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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf (2020)

This report presents a state-of-the-art wind resource data set produced by the National Renewable Energy Laboratory (NREL) for the California Pacific Outer Continental Shelf (OCS). This data set replaces NREL's Wind Integration National Dataset (WIND) Toolkit for the California OCS, which was produced and released publicly in 2013 and is currently the principal data set used by stakeholders for wind resource assessment in the continental United States.

17 WIND ENERGY↗
NASA NTRS2002

Comparison of ScaRaB, GOES 8, Aircraft, and Surface Observations of the Absorption of Solar Radiation by Clouds

Data obtained by the Scanner for Radiation Budget (ScaRaB) instrument on the Meteor 3 satellite have been analyzed and compared to satellite (GOES 8), aircraft (Radiation Measurement System, RAMS), and surface (Baseline Solar Radiation Network (BSRN), Solar and Infrared Observations System (SIROS), and RAMS) measurements of irradiance obtained during the Atmospheric Radiation Measurements Enhanced Shortwave Experiment (ARESE). It is found that the ScaRaB data covering the period from March 1994 to February 1995 (the instrument's operational lifetime) indicate excess absorption of solar radiation by the cloudy atmosphere in agreement with previous aircraft, surface, and GOES 8 results. The full ScaRaB data set combined with BSRN and SIROS surface observations gives an average all-sky absorptance of 0.28. The GOES 8 data set combined with RAMS surface observations gives an average all-sky absorptance of 0.26. The aircraft data set (RAMS) gives a mean all-sky absorptance of 0.24 (for the column between 0.5 and 13 km).

Pope, Shelly K.↗
DOE OSTI2024

Plan Position Indicator Hydrometeor Field Statistics (PPIHYD) Evaluation Data Product Version 1.0

The PPIHYD evaluation data product provides distinct hydrometeor field statistics calculated from U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility scanning radar plan position indicator (PPI) scans. These statistics include the equivalent reflectivity factor and Doppler spectral width percentiles, min/max values, and first four moments (mean, standard deviation, skewness, and kurtosis) of distinct hydrometeor features (clustered hydrometeor fields). Statistics also include morphological properties, water content and precipitation rate parameterization-based estimates, and thermodynamic properties interpolated using the Interpolated Sonde value-added product (INTERPSONDE VAP). The data set is organized in tabular form and is accompanied by mask arrays with corresponding indices. This straightforward file structure simplifies scanning radar data processing and renders this data set useful for process understanding and model evaluation studies. This report describes the data set and its processing algorithm and provides some examples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Transferring a Molecular Foundation Model for Polymer Property Predictions

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. Further, state-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Magnetic field properties of Jupiter's tail at distances from 80 to 7500 Jovian radii

The results of a detailed study of the magnetic field data on the near and distant Jovian magnetotail from both Voyager 1 and 2 are presented. The spacecraft trajectories and the data are reviewed, and four distant tail encounters are examined and compared with the corresponding Voyager 1 interplanetary data sets. A power spectral analysis of both the near and distant tail intervals is given, and some of the differences between the tail encounters and the power spectra of these control data sets are discussed. Two solar wind or magnetosheath data sets obtained when Voyager 2 was not in the distant tail are analyzed. These more 'normal' solar wind conditions are contrasted with those reflected in both the Voyager 2 distant tail encounters and the conditions monitored by Voyager 1 farther downstream.

Goldstein, M. L.↗
DOE OSTI2026

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗
DOE OSTI2020

Estimating vehicle fuel economy from overhead camera imagery and application for traffic control

In this work, we explore the ability to estimate vehicle fuel consumption using imagery from overhead fisheye lens cameras deployed as traffic sensors. We utilize this information to simulate vision-based control of a traffic intersection, with a goal of improving fuel economy with minimal impact to mobility. We introduce the ORNL Overhead Vehicle Dataset (OOVD), consisting of a data set of paired, labeled vehicle images from a ground-based camera and an overhead fisheye lens traffic camera. The data set includes segmentation masks based on Gaussian mixture models for vehicle detection. We show the dataset utility through three applications: the estimate of fuel consumption based on segmentation bounding boxes, vehicle discrimination for those vehicles with largest bounding boxes, and a fine-grained classification on a limited number of vehicle makes and models using a pre-trained set of convolutional neural network models. We compare these results with estimates based on a large open-source data set based on web-scraped imagery. Finally, we show the utility of the approach using reinforcement learning in a traffic simulator using the open source Simulation of Urban Mobility (SUMO) package. Our results show the feasibility of the approach for controlling traffic lights for better fuel efficiency based solely on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗
NASA NTRS1995

