Assessing Resilience in Power Grids as a Particular Case of Supply Chain Management

Electrical power grids represent a critical infrastructure for a nation as well as strategically important. Literature review identified that power grids share basic characteristics with Supply Chain Management. This thesis presents a linear programming model to assess power grid resilience as a particular case of Supply Chain Management. Since resilient behavior is not an individual or specific system\u27s attribute but a holistic phenomenon based on the synergic interaction within complex systems, resilience drivers in power grids were identified. Resilience is a function of Reliability, Recovery Capability, Vulnerability and Pipeline Capacity. In order to embed heterogeneous variables into the model, parameterization of resilience drivers were developed. A principle of improving resilience through redundancy was applied in the model by using a virtual redundancy in each link which allows reliability improvement throughout the entire network. Vulnerability was addressed through the standard MIL-STD 882D, and mitigated through security allocation. A unique index (R) integrates the resilience complexity to facilitate alternate scenarios analysis toward strategic decision making. Decision makers are enabled to improve overall power grid performance through reliability development as well as security allocation at the more strategic links identified by the optimal solutions. Moreover, this tool lets decision makers fix grid variables such as reliability, reduced pipeline capacity, or vulnerabilities within the model in order to find optimal solutions that withstand disruptions. The model constitutes an effective tool not only for efficient reliability improvement but also for rational security allocation in the most critical links within the network. Finally, this work contributes to the federal government mandates accomplishment, intended to address electrical power-related risks and vulnerabilities

Assessing the Consequences of Natural Disasters on Production Networks: A Disaggregated Approach

This article proposes a framework to investigate the consequences of natural disasters. This framework is based on the disaggregation of Input-Output tables at the business level, through the representation of the regional economy as a network of production units. This framework accounts for (i) limits in business production capacity; (ii) forward propagations through input shortages; and (iii) backward propagations through decreases in demand. Adaptive behaviors are included, with the possibility for businesses to replace failed suppliers, entailing changes in the network structure. This framework suggests that disaster costs depend on the heterogeneity of losses and on the structure of the affected economic network. The model reproduces economic collapse, suggesting that it may help understand the difference between limited-consequence disasters and disasters leading to systemic failure.Natural disasters, Economic impacts, Economic Network

Review of Quantitative Methods for Supply Chain Resilience Analysis

Supply chain resilience (SCR) manifests when the network is capable to withstand, adapt, and recover from disruptions to meet customer demand and ensure performance. This paper conceptualizes and comprehensively presents a systematic review of the recent literature on quantitative modeling the SCR while distinctively pertaining it to the original concept of resilience capacity. Decision-makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which quantitative methods can be used at different levels of capacity resilience. Finally, the gaps and limitations of existing SCR literature are identified and future research opportunities are suggested

Review of Quantitative Methods for Supply Chain Resilience Analysis

Supply chain resilience (SCR) manifests when the network is capable to withstand, adapt, and recover from disruptions to meet customer demand and ensure performance. This paper conceptualizes and comprehensively presents a systematic review of the recent literature on quantitative modeling the SCR while distinctively pertaining it to the original concept of resilience capacity. Decision-makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which quantitative methods can be used at different levels of capacity resilience. Finally, the gaps and limitations of existing SCR literature are identified and future research opportunities are suggested

MACHS: Mitigating the Achilles Heel of the Cloud through High Availability and Performance-aware Solutions

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their HA and satisfying the QoS requirements. Second, a Stochastic Petri Net (SPN) model is proposed to capture the stochastic characteristics of cloud services and quantify the expected availability offered by an application deployment. The SPN model is then associated with an extensible policy-driven cloud scoring system that integrates other cloud challenges (i.e. green and cost concerns) with HA objectives. The proposed HA-aware solutions are extended to include a live virtual machine migration model that provides a trade-off between the migration time and the downtime while maintaining HA objective. Furthermore, the thesis proposes a generic input template for cloud simulators, GITS, to facilitate the creation of cloud scenarios while ensuring reusability, simplicity, and portability. Finally, an availability-aware CloudSim extension, ACE, is proposed. ACE extends CloudSim simulator with failure injection, computational paths, repair, failover, load balancing, and other availability-based modules

