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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An experimental study of the existence regions and non-linear interactions of drift wave and Kelvin–Helmholtz instabilities in a linear magnetized plasma

Experimental observations of the intrinsic excitation and non-linear interactions of drift wave (DW) and Kelvin–Helmholtz (KH) instabilities in a linear magnetized plasma column are presented. The experiments are carried out in the inverse mirror plasma experimental device (IMPED)—a cylindrical, magnetized, linear plasma machine designed to study low-frequency waves and instabilities in plasma. A novel feature of IMPED is the ability to control plasma profiles, such as the density n(r)⁠, electron temperature T e (r)⁠, and plasma potential V p (r) by varying the ratio Rm of the magnetic field in the main chamber to that in the source chamber. At high values of Rm, higher-density gradient scale length promotes the drift wave (DW) instability while lower Rm value results in a higher radial electric field, inducing a sheared poloidal flow that enhances the dominance of the Kelvin–Helmholtz (KH) mode. The background and fluctuating plasma parameters are characterized using various configurations of multiple in situ electric probes at different spatial locations to quantify the local gradients that excite the low-frequency primary instabilities. Statistical, spectral, and bispectral analysis of the density and potential signals help identify these modes in terms of wave number, frequency, phase, and amplitude and also delineate the nature of their non-linear interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Global mean frequency increases of daily and sub-daily heavy precipitation in ERA5

Abstract Changes in heavy precipitation frequency can be viewed as a change in the event return period, a common metric of risk. Compared with intensity, frequency changes are less well-studied and past work has largely been constrained to analysis of well-instrumented regions. We exploit the latest ERA5 reanalysis and its global hourly accumulations at 1/4° spatial resolution and apply a metric that captures frequency changes across both wet and dry regions. According to ERA5 and in a global average sense, during 1989–2018, hourly events that occurred once per year in 1979–1988 increased in frequency by 71 (53–93, 95% range) %, while the one day per year heavy event frequency increased by 44 (37–54) %. Thus, hourly events that occurred once per year in the baseline decade are on track to double in frequency by 2021–2030, and the daily events by 2047–2056. Furthermore, our results replicate prior findings that relative frequency increases are larger for increasingly rare events, and for the first time we quantify that mean frequency increases have been greater over ocean than land. Ocean increases are larger by factors of 3.0 and 2.1 for the hourly and daily events that occurred once per year in 1979–1988, respectively.

Environmental Sciences & Ecology↗
DOE OSTI2021

Dynamical Large Deviations of Two-Dimensional Kinetically Constrained Models Using a Neural-Network State Ansatz

We use a neural-network ansatz originally designed for the variational optimization of quantum systems to study dynamical large deviations in classical ones. We use recurrent neural networks to describe the large deviations of the dynamical activity of model glasses, kinetically constrained models in two dimensions. We present the first finite size-scaling analysis of the large-deviation functions of the two-dimensional Fredrickson-Andersen model, and explore the spatial structure of the high-activity sector of the South-or-East model. These results provide a new route to the study of dynamical large-deviation functions, and highlight the broad applicability of the neural-network state ansatz across domains in physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

PANDA-FES: Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science

Nuclear fusion is a potential source of carbon-free electricity with many concepts in development. The Portable and Adaptable Neutron Diagnostics for Advancing Fusion Energy Science (PANDA-FES) suite has been deployed since 2021 to measure neutron yield, energy, and spatiotemporal source location at two different Z-pinch fusion devices. This diagnostic can be used at a variety of facilities pursuing fusion in the magnetic, inertial, and magneto-inertial regimes. These different regimes have a wide range of time scales from less than 100 ns to a few μ s, neutron yields from 10 6 to 10 11 , and noise environments. Neutron yield is measured through activation of 79 Br and 89 Y with calibrated detectors. Temporal, spatial, and energy dependence of neutrons is measured with scintillators coupled to photomultiplier tubes (PMTs). Experimental setups and data analysis methods have been developed for these conditions. Finally, neutron yield, neutron energy anisotropy, and spatiotemporal evolution of the source have been measured.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗
DOE OSTI2020

Grid generation, coupling strategies, and spatially-dependent time stepping for ocean-tidal/estuary systems and other ESM components (Final Report)

There are many multiple scale issues in the ocean modeling, including different mesh resolutions (local) and different physical processes (global). In order to gain efficiency and fidelity in modern ESMs, it is vital to develop high quality, highly nonuniform meshes and spatially-dependent time stepping strategies for coupling various climate system components. The USC/FSU team has worked on the design, analysis, and implementation of fast CVT grid generation and novel time- stepping schemes that could address all the requirements for global and regional ocean models on highly nonuniform meshes.

