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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Modeling Failure of Electrical Transformers due to Effects of a HEMP Event

Understanding the effect of a high-altitude electromagnetic pulse (HEMP) on the equipment in the United States electrical power grid is important to national security. A present challenge to this understanding is evaluating the vulnerability of transformers to a HEMP. Evaluating vulnerability by direct testing is cost-prohibitive, due to the wide variation in transformers, their high cost, and the large number of tests required to establish vulnerability with confidence. Alternatively, material and component testing can be performed to quantify a model for transformer failure, and the model can be used to assess vulnerability of a wide variety of transformers. This project develops a model of the probability of equipment failure due to effects of a HEMP. Potential failure modes are cataloged, and a model structure is presented which can be quantified by the results of small-scale coupon tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

HEMP Transformer Defense Through Power Electronics

High altitude electromagnetic pulses and geo-magnetic disturbances have the potential to severely impact the electric power grid by damaging large power transformers and causing severe power quality issues. This impact comes as a result of a quasi-static bias induced on transmission lines by geomagnetically induced currents which saturate magnetic components in the electric power system. This paper introduces the concept of utilizing a h-bridge inverter on the neutral of a LPT to inject a DC bias equivalent voltage onto the neutral side of the transformer windings. This biasing floats the transformer windings, eliminating the effect of the DC current and keeping the transformer from saturating. Schematic diagrams will be presented, along with simulation model data using Typhoon and PLECS, and finally test results from a benchtop hardware test.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
DOE OSTI2024

Vision Transformers Explained Series

Since their introduction in 2017 with Attention is All You Need¹, transformers have established themselves as the state of the art for natural language processing (NLP). In 2021, An Image is Worth 16x16 Words successfully adapted transformers for computer vision tasks. Since then, numerous transformer-based architectures have been proposed for computer vision. This article walks through the Vision Transformer (ViT) as laid out in An Image is Worth 16x16 Words.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Overcoming Barriers in Plant Transformation: A Focus on Bioenergy Crops

Although 2023 marked the 40th anniversary of the first transgenic plant, routine transformation of most plant genotypes remains elusive. Rapid systems to overexpress, interfere, or knock out genes— collectively defined in this report as “transformation and editing technologies”—are needed to understand plant gene function. This understanding in turn is crucial for efficiently developing new, sustainable, high-yielding, and climate-resilient crops to meet the growing demand for food, feed, fiber, and fuel. In particular, the ability to apply transformation and editing technologies to bioenergy crops has remained largely unrealized. To address this opportunity, the U.S. Department of Energy (DOE) Biological and Environmental Research Program convened a workshop on September 18–20, 2023, to define transformation and editing needs and barriers focused on bioenergy crops. The main conclusions are summarized below.

09 BIOMASS FUELS↗
DOE OSTI2024

Interpreting and Accelerating Transformers for Jet Tagging

Attention-based transformers are ubiquitous in machine learning applications from natural language processing to computer vision. In high energy physics, one central application is to classify collimated particle showers in colliders based on the particle of origin, known as jet tagging. In this work, we study the interpretatbility and prospects for acceleration of Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging performance. We analyzing ParT's attention maps and particle-pair correlations in the eta-phi plane, revealing intriguing features, such as a binary attention pattern that identifies critical substructure in jets. These insights enhance our understanding of the model's internal workings and learning process and hint at ways to improve its efficiency. Along these lines, we also explore low-rank attention, attention alternatives, and dynamic quantization to accelerate transformers for jet tagging. With quantization, we achieve a 50% reduction in model size and a 10% increase in inference speed without compromising accuracy. These combined efforts enhance both the performance and the interpretability of transformers in high-energy physics, opening avenues for more efficient and physics-driven model designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Transformative Pathways for U.S. Industry: Unlocking American Innovation

The United States (U.S.) is undergoing an energy transformation that will depend on continued U.S. innovation. Although U.S. industry has been foundational to the nation’s economic growth and prosperity, it has also given rise to decades’ worth of industrial pollutants in our air and water, which acutely impact the most vulnerable communities, as well as greenhouse gas (GHG) emissions contributing to climate risk. At the same time, U.S. industry is facing growing competitive pressures. Global investors and financial regulations are increasingly focusing on emissions footprints, governments are developing emissions-based trade adjustments and procurement specifications, and downstream demand for low-carbon products is emerging. Developing cost-competitive solutions to meet these needs provides an opportunity to fundamentally transform U.S. industry and sharpen its competitive edge, while reducing the GHG emissions and adverse environmental and health impacts (see Figure ES-1). Innovation is central to this transformation. Pathways to Commercial Liftoff: Industrial Decarbonization, which provides a descriptive fact base on what is needed to reach commercial scale in the marketplace, estimates that over 60% of emissions reduction for the industrial sector will need to come from technologies that are still nascent today. This report, Transformative Pathways for U.S. Industry,3 focuses on the pathways that rely on the nascent and innovative technologies that were too early for consideration in the Pathways to Commercial Liftoff report. Targeted and sustained public and private investment in research, development, demonstration, and deployment is required to catalyze innovation and meet this moment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