Millimeter and Submillimeter Spectroscopy of Molecules of Atmospheric Importance

In our proposal we laid out work in three areas of relevance to atmospheric science: millimeter and submillimeter spectroscopy, variable temperature pressure broadening, and band and intensity measurements in the FIR. Below we will briefly discuss our progress during the second year of this project. In our millimeter and submillimeter (mm/submm) spectroscopic work, one of our goals has been to work towards the unification of the rotational (primarily obtained by mm/submm techniques) and rotational-vibrational (primarily obtained by infrared techniques) data sets in the context of theoretically well founded models which take advantage of the strengths of the data from each experimental technique. From the point of view of the development of the optimal data base for atmospheric observations, this is clearly a desirable goal. During the first year of this project we did an analysis of a weighted, mixed infrared and mm/submm data set of the n = 0, 1, and 2 torsional states of the ground vibrational state of HOOH. The purpose of this work is to provide a unified understanding of the spectrum, which is applicable in both the rotational and rotational - vibrational regimes. We have succeed in doing this in the context of a single weighted fit which accounts for both data sets to their respective experimental uncertainty (-0.1 and 10 MHz, respectively). Additionally, we have now done a similar analysis on the n = 0 torsional state of v(sub 3) and begun a similar analysis on v(sub 6). For several years we have been working on the mm/submm rotational spectra of the many excited vibrational states of HNO3, again with particular emphasis on the relationships between the mm/submm and infrared spectra. During the first year of this project we were able to use mm/submm spectroscopy to fully resolve the torsional splittings in 2 v(sub 9) and v(sub 5), establish a theoretically well founded quantitative relation between them, and show that both have their physical origin in the torsional motion of the v(sub 9) mode.This result has now been incorporated in a recent reanalysis of the infrared spectrum and has resulted in improved fits - eliminating what was in retrospect a systematic error associated with this previously unknown effect.

DeLucia, Frank C.↗
NASA NTRS1994

Distribution and nature of UV absorbers on Triton's surface

Substantial evidence suggests that a UV Spectrally Absorbing Material (UV-SAM) exists on Triton's surface. This evidence is found in the positive slope in Triton's spectrum from the UV to the near-IR, and the increasing contrast in Triton's light curve in the blue and UV. Although it is now widely-thought that UV-SAM's exist on Triton, little is known about their distribution and spectral properties. The goal of this NDAP Project is to determine the spatial distribution and geological context of the UV-SAM material. We hope to determine if UV-SAM's on Triton are correlated with geologic wind streaks, craters, calderas, geomorphic/topographic units, regions containing (or lacking) volatile frosts, or some other process (e.g., magnetospheric interactions). Once the location and distribution of UV-SAM's has been determined, further constraints on their composition can be made by analyzing the spectrographic data set. To accomplish these goals, various data sets will be used, including Voyager 2 UV and visible images of Triton's surface, IUE and HST spectra of Triton, and a geologic map of the surface based on Voyager 2 and spectrophotometric data. The results of this research will be published in the planetary science literature.

Stern, S. Alan↗
NASA NTRS1995

Distribution and nature of UV absorbers on Trition's surface

Substantial evidence suggests that a UV (ultraviolet) Spectrally Absorbing Material (UV-SAM) exists on Triton's surface. This evidence is found in the positive slope in Triton's spectrum from the UV to the near-IR, and the increasing contrast in Triton's light curve in the blue and UV. Although it is now widely-thought that UV-SAM's exist on Triton, little is known about their distribution and spectral properties. The goal of this NDAP Project is to determine the spatial distribution and geological context of the UV-SAM material. We hope to determine if UV-SAM's on Triton are correlated with geologic wind streaks, craters, calderas, geomorphic/topographic units, regions containing (or lacking) volatile frosts, or some other process (e.g., magnetospheric interactions). Once the location and distribution of UV-SAM's has been determined, further constraints on their composition can be made by analyzing the spectrographic data set. To accomplish these goals, various data sets will be used, including Voyager 2 UV and visible images of Triton's surface, IUE and HST spectra of Triton, and a geologic map of the surface based on Voyager 2 and spectrophotometric data. The results of this research will be published in the planetary science literature.

Stern, S. Alan↗
NASA NTRS1995

Distribution and nature of UV absorbers on Triton's surface

Substantial evidence suggests that a UV spectrally Absorbing Material (UV-SAM) exists on Triton's surface. This evidence is found in the positive slope in Triton's spectrum from the UV to the near-IR, and the increasing contrast in Triton's light curve in the blue and UV. Although it is now widely-thought that UV-SAMs exist on Triton, little is known about their distribution and spectral properties. The goal of this NDAP Project is to determine the spatial distribution and geological context of the UV-SaM material. We hope to determine if UV-SAMs on Triton are correlated with geologic wind streaks, craters, calderas, geomorphic/topographic units, regions containing (or lacking) volatile frosts, or some other process (e.g., magnetospheric interactions). Once the location and distribution of UV-SAMs has been determined, further constraints on their composition cable made by analyzing the spectrographic data set. To accomplish these goals, various data sets will be used, including Voyager 2 UV and visible images of Triton's surface, IUE and HST spectra of Triton, and a geologic map of the surface based on voyager 2 and spectrophotometric data. The results of this research will be published in the planetary science literature.

