systems can be greatly simplified and made more approachable systems to study. The simplified methodology does not result in a comprehensive risk assessment, rather it provides an abbreviated risk profile of catastrophic risk; risk that constitutes ruin. By providing an assessment of only catastrophic lifeline risk, the risk of greatest importance is measured, while smaller recoverable risk remains unknown. This methodology aligns itself with the principle of resilience, the ability to withstand shocks and rebound. Assessments can be used directly to consider mitigation options that directly address stakeholder resilience. Many of the same probabilistic issues remain, but by simplifying the process, abbreviated lifelines assessments are more feasible providing stakeholders with information to make decisions in an environment that currently is largely unknown

A dual perspective towards building resilience in manufacturing organizations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures under a life cycle perspective. A quantitative analysis of industry expert survey data through graph theory and matrix approach is presented second to prioritize resilience factors for strategic practical implementation

Wide-Area Situation Awareness based on a Secure Interconnection between Cyber-Physical Control Systems

Posteriormente, examinamos e identificamos los requisitos especiales que limitan el diseño y la operación de una arquitectura de interoperabilidad segura para los SSC (particularmente los SCCF) del smart grid. Nos enfocamos en modelar requisitos no funcionales que dan forma a esta infraestructura, siguiendo la metodología NFR para extraer requisitos esenciales, técnicas para la satisfacción de los requisitos y métricas para nuestro modelo arquitectural. Estudiamos los servicios necesarios para la interoperabilidad segura de los SSC del SG revisando en profundidad los mecanismos de seguridad, desde los servicios básicos hasta los procedimientos avanzados capaces de hacer frente a las amenazas sofisticadas contra los sistemas de control, como son los sistemas de detección, protección y respuesta ante intrusiones. Nuestro análisis se divide en diferentes áreas: prevención, consciencia y reacción, y restauración; las cuales general un modelo de seguridad robusto para la protección de los sistemas críticos. Proporcionamos el diseño para un modelo arquitectural para la interoperabilidad segura y la interconexión de los SCCF del smart grid. Este escenario contempla la interconectividad de una federación de proveedores de energía del SG, que interactúan a través de la plataforma de interoperabilidad segura para gestionar y controlar sus infraestructuras de forma cooperativa. La plataforma tiene en cuenta las características inherentes y los nuevos servicios y tecnologías que acompañan al movimiento de la Industria 4.0. Por último, presentamos una prueba de concepto de nuestro modelo arquitectural, el cual ayuda a validar el diseño propuesto a través de experimentaciones. Creamos un conjunto de casos de validación que prueban algunas de las funcionalidades principales ofrecidas por la arquitectura diseñada para la interoperabilidad segura, proporcionando información sobre su rendimiento y capacidades.Las infraestructuras críticas (IICC) modernas son vastos sistemas altamente complejos, que precisan del uso de las tecnologías de la información para gestionar, controlar y monitorizar el funcionamiento de estas infraestructuras. Debido a sus funciones esenciales, la protección y seguridad de las infraestructuras críticas y, por tanto, de sus sistemas de control, se ha convertido en una tarea prioritaria para las diversas instituciones gubernamentales y académicas a nivel mundial. La interoperabilidad de las IICC, en especial de sus sistemas de control (SSC), se convierte en una característica clave para que estos sistemas sean capaces de coordinarse y realizar tareas de control y seguridad de forma cooperativa. El objetivo de esta tesis se centra, por tanto, en proporcionar herramientas para la interoperabilidad segura de los diferentes SSC, especialmente los sistemas de control ciber-físicos (SCCF), de forma que se potencie la intercomunicación y coordinación entre ellos para crear un entorno en el que las diversas infraestructuras puedan realizar tareas de control y seguridad cooperativas, creando una plataforma de interoperabilidad segura capaz de dar servicio a diversas IICC, en un entorno de consciencia situacional (del inglés situational awareness) de alto espectro o área (wide-area). Para ello, en primer lugar, revisamos las amenazas de carácter más sofisticado que amenazan la operación de los sistemas críticos, particularmente enfocándonos en los ciberataques camuflados (del inglés stealth) que amenazan los sistemas de control de infraestructuras críticas como el smart grid. Enfocamos nuestra investigación al análisis y comprensión de este nuevo tipo de ataques que aparece contra los sistemas críticos, y a las posibles contramedidas y herramientas para mitigar los efectos de estos ataques

Reliability Evaluation of Common-Cause Failures and Other Interdependencies in Large Reconfigurable Networks

This work covers the impact of Interdependencies and CCFs in large repairable networks with possibility of "re-configuration" after a fault and the consequent disconnection of the faulted equipment. Typical networks with these characteristics are the Utilities, e.g. Power Transmission and Distribution Systems, Telecommunication Systems, Gas and Water Utilities, Wi Fi networks. The main issues of the research are: (a) Identification of the specific interdependencies and CCFs in large repairable networks, and (b)Evaluation of their impact on the reliability parameters (load nodes availability, etc.). The research has identified (1) the system and equipment failure modes that are relevant to interdependencies and CCF, and their subsequent effects, and (2) The hidden interdependencies and CCFs relevant to control, supervision and protection systems, and to the automatic change-over systems, that have no impact in normal operation, but that can cause relevant out-of-service when the above automatic systems are called to operate under and after fault conditions. Additionally methods were introduced to include interdependencies and CCFs in the reliability and availability models. The results of the research include a new generalized approach to model the repairable networks for reliability analysis, including Interdependencies/CCFs as a main contributor. The method covers Generalized models for Nodes, Branches and Load nodes; Interdependencies and CCFs on Networks / Components; System Interdependencies/CCFs; Functional Interdependencies/CCFs; Simultaneous and non-simultaneous Interdependencies/CCFs. As an example detailed Interdependency/CCFs analysis and generalized model of an important network structure (a "RING" with load nodes) has been analyzed in detail

