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ECAR-6440 Rev 2 MARVEL Hazard Evaluation

This hazard evaluation supports the Microreactor Applications Research, Validation, and Evaluation (MARVEL) Project’s design effort and the development of the preliminary documented safety analysis (PDSA) (addendum to safety analysis report [SAR]-420, “Transient Reactor Test [TREAT] Facility FSAR”) (SAR-420-ADD-1). The hazard evaluation process for the MARVEL project for compliance with the requirements in 10 CFR 830, “Nuclear Safety Management,” follows a process similar to the Licensing Modernization Project (LMP) as outlined in Nuclear Energy Institute (NEI)-18-04, “Risk-Informed Performance-Based Guidance for Non-Light Water Reactor Licensing Basis Development,” and supporting documents. The LMP process is adapted to fit Department of Energy (DOE) reactor regulatory requirements as applicable and appropriate using a graded approach based on the MARVEL microreactor design. This approach provides reasonable assurance of meeting the requirements of 10 CFR 830 for protection of the public, workers, and environment.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hazard Analysis to Support Fusion Systems Safety Assessments

Reliability, safety, and performance are vital aspects of any nuclear operation. Fusion technology continues to grow in public, private, and research interest, and coupled with rapidly growing energy needs, fusion technology research is poised for fast progress. The development of a Fusion Nuclear Science Facility (FNSF) is seen as stepping stone for demonstrating long-cycle fusion. Naturally, such operation requires systems that are available, reliable, and safe. This work provides a novel demonstration of systems theory coupled with traditional hazard analysis to provide insights into the risk priority of components and systems found within the FNSF. The results of this work are a set of identified hazards that should be considered for the risk-informed design and development of the FNSF.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Elastic-wave sensitivity-guided adaptive seismic survey design for cost-effective monitoring of geological carbon storage

Effective seismic monitoring is essential for verifying CO₂ containment, detecting potential leakage, and optimizing operational decisions in geologic carbon storage. Here, this study presents a time-adaptive, elastic-wave sensitivity-guided framework for designing cost-effective seismic monitoring layouts for tracking CO₂ plume migration. The method is based on elastic-wave sensitivity analysis, which quantifies how variations in subsurface properties impact seismic wavefields. Two complementary design strategies are developed: one based on selecting a fixed number of seismic sources (Method A), and the other based on selecting source–receiver pairs contributing to a fixed fraction of cumulative elastic-wave sensitivity energy (Method B). The optimization workflow to identify source–receiver configurations with the highest detection potential is demonstrated using a hypothetical GCS scenario at the Kimberlina site in California using simulations of elastic-wave sensitivity data at multiple post-injection timesteps. Results show that both strategies adapt to evolving plume geometries and wavefield sensitivities, with Method B offering broader spatial coverage and Method A ensuring simpler deployment. This framework enables site-specific, cost-effective, and risk-informed seismic survey designs, enhancing the ability to monitor CO₂ migration over time in evolving geological environments

58 GEOSCIENCES↗

Consequence analyses of sabotage-induced radiological releases in sodium-cooled fast microreactors

Analysis of three sodium-cooled fast microreactors (SFMs) with thermal powers of 10, 30, and 50 MWt showed that smaller reactors result in lower radiological consequences during a postulated sabotage-induced event because of their reduced core inventory. All SFMs used U-10Zr metal fuel enriched to 15 wt% high-assay low-enriched uranium and operated until their respective effective multiplication factor (k eff ) reduced to less than 1 or until the end of their operational lifespan. Sabotage scenarios were simulated at this point, when the fuel inventory within the core contains the highest-level of radioactivity. Radionuclide core inventories were calculated using the SCALE code at shutdown and 3 days post-shutdown. Dose consequence analyses were performed for three sabotage scenarios using the RASCAL tool. As microreactor developers plan for minimal on-site or complete off-site emergency response, it remains essential to evaluate their physical protection needs and potential hazards, including assessing postulated sabotage-induced events that could become more relevant. SFM licensees should identify a credible worst-case, major accident, estimate release source terms, and perform dose consequence analyses to evaluate site-specific physical protection measures. In conclusion, this recommendation supports a risk-informed, performance-based approach, aligning with applicable regulatory requirements, i.e., 10 CFR Parts 100 and 53 rulemaking in the United States.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization

