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Chemical supply chain modeling for analysis of homeland security events

Computers and Chemical Engineering

Ehlen, Mark E.; Sun, Amy C.; Pepple, Mark A.; Eidson, Eric D.; Jones, Brian S.

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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Economics definitions, methods, models, and analysis procedures for Homeland Security applications

Ehlen, Mark E.; Smith, Braeton J.; Warren, Drake E.; Downes, Paula S.; Eidson, Eric D.; Mackey, Greg

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.

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Simulating economic effects of disruptions in the telecommunications infrastructure

Barton, Dianne C.; Barton, Dianne C.; Eidson, Eric D.; Schoenwald, David A.; Cox, Roger G.; Reinert, Rhonda K.

CommAspen is a new agent-based model for simulating the interdependent effects of market decisions and disruptions in the telecommunications infrastructure on other critical infrastructures in the U.S. economy such as banking and finance, and electric power. CommAspen extends and modifies the capabilities of Aspen-EE, an agent-based model previously developed by Sandia National Laboratories to analyze the interdependencies between the electric power system and other critical infrastructures. CommAspen has been tested on a series of scenarios in which the communications network has been disrupted, due to congestion and outages. Analysis of the scenario results indicates that communications networks simulated by the model behave as their counterparts do in the real world. Results also show that the model could be used to analyze the economic impact of communications congestion and outages.

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Aspen-EE: An Agent-Based Model of Infrastructure Interdependency

Barton, Dianne C.; Eidson, Eric D.; Schoenwald, David A.; Stamber, Kevin L.; Reinert, Rhonda K.

This report describes the features of Aspen-EE (Electricity Enhancement), a new model for simulating the interdependent effects of market decisions and disruptions in the electric power system on other critical infrastructures in the US economy. Aspen-EE extends and modifies the capabilities of Aspen, an agent-based model previously developed by Sandia National Laboratories. Aspen-EE was tested on a series of scenarios in which the rules governing electric power trades were changed. Analysis of the scenario results indicates that the power generation company agents will adjust the quantity of power bid into each market as a function of the market rules. Results indicate that when two power markets are faced with identical economic circumstances, the traditionally higher-priced market sees its market clearing price decline, while the traditionally lower-priced market sees a relative increase in market clearing price. These results indicate that Aspen-EE is predicting power market trends that are consistent with expected economic behavior.

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4 Results
4 Results