ARI-MA: Interdicting Smuggled Nuclear Material

University Of Texas At Austin, Austin TX

Investigators

Abstract

0736231 Morton This project will develop a class of stochastic interdiction models on a transportation network consisting of two adversaries: a smuggler and an interdictor. The models are hierarchical, stochastic, and involve strategic gaming. The interdictor first will install radiation detectors on the network. These installations are permanent, transparent to the smuggler, and are made under an uncertain threat scenario, which specifies the smuggler's origin and destination, the nature of the material being smuggled, the manner in which it is shielded, and the mechanism by which the smuggler will select a smuggling route. Next, intelligence may yield updated information on the still-unknown threat scenario. The interdictor then deploys additional mobile detectors and may adjust alarm thresholds, and the smuggler simultaneously chooses a path over the network in a two-person zero-sum game. The interdictor's goal is to minimize the probability the smuggler avoids detection. The intellectual merit of the proposal lies in three areas: stochastic interdiction optimization, probability and statistical modeling of uncertainties, and nuclear radiation transport modeling and analysis. This approach will produce a rich family of models, with accompanying solution techniques, that allow one to select any combination of the proposed modules in a plug-and-play"" decision-support system depending on the nature of the specific problem to be analyzed. Graduate and postdoctoral students who can carry out work in this domain will be trained. Collaborations with the D-5 (Nuclear Design & Risk Analysis) and D-6 (Risk Analysis & Decision Support System) groups at Los Alamos National Laboratory (LANL) will lead to its incorporation in decision-support software at LANL for selecting sites to receive detection equipment upgrades.