The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200 000 integrated design evaluations were performed exploring the trade-offs between capital cost minimization and operational reliability (maximizing q 95 ) while satisfying engineering constraints including 250 ± 50 MW net electric power, tritium breeding ratio > 1.1, power exhaust limits and an hour flattop time. Both configurations achieve similar cost-performance Pareto fronts through contrasting design philosophies. PT, while demonstrating resilience to pedestal degradation (compensating for up to 40% reduction), are constrained to larger machines (R 0 > 6.5 m) by the narrow operational window between L–H threshold requirements and the research-established power exhaust limit (P sol /R < 15 MW m –1 ). This forces optimization through comparatively reduced magnetic field (∼8 T). NT configurations exploit their freedom from these constraints to access compact, high-field designs (R 0 ~ 5.5 m, B 0 >12 T), creating natural synergy with advancing HTS technology. Sensitivity analyses reveal that PT’s economic viability depends critically on uncertainties in L–H threshold scaling and power handling limits. Notably, a 50% variation in either could eliminate viable designs or enable access to the compact design space. These results suggest configuration selection should be risk-informed: PT offers the lowest-cost path when operational constraints can be confidently predicted, while NT is robust to large variations in constraints and physics uncertainties.

FUSE framework↗

Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Risk assessment of wellbore leakage during underground hydrogen storage

The expansion of renewable energy sources would require large-scale energy storage options to overcome the intermittent nature of these sources. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs offers a scalable and practical energy storage solution. These reservoirs are chosen for their availability and large capacity, but the unique properties of hydrogen raise concerns about potential leakage pathways, particularly through wellbores. In this study, we develop and apply, for the first time, reduced-order models (ROMs) specifically designed for efficient leakage risk prediction in UHS systems operating in depleted hydrocarbon reservoirs. Using 3,000 high-fidelity simulation scenarios, we examine the influence of 11 key parameters, including reservoir and aquifer depths, wellbore permeability and porosity, initial saturations of water, oil and gas fractions (hydrogen, light, intermediate, and heavy hydrocarbons), reservoir pressure multiplier, and the aquifer-to-reservoir volume ratio, to simulate leakage behavior over a 1,000-year timescale. We train ROMs using a two-step classification-regression approach, achieving R 2 values exceeding 99 % across all targets. These ROMs effectively capture the leakage evolution and identify critical controls of leakage, guiding the design of mitigation strategies. Results indicate that gas leakage occurs in about 27 % of scenarios as early as five years post-operation, reaching volumes of up to 106 ft3. Oil leakage is less frequent (~17 %) and typically begins decades later. Our findings also show that hydrogen often migrates first, owing to its smaller molecular size and higher buoyancy, followed by heavier hydrocarbons. Over time, these heavier components contribute significantly to the total leaked volume, reinforcing the need for targeted monitoring and remediation strategies. Our analysis highlights that deeper storage reservoirs, shallower aquifers, and low-permeability wellbores significantly reduce leakage risks. In conclusion, this work offers a robust framework for risk-informed UHS deployment, supporting energy security through reliable large-scale hydrogen storage while safeguarding environmental integrity.

08 HYDROGEN↗

Evaluating Supply Prioritization Strategies for Risk-Informed Decision Making in an Arbitrary Gas Network

Supply disruptions and infrastructure failures in natural gas networks present critical challenges to energy reliability and risk-informed planning. This study evaluates two supply prioritization strategies, Maximum Delivery Prioritization (MDP) and Demand-Based Prioritization (DBP), within an arbitrary natural gas network under conditions of supply shortage. Model performance under both strategies is assessed in response to node and edge failure using demand satisfaction metrics, system-wide and localized dependency scores, and geographic information system (GIS)-based spatial analysis. Results show that DBP better preserves supply for high-demand nodes, while MDP offers broader coverage. The underlying network topology plays a critical role in shaping prioritization outcomes. Integrated GIS visualization enhances the interpretability of vulnerability assessments, revealing structurally critical components and localized vulnerabilities. The proposed framework supports scalable, data-driven decision-making for infrastructure planners and engineers, enabling improved disruption recovery and efficiency in constrained natural gas networks. These insights contribute to the development of more robust energy systems capable of withstanding stress and disruptions.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗

Developing a Process for Collaboration-Based Siting of a Federal Consolidated Interim Storage Facility in the United States: Learning from Communities Living with Legacy Waste