An integrated operation and maintenance framework for offshore renewable energy

Offshore renewable devices hold a large potential as renewable energy sources, but their deployment costs are still too high compared to those of other technologies. Operation and maintenance, as well as management of the assets, are main contributors to the overall costs of the projects, and decision-support tools in this area are required to decrease the final cost of energy.\\ In this thesis a complete characterisation and optimisation framework for the operation, maintenance and assets management of an offshore renewable farm is presented. The methodology uses known approaches, based on Monte Carlo simulation for the characterisation of the key performance indicators of the offshore renewable farm, and genetic algorithms as a search heuristic for the proposal of improved strategies. These methods, coupled in an integrated framework, constitute a novel and valuable tool to support the decision-making process in this area. The methods developed consider multiple aspects for the accurate description of the problem, including considerations on the reliability of the devices and limitations on the offshore operations dictated by the properties of the maintenance assets. Mechanisms and constraints that influence the maintenance procedures are considered and used to determine the optimal strategy. The models are flexible over a range of offshore renewable technologies, and adaptable to different offshore farm sizes and layouts, as well as maintenance assets and configurations of the devices. The approaches presented demonstrate the potential for cost reduction in the operation and maintenance strategy selection, and highlight the importance of computational tools to improve the profitability of a project while ensuring that satisfactory levels of availability and reliability are preserved. Three case studies to show the benefits of application of such methodologies, as well as the validity of their implementation, are provided. Areas for further development are identified, and suggestions to improve the effectiveness of decision-making tools for the assets management of offshore renewable technologies are provided.European CommissionMojo Ocean Dynamics Ltd. T/A Mojo Maritime Lt

Reliability Assessment of Power Systems Integrated with High-Penetration of Power Converters

Moving towards renewable and environmental-friendly energy resources has intensified the importance of power electronic converters in future power systems. The issue of reliability becomes more critical than ever before. This research proposes a hierarchical reliability framework to evaluate the electric power system reliability from the power electronic converter level to the overall system level. In the first stage, the reliability of each power converter is modeled in an accurate manner. Dynamic behaviors of various integrated semiconductor devices and the converter topology are considered. In the second stage, we calculate system-level reliability indicators such as expected energy not served (EENS) and loss of load expectation (LOLE) are estimated through a non-sequential Monte Carlo simulation. Machine learning regression models such as support vector regression (SVR) and random forests (RF) are implemented to bridge the nonlinear reliability relationship between two stages. Moreover, a variance-based global sensitivity analysis (GSA) is conducted to rank and identify the most influential converter uncertainties with respect to the variance of system EENS. Based on the GSA conclusions, system operators can take proactive actions to mitigate the potential risk of the system. Furthermore, Bayesian network (BN) structure learning and scoring algorithms are applied to visualize a converter-based BN structure. Reliability interdependencies among different nodes are quantified through information entropy theory such that reliability causal relations can be revealed. This dissertation also studies and discusses opportunities of various emerging technologies. Some improvements and suggestions of the proposed framework are included as well.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/171266/1/Bowen Zhang Final Dissertation.pdfDescription of Bowen Zhang Final Dissertation.pdf : Dissertatio

Post-disaster functional recovery of the built environment: A systematic review and directions for future research

Life safety has been a primary design requirement in codes and standards for the built environment. However, over the past several years, better building performance goals that consider acceptable recovery times and continued functionality following major disasters have been advocated. Functional recovery, a new design philosophy that establishes holistic performance goals, and focuses on the robustness of structures, enhanced safety, and, specifically, fast return to operation post-disaster, has been introduced in earthquake engineering to govern future building designs. This article utilised the systematic review procedures as a tool to provide a state-of-the-art review of functional recovery research within the built environment. A critical review of 78 publications was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The evolution of paradigm shifts from seismic resilience to functional recovery in earthquake engineering research has been discussed in detail. Two frameworks, namely the Federal Emergency Management Agency's (FEMA) P-58 and Arup's Resilience-Based Earthquake Design Initiative (REDi), have been recognised as the most commonly utilised frameworks for modelling the functional recovery of buildings post-earthquake due to their effectiveness and widespread adoption. However, it is essential to acknowledge that recently developed frameworks, such as the F-Rec framework, ATC-138, and TREADS, which explicitly formulate functional recovery calculation procedures, have the potential to replace FEMA P-58 and REDi and advance functional recovery research in the future. Moreover, aligned with modular-based characteristics of existing frameworks, indicators required in functional recovery analysis have been extracted and classified into four distinct categories: 1) hazard analysis, 2) structural response analysis, 3) damage analysis, and 4) recovery analysis. This categorisation enables a comprehensive and systematic approach to understanding the multifaceted aspects of functional recovery in a structured manner. Detailed investigation of frameworks and indicators offers insights for future research exploration. These include (a) expanding the fragility library of components to permit more widespread recovery analysis, (b) comparing, validating and optimising existing frameworks and models, (c) enhancing the modelling of interdependencies between the building and its adjacent buildings and services, (d) improving the capability for uncertainty analysis, and (e) acquiring empirical data to enable predictability of the existing frameworks and models for functional recovery