AC to AC Solid State Transformer with Bidirectional Switches

This report details the work of the 3-year project for the AC-to-AC Solid State Transformer with Bidirectional Switches project devoted to developing and demonstrated a Type I Solid State Transformer. This report details the design, fabrication, and evaluation of both three-phase and single-phase versions of this solid state transformer operating as a single module, modules in parallel, and modules in cascade. Additionally, this report details the fabrication and evaluation of custom Silicon Carbide bidirectional switches to enable this topology with a comparison between monolithically integrated bidirectional switches as well as co-packaged back-to-back unidirectional devices. Finally, results for custom-fabricated Fe 4 N/ferrite laminated toroidal cores for high frequency transformers are present.

42 ENGINEERING↗
DOE OSTI2026

Transformational Sorbent System for Post-Combustion Carbon Capture (Final Report)

As part of this DOE Contract (Transformational Sorbent System for Post-Combustion Carbon Capture, DE-FE0031734),TDA Research Inc. developed a transformational sorbent system for post combustion CO 2 capture process that captures more than 95% of CO 2 emissions from a coal fired power plant, recovering CO 2 at 95% purity with a cost of CO 2 capture significantly lower than with amine-based system (~$30 per tonne (MT) of CO 2 captured). TDA’s transformational sorbent system uses a novel, highly stable, high-capacity metal organic framework (MOF) based CO 2 sorbent in a new vacuum/concentration swing adsorption (VCSA) process that allows us to use high efficiency vacuum pumps with a low auxiliary load. A pulverized coal fired power plant equipped with TDA’s transformational sorbent system for post combustion CO 2 capture is expected to efficiently produce electricity with a low Cost of Electricity (COE) and capture greater than 95% of the CO 2 from the power plant exhaust.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

JGI Plant Transformation Workshop, May 20-21, 2025

Domestic biomass crops such as sorghum, switchgrass, Miscanthus, and poplar can provide United States industries with renewable feedstocks while also supporting low-input farming systems and strengthening supply chains for biofuels, biochemicals and biomaterials. The U.S. leads globally in biomass crop genomics, yet progress in engineering traits is constrained by slow, genotype-dependent transformation methods and lengthy Design-Build-Test-Learn (DBTL) cycles. At a May 2025 workshop, a panel of experts recommended establishing a DOE Plant Transformation Capability (PTC) to overcome these barriers. The PTC would unite two missions: advancing research to achieve genotype-independent, automated methods, and delivering scalable transformation services through a user-facility model. With expected gains of 10–100x in efficiency, including transformation and cost reduction, the PTC would accelerate the path from discovery to engineered plants, expand community access and training, and support downstream applications and workflows including field trials and regulatory navigation. By enabling rapid and predictable crop engineering, the PTC would strengthen U.S. supply chains, enhance industrial competitiveness, and ensure that DOE’s genomic investments deliver national impact.

09 BIOMASS FUELS↗
DOE OSTI2026

Irradiation Tailoring of Deformation-Induced Phase Transformations

The objective of this project is to understand how irradiation enables deformation‐induced phase transformations in fcc metallic alloys. Low‐temperature deformation of face centered cubic (fcc) metals and alloys can occur through several modes, one of which is martensitic transformation, wherein fcc γ‐Fe austenite reverts to hexagonal close packed (hcp) ε‐ martensite or body centered cubic (bcc) α’‐martensite. Irradiation is believed to enhance the tendency for this transformation to occur, considering that irradiation similarly enhances other low‐temperature deformation modes such as dislocation channeling and deformation twinning. However, the mechanisms underlying the irradiation enhancement of martensitic transformations remain unknown.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthetic Promoter Screening Using Poplar Mesophyll Protoplast Transformation

Plant protoplasts are useful to study both transcriptional regulation and protein subcellular localization in rapid screens. Protoplast transformation can be used in automated platforms for design-build-test cycles of plant promoters, including synthetic promoters. A notable application of protoplasts comes from recent successes in dissecting synthetic promoter activity with poplar mesophyll protoplasts. For this purpose, we constructed plasmids with TurboGFP driven by a synthetic promoter together with TurboRFP constitutively controlled by a 35S promoter, to monitor transformation efficiency, allowing versatile screening of high numbers of cells by monitoring green fluorescent protein expression in transformed protoplasts. Herein, we introduce a protocol for poplar mesophyll protoplast isolation followed by protoplast transformation and image analysis for the selection of valuable synthetic promoters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fock-Space Schrieffer–Wolff Transformation: Classically-Assisted Rank-Reduced Quantum Phase Estimation Algorithm