In June of 2023, the U.S. Department of Energy (DOE), Office of Nuclear Energy (NE) announced the selection of its Collaboration-Based Siting (CBS) Consortia, a group of 12 awardees, including the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) (led by Vanderbilt University) to assist DOE-NE with the development of its process for siting a federal consolidated interim storage facility (FCISF) for spent nuclear fuel (SNF) storage. At this time, DOE NE is not soliciting interested host communities, rather the CBS Consortia are tasked with in-depth engagement, mutual learning, and capacity building to provide DOE NE with feedback on the CBS process. CRESP’s objective is to engage communities in two regions (the Pacific Northwest and the Southeast) with sites currently storing defense- and research-related SNF to foster learning concerning the best and worst practices in community participation in risk-informed decision making. This includes learning from existing structures for public input in radioactive waste management decision making [e.g. citizen advisory boards (CABs)] and other local parties about how to build and sustain trust among the parties. CRESP has been working to engage stakeholders and Tribes surrounding two DOE sites historically differing in receptiveness to engaging with DOE and trusting in DOE to accomplish its missions. CRESP’s approach to date has consisted of (1) engaging voluntarily members and former members of the DOE Office of Environmental Management’s CABs to develop a mutual understanding of their perspectives, values, and experiences related to risk and participatory decision making; (2) engaging members of those communities that would likely be part of any radioactive waste management discussions and who may provide valuable feedback for the development of the CBS process; and in the longer term, (3) engaging communities to foster knowledge sharing on understanding and definitions of risk and how risk is factored into community decision making. Our emphasis is to identify opportunities for improving risk communication frameworks, strategies, and decision making. The selection of a future FCISF site is likely to result in the creation of a structure similar to a CAB composed of members of the local community. We anticipate that these insights can help DOE NE learn from existing participatory risk communication structures in place at sites storing defenseor research-related SNF to understand best practices for fostering enduring and participatory relationships with future CABs. Within this paper, we (1) describe CRESP’s overall approach to assisting DOE NE with maturing the CBS process; (2) present a summary of preliminary phase 1 project results, including the development of a body of knowledge (describing available resources to support community engagement, risk communica tion, and participatory decision making) and community ecosystem information (leveraging demographic, social, economic, and environmental attribute mapping and advanced sentiment analysis of social media data); and (3) based on these results, provide observations for future research opportunities to support the development of CBS processes for radioactive waste management facilities, generally.

collaboration-based siting↗

Markov Decision Processes for Intelligent, Risk-Informed Asset-Management Decision-Making

Advanced nuclear reactors are a promising option for aiding the world in achieving its net-zero carbon emission goals, however, there are significant challenges to attaining and maintaining economic competitiveness with other sources of electricity. To improve the economic competitiveness of advanced reactor designs, a project was initiated to explore the use of Markov Decision Processes (MDPs) to guide asset-management decision-making during advanced reactor operation. MDPs are a powerful tool for optimizing decision-making in complex environments and their application to advanced reactors can aid in planning maintenance and repair activities to minimize downtime and maximize generation. The described approach expands on previous work regarding the use of MDPs for operational decision-making through the direct incorporation of real-time plant information. The integral MDP analysis includes information from online component diagnostic tools and the plant’s real-time generation risk assessment (GRA) and probabilistic risk assessment (PRA), which evaluate plant risk from both an economic and safety perspective. The result is an asset-management optimization framework that is based on real-time data regarding plant component status and the current best-estimate of plant risk. The paper presents an overview of the theoretical framework to incorporate the different information pathways into an integral MDP analysis, along with example analyses.

Grabaskas, David↗

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗

Idaho National Laboratory Integrated Multisite SSHAC Level 3: Probabilistic Volcanic Hazards Assessment

