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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Safety Review of the Hydrogen Components of a Reference Design of the Wind-H2-Green Steel/Ammonia Project

The Department of Energy Hydrogen Fuel Cell Technology Office and Wind Energy Technologies Office's Wind-H2-Green Steel/Ammonia project is an initiative to demonstrate the feasibility and efficacy of GW-scale integrated energy systems. The team designed reference facilities that utilize wind- and solar-produced hydrogen for industrial steel and ammonia production. This novel concept warranted review of safety codes and standards as they apply to the designs and the identification of codes and standards gaps. This report reviews hydrogen production and storage codes and standards using reference design specifications from a Minnesota steel plant. Requirements, recommendations, and exclusions for the system were identified. Observed gaps included non-specific salt cavern storage requirements, electrolyzer capacity beyond regulated ranges, and lack of requirements for iron reduction via hydrogen. This report will aide future project design efforts and may provide a basis for safety reviews in new designs for industrial facilities with hydrogen production integration.

08 HYDROGEN↗
DOE OSTI2024

Classifying photonic topology using the spectral localizer and numerical K -theory

Recently, the spectral localizer framework has emerged as an efficient approach for classifying topology in photonic systems featuring local nonlinearities and radiative environments. In nonlinear systems, this framework provides rigorous definitions for concepts such as topological solitons and topological dynamics, where a system’s occupation induces a local change in its topology due to nonlinearity. For systems embedded in radiative environments that do not possess a shared bulk spectral gap, this framework enables the identification of local topology and shows that local topological protection is preserved despite the lack of a common gap. However, as the spectral localizer framework is rooted in the mathematics of C*-algebras, and not vector bundles, understanding and using this framework requires developing intuition for a somewhat different set of underlying concepts than those that appear in traditional approaches for classifying material topology. In this tutorial, we introduce the spectral localizer framework from a ground-up perspective and provide physically motivated arguments for understanding its local topological markers and associated local measure of topological protection. In doing so, we provide numerous examples of the framework’s application to a variety of topological classes, including crystalline and higher-order topology. We then show how Maxwell’s equations can be reformulated to be compatible with the spectral localizer framework, including the possibility of radiative boundary conditions. To aid in this introduction, we also provide a physics-oriented introduction to multi-operator pseudospectral methods and numerical K-theory, two mathematical concepts that form the foundation for the spectral localizer framework. Finally, we provide some mathematically oriented comments on the C*-algebraic origins of this framework, including a discussion of real C*-algebras and graded C*-algebras that are necessary for incorporating physical symmetries. Looking forward, we hope that this tutorial will serve as an approachable starting point for learning the foundations of the spectral localizer framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

SRF cavity instability detection with machine learning at CEBAF

During the operation of the Continuous Electron Beam Accelerator Facility (CEBAF), one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detectfast transient instabilities during these trip events. These challenges make the identification of an unstable cavity out of the hundreds installed at CEBAF a difficult and time-consuming task. To tackle these issues, a fast data acquisition system (DAQ) for the legacy SRF cavities has been developed, which records the sample at 5 kHz. An unsupervised learning framework has been developed to identify anomalous SRF cavity behavior. We will discuss the present status of the DAQ system and our framework, along with recent successes in detecting anomalous cavity behavior. Overall, our method offers a practical solution for identifying unstable SRF cavities, contributing to increased beam availability and machine reliability.

Accelerator Physics↗
DOE OSTI2025

BioPac

BioPAC is the Biological and other Particles in Aerosols Classifier. It is a software to assist in the accurate measurement and identification of primary biological aerosol particles, which play a pivotal role in mediating the reciprocal relationships between biological systems and atmospheric conditions.

Rahman, Ashfiqur [Pacific Northwest National Labor↗
DOE OSTI2024

Reevaluation of XPS Pt 4f peak fitting: Ti 3s plasmon peak interference and Pt metallic peak asymmetry in Pt@TiO2 system

The structural, electronic, and electrochemical properties of noble metals supported on transition metal oxides, such as Pt nanoparticles (NPs) supported on TiO2 (Pt@TiO2), have been extensively studied for their relevance to energy technologies, including photocatalysis, electrocatalysis, and electrochemical energy conversion. As the need to lower the amount of Pt and other noble metals used in energy conversion systems becomes urgent, it is essential to accurately quantify the loading of these metals and electronic density redistribution between them and their supports. X-ray photoelectron spectroscopy (XPS) is widely used for the identification and quantification of chemical species. In particular, fitting of the Pt 4f spectra for Pt@TiO2 is frequently performed to determine the chemical environment and oxidation state of Pt, which strongly affect the physical behavior and catalytic performance of this system. Here, we show that neglecting contributions due to the Pt surroundings and the asymmetry of the Pt metal peak in the line shape fitting can lead to severe mischaracterization of the oxidation state of Pt. We quantify the effects of background contributions that stem from the TiO2 support and discuss how factoring in the strong asymmetry of Pt 4f doublets, which stems from the shake-up type processes, affects the interpretation of Pt 4f XPS line shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Monitoring Methods for Early Detection of Inadvertent Fission Product Release at the Advanced Test Reactor

