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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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Subdiffusive transport in the Fredkin dynamical universality class
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Universality classes of relativistic fluid dynamics: Applications
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10 kV Class 14 MHz Isolated Power Supply
This paper presents a single-switch based isolated power supply, utilizing a PCB based core-less transformer to achieve high inter-winding isolation and low common-mode capacitance. Detailed design procedure, considering the transformer to achieve full range ZVS, minimize voltage stress and minimize RMS currents is presented. The proposed methodology is experimentally validated at 14 MHz, with a load variation of 10:1 in output power and a maximum output power of 4 W. The proposed power supply is useful in applications such as MV gate drives and sensors.
A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]
Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.
An Improved Class-E Current Inverter With Two Coupled Inductors for Isolation and Power Scaling Without Affecting Switch Voltage Stress
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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.
Scaling the memory wall using mixed-precision - HPG-MxP on an exascale-class machine
Mixed-precision algorithms have been proposed as a way for scientific computing to benefit from some of the gains seen for AI on recent high performance computing (HPC) platforms. A few applications dominated by dense matrix operations have seen substantial speedups by utilizing low precision formats such as FP16. However, a majority of scientific simulation applications are memory bandwidth limited. Beyond preliminary studies, the practical gain from using mixed-precision algorithms on a given high-performance computing (HPC) system is largely unclear. The High Performance GMRES Mixed Precision (HPG-MxP) benchmark has been proposed to measure the useful performance of a HPC system on sparse matrix-based mixed-precision applications. In this work, we present an implementation of the HPG-MxP benchmark for an exascale system and describe our algorithm enhancements. We show for the first time a speedup of 1.6x using a combination of double- and single-precision keeping the same residual level on modern GPU-based supercomputers.
NETL RDE Image Classification Dataset 2025 - 14 Classes
Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.
NETL RDE Image Classification Dataset 2020 - 10 Classes
Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 100,000 images with 10 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, and Deflagration. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.
Complementing the CCS Class VI Well Permit Process with DOE-NETL's SMART Initiative Tools and Workflows
This is a presentation on model explorer developed under SMART initiative Task 2. Our team will present the current progress of the model explorer in using machine learning models to accelerate CCS project at GWPC meeting. Model explorer bring new capabilities, (fast, Realtime, and accurate) that can help CCS stakeholders including regulatory agencies, public and site operators make faster decisions and process information and data.
Model to predict annual energy production loss based on blade erosion class
Leading edge erosion (LEE) of wind turbine blades has been identified as a major factor in decreased wind turbine blade lifetimes and energy output over time. Accordingly, the International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) has created the Task 46 to undertake cooperative research in the key topic of blade erosion. Participants in the task are given in Table 1.
Novel CCS Monitoring of Approved Class VI Storage in North Dakota
Presentation at Dallas Geophysical Society Meeting, Dallas, Texas, April 24, 2025. This high-level overview of focuses on novel and sustainable monitoring methods at various stages of planning or demonstration to accelerate the deployment at future carbon capture, utilization, and storage (CCUS) sites.
State's Perspective on Regulating CO 2 Storage and Permitting UIC Class VI Injection Wells
Conference presentation at 48th International Technical Conference on Clean Energy (Clearwater Clean Energy Conference), Clearwater, Florida, June 16–19, 2024. An overview of the Plains CO 2 Reduction (PCOR) Partnership Initiative, the regulatory framework for carbon capture, utilization, and storage (CCUS), and a timeline of the state and federal permitting process.
Advanced Mixed Mode Combustor for Hydrogen F-Class Retrofit (Final Report)
This objective of this project was to develop a retrofittable combustor module for the GE Vernova Operations LLC (GE Vernova, GEV) frame 7F gas turbine (GT) that would allow operation on blends of hydrogen in Natural Gas (NG) between 0% and 100%. The new system was to be part of a package that retained current cycle performance while limiting the increase in NOx emissions to the equivalent of 25ppm (parts per million by volume dry at 15% O2, ppmvd15) with consideration for the impact of hydrogen fuel on the O2 correction. The expectation was that with the addition of Axial Fuel Staging (AFS), turndown within emission compliance would be extended to below 20% GT load. The original project plan included three budget periods (BPs): BP1 spanning October 1, 2022 through August 31, 2024; BP2 spanning September 1, 2024 through December 31, 2025; and BP3 spanning January 1, 2026 through September 30, 2026. The project was terminated early by the DOE on October 10, 2025 about three months prior to the end of BP2. BP3 activities were therefore cancelled. The program was on track to meet all objectives prior to the DOE termination. This Final Report covers work completed during BP1 and BP2 prior to the program termination.
One Earth Energy CO 2 Capture Facility FEED Study and Class 4 Cost Estimate
The One Earth Energy (OEE) plant in Gibson City, Illinois produces ethanol through a corn fermentation process. For this project, the maximum possible ethanol production rate for this facility is 160 million gallons per year (MMgal/yr) based on discussions with plant personnel regarding recent annual production rates and any foreseeable plans or possibilities to increase ethanol production at this facility. Yeast ferments the corn mash to produce ethanol and produces carbon dioxide (CO 2 ) as a by-product at the same time. The CO 2 bubbles out of the mash and flows through a packed bed water scrubber to remove volatile organic compounds before the gas vents to atmosphere. CO 2 will be captured after it has passed through the existing scrubber.
Class 5 Map and Plan Safe Performance Testing
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