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DOE OSTI2018

Safeguards by Design in Nuclear Engineering Design Courses: Engaging Universities in Safeguards by Design

Engaging professionals across the breadth of the nuclear industry to educate them on international safeguards objectives and methodology is logistically challenging, especially in the United States, where individuals may not interact with the IAEA and are not as familiar with implementing international safeguards. However, incorporating international safeguards concepts into the mandatory curriculum of nuclear-related university degree programs around the world, complementary to nuclear safety and security concepts, could reach individuals who will go on to be professionals acting in a variety of roles across the nuclear industry (e.g., developing nuclear-related advanced technologies, designing or operating nuclear facilities, serving as State regulators). This would ultimately lead to more effective and efficient safeguards, including helping to move safeguards by design from a concept to a standard practice, as future designers, operators, and State regulators would be more familiar with international safeguards. This could also potentially address human resource challenges by creating a broader base of individuals knowledgeable about the IAEA mission from which to draw future inspectors and analysts. In order to implement this idea, the Y-12 National Security Complex in Oak Ridge, Tennessee, in conjunction with the Center for Nuclear Security Science & Policy Initiatives (a research institute associated with Texas A&M University), targeted nuclear engineering undergraduate students taking the mandatory design course at Texas A&M and the University of Tennessee. The project objective was to introduce safeguards by design concepts to individuals who are planning to work in a broad range of nuclear-related careers. The paper describes the project methodology, which included the project leads creating and presenting lectures on safeguards to the design class and mentoring teams working on design team projects that incorporated safeguards. The paper also identifies lessons learned while incorporating safeguards topics into nuclear engineering university degree programs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Brain Science and International Nuclear Safeguards: Implications from Cognitive Science and Human Factors Research on the Provision and Use of Safeguards-Relevant Information in the Field

Today’s international nuclear safeguards inspectors have access to an increasing volume of supplemental information about the facilities under their purview, including commercial satellite imagery, nuclear trade data, open source information, and results from previous safeguards activities. In addition to completing traditional in-field safeguards activities, inspectors are now responsible for being able to act upon this growing corpus of supplemental safeguards-relevant data and for maintaining situational awareness of unusual activities taking place in their environment. However, cognitive science research suggests that maintaining too much information can be detrimental to a user’s understanding, and externalizing information (for example, to a mobile device) to reduce cognitive burden can decrease cognitive function related to memory, navigation, and attention. Given this dichotomy, how can international nuclear safeguards inspectors better synthesize information to enhance situational awareness, decision making, and performance in the field? This paper examines literature from the fields of cognitive science and human factors in the areas of wayfinding, situational awareness, equipment and technical assistance, and knowledge transfer, and describes the implications for the provision of, and interaction with, safeguards-relevant information for international nuclear safeguards inspectors working in the field.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Safeguards Challenges and Safeguards Technology Needs Assessment for Leading Thorium Fuel Cycles

Several thorium fuel cycle variants are currently being actively pursued by the global nuclear energy community. These variants have short-, medium-, and long-term deployment pathways in a variety of reactor types, including thorium-fueled molten salt reactors. Those pathways in turn give rise to a variety of fuel designs, fuel cycle facilities, and nuclear material processing requirements. These emerging fuel cycles will impact the technical implementation of safeguards, and they already raise questions about the applicability of current verification technologies. To address this issue, research is being performed to produce a detailed safeguards technology road map. It will include a needs assessment of the detection research and development (R&D;) necessary to transition the current safeguards technology toolkit to meet the verification needs of thorium fuel cycles, and to formulate the scientific basis for building new instrumentation to fill any potential capability gaps. The purpose of this technology road map is to define and inform on the safeguards technology needs for thorium fuel cycles, reflecting only the leading candidate thorium fuel cycles prioritized based on implementation timescales and the current direction of international programs. This work provides a guide to the priorities for future directed R&D; needed to bring the technology readiness levels (TRLs) of safeguards detection solutions in line with the higher TRLs of the most promising thorium fuel cycles. Herein, a summary is presented of thorium fuel cycle options and activities currently under way worldwide, which provides the technical basis for the needs evaluation. The key synergies and differences between these fuel cycles and current conventional uranium- and plutonium-based fuel cycles will be discussed from a nuclear material accountancy and detection standpoint. Reactor inventory calculations, fuel cycle simulations, and conclusions from the safeguards technology needs assessment will be presented, together with plans for experimental validation.

Worrall, Louise G.↗
DOE OSTI2026

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