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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Modernizing GlideinWMS Factory Monitoring with Prometheus & Grafana

Large-scale scientific experiments like CMS and DUNE rely on the distributed workload management system GlideinWMS to efficiently utilize computing resources across heterogeneous computing environments. GlideinWMS currently records Factory statistics using Round Robin Databases (RRDBs), XML, and JSON files, and these statistics are displayed via custom monitoring Web pages, thereby limiting integration with modern observability platforms. This project investigates the use of Prometheus-based instrumentation to expose Factory metrics using OpenTelemetry principles. Factory statistics related to Glidein submission and job execution are exported as Prometheus metrics through the Prometheus Python Client Library and are served via an HTTP metrics endpoint. The collected metrics are inspected using the Prometheus web-based interface and are visualized through Grafana dashboards within the Landscape monitoring infrastructure at Fermilab. This project significantly streamlines the integration of modern monitoring technologies into GlideinWMS and establishes a framework for extending observability across additional system components.

Appiah, Gideon [Grambling State U.]

Frontier Job-Centric Telemetry Dataset

Comprehensive analysis of high-performance computing (HPC) systems requires linking workload execution to system behavior. This kind of analysis is vital for diagnosing performance issues, managing capacity, detecting anomalous workloads, and understanding how applications interact with system hardware. This job-centric telemetry dataset unifies scheduler job records with node-level measurements, enabling direct association between workloads and their corresponding power, thermal, and performance characteristics. It contains sanitized, scheduler related metadata for 152,400 individual jobs that ran on the Frontier supercomputer and ended on selected days throughout 2024 and 2025, a subpopulation of ~6.8% of the total number of allocated jobs with non-zero run time on the system over that same period. Each is linked with files that contain telemetry time series records of the power utilization and temperature behavior of its allocated nodes and their processors during the run time of the job. Where available, a portion of the job files also contain network performance time series. Jobs are sampled from select days that reflect normal levels of user activity and possess job size distributions with large numbers of leadership class jobs (>20% of Frontier nodes). Jobs in this dataset attempt to best represent successful user workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

pdas-experiments

SAND2025-04589O pdas-experiments automates computational experiments of fluid flow simulations. It uses the pressio-demoapps-schwarz package as a basis to break down complex simulations into smaller, manageable parts. This application is an extension of the Sandia Pressio software which uses domain decomposition to work with complex simulations more efficiently. Users can test different simulation setups, while keeping a detailed record of their experiments so they can be reproduced later. The software includes a C++ program that runs individual experiments based on user-defined settings in a YAML file, as well as a Python script that can manage multiple simulations at once. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tezaur, Irina [Sandia National Lab. (SNL-CA), Live

Compliance of NNSS Activities with P322-4 Issues Management and NNSSWAC Requirements

The Institutional Quality and Performance Assurance Division's Quality Support Services Group conducted a surveillance of the compliance of Waste Management Program activities to Issues Management/Corrective Action requirements communicated in P322-4 and the Nevada National Security Site Waste Acceptance criteria (NNSSWAC). All corrective actions reviewed and records examined were found to be compliant with appropriate and relevant procedures. There were no Findings or Opportunities for Improvement noted.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Electrical Load Forecasting Over Multihop Smart Metering Networks With Federated Learning

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) record household energy data. Traditional machine learning (ML) methods are often employed for load forecasting, but require data sharing, which raises data privacy concerns. Federated learning (FL) can address this issue by running distributed ML models at local SMs without data exchange. However, current FL-based approaches struggle to achieve efficient load forecasting due to imbalanced data distribution across heterogeneous SMs. Here, this article presents a novel personalized FL (PFL) method for high-quality load forecasting in metering networks. A meta-learning-based strategy is developed to address data heterogeneity at local SMs in the collaborative training of local load forecasting models. Moreover, to minimize the load forecasting delays in our PFL model, we study a new latency optimization problem based on optimal resource allocation at SMs. A theoretical convergence analysis is also conducted to provide insights into FL design for federated load forecasting. Extensive simulations from real-world datasets show that our method outperforms existing approaches regarding better load forecasting and reduced operational latency costs.

Rahman, Ratun [Univ. of Alabama, Huntsville, AL (U

Underground Test Area (UGTA) Sampling Plan for Corrective Action Units 101 and 102: Central and Western Pahute Mesa, Nevada National Security Site, Nevada, Revision 2

The purpose of this groundwater sampling plan (referred to herein as “the Plan”) is to describe the approach for collecting and analyzing groundwater samples to meet the objectives of the U.S. Department of Energy (DOE), Environmental Management (EM) Nevada Program’s Underground Test Area (UGTA) Activity. The Plan is focused on the Central and Western Pahute Mesa corrective action units (CAUs 101 and 102), which are currently in the Corrective Action Decision Document (CADD)/Corrective Action Plan (CAP) stage of the Federal Facility Agreement and Consent Order (FFACO) UGTA Strategy. The remaining UGTA CAUs are in the final stage of the UGTA strategy (Closure Report [CR] stage), and monitoring requirements for these CAUs are described in the Federal Facility Agreement and Consent Order Nevada National Security Site Use Restriction Management Plan (DOE/EMNV, 2024a). The Plan supersedes the Nevada National Security Site Integrated Groundwater Sampling Plan and its ensuing Record of Technical Change (ROTC) (DOE/EMNV, 2019b).

