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Earthquake warning system for infrastructures : a scoping analysis

Kelic, Andjelka; Stamber, Kevin L.; Brodsky, Nancy S.; Vugrin, Eric D.; Corbet, Thomas F.; O'Connor, Sharon L.

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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TYPE SAND Report YEAR 2011
OSTIDOI

An input-output procedure for calculating economy-wide economic impacts in supply chains using homeland security consequence analysis tools

Warren, Drake E.; Vargas, Vanessa N.; Smith, Braeton J.; Vugrin, Eric D.

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.

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TYPE Conference YEAR 2010
OSTI

Optimal recovery sequencing for critical infrastructure resilience assessment

Vugrin, Eric D.; Brown, Nathanael J.

Critical infrastructure resilience has become a national priority for the U. S. Department of Homeland Security. System resilience has been studied for several decades in many different disciplines, but no standards or unifying methods exist for critical infrastructure resilience analysis. This report documents the results of a late-start Laboratory Directed Research and Development (LDRD) project that investigated the identification of optimal recovery strategies that maximize resilience. To this goal, we formulate a bi-level optimization problem for infrastructure network models. In the 'inner' problem, we solve for network flows, and we use the 'outer' problem to identify the optimal recovery modes and sequences. We draw from the literature of multi-mode project scheduling problems to create an effective solution strategy for the resilience optimization model. We demonstrate the application of this approach to a set of network models, including a national railroad model and a supply chain for Army munitions production.

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TYPE SAND Report YEAR 2010
OSTIDOI
Results 76–100 of 133
Results 76–100 of 133