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DOE OSTI2024

Pressure Spike in The LBNF Absorber Core s Gun Drilled Cooling Channel from an Accident Beam Pulse

The LBNF Absorber consists of thirteen 6061-T6 aluminum core blocks. The core blocks are water cooled with de-ionized (DI) water which becomes radioactive during beam operations. The cooling water flows through gun-drilled channels in the core blocks. The cooling water is supplied by the LBNF Absorber Radioactive Water (RAW) cooling system which is designed as per ASME B31.3 Normal Fluid Service [1]. An uninhibited beam accident pulse striking the water channels was identified as a credible accident scenario. In this study, it is assumed that the beam pulse hits the Absorber directly without interacting with any of the other upstream beamline components. The beam parameters used for the LBNF beam are 120 GeV, 2.4 MW with a 1.2 s cycle time. The accident pulse lasts for 10 μs. The maximum energy is deposited in the 3rd aluminum core block. For the sake of simplicity, it is assumed that the accident pulse strikes the 1 in. ID water channel directly. The analysis here simulates the pressure rise in the water during and after the beam pulse and its effects on the aluminum piping components that deliver water to the core blocks. The weld strengths as determined by the Load and Resistance Factor Design (LRDF) and the Allowable Strength Design (ASD) are compared to the forces generated in the weld owing to the pressure spike. A transient structural analysis was used to determine the equivalent membrane, peak, and bending stresses and they were com-pared to allowable limits.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Pressure Spike in The LBNF Absorber Core s Gun Drilled Cooling Channel from an Accident Beam Pulse

he LBNF absorber consists of thirteen 6061-T6 aluminum core blocks. The core blocks are water cooled with de-ionized (DI) water which becomes radioactive during beam operations. The cooling water flows through gun-drilled channels in the core blocks. The cooling water is supplied by the LBNF absorber radioactive water (RAW) cooling system which is designed as per ASME B31.3 normal fluid service. An uninhibited beam accident pulse striking the water channels was identified as a credible accident scenario. In this study, it is assumed that the beam pulse hits the absorber directly without interacting with any of the other upstream beamline components. The beam parameters used for the LBNF beam are 120 GeV, 2.4 MW with a 1.2 s cycle time. The accident pulse lasts for 10 µs. The maximum energy is deposited in the 3rd aluminum core block. For the sake of simplicity, it is assumed that the accident pulse strikes the 1 in. ID water channel directly. The analysis here simulates the pressure rise in the water during and after the beam pulse and its effects on the aluminum piping components that deliver water to the core blocks. The weld strengths as determined by the Load and Resistance Factor Design (LRDF) and the Allowable Strength Design (ASD) are compared to the forces generated in the weld owing to the pressure spike. A transient structural analysis was used to determine the equivalent membrane, peak, and bending stresses and they were compared to allowable limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗

DOE OSTI2025

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↗

DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗

DOE OSTI2025

Tight Bound on the Neutron Star Radius with Quasiperiodic Oscillations in Short Gamma-Ray Bursts

Abstract Quasiperiodic oscillations (QPOs) have been recently discovered in the short gamma-ray bursts (GRBs) 910711 and 931101B. Their frequencies are consistent with those of the quasiradial and quadrupolar oscillations of binary neutron star (BNS) merger remnants, as obtained in numerical relativity simulations. These simulations reveal quasi-universal relations between the remnant oscillation frequencies and the tidal coupling constant of the binaries. Under the assumption that the observed QPOs are due to these postmerger oscillations, we use the frequency–tide relations in a Bayesian framework to infer the source redshift, as well as the chirp mass and the binary tidal deformability of the BNS progenitors for GRBs 910711 and 931101B. We further use this inference to estimate bounds on the mass–radius relation for neutron stars. By combining the estimates from the two GRBs, we find a 68% credible range R 1.4 = 12.4 8 − 0.40 + 0.41 km for the radius of a neutron star with mass M = 1.4 M ⊙ , which is one of the tightest bounds to date.