We present an extension of many-body downfolding methods to reduce the resources required in the quantum phase estimation (QPE) algorithm. In this paper, we focus on the Schrieffer–Wolff (SW) transformation of the electronic Hamiltonians for molecular systems that provides significant simplifications of quantum circuits for simulations of quantum dynamics. We demonstrate that by employing Fock-space variants of the SW transformation (or rank-reducing similarity transformations (RRST)) one can significantly increase the locality of the qubit-mapped similarity-transformed Hamiltonians. The practical utilization of the SW-RRST formalism is associated with a series of approximations discussed in the manuscript. In particular, amplitudes that define RRST can be evaluated using conventional computers and then encoded on quantum computers. The SW-RRST QPE quantum algorithms can also be viewed as an extension of the standard state-specific coupled-cluster downfolding methods to provide a robust alternative to the traditional QPE algorithms to identify the ground and excited states for systems with various numbers of electrons using the same Fock-space representations of the downfolded Hamiltonian. The RRST formalism serves as a design principle for developing new classes of approximate schemes that reduce the complexity of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics

Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resources both for training and deployment. The problem is exacerbated as the amount and complexity of the data increases. Quantum-based vision transformer models could potentially alleviate this issue by reducing the training and operating time while maintaining the same predictive power. Although current quantum computers are not yet able to perform high-dimensional tasks, they do offer one of the most efficient solutions for the future. In this work, we construct several variations of a quantum hybrid vision transformer for a classification problem in high-energy physics (distinguishing photons and electrons in the electromagnetic calorimeter). We test them against classical vision transformer architectures. Our findings indicate that the hybrid models can achieve comparable performance to their classical analogs with a similar number of parameters.

Unlu, Eyup B. (ORCID:0000000266836463)↗
DOE OSTI2018

Tracing Phase Transformation and Lattice Evolution in a TRIP Sheet Steel under High-Temperature Annealing by Real-Time In Situ Neutron Diffraction

Real-time in situ neutron diffraction was used to characterize the crystal structure evolution in a transformation-induced plasticity (TRIP) sheet steel during annealing up to 1000 °C and then cooling to 60 °C. Based on the results of full-pattern Rietveld refinement, critical temperature regions were determined in which the transformations of retained austenite to ferrite and ferrite to high-temperature austenite during heating and the transformation of austenite to ferrite during cooling occurred, respectively. The phase-specific lattice variation with temperature was further analyzed to comprehensively understand the role of carbon diffusion in accordance with phase transformation, which also shed light on the determination of internal stress in retained austenite. These results prove the technique of real-time in situ neutron diffraction as a powerful tool for heat treatment design of novel metallic materials.

Yu, Dunji [ORNL] (ORCID:0000000189467851)↗
DOE OSTI2023

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Explicit Form for the Most General Lorentz Transformation Revisited

Explicit formulae for the 4×4 Lorentz transformation matrices corresponding to a pure boost and a pure three-dimensional rotation are very well known. Significantly less well known is the explicit formula for a general Lorentz transformation with arbitrary non-zero boost and rotation parameters. We revisit this more general formula by presenting two different derivations. The first derivation (which is somewhat simpler than previous ones appearing in the literature) evaluates the exponential of a 4×4 real matrix A, where A is a product of the diagonal matrix diag(+1,−1,−1,−1) and an arbitrary 4×4 real antisymmetric matrix. The formula for expA depends only on the eigenvalues of A and makes use of the Lagrange interpolating polynomial. The second derivation exploits the observation that the spinor product η†σ¯μχ transforms as a Lorentz four-vector, where χ and η are two-component spinors. The advantage of the latter derivation is that the corresponding formula for a general Lorentz transformation Λ reduces to the computation of the trace of a product of 2×2 matrices. Both computations are shown to yield equivalent expressions for Λ.

Science & Technology - Other Topics↗
DOE OSTI2025

A novel transformation of the ice sheet Stokes equations and some of its properties and applications

We introduce a novel transformation of the Stokes equations into a form closely resembling the shallow Blatter–Pattyn equations. The two forms differ by only a few additional terms, while their variational formulations differ only by a single term in each horizontal direction. Specifically, the variational formulation of the Blatter–Pattyn model drops the vertical velocity in the second invariant of the strain rate tensor. Here we make use of the new transformation in two ways. First, we consider incorporating the transformed equations into a code that can be very easily converted from a Stokes to a Blatter–Pattyn model, and vice versa, by switching these terms on or off. This may be generalized so that the Stokes model is switched on adaptively only where the Blatter–Pattyn model loses accuracy. Second, the key role played by the vertical velocity in the Blatter–Pattyn approximation motivates new approximations. Two examples are presented. These require a mesh that enables the discrete continuity equation to be invertible for the vertical velocity in terms of the horizontal velocity components. Examples of such meshes, such as the first-order P1–E0 mesh and the second-order P2–E1 mesh, are given in both 2D and 3D. However, the transformed Stokes model has the same type of gravity forcing as the Blatter–Pattyn model, determined by the ice surface slope, thereby forgoing some of the mesh generality of the traditional formulation of the Stokes model.

58 GEOSCIENCES↗