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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Forced Oscillation Source Location of Bulk Power Systems Using Synchrosqueezing Wavelet Transform

Forced oscillation source location (FOSL) plays a significant role in mitigating forced oscillations (FOs), which threaten the power system stability. Here, this paper proposes a data-driven approach for FOSL in power systems using synchrosqueezing wavelet transform (SWT). The proposed approach conducts SWT on the measured system responses to obtain the SWT matrix. Then, the SWT-based dissipating energy flow (DEF) model in time-frequency domain and dissipating energy spectrum (DES) model in frequency domain are derived from the traditional DEF model. Further, the characteristics of SWT-based DEF and DES are revealed by referring to the traditional DEF, and the FOSL criteria of the SWT-based DEF and DES can be hereby obtained. Using the obtained FOSL criteria, the FO source can be located from the measured responses. The performance of the proposed FOSL method is evaluated by simulation data of the WECC 179-bus test system and field-measurement PMU data of the ISO New England. The results confirm the accuracy and efficiency of the proposed method in the FOSL.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

One-shot gas detection with transformer paired neural networks in Mako collected longwave infrared hyperspectral imagery

To date, careful data treatment workflows and statistical detectors are used to perform hyperspectral image (HSI) detection of any gas contained in a spectral library, which is often expanded with physics models to incorporate different spectral characteristics. In general, surrounding evidence or known gas-release parameters are used to provide confidence in or confirm detection capability, respectively. This makes quantifying detection performance difficult as it is nearly impossible to develop an absolute ground truth for gas target pixel presence in collected HSI. Consequently, developing and comparing new detection methods, especially machine learning (ML)-based methods, is susceptible to subjectivity in derived detection map quality. Here, in this work, we demonstrate the first use of transformer-based paired neural networks (PNNs) for one-shot gas target detection for multiple gases while providing quantitative classification and detection metrics for their use on labeled data. Terabytes of training data are generated from a database of long-wave infrared HSI obtained from historical Mako sensor campaigns over Los Angeles. By incorporating labels, singular signature representations, and a model development pipeline, we can tune and select PNNs to detect multiple gas targets that are not seen in training on a quantitative basis. We additionally assess our test set detections using interpretability techniques widely employed with ML-based predictors, but less common with detection methods relying on learned latent spaces.

Hyperspectral imaging↗
DOE OSTI2025

A Class of Sparse Johnson–Lindenstrauss Transforms and Analysis of their Extreme Singular Values

The Johnson–Lindenstrauss (JL) lemma is a powerful tool for dimensionality reduction in modern algorithm design. The lemma states that any set of high-dimensional points in a Euclidean space can be projected into lower dimensions while approximately preserving pairwise Euclidean distances. Random matrices satisfying this lemma are called JL transforms (JLTs). Inspired by existing $s$-hashing JLTs with exactly $s$ nonzero elements on each column, the present work introduces an ensemble of sparse matrices encompassing so-called $s$-hashing-like matrices whose expected number of nonzero elements on each column is $s$. The independence of the sub-Gaussian entries of these matrices and the knowledge of their exact distribution play an important role in their analyses. Using properties of independent sub-Gaussian random variables, these matrices are demonstrated to be JLTs, and their smallest nontrivial singular values and largest singular values are estimated nonasymptotically using a technique from geometric functional analysis. As the dimensions of the matrix grow to infinity, these singular values are proved to converge almost surely to fixed quantities (by using the universal Bai–Yin law) and in distribution to the Gaussian orthogonal ensemble Tracy–Widom law after proper rescalings. Understanding the behaviors of extreme singular values is important in general because they are often used to define a measure of stability of matrix algorithms. For example, JLTs were recently used in derivative-free optimization algorithmic frameworks to select random subspaces in which are constructed random models or poll directions to achieve scalability, and hence estimating their smallest singular value in particular helps determine the dimension of these subspaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Coupling Pulse Radiolysis with Nanosecond Time-Resolved Step-Scan Fourier Transform Infrared Spectroscopy: Broadband Mid-Infrared Detection of Radiolytically Generated Transients