The Idaho National Laboratory (INL) resides on the eastern Snake River Plain (ESRP), part of the Snake River Plain (SRP) with a complex origin and geologic history of volcanism. Much of the Quaternary (last 2.58 million years) volcanism within 400 km of INL is genetically associated with a major thermal anomaly referred to as the Yellowstone hotspot, which is currently located more than 180 km northeast of INL. Near INL, local volcanic sources include silicic domes near its southern border, and numerous dike-fed basaltic vents of the ESRP, some of which are near or within the INL boundaries. Quantitative probabilistic assessments of screened-in volcanic hazardous phenomena for nine different facility complexes at the INL are presented for a Senior Seismic Hazard Analysis Committee (SSHAC) Level 3 (SL3) study. The comprehensive, integrated multisite SSHAC study consists of a single regional Probabilistic Volcanic Hazards Assessment (PVHA) that pertains to all nine INL facility complexes, with site-specific information developed at each respective area of interest (AOI), referred to as the "INL facility AOI" (Figure ES-1). Hazard products are generated for specified INL facility AOIs for use by multiple stakeholders from different agencies in risk-informed decision-making regarding site selection, operations, and design of nuclear facilities at INL, consistent with U.S. Department of Energy (DOE) and U.S. Nuclear Regulatory Commission (NRC) regulatory guidance. The study also serves as the basis for future periodic safety assessments required for existing DOE facilities, such as 10-year evaluations of natural-phenomena hazards. Elements of the INL PVHA including initial characterization, screening, quantitative assessments of eruption and hazard potential, and consideration of facility needs are conducted using the three phases of the SSHAC process: evaluation, integration, and documentation. As per regulatory guidance, the SSHAC framework provided the necessary processes and procedures for the PVHA Technical Integration (TI) team, at three workshops, five formal working meetings and many TI team remote meetings, to conduct initial characterization, screen the volcanic hazards, create PVHA model inputs, exercise those models in the PVHA, consider facility-specific volcanic hazard needs, and perform final hazard calculations. The Participatory Peer Review Panel (PPRP) provided independent oversight and performed process and technical reviews of the PVHA throughout its duration. The study included an extensive New Data Collection and Analyses (NDCA) program developed by the PVHA TI team to reduce uncertainties in hazard-significant elements in the PVHA model. NDCA activities generated 20 reports providing important contributory datasets and results to the project database for characterizing the ESRP. For example, a report compiling the dimensions of ESRP shield volcanoes and lava fields was used to construct volcanic footprints (areas of impact), was compared with data from INL subsurface cores, and was used to validate the results of lava-flow inundation modeling on the contemporary terrain. Another example is the acquisition of aeromagnetic data over INL and its surrounding area, with maps of buried magmatic features (e.g., subsurface volcanoes and swarms of feeder dikes) that informed the PVHA conceptual model of volcanism. The SSHAC evaluation process was used to conduct all elements of the PVHA including initial characterization and screening. Existing data and NDCA activities provided the foundation to develop the tectonomagmatic conceptual model of volcanism for the region of geographical interest in the SRP and Yellowstone hotspot volcanic system, and for considering volcanoes in the western US. Considering Quaternary volcanic sources active during this period, the screening approach identified and evaluated magma compositions, types of eruptive and intrusive phenomena, types of hazardous phenomena, and proximity of sources to INL. The PVHA TI team evaluated 18 types of magmatic sources in terms of 20 potentially hazardous phenomena, resulting in 360 screening decisions. The screening process resulted in 140 screened-in hazardous volcanic phenomena for Quaternary volcanic sources 1) proximal to INL facility complexes in the ESRP (64 basaltic and 54 silicic), 2) regional sources associated with the Yellowstone caldera system and Blackfoot Reservoir volcanic field (7), and 3) more distal sources from thirteen Cascade volcanoes and two volcanoes at Long Valley caldera (CA).

58 GEOSCIENCES↗

Templates for Risk Informed Assurance with Curvature Embeddings (TRACE)

We investigate recovery of geometric structure from networks embedded in manifolds with spatially varying curvature, extending the constant-curvature framework of Lubold et al. (2023). Our work supports cascade risk assessment in critical infrastructure through the Templates for Risk-informed Assurance with Curvature Embeddings (TRACE) framework. Simulations on a bi-modal Gaussian surface show that constant-curvature methods yield weighted averages shaped by clique patterns, while hierarchical clustering identifies distinct regimes. Localized estimation, however, reveals boundary contamination in transitional regions. To address heterogeneity, we develop distance metrics for graphs with edge and node features, proving their metric validity, and validate them via deterministic graph generation from canonical tilings. We further propose a diffusion-based anomaly detection approach that treats networks as glued manifolds, using curvature discontinuities to detect structural anomalies. Employing the carré-du-champ operator and scalar curvature, we achieve robust anomaly discrimination, demonstrated on the Singapore Water Treatment (SWaT) dataset with joint network-traffic and sensor features. Integration with TRACE reveals how curvature shapes cascade dynamics: positive curvature impedes, while negative curvature accelerates propagation. This geometric perspective provides interpretable risk metrics and visualization tools for critical infrastructure managers. While full validation remains ongoing, our contributions establish a rigorous foundation for geometric analysis of network resilience and cascade vulnerability.