Guedes, Victor↗

DOE OSTI2025

Regional Oil and gas Aerial Methane Synthesis model (ROAMS) v2.0

The Regional Oil and gas Aerial Methane Synthesis model is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

DOE OSTI2025

Regional Oil and gas Aerial Methane Synthesis model (Analytica) (ROAMS Analytica) v1.5.2

The Regional Oil and gas Aerial Methane Synthesis model (Analytica) is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). This version is written in the Analytica programming language, and this version accompanies a correction in preparation for submission to Sherwin et al. 2024 (Nature). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

DOE OSTI2025

A Decadal Hybrid GCM Simulation Using Deep‐Learning‐Based Cloud and Convection Parameterization Generalized to a Warm Climate

A critical challenge for machine‐learning (ML) parameterization in global climate models (GCMs) is to achieve stable, accurate simulations under climates not seen during training. Previous studies have demonstrated promising offline performance and year‐long online stability in aquaplanet simulations but have encountered difficulties in real geography and under climate warming. Here we report that a GCM with real geography configuration using neural‐network‐based cloud and convection parameterization, trained exclusively with present‐day climate data, successfully performs a stable, decade‐long simulation of a warm climate with +4 K sea surface temperature (SST). The neural network (NN) is based on Han et al. (2023, https://doi.org/10.1029/2022ms003508 ) with additional inputs. The simulation captures the global precipitation distribution, surface temperatures, vertical atmospheric structures, and extreme precipitation very well, closely matching simulations from both the superparameterized CAM (SPCAM) and the conventional CAM5 in the warm climate without accuracy degradation compared to those in the baseline climate. Moreover, it produces a climate response to +4 K SST in atmospheric thermodynamic states and circulations similar to those from SPCAM and CAM5. Prognostic ablation tests on NN input variables show that the NN without convective memory as input suffers from numerical instability, and the NN without considering radiative variables and land fraction as input, or with reduced training samples produce less accurate results. To our knowledge, this is the first time an ML parameterization successfully achieves online extrapolation to a warm climate without using additional warm‐climate data for training. It demonstrates the potential of ML‐driven parameterizations for credible long‐term climate projections.

Atmosphere model↗

DOE OSTI2026

Community-Engaged Modeling of Urban Flood Adaptation Pathways

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Spangler, Ava [Pennsylvania State University] (ORC↗

DOE OSTI2026

Community-Informed Urban Flood Modeling for Impact Mitigation

Baltimore MD↗

DOE OSTI2026

Reviving sub-keV warm dark matter: a UVLF-based analysis

Thermal warm dark matter (WDM) particles with m WDM ≤ 1 keV are ruled out at more than 4σ by multiple observational probes, owing to the strong suppression of small-scale structure induced by early-time free-streaming. Recently, it was highlighted that a small admixture of ∼ 1% (f CDM ∼ 0.01) cold dark matter (CDM) endowed with a blue-tilted isocurvature spectrum could offset the WDM-induced suppression and relax the WDM mass bound by a factor of 𝒪(10). If viable, this “warm + cold-isocurvature” scenario would allow sub-keV WDM particles to constitute nearly the full dark matter abundance while potentially alleviating some small-scale tensions. In this work, we test this mechanism by constraining the WDM mass mWDM while marginalizing over CDM isocurvature parameters. We combine ultraviolet luminosity function measurements from the Hubble Space Telescope and James Webb Space Telescope over redshift 4 ≤ z ≤ 11 with CMB, BAO, and SNe data. For a pure WDM model, our joint analysis yields a lower bound m WDM > 1.8 keV (95% credible intervals). When CDM isocurvature is introduced at f CDM = 0.01, the limit relaxes to m WDM > 0.27 keV (95% credible intervals), reflecting a shallow degeneracy in which blue-tilted isocurvature fluctuations partially compensate for WDM suppression. These results provide new constraints on thermal WDM in the presence of CDM isocurvature fluctuations and quantify the extent to which such fluctuations can mask the small-scale signatures of light relics.

cosmological parameters from CMBR↗

DOE OSTI2025

Virtual Reality for Shoot/No-Shoot Decision Training in Law Enforcement: A Literature Review and Research Agenda

