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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
NASA NTRS2016

TransFormers for Ensuring Long-Term Operations in Lunar Extreme Environments

"Surviving Extreme Space Environments" (EE) is one of NASA's Space Technology Grand Challenges. Power generation and thermal control are the key survival ingredients that allow a robotic explorer to cope with the EE using resources available to it, for example, by harvesting the local solar energy or by utilizing an onboard radioisotope thermoelectric generator (RTG). TransFormers (TFs) are a new technology concept designed to transform a localized area within a harsh extreme environment into a survivable micro-environment by projecting energy to the precise location where robots or humans operate. For example, TFs placed at a location on the rim of Shackleton Crater, which is illuminated by solar radiation for most of the year, would be able to reflect solar energy onto robots operating in the dark cold crater. TFs utilize a shape transformation mechanism to un-fold from a compact volume to a large reflective surface, and to control how much-and where-the energy is projected, and by adjusting for the changing position of the sun. TFs would enable in-situ resource utilization (ISRU) activities within locations of high interest that would normally be unreachable because of their extreme environment

ISRU↗
NASA NTRS2014

TransFormers for Extreme Environments: Projecting Favorable Micro-Environments Around Robots and Areas of Interest

“Surviving Extreme Space Environments” (EE) is one of NASA’s Space Technology Grand Challenges; we propose a paradigm shift in addressing this challenge. TransFormers (TFs) transform a region of an extreme environment into a favorable micro-environment, projecting energy at the precise location where robots or humans operate. TFs often use shape transformation to control the energy projection.

Stoica, Adrian↗
NASA NTRS2019

Denoising with Three Dimensional Fourier Transform for Three Dimensional Images, Including Image Sequences

A method of mitigating noise in source image data representing pixels of a 3-D image. The "3-D image" may be any type of 3-D image, regardless of whether the third dimension is spatial, temporal, or some other parameter. The 3-D image is divided into three-dimensional chunks of pixels. These chunks are apodized and a three-dimensional Fourier transform is performed on each chunk, thereby producing a three-dimensional spectrum of each chunk. The transformed chunks are processed to estimate a noise floor based on spectral values of the pixels within each chunk. A noise threshold is then determined, and the spectrum of each chunk is filtered with a denoising filter based on the noise threshold. The chunks are then inverse transformed, and recombined into a denoised 3-D image.

DeForest, Craig E.↗
NASA NTRS2023

Remote Sensing of Dissolved Organic Carbon (DOC) Stocks, Fluxes and Transformations Along the Land-Ocean Aquatic Continuum: Advances, Challenges, and Opportunities

From stream headwaters to the deep ocean, dissolved organic carbon (DOC) is ubiquitous across the world’s aquatic systems, where it fulfills important biogeochemical and ecological functions. Importantly, DOC is a dynamic component of the carbon cycle and represents a global reservoir (mass of carbon) equivalent in size to the atmospheric CO 2 pool. The mobilization, transport, and transformations of DOC along the land-ocean aquatic continuum biogeochemically connect terrestrial landscapes, freshwater and marine ecosystems, and the atmosphere. As a result, DOC budgets are vulnerable to climate- and human-driven changes. Having the ability to quantify DOC stocks, fluxes, and transformations consistently and accurately in aquatic systems is therefore critical to our understanding of DOC’s functions in the environment and of their susceptibility to change. In recent years, optical techniques and synoptic earth observations have opened new doors to achieve this objective on a global scale. In this review, we explore how in situ measurements, earth observations, and the models they inform have facilitated the large-scale quantification of DOC stocks, fluxes, and transformations along the land-ocean aquatic continuum and how they have helped shape our current understanding of the global DOC cycle. The review also explores the limitations and challenges we still face today, and discusses how upcoming and future sensors are expected to provide new insights into our understanding of the global DOC cycle.