58 GEOSCIENCES↗
DOE OSTI2023

Characterization of Rare-Earth Elements in Lignite Coal of the Williston Basin: Past Efforts and Ongoing Work

Rare-earth elements (REEs) have been a subject area of high interest for their unique properties. REEs are crucial materials used in an incredible array of consumer goods, energy system components, and military defense applications. While the United States has one operating REE mine, the product is sent overseas for refining into usable metals making the United States 100% import-reliant on these critical materials. This has led the Federal Government to declare the REE market an issue of national security. The Energy and Environmental Research Center (EERC) under funding provided by the Department of Energy (DOE) has undertaken efforts to determine if the lignite coal found in the Williston Basin has the potential to be an ore body containing sufficient quantities of REEs and Critical Minerals (CM) for extraction and processing. In one such effort, the EERC collected over 400 samples from the Williston Basin lignite coal seams including outcrops as well as active mines. Those efforts have been followed up with ongoing work under the U.S. DOE’s Carbon Ore, Rare Earth and Critical Minerals Initiative (CORE-CM) currently ongoing in the Williston Basin as well as other basins in the United States. This ongoing work in the Williston Basin characterizing REEs in coal has focused on the collection of new sampling and analysis of REEs in coal and building upon previous characterization work. This information is being used to understand the spatial distribution of REEs through mapping and 3D modeling. The goals of these efforts are to better understand the mechanisms for distribution of the REEs in lignite coal as well as their concentration and determine knowledge gaps in characterization and to start to build the database required to understand the potential resource in the Williston Basin.

Feole, Ian K.↗
DOE OSTI2022

ENSO Impact on Winter Precipitation in the Southeast United States through a Synoptic Climate Approach

The ENSO impact on winter precipitation in the Southeast United States was analyzed from the perspective of daily weather types (WTs). We calculated the dynamic contribution associated with the change in frequency of the WTs and the thermodynamic contribution due to changes in the spatial patterns of the environmental fields of the WTs. Six WTs were obtained using a k-means clustering analysis of 850 hPa winds in reanalysis data from November to February of 1948–2022. All the WTs can only persist for a few days. The most frequent winter weather type is WT1 (shallow trough in Eastern U.S.), which can persist or likely transfer to WT4 (Mississippi River Valley ridge). WT1 becomes less frequent in El Niño years, while the frequency of WT4 does not change much. WTs 2–6 correspond to a loop of eastward propagating waves with troughs and ridges in the mid-latitude westerlies. Three WTs with a deep trough in the Southeast U.S., which are WT2 (east coast trough), WT3 (off east coast trough) and WT6 (plains trough), become more frequent in El Niño years. The more frequent deep troughs (WTs 2, 3 and 6) and less frequent shallow trough (WT1) result in above-normal precipitation in the coastal Southeast U.S. in the winter of El Niño years. WT5 (off coast Carolina High), with maximum precipitation extending from Mississippi Valley to the Great Lakes, becomes less frequent in El Niño years, which corresponds to the below-normal precipitation from the Great Lakes to Upper Mississippi and Ohio River Valley in El Niño years, and vice versa in La Niña years. The relative contribution of the thermodynamic and dynamic contribution is location dependent. On the east coast, the two contributions are similar in magnitude.