Stern, S. Alan↗
NASA NTRS1999

Generation of Level 3 SMMR and SSM/I Brightness Temperatures for the Period 1978-1999

The NOAA/NASA Pathfinder Program was initially designed to assure that certain key remote sensing data sets of particular significance to global change research were scientifically validated, consistently processed and made readily available to the research community at minimal cost. Through this Program the National Snow and Ice Data Center (NSIDC), University of Colorado has successfully processed, archived and distributed the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) Level 3 (EASE-Grid format) Pathfinder data sets for the period 1978 to 1999. These data are routinely distributed to approximately 150 researchers through various media including CD-ROM, 8 mm tape, ftp and the EOS Information Management System (IMS). At NSIDC these data are currently being applied in the development and validation of algorithms to derive snow water equivalent (NASA NAG5-6636), the mapping of frozen ground and the detection of the onset of melt over ice sheets, sea ice and snow cover. The EASE-Grid format, developed at NSIDC in conjunction with the SMMR-SSM/I Pathfinder project has also been applied to Advanced Very High Resolution Radiometer (AVHRR) and TOVS Pathfinder data, as well as ancillary data such as digital elevation, land cover classification and several in situ data sets. EASE-Grid will also be used for all land products derived from the NASA EOS AMSR-E instrument.

Partington, Kim↗
NASA NTRS2000

BOREAS TF-11 CO2 and CH4 Concentration Data from the SSA-Fen

The BOREAS TF-11 team collected several data sets in its efforts to fully describe the flux and site characteristics at the SSA-Fen site. This data set contains temperature, pH, and concentration profiles of methane and carbon dioxide within the surface 50 cm of peat. The measurements were conducted as part of a 2 x 2 factorial experiment in which we added carbon (300 g/sq m as wheat straw) and nitro-gen (6 g/sq m as urea) to four replicate locations in the vicinity of the TF-11 tower. The data set covers the period from the first week of June 1994 through the second week of September 1994. The data are stored in tabular ASCII files.

Hall, Forrest G.↗
DOE OSTI2023

Main Bearing Replacement and Damage - A Field Data Study on 15 Gigawatts of Wind Energy Capacity

This study seeks to establish a comprehensive baseline of knowledge for the replacement and damage of main bearings in wind turbines. The purpose of this report is to provide a high-level summary of the data set, methodology, and results of this work. Full technical details and an extended analysis will be made available in a future publication. We collected data on main bearing replacements and reported damage from industrial partners based in Europe and the United States. In total, we obtained data for 167 wind power plants, with a combined capacity of 15.3 gigawatts (GW). Most of the data set was comprised of land-based, three-point mount, spherical roller bearings. Within this data set were 689 instances of main bearing replacement. Analysis was undertaken in two parts: first, a statistical analysis of the main bearing time-to-replacement data using survival analysis techniques; second, quantitative and qualitative analyses of the obtained damage information. Our results showed that 10% of a fixed main bearing population would be expected to have been replaced by 10.5 years. This is close to half of the 20-year design value. Fitted parametric distributions then indicated that by year 20, between 22% and 25% of main bearings are expected to have been replaced. Analysis of the damage reports revealed spalling to be the main type of damage listed. The additional presence of surface damage in the collected data indicates that at least part of the spalling cases are likely due to surface-initiated rolling contact fatigue. At this stage is not clear what proportion of spalling cases result from "wear induced", surface-initiated and subsurface-initiated rolling contact fatigue. While this work provides important insights into the current state of main bearing replacements and damage, many questions remain. An ongoing and expanding data collection and analysis effort focused on wind turbine main bearings is therefore recommended.

17 WIND ENERGY↗
NASA NTRS2000

BOREAS TF-11 CO2 and CH4 Flux Data from the SSA-Fen

The BOREAS TF-11 team collected several data sets in its efforts to fully describe the flux and site characteristics at the SSA-Fen site. This data set contains fluxes of methane and carbon dioxide at the SSA-Fen site measured using static chambers. The measurements were conducted as part of a 2 x 2 factorial experiment in which we added carbon (300 g/sq m as wheat straw) and nitrogen (6 g/sq m as urea) to four replicate locations in the vicinity of the TF-11 tower. In addition to siting and treatment variables, it reports air temperature and water table height relative to the average peat surface during each measurement. The data set covers the period from the first week of June 1994 through the second week of September 1994. The data are stored in tabular ASCII files.

Valentine, David W.↗
DOE OSTI2021

Robust verification of stochastic simulation codes

We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. Furthermore, this approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations..

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

A Compilation of Global Bio-Optical in Situ Data for Ocean Colour Satellite Applications – Version Three

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately.

ocean color↗