Isotope effluent data obtained during three instances of experiment failures at the Advanced Test Reactor (ATR) are analyzed to provide an overview of the methods used to detect initial signs of unintended fission product release. The data is contextualized with the operational experience, including means of identification and subsequent mitigation strategies, gained during these events. General trends as well as variations in isotopic behavior between the three failures are explored. Background on the Real Time Monitor, a High Purity Germanium detector, and other fission product monitoring systems utilized at the Advanced Test Reactor is also provided. The presented analysis was used to establish administrative action levels which are currently utilized by ATR for early detection of experiment fission product release. Early identification provides time to make programmatic decisions before approaching safety and environmental limits.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Low-Cost Identification and Monitoring of Diverse MELs in Residential and Commercial Buildings with PowerBlade (Final Technical Report)

This report describes our progress in developing a scalable wireless metering system that integrates plug-load energy meters that measure real, reactive, and apparent power along with load monitoring based on extracting high-fidelity electrical waveform features collected at every load to capture power profiles and automatically identify and categorize MELs, and make this technology available to the research, commercial, and government sectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Responses of summer mesoscale convective systems to irrigation over the North China Plain based on convection-permitting model simulations

Extensive irrigation activities in the North China Plain (NCP) significantly influence regional weather and climate. However, previous studies focusing on the NCP were primarily based on coarse-resolution models, which are unable to explicitly resolve convection systems, causing large uncertainty in precipitation simulations. In this study, a convection-permitting model coupled with a dynamic irrigation scheme is utilized to investigate the impacts of irrigation on summertime mesoscale convective systems (MCSs) over the NCP. Sensitivity experiments with irrigation off and on are conducted for 5 summers and an MCS identification and tracking algorithm is applied to both satellite observations and model simulations. We find that incorporating irrigation in the model increases MCS precipitation, which agrees more with observations. The probability distributions of MCS lifetime, area, propagation speed, and intensity are all better simulated with irrigation. Irrigation increases the occurrence frequency of MCSs throughout the entire day. The nighttime increase is partly because of more frequent local initiation of MCS developed from isolated deep convection, while the daytime increase is mainly attributed to the changes in MCSs initiating elsewhere and then propagating to the NCP. On average, irrigation induces additional moisture that is more thermodynamically favorable for precipitation, but this effect is partially offset by the weakened ascending air motion primarily caused by irrigation surface cooling. Compared to weak MCS precipitation events, strong MCS precipitation events experience greater enhancement in precipitation intensity when including irrigation because the offset effect from the change in large-scale ascending air motion is insignificant. In addition, irrigation makes the variation of MCS precipitation intensity more correlated with the variation in ascending motion but less correlated with that in atmospheric moisture. Our results suggest the pronounced impacts of irrigation on MCSs over the NCP which should be included in numerical models to improve regional precipitation simulation and prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Novel Authentication Management for the Data Security of Smart Grid

Bidirectional wireless communication is employed in various smart grid components such as smart meters and control and monitoring applications where security is vital. The Trusted Third Party (TTP) and wireless connectivity between the smart meter and the third party in the key management-based encryption techniques for the smart grid are expected to be totally trustworthy and dependable. In a wired/wireless medium, however, a man-in-the-middle may seek to disrupt, monitor and manipulate the network, or simply execute a replay attack, revealing its vulnerability. Recognizing this, this study presents a novel authentication management (model) comprised of two layer security schema. The first layer implements an efficient novel encryption method for secure data exchange between meters and control center with the help of two partially trusted simple servers (constitutes the TTP). In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. It detects abnormal packets from suspicious sources. To implement this node-to-node authentication, One class support vector machine algorithm is proposed which takes advantages of the location information as well as the data transmission history (node identification, packet size, and data transmission frequency). This schema secures data communication, and imposes a comprehensive privacy throughout the system without considerably extending the complexity of the conventional key management scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Oak Ridge National Laboratory Evaluation of Stream-Trained Models in Practice

