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Stewart, Christopher

Publications and source records attributed to Stewart, Christopher.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

Employing antineutrino detectors to safeguard future nuclear reactors from diversions

The Non-Proliferation Treaty and other non-proliferation agreements are in place worldwide to ensure that nuclear material and facilities are used only for peaceful purposes. Antineutrino detectors, sensitive to reactor power and fuel changes, can complement the tools already at the disposal of international agencies to safeguard nuclear facilities and to verify the States' compliance with the agreements. Recent advancement in these detectors has made it possible to leverage them to reduce the likelihood of an undetected diversion of irradiated nuclear material. We study the sensitivity of antineutrino monitors to fuel divergence from two reactor types: a traditional light-water reactor and an advanced sodium-cooled reactor design, a likely candidate for future deployment. The analysis demonstrates that a variety of potential diversion scenarios can be detected by such a system. We outline recent developments in monitoring capabilities and discuss their potential security implications to the international community.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2016

Semi-Autonomous Vehicle Project

The primary objective this summer is "evaluating standards for wireless architecture for the internet of things". The Internet of Things is the network of physical objects or "things" embedded with electronics, software, sensors and network connectivity which enables these objects to collect and exchange data and make decisions based on said data. This was accomplished by creating a semi-autonomous vehicle that takes advantage of multiple sensors, cameras, and onboard computers and combined them with a mesh network which enabled communication across large distances with little to no interruption. The mesh network took advantage of what is known as DTN - Disruption Tolerant Networking which according to NASA is the new communications protocol that is "the first step towards interplanetary internet." The use of DTN comes from the fact that it will store information if an interruption in communications is detected and even forward that information via other relays within range so that the data is not lost. This translates well into the project because as the car moves further away from whatever is sending it commands (in this case a joystick), the information can still be forwarded to the car with little to no loss of information thanks to the mesh nodes around the driving area.

Stewart, Christopher↗