97 MATHEMATICS AND COMPUTING↗

Radiological Releases from Novel Fuel Forms in Advanced Reactors During Severe Accidents for Consequence Analyses

Various advanced reactor developers are exploring the potential for reductions in the size of physical security forces and emergency planning zones. These reductions are based on robust fuel forms and inherently safe reactor designs. However, such reductions in physical protection measures could increase the risk of sabotage. To assess the possibility of reducing these measures, sabotage-induced radiological consequence analyses were carried out. These analyses considered accident scenarios that were beyond design basis accidents and overly conservative (Shah, 2025a; Shah, 2025b; Shah and Hartanto, 2026), yielding very large release fractions. These fractions, which can be used to evaluate physical protection and emergency planning requirements, have been crudely determined and applied as demonstrations for a sodium-cooled fast reactor (SFR) (Shah and Hartanto, 2025a), a high-temperature gas-cooled reactor (HTGR) (Shah and Hartanto, 2025b), a heat pipe–cooled reactor (HPR) (Shah and Hartanto, 2025c), and a molten salt–cooled reactor (MSR) (Shah et al., 2026). A Sandia National Laboratories (SNL) team used MELCOR—a fully integrated severe accident analysis code—to demonstrate the code’s capability to analyze advanced (i.e., not light water–cooled) reactors (including a fluoride salt–cooled high-temperature reactor [FHR]) and calculate radiological releases to the environment during severe accidents (Wagner et al., 2022a, 2022b, 2022c, 2023a, and 2023b). Although the analyses were carried out to demonstrate MELCOR’s growing capability, the release source terms were estimated for advanced reactors, providing valuable insights into the accident progression and radiological releases. These findings from prior SNL studies, including estimated source terms and related sensitivity studies, were leveraged to derive source terms for postulated sabotage-induced accidents. Insights from these sensitivity studies informed the scaling of SNL’s estimated source terms for the defined accident scenarios. The derived release fractions for the severe accident scenarios for the respective reactor designs can be used to perform more nuanced dose consequence analyses to evaluate the reactors’ physical protection and emergency planning zone requirements. These analyses are in accordance with the risk-informed, performance-based approach proposed under 10 CFR Part 53. This study builds on the prior source term analyses and associated sensitivity studies by SNL to derive time-dependent and design-informed release fractions. Section 2 describes the diverse advanced reactor designs analyzed by the SNL team. Section 3 discusses the severe accident analyses, the release fractions calculated, and the limitations and assumptions of the demonstration project. Section 4 presents the release percentages derived for the hypothetical sabotage-induced severe accidents at the advanced reactors. Section 5 summarizes the study’s findings and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Important Human Actions for Advanced Reactors: Implications for Human Factors

As advanced reactor platforms continue to develop and gain traction in the energy sector there is a need for risk-informed, scalable regulations that match that progress. This is a core component of the U.S. Nuclear Regulatory Commission’s proposed Part 53 Rule Making; the Accelerating Deployment of Versatile, Advanced Nuclear for Clean Energy (ADVANCE) Act; and other efforts that seek to update nuclear power regulations. This paper covers one key aspect of that regulatory evolution: Important Human Actions (IHA). In this paper, we discuss how the understanding and definitions of IHAs have changed and what that means for human factors engagement through the process of developing these technologies. Instead of a narrow focus on control actions that led to an increase in core damage risk, the new focus is on IHAs is “wherever they occur.” What this means is that having a highly automated or passive safety system does not eliminate IHAs. Rather, it shifts the focus point to all the actions that enable these systems. Everything from maintenance, to design, to training can be considered an IHA and that dramatically shifts the efforts and level of engagement necessary for human factors to enable these technologies. We discuss the notions of risk-informed human factors that underpin these efforts, give several examples, and briefly describe the risk assessment methodologies that will be needed. In the past, IHAs were identified and then became a focus point of human factors engineering (HFE) activities to ensure a robust evaluation of the task was completed. The future is less clear. HFE for nuclear energy will need to evolve and become more integrated in technology development than ever before.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