We describe the first implementation of broadband, nanosecond time-resolved step-scan Fourier transform infrared (S 2 -FT-IR) spectroscopy at a pulse radiolysis facility. This new technique allows the rapid acquisition of nano- to microsecond time-resolved infrared (TRIR) spectra of transient species generated by pulse radiolysis of liquid samples at a pulsed electron accelerator. Wide regions of the mid-infrared can be probed in a single experiment, which often takes < 20–30 min to complete. It is therefore a powerful method for rapidly locating the IR absorptions of short-lived, radiation-induced species in solution, and for directly monitoring their subsequent reactions. Time-resolved step-scan FT-IR detection for pulse radiolysis thus complements our existing narrowband quantum cascade laser-based pulse radiolysis-TRIR detection system, which is more suitable for acquiring single-shot kinetics and narrowband TRIR spectra on small-volume samples and in strongly absorbing solvents, such as water. We have demonstrated the application of time-resolved step-scan FT-IR spectroscopy to pulse radiolysis by probing the metal carbonyl and organic carbonyl vibrations of the one-electron-reduced forms of two Re-based CO 2 reduction catalysts in acetonitrile solution. Transient IR absorption bands with amplitudes on the order of 1 × 10 −3 are easily detected on the sub-microsecond timescale using electron pulses as short as 250 ns.

(S2-FT-IR)↗
DOE OSTI2020

General Bayesian Inference over the Stiefel Manifold via the Givens Transform

We introduce here an approach based on the Givens representation for posterior inference in statistical models with orthogonal matrix parameters, such as factor models and probabilistic principal component analysis (PPCA). We show how the Givens representation can be used to develop practical methods for transforming densities over the Stiefel manifold into densities over subsets of Euclidean space. We demonstrate how to deal with issues arising from the topology of the Stiefel manifold and how to inexpensively compute the change-of-measure terms. We introduce an auxiliary parameter approach that limits the impact of topological issues. We provide both analysis of our methods and numerical examples demonstrating the effectiveness of the approach. We also discuss how our Givens representation can be used to define general classes of distributions over the space of orthogonal matrices. We then give demonstrations on several examples showing how the Givens approach performs in practice in comparison with other methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High resolution characterization of soil dissolved organic matter with FTICR-MS (Fourier-transform ion cyclotron resonance mass spectrometry) from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.This package contains Fourier transform ion cyclotron resonance mass spectrometry (21 Tesla FTICR-MS) data measured in negative and positive ionization mode from water and methanol soil extracts. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) fticr_neg_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (2) fticr_neg_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (3) fticr_neg_metadata.csv: metadata for samples/measurements in negative ion mode, (4) fticr_pos_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (5) fticr_pos_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (6) fticr_pos_metadata.csv: metadata for samples/measurements in positive ion mode.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A scalable transformer model for real-time decision making in neutron scattering experiments

The U.S. Department of Energy's (DOE's) neutron research facilities at Oak Ridge National Laboratory (ORNL), including the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS), are a state-of-the-art neutron scattering facility that allows researchers to study the structure and dynamics of materials at the atomic scale. At the SNS, neutrons are measured using the time-of-flight (TOF) technique as they move through a neutron beamline to interact with a sample. Large volumes of neutron scattering data are collected and recorded in neutron event mode. Optimal productivity of the TOF instrument is limited due to the lack of real-time data analysis tools. The large amount of data generated by the experiments can be challenging to process and analyze in real time, particularly for experiments that require rapid feedback and adjustment of experimental parameters. The regular computer/workstation cannot keep up with the experiment speed to provide real-time feedback to adjust experimental parameters, so connecting the supercomputers available to the neutron facility is necessary to achieve real-time data analysis and experiment steering. To address this challenge, we exploit the Frontier supercomputer at Oak Ridge Leadership Computing Facility (OLCF) to train a scalable temporal fusion transformer model for real-time decision making of TOF neutron scattering experimentation. Here, in this paper, we present the results using Frontier to provide the processing power needed to rapidly process and analyze large volumes of single-crystal diffraction data collected at TOPAZ, a neutron time-of-flight Laue single-crystal diffractometer at the SNS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Energy Assets Transformation Web Mapping Application

This submission contains the link and geospatial materials used in the Energy Assets Transformation Web Mapping Application. The zip file contains 19 geospatial layers in a file geodatabase called EAT.gdb to be grouped in the following categories. 1. Industrial Assets: Coal Generation Units Retirements 2012-2040 (EIA); Examples of Repurposing Projects (32 projects in total); Abandoned Coal Mines (CORD, SkyTruth); Abandoned or Orphaned Wells (for ten states only). 2. Energy Transition Communities: 48C (e) Tax Credits - Designated Energy Communities (IRA); Index of Deep Disadvantage; Local Energy Action Program (LEAP); EJ Index for Proximity to Hazardous Waste (EPA). 3. Regional Landscape: State-Level Funding Programs (relevant to repurposing projects, for 2022 and 2023 only); Coal Flows from Mine to Plant 2021 (EIA), Variable Renewable Energy Shares (Wind and Solar, 2021, EIA). 4. Supporting Infrastructure: Railroads (HIFLD), Electric Power Transmission Lines (HIFLD), Major Highways (NHPN, DOT), Major Ports (National Atlas of the U.S.); Independent System Operators (HIFLD), NERC Regions and Subregions (HIFLD).

