Publications

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The potential impacts of man-made and natural disasters on chemical plants, complexes, and supply chains are of great importance to homeland security. To be able to estimate these impacts, we developed an agent-based chemical supply chain model that includes: chemical plants with enterprise operations such as purchasing, production scheduling, and inventories; merchant chemical markets, and multi-modal chemical shipments. Large-scale simulations of chemical-plant activities and supply chain interactions, running on desktop computers, are used to estimate the scope and duration of disruptive-event impacts, and overall system resilience, based on the extent to which individual chemical plants can adjust their internal operations (e.g., production mixes and levels) versus their external interactions (market sales and purchases, and transportation routes and modes). To illustrate how the model estimates the impacts of a hurricane disruption, a simple example model centered on 1,4-butanediol is presented. © 2013 Elsevier Ltd.

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As alternative energy generating devices (i.e., solar, wind, etc) are added onto the electrical energy grid (AC grid), irregularities in the available electricity due to natural occurrences (i.e., clouds reducing solar input or wind burst increasing wind powered turbines) will be dramatically increased. Due to their almost instantaneous response, modern flywheel-based energy storage devices can act a mechanical mechanism to regulate the AC grid; however, improved spin speeds will be required to meet the necessary energy levels to balance these green energy variances. Focusing on composite flywheels, we have investigated methods for improving the spin speeds based on materials needs. The so-called composite flywheels are composed of carbon fiber (C-fiber), glass fiber, and a glue (resin) to hold them together. For this effort, we have focused on the addition of fillers to the resin in order to improve its properties. Based on the high loads required for standard meso-sized fillers, this project investigated the utility of ceramic nanofillers since they can be added at very low load levels due to their high surface area. The impact that TiO2 nanowires had on the final strength of the flywheel material was determined by a three-point-bend test. The results of the introduction of nanomaterials demonstrated an increase in strength of the flywheels C-fiber-resin moiety, with an upper limit of a 30% increase being reported. An analysis of the economic impact concerning the utilization of the nanowires was undertaken and after accounting for new-technology and additional production costs, return on improved-nanocomposite investment was approximated at 4-6% per year over the 20-year expected service life. Further, it was determined based on the 30% improvement in strength, this change may enable a 20-30% reduction in flywheel energy storage cost ($/kW-h).

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This paper describes the Regional Economic Accounting (REAcct) analysis tool that has been in use for the last 5 years to rapidly estimate approximate economic impacts for disruptions due to natural or manmade events. It is based on and derived from the well-known and extensively documented input-output modeling technique initially presented by Leontief and more recently further developed by numerous contributors. REAcct provides county-level economic impact estimates in terms of gross domestic product (GDP) and employment for any area in the United States. The process for using REAcct incorporates geospatial computational tools and site-specific economic data, permitting the identification of geographic impact zones that allow differential magnitude and duration estimates to be specified for regions affected by a simulated or actual event. Using these data as input to REAcct, the number of employees for 39 directly affected economic sectors (including 37 industry production sectors and 2 government sectors) are calculated and aggregated to provide direct impact estimates. Indirect estimates are then calculated using Regional Input-Output Modeling System (RIMS II) multipliers. The interdependent relationships between critical infrastructures, industries, and markets are captured by the relationships embedded in the inputoutput modeling structure.

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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 efficiently reduce 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 paper 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.

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While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of the U.S. economy.

This report gives an overview of the types of economic methodologies and models used by Sandia economists in their consequence analysis work for the National Infrastructure Simulation & Analysis Center and other DHS programs. It describes the three primary resolutions at which analysis is conducted (microeconomic, mesoeconomic, and macroeconomic), the tools used at these three levels (from data analysis to internally developed and publicly available tools), and how they are used individually and in concert with each other and other infrastructure tools.

Staggered bioterrorist attacks with aerosolized pathogens on population centers present a formidable challenge to resource allocation and response planning. The response and planning will commence immediately after the detection of the first attack and with no or little information of the second attack. In this report, we outline a method by which resource allocation may be performed. It involves probabilistic reconstruction of the bioterrorist attack from partial observations of the outbreak, followed by an optimization-under-uncertainty approach to perform resource allocations. We consider both single-site and time-staggered multi-site attacks (i.e., a reload scenario) under conditions when resources (personnel and equipment which are difficult to gather and transport) are insufficient. Both communicable (plague) and non-communicable diseases (anthrax) are addressed, and we also consider cases when the data, the time-series of people reporting with symptoms, are confounded with a reporting delay. We demonstrate how our approach develops allocations profiles that have the potential to reduce the probability of an extremely adverse outcome in exchange for a more certain, but less adverse outcome. We explore the effect of placing limits on daily allocations. Further, since our method is data-driven, the resource allocation progressively improves as more data becomes available.

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Based primarily on the results of a month-long experiment and a crisis management exercise, synchronous multimedia collaboration within a taskoriented, time-constrained distributed team appears to exhibit three layers of structure. The first layer is episodic, and results in collections of related multimedia collaboration artifacts that can be called "chapters" or "scenes" in the collaboration. The second layer is the multivalent nature of collaboration, in which collaboration conversations at multiple subgroup levels take place at the same time. The third, top-level, layer is the agenda that drives the collaboration. The implications for the design of synchronous collaboration systems are that multiple views, representations, and metaphors for this conversation structure are needed. Chapter views, subgroup views, and agenda views are presented as alternative packaging mechanisms and entry points into the collaboration data. Other metaphors and presentations include the collaboration tree and infinitely recursive conference room, as well as network graphs of subgroup structure and agenda-based group awareness. © 2006 IEEE.

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Concepts from Complexity Science are valuable and allow a simulation approach for critical infrastructures that is flexible and has wide ranging applications.

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The nation's electric power sector is highly interdependent with the economic sectors it serves; electric power needs are driven by economic activity while the economy itself depends on reliable and sustainable electric power. To advance higher level understandings of the vulnerabilities that result from these interdependencies and to identify the loss prevention and loss mitigation policies that best serve the nation, the National Infrastructure Simulation and Analysis Center is developing and using N-ABLE{trademark}, an agent-based microeconomic framework and simulation tool that models these interdependencies at the level of collections of individual economic firms. Current projects that capture components of these electric power and economic sector interdependencies illustrate some of the public policy issues that should be addressed for combined power sector reliability and national economic security.

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Acts of terrorism could have a range of broad impacts on an economy, including changes in consumer (or demand) confidence and the ability of productive sectors to respond to changes. As a first step toward a model of terrorism-based impacts, we develop here a model of production and employment that characterizes dynamics in ways useful toward understanding how terrorism-based shocks could propagate through the economy; subsequent models will introduce the role of savings and investment into the economy. We use Aspen, a powerful economic modeling tool developed at Sandia, to demonstrate for validation purposes that a single-firm economy converges to the known monopoly equilibrium price, output, and employment levels, while multiple-firm economies converge toward the competitive equilibria typified by lower prices and higher output and employment. However, we find that competition also leads to churn by consumers seeking lower prices, making it difficult for firms to optimize with respect to wages, prices, and employment levels. Thus, competitive firms generate market ''noise'' in the steady state as they search for prices and employment levels that will maximize profits. In the context of this model, not only could terrorism depress overall consumer confidence and economic activity but terrorist acts could also cause normal short-run dynamics to be misinterpreted by consumers as a faltering economy.

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