54 ENVIRONMENTAL SCIENCES

Assessment of Bird Strike Likelihood to Refine Bird Strike Risk Models

In its most basic form, bird strike risk is comprised of a frequency component that reflects the likelihood of a collision and a severity component that reflects the cost (monetary or otherwise) of the incident. The bird strike risk model currently used by United State Department of Agriculture (USDA) Wildlife Services to evaluate the risk posed by individual bird species at airports and establish priorities for management was developed in 2018. The model uses airport-specific data on the number of reported strikes for a species recorded in the Federal Aviation Administration (FAA)’s National Wildlife Strike Database as a measure of frequency and the species’ relative hazard score as a measure of severity. The model was tested against independent data, found to perform well overall, and is being implemented widely across the United States. However, the model has limitations, including that species known to pose risk to aircraft locally, but not present in the strike record database, are not reflected as a major component of risk. Standard bird survey methodology commonly used at airports (e.g. point counts or transects) potentially can be used to complement wildlife strike records to calculate frequency or relative abundance of species. However, these methods generally focus on airport-wide population estimation and often ignore vital information that contributes to the true likelihood of a strike, such as use of runway protection zones and other critical areas, and spatial and temporal overlap with departing or approaching aircraft. As such, a more detailed understanding of space use by birds across landcovers and population fluctuations across the year is needed to accurately estimate the likelihood of bird strikes at airports. In this manuscript, we will review the extant risk model, including a discussion on its limitations. We then discuss approaches for refining our understanding of strike likelihood and briefly touch on needs for estimating probability of strike severity (cost).

bird strike, aircraft collision, damage by wildlif

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment.

Parazoo, Nicholas C. [California Institute of Tech

Leveraging Radiofrequency Identification Success Beyond Hazardous Material Inventory Management at a National Laboratory

Effective inventory management can be overshadowed by conflicting priorities in organizational procedures, particularly in research-focused institutions such as national laboratories that handle expensive, delicate, and hazardous materials. Here, this study investigated the potential of radiofrequency identification (RFID) technology, currently used for hazardous chemical inventory, in applications with higher metal interference and absorption, specifically pressure release device (PRD) compliance and nuclear container management, at Lawrence Livermore National Laboratory (LLNL). This study was done to document best practices to enhance inventory identification speeds for inventory reconciliation and inventory recall and to explore optimal configurations for RFID implementation compared to traditional manual methods of equipment management. Tests were conducted to determine the ideal RFID tag orientation (read at angles of 0°, 90°, and 270°), various container layouts (linear, separated, curved, operational), and ID methods such as manual, barcode, and RFID performing three trials per method per orientation. Results indicated that 0° was the optimal read angle for minimizing metallic interference, and the operational and curved arrangements significantly outperformed the linear and separated configurations in read speed. 3D printed mounts were developed and tested, increasing the read range of the RFID reader by up to 235% in cases of high metallic interference. The RFID technology demonstrated an average speed increase of 65% over a simplified manual identification, which supports the conclusion that RFID is a more efficient method for large hazardous inventory management and equipment reconciliation. Additionally, capturing meta-data, such as location and date, can be used to query for inventory recall and automated updating of record information.

42 ENGINEERING

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES

Mitigation for the demolition of building 25-3124,equipment testing laboratory, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-3124 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-3124 (State Historic Preservation Office [SHPO] Resource # B19009) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19009

Kivalina Biomass Reactor

This report summarizes work performed under DOE Award DE-EE00010149 to support the reliable operation of a community-scale biochar reactor system in Kivalina, Alaska. The project focused on improving sanitation and waste management in a remote community by assessing the installed system, identifying spare parts, defining key performance indicators (KPIs), preparing operator and maintenance manuals, and developing mobile reporting tools for operational data and KPI tracking. The team also produced training materials and recorded videos to support operator onboarding and continuity. The project demonstrated progress in system readiness, documentation, and digital reporting, while also identifying challenges common to remote deployments, including travel constraints, upstream system failures, and local resource limitations. This work provides a practical framework for improving the operation, monitoring, and future replication of biomass reactor systems in remote communities.

09 BIOMASS FUELS

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION

Greybox Thermal Parameter Identification of Electric Machine Stators

The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.

33 ADVANCED PROPULSION SYSTEMS

Mitigation for the demolition of the foundation of building 25-3113/3113a, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish the foundation of Building 25-3113/3113A and the adjoining test pad at Test Cell A in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). The foundation of Building 25-3113/3113A (State Historic Preservation Office [SHPO] Resource # B2443) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B2443

Mitigation for the demolition of building 25-3153, fire station, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-3153 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-3153 (State Historic Preservation Office [SHPO] Resource # B19004) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19004