Dissolved organic carbon↗
NASA NTRSDate not supplied

Transformational Propulsion for In-Space Fast Transits

NASA has ambitious mission objectives requiring much faster transits to and from Mars, interstellar probes and a gravity lens observatory. However, there has been very little investment in transformational propulsion system development activities since the 1970s. There have been dozens of concepts proposed for high acceleration propulsion solutions, but nearly all have been limited to paper studies. A quick assessment was completed in 2023 to determine the potential of transformational propulsion concepts to enable faster transits, with a focus on crewed missions to and from Mars. Far-term conventional nuclear thermal propulsion is limited to very modest improvement in transfer times. Advanced nuclear propulsion options have significant performance potential, but limited interim evolutionary payoff for NASA. Advanced electric propulsion, both solar and nuclear, offers transformational performance potential with high payoff during interim progress for power production, conversion, and heat rejection technologies. Study results and recommendations for near-term investments are presented herein.

Propulsion↗
DOE OSTI2021

Unified conductor to lower the resistance between a planar transformer and one or more inductors

An apparatus is provided including a transformer including a first printed circuit board having one or more conducting layers, the one or more conducting layers forming, at least in part, a transformer coil; at least one inductor; and at least one continuous piece of conducting material external to the printed circuit board, where the at least one continuous piece of conducting material forms a connection between the transformer and the at least one inductor. A method is also provided for assembling a switched-mode power supply.

Coteus, Paul W.↗
DOE OSTI2021

Transformer and an associated method thereof

A transformer having an insulation system is presented. The transformer includes a magnetic core having an opening. Also, the transformer includes a plurality of primary windings disposed extending through the opening of the magnetic core. Further, the insulation system includes a first insulation substantially encapsulating the plurality of primary windings and impregnating spaces between the plurality of primary windings, and a second insulation disposed around the first insulation, where the second insulation has at least one of a predetermined dielectric strength and a predetermined thickness configured to isolate a first voltage signal in the plurality of primary windings from the magnetic core.

Chen, Qin↗
DOE OSTI2021

Low modulation index 3-phase solid state transformer

A solid-state transformer (SST) comprises a transformer core, a primary winding, a secondary winding, a primary-side switch bank, and a secondary-side switch bank. Each of the switch banks includes six 4-quadrant switches. The twelve 4-quadrant switches are toggled on and off over six clock cycles in a repetitive sequence with a period that is a function of a desired operating frequency of the transformer. The sequence is configured such that at any given time, 2 of 3 input and output phases are connected to the primary and secondary windings. The SST further includes L-C filter circuits that are configured to filter high-frequency components of current and voltage waveforms such that these components are not back-fed to the electrical mains or delivered to a load. The SST includes a primary-side filter circuit and a secondary-side filter circuit that can each include respective L-C filters for three input or output phases.

Koplow, Jeffrey P.↗
DOE OSTI2022

DC compensation for power transformer through neutral DC injection

A power transmission system can include a transformer and compensator circuit(s), each coupled between a node of the transformer and a ground connection. The compensator circuit(s) can each be configured to counteract a DC signal component of an AC signal at the transformer. The compensator circuit(s) can include a converter circuit having an AC side and a DC side and configured to convert a DC voltage on the DC side to an AC signal at the AC side. The compensator circuit(s) can include a DC link coupled to the DC side of the converter circuit. The compensator circuit(s) can include a controller configured to measure a DC signal component between the load and the ground; to determine, based at least in part on the DC signal component, a compensating signal configured to counteract the DC signal component; and to inject, by the converter circuit, the compensating signal to counteract the DC signal component.

Burkes, Klaehn W.↗
DOE OSTI2024

Atmospheric Transformation of Refrigerants: Current Research Developments and Knowledge Gaps

Refrigerants have evolved through the years to reduce their global warming potential while providing sufficient cooling in refrigeration systems. Replacements for hydrofluorocarbons (HFCs) and chlorofluorocarbons (CFCs) are the hydrofluoroolefins (HFOs), which contain reactive double bonds that decrease the atmospheric lifetime of fluorinated compounds. However, the transformation of unsaturated fluorinated compounds in the atmosphere could generate persistent pollutants, particularly trifluoroacetic acid (TFA) which is the simplest Perfluoroalkyl carboxylic acids (PFCAs). Understanding the transformation of refrigerants is critical in assessing their contribution to atmospheric levels of TFA and their impact on watersheds and human health. This article will present the reactivity of the refrigerants, atmospheric oxidation source, and sink processes of fluorinated refrigerants under daytime conditions, particularly the variability of TFA from refrigerants. Moreover, the discussion will suggest experimental procedures that can quantify the low concentration (~parts per trillion) of TFA generated from the transformation of HFOs. New state-of-the-art techniques such as chemical ionization mass spectrometers (HR-CIMS) will be assessed in providing high temporal resolution (minutes to hourly) to fully capture the atmospheric sources and variability of TFA. Likewise, local, regional, and global concentrations of TFA accounted from the oxidation of refrigerants will be examined. This will include data from both experimental procedures and simulation models. Participation of TFA in critical atmospheric processes such as new particle formation will also be included in this study. Lastly, overall knowledge gaps related to the oxidation products and their dispersion in the environment will be summarized to guide future research needs.