Qian, Jian-Hua↗
DOE OSTI2024

Strategic Siting of Direct Air Capture Facilities in the United States

Direct air capture (DAC) systems that capture carbon dioxide (CO 2 ) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO 2 emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO 2 . A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO 2 concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO 2 along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO 2 reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

The Eel Pulsar Wind Nebula: A PeVatron-candidate Origin for HAWC J1826-128 and HESS J182-130

HAWC J1826–128 is one of the brightest Galactic TeV γ-ray sources detected by the High Altitude Water Cherenkov (HAWC) observatory, with photon energies extending up to nearly ~100 TeV. This HAWC source spatially coincides with the H.E.S.S. TeV source HESS J1826–130 and the "Eel" pulsar wind nebula (PWN), which is associated with the GeV pulsar PSR J1826–1256. In the X-ray band, Chandra and XMM-Newton revealed that the Eel PWN is composed of both a compact nebula (~15'') and diffuse X-ray emission (~6' × 2') extending away from the pulsar. Our NuSTAR observation detected hard X-ray emission from the compact PWN up to ~20 keV and evidence of the synchrotron burn-off effect. In addition to the spatial coincidence between HESS J1826–130 and the diffuse X-ray PWN, our multiwavelength spectral energy distribution (SED) analysis using X-ray and γ-ray data establishes a leptonic origin of the TeV emission associated with the Eel PWN. Furthermore, our evolutionary PWN SED model suggests (1) a low PWN B-field of ~1 μG, (2) a significantly younger pulsar age (t ~ 5.7 kyr) than the characteristic age (τ = 14.4 kyr), and (3) a maximum electron energy of ${E}_{\max }=2$ PeV. The low B-field, as well as the putative supersonic motion of the pulsar, may account for the asymmetric morphology of the diffuse X-ray emission. Our results suggest that the Eel PWN may be a leptonic PeVatron particle accelerator powered by the ~6 kyr old pulsar PSR J1826–1256 with a spin-down power of 3.6 × 10 36 erg s –1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Figuring Out Gas & Galaxies in Enzo (FOGGIE). VI. The Circumgalactic Medium of L * Galaxies Is Supported in an Emergent, Nonhydrostatic Equilibrium

The circumgalactic medium (CGM) is often assumed to exist in or near hydrostatic equilibrium, with the regulation of accretion and the effects of feedback treated as perturbations to a stable balance between gravity and thermal pressure. We investigate global hydrostatic equilibrium in the CGM using four highly resolved L* galaxies from the Figuring Out Gas & Galaxies in Enzo (FOGGIE) project. The FOGGIE simulations were specifically targeted at fine spatial and mass resolution in the CGM (Δx ≲ 1 kpc h –1 and M ≃ 200M ⊙ ). We develop a new analysis framework that calculates the forces provided by thermal pressure gradients, turbulent pressure gradients, ram pressure gradients of large-scale radial bulk flows, centrifugal rotation, and gravity acting on the gas in the CGM. Thermal and turbulent pressure gradients vary strongly on scales of ≲5 kpc throughout the CGM. Thermal pressure gradients provide the main supporting force only beyond ~0.25R 200 , or ~50 kpc at z = 0. Within ~0.25R 200 , turbulent pressure gradients and rotational support provide stronger forces than thermal pressure. More generally, we find that global equilibrium models are neither appropriate nor predictive for the small scales probed by absorption line observations of the CGM. Local conditions generally cannot be derived by assuming a global equilibrium, but an emergent global equilibrium balancing radially inward and outward forces is obtained when averaging over the nonequilibrium local conditions on large scales in space and time. Approximate hydrostatic equilibrium holds only at large distances from galaxies, even when averaging out small-scale variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
DOE OSTI2025

Analysis of streaked images of x-ray self-emission in laser-driven spherical implosions

Imaging of x-ray self-emission provides a powerful in situ measurement of the spatial and temporal evolution of high-energy-density plasmas. However, interpretation of these measurements requires detailed understanding of the data-generating process. This work presents a case study in the interpretation of x-ray self-emission data for the specific application of streaked one-dimensional slit imaging of spherical laser-driven implosions. A comprehensive generative model of the streaked slit-imaging diagnostic is developed including detailed treatments of the radiation transfer, photometrics, and photostatistics associated with the measurement. The model is used to generate realistic synthetic streaked images and to analyze experimental streaked images to extract important physical quantities of interest. An example analysis of streaked images from implosion experiments on the OMEGA laser is presented, where the model developed in this work is used to constrain the trajectory and peak velocity of the implosion using Bayesian inference.