Critical Infrastructure Protection Metrics and Tools Papers and Presentations

Contents: Dr. Hilda Blanco: Prioritizing Assets in Critical Infrastructure Systems; Christine Poptanich: Strategic Risk Analysis; Geoffrey S. French/Jin Kim: Threat-Based Approach to Risk Case Study: Strategic Homeland Infrastructure Risk Assessment (SHIRA); William L. McGill: Techniques for Adversary Threat Probability Assessment; Michael R. Powers: The Mathematics of Terrorism Risk Stefan Pickl: SOA Approach to the IT-based Protection of CIP; Richard John: Probabilistic Project Management for a Terrorist Planning a Dirty Bomb Attack on a Major US Port; LCDR Brady Downs: Maritime Security Risk Analysis Model (MSRAM); Chel Stromgren: Terrorism Risk Assessment and Management (TRAM); Steve Lieberman: Convergence of CIP and COOP in Banking and Finance; Harry Mayer: Assessing the Healthcare and Public Health Sector with Model Based Risk Analysis; Robert Powell: How Much and On What? Defending and Deterring Strategic Attackers; Ted G. Lewis: Why Do Networks Cascade

Holistic Resilience Quantification Framework of Rural Communities

Communities need to prepare for anticipated hazards, adapt to varying conditions, and resist and recover rapidly from disturbances. Protecting the built environment from natural and man-made hazards and understanding the impact of these hazards helps allocate resources efficiently. Recently, an indicator-based and time-dependent approach was developed for defining and measuring the functionality and disaster resilience continuously at the community level. This computational method uses seven dimensions that find qualitative characteristics and transforms them into quantitative measures. The proposed framework is used to study the resilience of rural communities’ subject to severe flooding events. Harlan County in the Appalachian region is chosen as a case study to evaluate the proposed resilience quantification framework subject to severe flooding. The results show the validity of the proposed approach as a decision-support mechanism to assess and enhance the resilience of rural communities

Absence of freight transportation plans in state and county emergency operations plans

Natural disasters have the ability to disrupt structured systems in the United States, such as transportation systems and freight routes. When a natural disaster occurs, freight is forced to reroute around the effected areas. Rerouting slows recovery efforts, as well as normal transportation of goods within the United States. Therefore, natural disasters, with respect to freight routes, have widespread impacts and the possibility for acute hardship in disaster-prone areas. This thesis examines how comprehensive state and local level emergency operations plans are with respect to freight transportation rerouting following a natural disaster. Coastal cities can modify freight routes and this rerouting might affect recovery efforts and the normal flow of freight. First, seven coastal cities emergency operations plans are examined for specific elements of freight transportation planning. From there, the project determined how complete local level emergency operations plans are in terms of freight transportation and the framework needed for a freight transportation plan. The result of this research was policy recommendations to improve the resiliency of freight transportation networks surrounding coastal cities and incorporate freight transportation planning into emergency operations. The resiliency of freight routes following natural disasters is important because there can be widespread effects on the delivery of goods to the U.S. as well as recovery supplies to the effected area. If freight routes could be modeled to efficiently deliver rescue supplies and goods, while also minimizing the environmental effects, the benefits of uninterrupted service to the transportation system and society could possibly be substantial. The transportation system cannot encounter difficulties whenever a natural or manmade disaster occurs; therefore the United States needs to be better equipped to counteract interruptions in freight routes

Transportation Network Resiliency: A Study of Self-Annealing

Transportation networks, as important lifelines linking communities and goods, are indispensable for the smooth functioning of society. These networks are, however, fragile and vulnerable to natural and manmade disasters, which can disrupt their vital functionality. The role of the transportation sector becomes more crucial during disasters due to its role in pre-disaster evacuation as well as post-disaster recovery. The ability of transportation systems to retain performance during and after disasters undergoing little to no loss and their ability to return to the normal state of operation quickly after disasters defines their resilience. Authorities need to understand the degree of resilience within the transportation system under their jurisdiction and plan for improvements. In this research, attempts have been made to deal with resilience in quantitative ways to provide defensible data to decision makers to support investment strategies. Total loss in the network performance can be quantified by dealing with the variation of network performance over time after disasters and the network resilience can be measured by the ability to minimize this loss. It has been shown that robust networks retain better performance after disruptions and recovery works, which follow optimized recovery paths, in spite of constraints of resources and time, help to minimize the total losses and enhance the network resilience. The objective of this research is to create a conceptual framework to quantify resilience and discuss quantitatively the properties determining resilience of transportation networks. The concepts presented are applied to a test network to illustrate the mathematical procedures. Such methods can help decision makers analyze relative improvements in resiliency as a consequence of proposed project alternatives and help to perform benefit-cost analysis for such projects