Salvador, Christian↗
DOE OSTI2024

Interpreting Transformers for Jet Tagging

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging tasks, which are critical for identifying particles resulting from proton collisions. This study focuses on interpreting ParT by analyzing attention heat maps and particle-pair correlations on the $\eta$-$\phi$ plane, revealing a binary attention pattern where each particle attends to at most one other particle. At the same time, we observe that ParT shows varying focus on important particles and subjets depending on decay, indicating that the model learns traditional jet substructure observables. These insights enhance our understanding of the model's internal workings and learning process, offering potential avenues for improving the efficiency of transformer architectures in future high-energy physics applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Transformer designs for very high isolation with high coupling

Various examples are provided related to transformer designs that offer very high isolation while maintaining high coupling between the windings. In one example, an isolation transformer includes a first excitation coil wound around a first core and a second excitation coil wound about a second core. The second core is electrically separated from the first core by a high resistivity magnetic material or a non-conductive material. The first and second cores can include corresponding core segments arranged in a trident geometry or a quindent geometry. The core segments can align when the first excitation coil is inserted into a void of the second excitation coil. The isolation transformer designs are mechanically separable which can result in safe, energized, plug operations.

Beddingfield, Richard Byron↗
DOE OSTI2025

Why Is Attention Sparse In Particle Transformer?

Transformer-based models have achieved state-of-the-art performance in jet tagging at the CERN Large Hadron Collider (LHC), with the Particle Transformer (ParT) representing a leading example of such models. A striking feature of ParT is its sparse, nearly binary, attention structure, raising questions about the origin of this behavior and whether it encodes physically meaningful correlations. In this work, we investigate the source of ParT's sparse attention by comparing models trained on multiple benchmark datasets and examine the relative contributions of the attention term and the physics-inspired interaction matrix before softmax. We find that binary sparsity arises primarily from the attention mechanism itself, with the interaction matrix playing a secondary role. Moreove, we show that ParT is able to identify key jet substructure elements, such as leptons in semileptonic top decays, even without explicit particle identification inputs. These results provide new insight into the interpretability of transformer-based jet taggers and clarify the conditions under which sparse attention patterns emerge in ParT.

Legge, Timothy [UC, San Diego]↗
DOE OSTI2022

Resolving the Martensitic Transformation in Q&P Steels In-Situ at Dynamic Strain Rates Using Synchrotron X-ray Diffraction

Herein the dynamic deformation response of two quenching and partitioning (Q&P) steels was investigated using a high strain rate tension pressure bar and in-situ synchrotron radiography and diffraction. This allowed for concurrent measurements of the martensitic transformation, the elastic strains/stresses on the martensite and ferrite, and the bulk mechanical behavior. The steel with the greater fraction of ferrite exhibited greater ductility and lower strength, suggesting that dislocation slip in ferrite enhanced the deformability. Meanwhile, the kinetics of the martensitic transformation appeared similar for both steels, although the steel with a greater ferrite fraction retained more austenite in the neck after fracture.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Residual Stress Modeling with Phase Transformation for Wire Arc Additive Manufacturing of B91 Steel

