July 16, 2009
ITHACA, NY, July 16 -- Linda Nozick, Cornell professor of civil and environmental engineering, and PhD student Yashoda Dadkar used high-performance computing systems at the Cornell Center for Advanced Computing to develop a model that simulates the threat of terrorist attacks on hazardous materials (hazmat) shipments.
This model has relevance to national security. Approximately 800,000 shipments of hazardous materials move daily through the U.S. transportation system and approximately one truck in five on U.S. highways is carrying some form of hazmat. While the safety record is excellent, public sensitivity to the risks associated with hazmat shipments is substantial.
The modeling tools that have been developed over the last 25 years for the identification of routes for hazmat shipments emphasize the tradeoffs between cost minimization to the shippers/carriers of the hazmat and controlling the "natural" consequences that would stem from an accident. Traditionally, the public sector plays a direct role in managing the level of risk through the regulation of the transportation network. Government agencies can determine which specific facilities to restrict or allow for each class of material and for which times of the day and/or week.
Nozick and Dadkar's game-theoretic model simulates the interactions between government agencies, shippers/carriers, and terrorists. Each of the relevant actors makes choices over time and has only partial control over the results of their choices. Incorporating the goals and activities of the terrorists into the routing models for the shippers/carriers is essential in order to provide guidance to federal, state and local governments.
This research was sponsored by the National Infrastructure Simulation and Analysis Center (NISAC) at Sandia National Laboratories which provides analytic support and modeling capabilities to the US Department of Homeland Security.
The Cornell Center for Advanced Computing receives support from the Cornell University, the National Science Foundation, and other leading public agencies, foundations, and corporations.
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Source: Cornell Center for Advanced Computing
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