The diversion of significant quantities of special nuclear material from the nuclear fuel cycle is major non-proliferation concern. These diversions must be detected in a timely manner using signatures and observables in order to properly safegaurd the fuel cycle. Pyroprocessing is an up and coming reprocessing technology capable of both converting current generation waste into molten salt fuel, and reprocessing next generation molten salt fuel types. With a new reprocessing technology comes new signatures and observables which in turn necessitate new diversion detection methods. The goal of this research is to identify potential signs of pyroprocessing diversion and implement models of these processes into a detailed pyroprocessing facility archetype to the modular, agent-based, fuel cycle simulator, Cyclus. This facility archetype will equip users of the Cyclus fuel cycle simulator to investigate the detection timeliness enabled by novel signatures and observables in various fuel cycle diversion scenarios.
2018-cnec-poster's Introduction
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