Christopher Ritter, Ross Hays, Jeren Browning, Ryan Stewart, Samuel Bays, Gustavo Reyes, Mark Schanfein, Adam Pluth, Piyush Sabharwall, Ross Kunz, Ashley Shields, John Koudelka, and Porter Zohner
This case study describes the development of technologies that enable digital-engineering and digital-twinning efforts in proliferation detection. The project presents a state-of-the-art approach to support International Atomic Energy Agency (IAEA) safeguards by incorporating diversion-pathway analysis, facility misuse, and the detection of indicators within the reactor core, applying the safeguards-by-design concept, and demonstrates its applicability as a sensitive monitoring system for advanced reactors and power plants. There are two pathways a proliferating state might take using the reactor core. One is “diversion,” where special fissionable nuclear material—i.e., Pu-239, U-233, U enriched in U-233/235—that has been declared to the IAEA is removed surreptitiously, either by taking small amounts of nuclear material over a long time (known as protracted diversion) or large amounts in a short time (known as abrupt diversion). The second pathway is “misuse,” where undeclared source material—material that can be transmuted into special fissionable nuclear material: depleted uranium, natural uranium, and thorium—is placed in the core, where it uses the neutron flux for transmutation. Digital twinning and digital engineering have demonstrated significant performance improvement and schedule reduction in the aerospace, automotive, and construction industries. This integrated modeling approach has not been fully applied to nuclear safeguards programs in the past. Digital twinning, combined with machine learning technologies, can lead to new innovations in process-monitoring detection, specifically in event classification, real-time notification, and data tampering. It represents a technological leap in evaluation and detection capability to safeguard any nuclear facility.