The goal of this integration is to replicate the results from the original paper Autonomous Utility Pole Identification on different camera hardware and integrate the model into a live video stream provided by the unmanned aerial system (UAS) itself while in operation. This involves retraining the original model and validating its efficacy on multiple camera modules to select the most effective device for installation. Moreover, this integration requires writing software to handle the reception of a real-time streaming protocol stream from the UAS and run each frame through the model while allowing a user to monitor the camera feed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Calorimeter calibration and performance for the Mu2e experiment

The Mu2e experiment at Fermilab will search for the charged lepton flavour-violating conversion of a muon into an electron, aiming to reach a sensitivity of $R_{\mu e} \sim 10^{-17}$, an improvement of four orders of magnitude over previous limits. To reach this goal, Mu2e will use an intense pulsed muon beam and a detector system composed of a high-precision straw tube tracker and a pure CsI crystal calorimeter. The calorimeter plays a crucial role in the experiment, as it provides particle identification capabilities that are necessary for background suppression. To perform its tasks, the detector must achieve an energy resolution better than 10% and a timing resolution below 500 ps for 100 MeV electrons. Cosmic-ray data and laser pulses are used to equalize the response of each channel, to calibrate the energy scale and to monitor the system's stability over time. This poster reports on the calibration and analysis techniques developed to ensure that the calorimeter requirements for precise energy and time measurements are met. Results for the calorimeter performance obtained during the commissioning phase will be discussed, and an overview of the current status in the Mu2e experimental hall will be presented.

Salamino, Sabrina [Frascati]↗
DOE OSTI2024

Accurate data-driven surrogates of dynamical systems for forward propagation of uncertainty

Stochastic collocation (SC) is a well-known non-intrusive method of constructing surrogate models for uncertainty quantification. In dynamical systems, SC is especially suited for full-field uncertainty propagation that characterizes the distributions of the high-dimensional solution fields of a model with stochastic input parameters. However, due to the highly nonlinear nature of the parameter-to-solution map in even the simplest dynamical systems, the constructed SC surrogates are often inaccurate. Here, this work presents an alternative approach, where we apply the SC approximation over the dynamics of the model, rather than the solution. By combining the data-driven sparse identification of nonlinear dynamics framework with SC, we construct dynamics surrogates and integrate them through time to construct the surrogate solutions. We demonstrate that the SC-over-dynamics framework leads to smaller errors, both in terms of the approximated system trajectories as well as the model state distributions, when compared against full-field SC applied to the solutions directly. We present numerical evidence of this improvement using three test problems: a chaotic ordinary differential equation, and two partial differential equations from solid mechanics.

42 ENGINEERING↗
DOE OSTI2026

Evaluation of Compton suppression for enhancing trace element identification in neutron activation analysis of reference materials

Neutron activation analysis (NAA) is a powerful technique for identifying and quantifying trace elements in materials. However, challenges such as high dead times, spectral interferences, and high Compton continuum often arise. This study employs a Compton suppression system (CSS) to enhance NAA sensitivity by reducing the Compton continuum, thereby improving the peak-to-Compton ratio. National Institute of Standards and Technology certified reference materials 1632d, 1633c, and Canadian National Research Council TORT-1 were irradiated in a thermal and epithermal neutron flux under various irradiation, decay and counting times and analyzed using high-resolution gamma-ray spectroscopy with and without Compton suppression. The reduction factor was calculated to evaluate the effectiveness of the CSS, demonstrating significant background reduction and improved detection limits for trace elements. Additional experiments with a 137Cs point source demonstrated the impact of detector-source geometry on system performance, showing a decrease in the reduction factor as the source was moved further from the NaI detector. An optimum distance between the source and HPGe detector was observed, yielding the highest peak-to-Compton ratio. The results highlight the CSS's ability to minimize spectral interference and enhance elemental identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Higher-order LaSDI: Reduced order modeling with multiple time derivatives

Solving complex partial differential equations (PDEs) is essential across scientific disciplines but often requires numerical models that can be prohibitively expensive in time-sensitive applications. Reduced-order models (ROMs) address this challenge by exploiting low-dimensional structure to create fast approximations. The Latent Space Dynamics Identification (LaSDI) framework has demonstrated success in learning ROMs for parameterized PDE families, but remains limited to first-order systems. Here, in this paper, we propose Higher-Order LaSDI (HLaSDI), which extends the LaSDI framework to PDEs with arbitrary order of time derivatives. This generalization significantly expands the applicability of LaSDI-based methods to systems previously outside their scope, including hyperbolic PDEs. We demonstrate HLaSDI’s accuracy and efficiency on several linear and nonlinear benchmark problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Cascading economic losses from port disruptions under capacity constrained multimodal freight networks

