Publications

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The study develops a novel stochastic frontier modeling approach to the gravity equation for rare earth element (REE) trade between China and its trading partners between 2001 and 2009. The novelty lies in differentiating betweenbehind the border' trade costs by China and theimplicit beyond the border costs' of China's trading partners. Results indicate that the significance level of the independent variables change dramatically over the time period. While geographical distance matters for trade flows in both periods, the effect of income on trade flows is significantly attenuated, possibly capturing the negative effects of financial crises in the developed world. Second, the total export losses due tobehind the border' trade costs almost tripled over the time period. Finally, looking atimplicit beyond the border' trade costs, results show China gaining in some markets, although it is likely that some countries are substituting away from Chinese REE exports.

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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 system's 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 Security's 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. © 2011 American Institute of Chemical Engineers (AIChE).

This report provides the results of a scoping study evaluating the potential risk reduction value of a hypothetical, earthquake early-warning system. The study was based on an analysis of the actions that could be taken to reduce risks to population and infrastructures, how much time would be required to take each action and the potential consequences of false alarms given the nature of the action. The results of the scoping analysis indicate that risks could be reduced through improving existing event notification systems and individual responses to the notification; and production and utilization of more detailed risk maps for local planning. Detailed maps and training programs, based on existing knowledge of geologic conditions and processes, would reduce uncertainty in the consequence portion of the risk analysis. Uncertainties in the timing, magnitude and location of earthquakes and the potential impacts of false alarms will present major challenges to the value of an early-warning system.

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Infrastructure resilience is a priority for homeland security in many nations around the globe. This paper describes a new approach forquantitatively 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 esilience assessment techniques. This paper describes the formulation of the optimal control problem for a set of representative infrastructure models. Thisexample demonstrates the importance of recovery costs in quantitative resilience analysis, and the increased capability provided by this approach's ability to discern between varying levels of resilience. © 2011 Inderscience Enterprises Ltd.

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Sandia National Laboratories has developed several models to analyze potential consequences of homeland security incidents. Two of these models (the National Infrastructure Simulation and Analysis Center Agent-Based Laboratory for Economics, N-ABLE{trademark}, and Loki) simulate detailed facility- and product-level consequences of simulated disruptions to supply chains. Disruptions in supply chains are likely to reduce production of some commodities, which may reduce economic activity across many other types of supply chains throughout the national economy. The detailed nature of Sandia's models means that simulations are limited to specific supply chains in which detailed facility-level data has been collected, but policymakers are often concerned with the national-level economic impacts of supply-chain disruptions. A preliminary input-output methodology has been developed to estimate national-level economic impacts based upon the results of supply-chain-level simulations. This methodology overcomes two primary challenges. First, the methodology must be relatively simple to integrate successfully with existing models; it must be easily understood, easily applied to the supply-chain models without user intervention, and run quickly. The second challenge is more fundamental: the methodology must account for both upstream and downstream impacts that result from supply-chain disruptions. Input-output modeling typically estimates only upstream impacts, but shortages resulting from disruptions in many supply chains (for example, energy, communications, and chemicals) are likely to have large downstream impacts. In overcoming these challenges, the input-output methodology makes strong assumptions about technology and substitution. This paper concludes by applying the methodology to chemical supply chains.