Bayesian inference↗
DOE OSTI2022

Quantifying the Influence of Defects on Selectivity of Electrodes Encapsulated by Nanoscopic Silicon Oxide Overlayers

Encapsulation of electrocatalysts and photocatalysts with semipermeable nanoscopic oxide overlayers that exhibit selective transport properties is an attractive approach to achieve high redox selectivity. However, defects within the overlayers-such as pinholes, cracks, or particle inclusions-may facilitate local high rates of parasitic reactions by creating pathways for facile transport of undesired reactants to exposed active sites. Scanning electrochemical microscopy (SECM) is an attractive method to determine the influence of defects on macroscopic performance metrics thanks to its ability to measure the relative rates of competing electrochemical reactions with high spatial resolution over the electrode. Here, we report the use of SECM to determine the influence of overlayer defects on the selectivity of silicon oxide (SiOx) encapsulated platinum thin-film electrocatalysts operated under conditions where two competing reactions-the hydrogen evolution and Fe(III) reduction reactions-can occur. After an SECM methodology is described to determine spatially resolved selectivity, representative selectivity maps are correlated with the location of defects that are characterized by optical, electron, and atomic force microscopies. This analysis reveals that certain types of defects in the oxide overlayer are responsible for ∼60-90% of the partial current density toward the undesired Fe(III) reduction reaction. By correcting for defect contributions to Fe(III) reduction rates, true Fe(III) permeability values for the SiOxoverlayers were determined to be over an order of magnitude lower than permeabilities determined from analyses that ignore the presence of defects. Lastly, different types of defects were studied revealing that defect morphology can have varying influence on both redox selectivity and calculated permeability. This work highlights the need for spatially resolved measurements to evaluate the performance of oxide-encapsulated catalysts and understand their performance limits.

25 ENERGY STORAGE↗
DOE OSTI2022

Oblique and rippled heliosphere structures from the Interstellar Boundary Explorer

Abstract Past analysis has shown that the heliosphere structure can be deduced from correlations between long-scale solar wind pressure evolution and energetic neutral atom emissions. However, this required spatial and temporal averaging that smoothed out small or dynamic features of the heliosphere. In late 2014, the solar wind dynamic pressure increased by roughly 50% over a period of 6 months, causing a time and directional-dependent rise in around 2–6 keV energetic neutral atom fluxes from the heliosphere observed by the Interstellar Boundary Explorer. Here, we use the 2014 pressure enhancement to provide a simultaneous derivation of the three-dimensional heliospheric termination shock (HTS) and heliopause (HP) distances at high resolution from Interstellar Boundary Explorer measurements. The analysis reveals rippled HTS and HP surfaces that are oblique with respect to the local interstellar medium upwind direction, with significant asymmetries in the heliosphere structure compared to steady-state heliosphere models. We estimate that the heliosphere boundaries contain roughly ten astronomical unit-sized spatial variations, with slightly larger variations on the HTS surface than the HP and a large-scale, southwards-directed obliquity of the surfaces in the meridional plane. Comparisons of the derived HTS and HP distances with Voyager observations indicate substantial differences in the heliosphere boundaries in the northern versus southern hemispheres and their motion over time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2022

Broadband piezoelectric energy harvesting microgyroscopes: Design and nonlinear analysis

Small devices in remote or difficult-to-reach areas can benefit from harvesting energy from mechanical wasted energy, which reduces the requirement for a new power source. A multi-purpose energy harvesting microgyroscope system based on piezoelectric materials is suggested. The necessity of taking spatially varying electrostatic forces is examined. Considering the effects of the system's width and thickness, DC voltage, and angular speed the systems inherent frequencies are found. The partial differential equations describing the system's dynamics are numerically solved by using the differential quadrature method. Further, the numerical analysis enables to identify the optimal system design for broadband energy harvesting. The simulation results reveal that a system with a non-symmetric beam design is adequate for broadband energy harvesting. This is associated with the applied DC voltage, which may be modified to improve the broadband frequency of the system. It is concluded that the nonlinear softening effects create a broadband frequency response with high voltage output. However, DC and AC voltages need to be carefully selected in order to avoid the dynamic pull-in.

30 DIRECT ENERGY CONVERSION↗