This study quantifies how throughput disruptions at major seaports cascade through capacity-constrained multimodal freight networks and interregional production systems. We couple an agent-based model (ABM) multimodal freight simulation that resolves rerouting, terminal queueing, and inventory drawdown under binding modal and facility capacities with a multiregional output loss input-output (MRIIM) model that propagates realized delivery shortfalls across regions and sectors. The framework is demonstrated for the Port of Los Angeles using Freight Analysis Framework flows and Bureau of Economic Analysis input-output accounts and is evaluated over a 52-week horizon under deterministic sector targeted shocks and stochastic disruption realizations with uncertain severity and duration. Results indicate nonlinear amplification: realized national losses concentrate in manufacturing and transportation/warehousing even when exogenous port shocks are dispersed, suggesting that congestion spillback and limited short-run substitution can dominate the initial shock allocation. We further evaluate a tabular reinforcement-learning (Q-learning) intervention layer that selects among a small set of implementable system level levers (truck-to-rail and truck-to-barge shift settings) without overriding shipper routing, finding that such interventions reduce total losses for moderate disruptions but yield diminishing returns once substitute modes approach capacity. By linking operational freight behavior to system wide impacts under uncertainty, the proposed ABM-MRIIM pipeline provides a reusable workflow for port disruption stress testing, identification of structurally critical sectors/corridors, and evaluation of resilience interventions under realistic capacity limits.

42 ENGINEERING↗
DOE OSTI2024

Photocathode characterisation for robust PICOSEC Micromegas precise-timing detectors

The PICOSEC Micromegas detector is a precise-timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and a Micromegas amplifying structure, targeting a time resolution of tens of picoseconds for minimum ionising particles. Initial single-pad prototypes have demonstrated a time resolution below σ = 25 ps, prompting ongoing developments to adapt the concept for High Energy Physics applications, where sub-nanosecond precision is essential for event separation, improved track reconstruction and particle identification. The achieved performance is being transferred to robust multi-channel detector modules suitable for large-area detection systems requiring excellent timing precision. To enhance the robustness and stability of the PICOSEC Micromegas detector, research on robust carbon-based photocathodes, including Diamond-Like Carbon (DLC) and Boron Carbide (B 4 C), is pursued. Results from prototypes equipped with DLC and B 4 C photocathodes exhibited a time resolution of σ ≈ 32 ps and σ ≈ 34.5 ps, respectively. Efforts dedicated to improve detector robustness and stability enhance the feasibility of the PICOSEC Micromegas concept for large experiments, ensuring sustained performance while maintaining excellent timing precision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Offshore Wind Farm Turbine and Energy Storage Optimization

Abstract This paper evaluates the technical and economic feasibility of repurposing decommissioned offshore oil and gas platforms as electrical substations for offshore wind projects in the U.S. Gulf of America, a region characterized by relatively low and highly variable wind speeds, extensive legacy offshore infrastructure, and exposure to merchant electricity markets. A unified techno-economic framework is developed using the Repurposing Offshore Infrastructure for Continued Energy (ROICE) Economic Model (REM) to integrate Gulfspecific wind resource assessment, commercial wind turbine performance, offshore infrastructure cost modeling, and wholesale electricity market exposure. Gulf wind speed data are vertically extrapolated to turbine hub height and combined with manufacturer power curves to compute annual energy production and capacity factors across a broad portfolio of commercial turbines, enabling identification of turbine designs best suited for low-wind offshore environments. Hourly electricity price data from the Midcontinent Independent System Operator (MISO) day-ahead market are incorporated to characterize revenue potential, price volatility, and the temporal alignment between wind generation and market conditions. In addition, a conceptual framework for offshore battery energy storage system (BESS) integration is developed to support future investigation of market-responsive energy shifting at repurposed platforms. Results from the turbine evaluation demonstrate that machines with lower cut-in wind speeds and earlier ‘rated-power’ characteristics significantly outperform larger, industry-standard offshore turbines for the same net power under Gulf wind conditions, underscoring the need for region-specific technology selection. Market analysis further reveals substantial price variability and limited intrinsic alignment between wind production and high-price periods, motivating consideration of operational flexibility mechanisms. While storage optimization is not implemented in this study, the REM framework establishes a transparent and replicable foundation for co-evaluating turbine selection, infrastructure constraints, and market exposure, providing a practical pathway for assessing the potential role of repurposed offshore platforms in enabling economically viable offshore wind development in the Gulf of America.

02 PETROLEUM↗