Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

Abstract

Digital twin technology can improve the effectiveness of international safeguards inspectors by providing a tool that can perform an accurate acquisition pathway analysis, identify pathway indicators, develop required sensors to detect indicators, and monitor facilities in real time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and to detect facility misuse; however, this analysis and verification effort is time consuming, and with limited funding, it is imperative that time spent at a nuclear facility is focused on key areas. We developed a virtual digital twin of two general sodium-cooled fast reactors and explored diversion and misuse scenarios to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs that would be difficult to detect via sensors alone; however, a machine learning adapter provided by the digital twin was able to show general trends in where proliferation is likely to take place.