Eric D. Vugrin

A Framework for Assessing the Resilience of Infrastructure and Economic Systems

Recent U.S. national mandates are shifting the country’s homeland security policy from one of asset-level critical infrastructure protection (CIP) to allhazards critical infrastructure resilience, creating the need for a unifying framework for assessing the resilience of critical infrastructure systems and the economies that rely on them. Resilience has been defined and applied in many disciplines; consequently, many disparate approaches exist. We propose a general framework for assessing the resilience of infrastructure and economic systems. The framework consists of three primary components: (1) a definition of resilience that is specific to infrastructure systems; (2) a quantitative model for measuring the resilience of systems to disruptive events through the evaluation of both impacts to system performance and the cost of recovery; and (3) a qualitative method for assessing the system properties that inherently determine system resilience, providing insight and direction for potential improvements in these systems.

A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane

In recent years, the nation has recognized that critical infrastructure protection should consider not only the prevention of disruptive events but also the processes that infrastructure systems undergo to maintain functionality following disruptions. This more comprehensive approach has been termed critical infrastructure resilience. Given the occurrence of a particular disruptive event, the resilience of a system to that event is the systems ability to reduce efficiently both the magnitude and duration of the deviation from targeted system performance levels. Under the direction of the U. S. Department of Homeland Securitys Science and Technology Directorate, Sandia National Laboratories has developed a comprehensive resilience assessment framework for evaluating the resilience of infrastructure and economic systems. The framework includes a quantitative methodology that measures resilience costs that result from a disruption to infrastructure function. The framework also includes a qualitative analysis methodology that assesses system characteristics affecting resilience to provide insight and direction for potential improvements. This article describes the resilience assessment framework and demonstrates the utility of the assessment framework through application to two hypothetical scenarios involving the disruption of a petrochemical supply chain by hurricanes.

Design for Resilience in Infrastructure Distribution Networks

The recognition that resilience is a critical aspect of infrastructure security has caused the national and homeland security communities to ask “How does one ensure infrastructure resilience?” Previous network resilience analysis methods have generally focused on either pre-disruption prevention investments or post-disruption recovery strategies. This paper expands on those methods by introducing a stochastic optimization model for designing network infrastructure resilience that simultaneously considers pre- and post-disruption activities. The model seeks investment–recovery combinations that minimize the overall cost to a distribution network across a set of disruption scenarios. A set of numerical experiments illustrates how changes to disruption scenarios probabilities affect the optimal resilient design investments.

Optimal recovery sequencing for enhanced resilience and service restoration in transportation networks

Critical infrastructure resilience has become a national priority for the US Department of Homeland Security. Rapid and efficient restoration of service in damaged transportation networks is a key area of focus. The intent of this paper is to formulate a bi-level optimisation model for network recovery and to demonstrate a solution approach for that optimisation model. The lower-level problem involves solving for network flows, while the upper-level problem identifies the optimal recovery modes and sequences, using tools from the literature on multi-mode project scheduling problems. Application and advantages of this method are demonstrated through two examples.

Infrastructure resilience assessment through control design

Infrastructure resilience is a priority for homeland security in many nations around the globe. This paper describes a new approach for quantitatively assessing the resilience of critical infrastructure systems. The mathematics of optimal control design provides the theoretical foundation for this methodology. This foundation enables the inclusion of recovery costs within the resilience assessment approach, a unique capability for quantitative resilience assessment techniques. This paper describes the formulation of the optimal control problem for a set of representative infrastructure models. This example demonstrates the importance of recovery costs in quantitative resilience analysis, and the increased capability provided by this approachs ability to discern between varying levels of resilience.

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.

Resilience certification for commercial buildings: a study of stakeholder perspectives

Infrastructure resilience has become a primary objective for homeland and national security organizations over the past decade. Recent initiatives have focused on resilient building design, and one approach under consideration is a voluntary resilience certification program for commercial buildings. The intent of this program would be to encourage the adoption of resilient design practices in construction and planning of the buildings. While resilience may be a frequently discussed concept within the security communities, its level of awareness within the construction, design, insurance, and building owner communities is not well known. Given the voluntary nature of the certification program under consideration, program development requires a comprehensive understanding of resilience as defined by the commercial building stakeholders. Toward this end, Sandia National Laboratories conducted a study of stakeholder perspectives on resilience to ascertain factors that would serve as motivation for participation in the resilience certification program. This paper describes how Sandia performed the study and the resulting conclusions. One of the key conclusions that the study found is that the term resilience is unfamiliar to many and inconsistently defined across the industries. Those familiar with the term frequently linked it to sustainability concepts. The study also found that increased participation in the resilience certification program is very likely affected by demonstrable returns on resilience investments and a public–private partnership model for program administration.

Potential Public Health Effects of Reducing Nicotine Levels in Cigarettes in the United States

Potential Health Effects of Reducing Nicotine Using a simulation model, the FDA has estimated that lowering the nicotine content in cigarettes to a minimally addictive level could substantially reduce tobacco-related mortality.

Optimization-based computation with spiking neurons

Considerable effort is currently being spent designing neuromorphic hardware for addressing challenging problems in a variety of pattern-matching applications. These neuromorphic systems offer low power architectures with intrinsically parallel and simple spiking neuron processing elements. Unfortunately, these new hardware architectures have been largely developed without a clear justification for using spiking neurons to compute quantities for problems of interest. Specifically, the use of spiking for encoding information in time has not been explored theoretically with complexity analysis to examine the operating conditions under which neuromorphic computing provides a computational advantage (time, space, power, etc.) In this paper, we present and formally analyze the use of temporal coding in a neural-inspired algorithm for optimization-based computation in neural spiking architectures.

Modeling evacuation of a hospital without electric power

Hospital evacuations that occur during, or as a result of, infrastructure outages are complicated and demanding. Loss of infrastructure services can initiate a chain of events with corresponding management challenges. This report describes a modeling case study of the 2001 evacuation of the Memorial Hermann Hospital in Houston, Texas (USA). The study uses a model designed to track such cascading events following loss of infrastructure services and to identify the staff, resources, and operational adaptations required to sustain patient care and/or conduct an evacuation. The model is based on the assumption that a hospitals primary mission is to provide necessary medical care to all of its patients, even when critical infrastructure services to the hospital and surrounding areas are disrupted. Model logic evaluates the hospitals ability to provide an adequate level of care for all of its patients throughout a period of disruption. If hospital resources are insufficient to provide such care, the model recommends an evacuation. Model features also provide information to support evacuation and resource allocation decisions for optimizing care over the entire population of patients. This report documents the application of the model to a scenario designed to resemble the 2001 evacuation of the Memorial Hermann Hospital, demonstrating the models ability to recreate the timeline of an actual evacuation. The model is also applied to scenarios demonstrating how its output can inform evacuation planning activities and timing.