abandoned coal mines↗
DOE OSTI2023

High-Efficiency, Medium-Voltage-Input, Solid-State-Transformer-Based 400-kW/1000V/400A Extreme Fast Charger for Electric Vehicles

Range anxiety and long battery charging time continue to be critical challenges to mass adaptation of EVs. A major identified gap to wider adoption of BEVs is the ability and availability to refuel quickly or to fast charge. Studies have shown that in areas where drivers have access to 50-kW or 120-kW fast charge stations, annual electric vehicle (EV) miles traveled (i.e., eVMT) increased by over 25%, even in cases where fast charging was used for 1% to 5% of total charging events. Charge stations of higher power not only alleviate the “range anxiety” and reduce the driver’s waiting time, but also requires less investment. Michigan Energy Office completed a study in early 2019 titled “Electric Vehicle Charger Placement Optimization in Michigan: Phase I – Highways”. This study finds a system with 150kW chargers, though more expensive individually, actually has lower total system cost when compared to a 50kW charging system when serving the same battery size EV. To be truly competitive to the ICEV refueling experience, even higher power stations are necessary. However, high power charge stations would create large power draws from the grid. If this occurs during peak demand periods, grid capacity could be overloaded. This problem needs to be addressed to reduce the impact on the electric utility infrastructure. The main goal of this project is to develop a 400-kW/400-A XFC system targeting total efficiency of 96.5 percent from the MVAC grid to a vehicle. The novel SST power cell topology, combined with a new silicon carbide (SiC) MOSFET device, enables a 3.5 percent improvement in system efficiency, a 50-percent smaller equipment footprint, and four times less weight than today’s DCFC systems. The SST technology would directly utilize MVAC at 4.8-kV or 13.2-kV. This would eliminate the line frequency transformer (LFT), which steps down medium-voltage AC to 3-Phase 480-V line-to-line voltage in current DCFC systems.

42 ENGINEERING↗
DOE OSTI2026

A Scalable Test-Bed for Direct Current Current Transformer Automated Functional Testing and Characterization

This article describes a scalable test-bed for automation of measurements of the direct current current transformers (DCCT). Automation of measurement involves functional measurements, fault event based measurements and data validation. The test-bed is designed to measure up to 20 DCCTs at a time with software based measurement repetition checks and validation of the measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Large Power Transformer Supply Chain Gap Analysis and Domestic Content Strategies for Hydropower Rehabilitation: Supplemental Report

Large Power Transformers (LPTs) are indispensable to U.S. hydropower operations, serving as generator step-up (GSU) units that interconnect hydro facilities to the transmission grid. Yet the LPT supply chain faces mounting stress from aging infrastructure, limited domestic production, and long lead times. Currently, more than 80% of LPT demand is met through imports, with primary suppliers including Mexico, South Korea, Brazil, Austria, and Canada. Domestic manufacturers supply only about 20% of units, constrained by bottlenecks in high-grade Grain-Oriented Electrical Steel (GOES), copper conductors, bushings, and on-load tap changers (OLTCs). Hydropower rehabilitation projects in particular face additional challenges due to custom design requirements, remote siting, and regulatory needs around domestic content. Regional cost disparities, driven by transportation logistics, labor markets, and import price volatility, further exacerbate project risks. To address these vulnerabilities, coordinated action is required: strengthening domestic capacity for GOES and secondary components, developing near-site assembly hubs, and leveraging IRS domestic content safe harbors to incentivize U.S. manufacturing. This addendum refines the 2024 NREL Hydropower Supply Chain Gap Analysis by focusing specifically on critical issues related to LPT domestic manufacturing capacity and key considerations for hydropower developers and asset owners.

13 HYDRO ENERGY↗
DOE OSTI2021

Hosting Capacity Improvement Method Using MV–MV Solid-State-Transformer

As a large number of distributed generations are connected to the distribution system, research on the hosting capacity is actively being conducted. In particular, various methods, such as smart inverter functionality, co-located energy storage systems (ESS), and the use of on-load tap changers (OLTC), have been proposed to improve the hosting capacity. In this paper, a method to improve the hosting capacity by utilizing a solid-state transformer (SST) and its unique control capability is proposed. Lastly, the proposed method is verified in the distribution system of the Republic of Korea using the OpenDSS program.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Solid State Transformer Controls for Mitigation of E3a High-Altitude Electromagnetic Pulse Insults

This paper explores the use of a solid state transformer (SST) to mitigate the 𝐸 3𝐴 component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the 𝐸 3𝐴 components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller.