Virtual reality (VR) can materially improve “shoot / no-shoot” (SNS) training by giving officers realistic, repeatable practice making high-stakes decisions under pressure. Traditional tools—live-fire ranges and video simulators—build basics, but they cannot adapt to each officer in real time or fully mirror the complexity of the field. VR closes that gap by creating immersive scenarios that are safer, more flexible, easier to scale across units, and able to capture objective performance data. SNS decisions are not just about marksmanship; they rely on perception, judgment, memory, and the ability to hold fire when a threat is uncertain. Effective training therefore needs realism, decision complexity, and branching outcomes that reflect the true consequences of choices. These elements strengthen recognition of hostile intent while reducing false positives and building the self-control required in ambiguous situations. VR brings specific advantages: dynamic environments, full-body interaction, and the ability to measure performance with precision—enabling targeted feedback and better transfer of learning to the street. At the same time, responsible deployment must address scenario quality (credible environments and behaviors), lawful decision models, and user wellbeing (appropriate stress levels, comfort, and safety). Sandia’s VIPER Lab is positioned to lead this work. The team combines human-performance science, AI/ML, and VR/AR development with a deep equipment bench (e.g., omnidirectional treadmill, eye-tracking, haptics, multiple HMDs). This ecosystem supports building and validating next-generation SNS training that is immersive, measurable, and trustworthy. Bottom line: Investment in VR-enabled SNS training that blends evidence-based design with careful validation and legal safeguards is expected to pay off in safer, more consistent decision-making and improved community trust, delivered through training that is practical to deploy at scale.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Credible Criticality Safety Margin in the 30B Package with LEU+ UF 6 and Hypothetical Water Ingress

The commercial nuclear industry is pursuing advancements in fuel and reactor design that increase the uranium enrichment above 5 wt. % 235 U. These advancements will necessitate the ability to transport bulk quantities of UF 6 at increased enrichments. Currently, the 30B cylinder is the primary container used by the industry for UF 6 storage and transportation and has a long history of successful shipments. This container can support up to 2,277 kg of UF 6 at a maximum enrichment of 5 wt. % 235 U. Previous evaluations have assessed the potential impact of criticality safety for 30B transport at higher enrichments but assumed moderator intrusion would not require evaluation. Although current regulations allow for the exception of moderator intrusion for UF 6 packages through the design and quality control of the package content, this exception is limited to enrichments up to 5 wt. % 235 U. Thus, an investigation of moderator intrusion into a 30B cylinder should be performed. Moderator intrusion into a 30B cylinder is a unique condition for criticality safety evaluation in transportation because of the violent chemical reactions that occur between UF 6 and H 2 O. The resulting intrusion is strongly dependent on the breach size, breach location, breach interface solid/ullage of the UF 6 content, the UF 6 distribution (which is temperature dependent), and temperature/pressure conditions which are dynamic in accident conditions. Additionally, the complexity of the HF-UO 2 F 2 -H 2 O interface that occurs during the event can influence the potential solubility of uranium in the system, as well as influence the amount of UF 6 reaction with H 2 O. With the operating experience from Orano Federal Services LLC, the UF 6 chemical expertise from Oak Ridge National Laboratory (ORNL), and the criticality safety expertise from ORNL, this paper evaluates the neutronic conditions (i.e., k eff ) that apply the understood chemistry and experimental conditions that occur during moderator intrusion of a breached 30B cylinder under postulated accidents. This report examines the historical evaluations of UF 6 transport and expands these evaluations for the enrichments expected for nuclear industry advancement. These simulations primarily feature a homogeneous mixture of UF 6 and H 2 O as an infinite media system and as a sphere with water reflection given an impurity limit of 0.5 wt. % UF 6 . This report demonstrates that this H/U limit is valid up to 8 wt. % enrichment for both H 2 O and HF as the moderating mixture. The water-reflected homogeneous mixed spheres evaluated demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. Additionally, this report evaluates moderator ingress scenarios of a 30B cylinder. The 30B cylinder simulations vary the cylinder orientation, the mass of UF 6 in the system, the mass of H 2 O in the system, and how much H 2 O has reacted with UF 6 . The moderator ingress of a 30B cylinder was evaluated for the water-reflected homogeneous mixed spheres to demonstrate the amount of safety margin applied by restricting the 30B cylinder impurity limit to 0.5 wt. %. These simulations are standard practice and are independent of the UF 6 -H 2 O reaction. This work also explored more complex simulations that layer the H 2 O over the UF 6 , which incorporates the amount of reacted UF 6 as a separate layer and considers solubility limits of UO 2 F 2 in H 2 O as it is produced. This approach is intended to simulate the postulated event of a large hairline crack occurring on a submerged cylinder. Finally, this work considers the potential of H 2 O mixing into the UF 6 solid heterogeneously using a sponge-like model. The water ingress into the UF 6 is treated as random size spheres, and the reaction products form into a layer over the spheres.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