Wire arc additive manufacturing (WAAM) is an energy-efficient manufacturing technique used for near-net-shape production of functional industrial components. However, heat accumulation during deposition and the associated mechanical and metallurgical changes result in complex residual stress profiles across the cross section of the fabricated components. These residual stresses are detrimental to the service life of the components. In this study, sequentially coupled thermomechanical analysis of WAAM B91 steel is conducted to quantify the residual stress variation across the component. The thermomechanical analysis includes a transient heat transfer model and a static stress model that incorporates the transformation-induced plasticity due to martensitic phase transformation. Here, the experimentally calibrated heat transfer model mirrors the temperature variation of the system during the deposition. The results from the stress model are validated via x-ray diffraction measurements, and the numerical results are in good agreement with the experimental data.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Automated Framework for Groundwater Monitoring Using DWT with LSTM and Transformers

Environmental monitoring is critical for safeguarding public health and ecological well-being. Traditional data structuring and workflow monitoring methods consume significant time and effort, hindering timely insights and effective decision-making. Our study addresses this challenge by presenting an AI framework that automates data cleaning, structuring, and modeling processes, specifically targeting applications in groundwater monitoring. By leveraging automation for data processing and model training, our framework establishes a novel and efficient paradigm for environmental monitoring, with its potential application to the vast network of over a hundred Department of Energy Environmental Management (DoE-EM) cleanup sites across the country. It analyzes data streams from a network of groundwater Internet-of-Things (IoT) sensors deployed at the Savannah River Site (SRS) for prediction modeling. This allows human experts to focus on analysis and decision-making, ultimately leading to better environmental outcomes.The framework employs multivariate time-series forecasting methods to study and model the behavior of varying chemical analytes. The continuous learning process is enabled by utilizing deep learning techniques. It allows the framework to become more nuanced in its analysis over time, adapting to the specific characteristics of the environmental site and the evolving nature of contaminant behavior. Deep learning models known for sequence modeling, LSTM, and Transformers are employed for time series forecasting. Data processing and structuring are essential components significantly impacting the final model's performance. This hypothesis was proven by presenting a comparative analysis of model performance with processed and unprocessed data. The feature engineering approach utilized was the Discrete Wavelet Transform, which works well with time series data.

Discrete Wavelet Transform (DWT)↗
DOE OSTI2023

Estimation of Participation Factors Using the Synchrosqueezed Wavelet Transform

This paper proposes a data-driven approach for estimating participation factors for a power system using only simulation results on selected disturbances. The approach is purely response-based and does not need a linearized system model for eigen-analysis, which makes it applicable to systems whose detailed, complete mathematical models are not available. Considering the unavoidable nonlinearity as exhibited in the transient period of a system response, the Synchrosqueezed Wavelet Transform is applied to simulated responses for modal analysis to obtain participation factors. Based on simulations of Kundur's two-area system using both the electromagnetic transient model and phasor model, the participation factors estimated by the proposed approach are compared with two other signal processing tools, the Prony analysis and continuous wavelet transform, and are also benchmarked with conventional model-based participation factors.

participation factor↗
DOE OSTI2022

Predictive Direct DC-Link Control for 7.2 kV Three-Port Low-Inertia Solid-State Transformer With Active Power Decoupling

Promising for applications including renewable energy and electric vehicle fast charging, a medium-voltage (MV) solid-state transformer (SST) typically has multiple modules series stacked, which requires the modules to be single phase. One critical issue of the single-phase SST is the double-line-frequency power ripple. Traditionally, large passives are used to buffer the ripple, resulting in significantly increased volume and cost. This article for the first time proposes active power decoupling (APD) for the SST and a predictive direct DC-link control method, using a current-source single-stage SST as an example. An electrolytic capacitor-less buffer port is used to absorb the ripple, which tolerates up to a 30% voltage ripple for small capacitance. The APD SST control is challenging. First, the current-source SST realizes isolation, DC link, and multiport in a single stage. Second, different from conventional SSTs or APD converters, the low-inertia DC link in this SST has a 40% switching ripple, which is difficult to stabilize. To address the control challenge, a direct DC-link control architecture and a predictive control method are proposed. Simulation and experimental results verify the proposed control method on an MV SiC modular soft-switching solid-state transformer (M-S4T) prototype. Here, the proposed APD reduces the SST volume by 53.8%. Importantly, the proposed concept is not limited to the M-S4T but is generic to other SSTs or APD converters.

14 SOLAR ENERGY↗