SUBJECT: M.S. Thesis Presentation
BY: Matthew Dunbrack
TIME: Wednesday, June 1, 2022, 11:00 a.m.
PLACE: Boggs, 3-47
TITLE: Evaluating System Confidence of Near-Field Antineutrino-Based Nuclear Reactor Safeguards
COMMITTEE: Dr. Anna Erickson, Chair (Nuclear & Radiological Engineering Program)
Dr.Steven Biegalski (Nuclear & Radiological Engineering Program)
Dr. Nathaniel Bowden (Lawrence Livermore National Laboratory)


The International Atomic Energy Agency (IAEA) relies heavily on surveying facilities and verifying inventories to ensure that special nuclear material (SNM) pathways are correct and complete. This process, conducted through on-site inspections, draws a significant amount of the limited resources from the IAEA. Through implementing near-field antineutrino detection systems, changes in reactor core composition can be continuously monitored without the need of any expensive and invasive inspection. Our confidence in such a system, however, needs to be carefully considered for the IAEA to implement antineutrino detection systems for nuclear reactor safeguards.

In this work, system confidence, or the certainty of the predicted antineutrino spectra, is evaluated to outline current antineutrino-based safeguard capabilities as well as to highlight the leading causes of uncertainty. The proposed system under evaluation is the Reactor Evaluation Through Inspection of Near-field Antineutrinos (RETINA) system, which utilizes high-fidelity modeling to predict the antineutrino spectra emitted from a simulated reactor. Certain deviations in real-time antineutrino spectra would indicate a shift in fissile inventory and a possible diversion of SNM from the reactor core. To fully analyze the role of reactor designs and diversion scenarios in the system evaluation, the antineutrino spectra was simulated for various next generation reactor designs as well as processed for possible diversion scenarios the IAEA would aim to detect. The results indicate that larger reactors with more common fissile inventories lead to lower system uncertainty. While some simulated diversion scenarios were consistently detected, the overlapping spectra led to low confidence of diversion following IAEA standards. Future work will go into modeling new reactor-detector systems as well as applying modern machine learning methods for confidence improvement.