HEMP mitigation↗
DOE OSTI2021

A Multiomic Approach to Understand How Pleurotus eryngii Transforms Non-Woody Lignocellulosic Material

Pleurotus eryngii is a grassland-inhabiting fungus of biotechnological interest due to its ability to colonize non-woody lignocellulosic material. Genomic, transcriptomic, exoproteomic, and metabolomic analyses were combined to explain the enzymatic aspects underlaying wheat–straw transformation. Up-regulated and constitutive glycoside–hydrolases, polysaccharide–lyases, and carbohydrate–esterases active on polysaccharides, laccases active on lignin, and a surprisingly high amount of constitutive/inducible aryl–alcohol oxidases (AAOs) constituted the suite of extracellular enzymes at early fungal growth. Higher enzyme diversity and abundance characterized the longer-term growth, with an array of oxidoreductases involved in depolymerization of both cellulose and lignin, which were often up-regulated since initial growth. These oxidative enzymes included lytic polysaccharide monooxygenases (LPMOs) acting on crystalline polysaccharides, cellobiose dehydrogenase involved in LPMO activation, and ligninolytic peroxidases (mainly manganese-oxidizing peroxidases), together with highly abundant H2O2-producing AAOs. Interestingly, some of the most relevant enzymes acting on polysaccharides were appended to a cellulose-binding module. This is potentially related to the non-woody habitat of P. eryngii (in contrast to the wood habitat of many basidiomycetes). Additionally, insights into the intracellular catabolism of aromatic compounds, which is a neglected area of study in lignin degradation by basidiomycetes, were also provided. The multiomic approach reveals that although non-woody decay does not result in dramatic modifications, as revealed by detailed 2D-NMR and other analyses, it implies activation of the complete set of hydrolytic and oxidative enzymes characterizing lignocellulose-decaying basidiomycetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

MTL_TX: A Multi-Task Transformer Model for Improved Radiation Time-Series Estimation

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed model: hierarchical feature embedding (HFE) and multi-level decomposition attention (MDA). Additionally, the multi-task learning (MTL) framework effectively leverages correlations among multiple sensors, enabling individual estimations for each sensor. MTL_TX achieved outstanding results on data collected in 2018, with an MSE of 0.1464, an RMSE of 0.2353, and an R 2 score of 0.8584. Furthermore, when trained on 2018 data, MTL_TX exhibited excellent generalization capability to unseen datasets from 2016 to 2019, achieving an MSE of 0.1407, an RMSE of 0.2263, and an R 2 score of 0.8831. These results demonstrate a significant improvement over existing state-of-the-art models.

Transformer↗
DOE OSTI2026

Hidden Rotation Symmetry of the Jordan–Wigner Transformation and Its Application to Measurement in Quantum Computation

Using a global rotation by 𝜃 about the z-axis in the spin sector of the Jordan–Wigner transformation rotates Pauli matrices 𝑋̂ and 𝑌̂ in the 𝑥−𝑦 -plane, while it adds a global complex phase to fermionic quantum states that have a fixed number of particles. With the right choice of angles, this relates expectation values of Pauli strings containing products of 𝑋̂ and 𝑌̂ to different products, which can be employed to reduce the number of measurements needed when simulating fermionic systems on a quantum computer. Here, we derive this symmetry and show how it can be applied to systems in Physics and Chemistry that involve Hamiltonians with only single-particle (hopping) and two-particle (interaction) terms. We also discuss the consequences of this for finding efficient measurement circuits in variational ground state preparation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Global Power System Transformation Consortium

The Global Power System Transformation (G-PST) Consortium, an expert- and practitioner-driven initiative, engages key power system operators, research and educational institutes, governments, businesses, and stakeholders in all regions of the world to accelerate clean energy transitions at the ambitious scope and scale that is required. The G-PST Consortium provides coordinated, holistic support and knowledge infusion for system operators pursuing clean energy transitions, including performing cutting-edge research; providing implementation support for world-class engineering and operational solutions; supporting workforce development; building and disseminating open-access data and tools; and accelerating localized technology adoption, standards development, and testing programs.

consortium↗
DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops an approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurements. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