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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
DOE OSTI2025

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1977

Characterization of terrestrial service environments - The simultaneous occurrence of combined conditions of solar insolation and climatic variables

Computational methods for occurrences of combined environmental and pollution variables are compared. General statistical data and diurnal statistics on 24 environmental variables are treated. Combinations of variables dealt with include: air temperature, relative humidity, wind speed, total insolation; air temperature and weather event (rain, fog); air pollutant and weather event; wind speed, wind direction, and weather event; air temperature, total insolation, and weather event; air temperature, relative humidity, wind speed, computed direct insolation levels; air temperature, relative humidity, air pollution.

Thomas, R. E.↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1980

Atmospheric variability and air-sea interaction

The topics studied include: (1) processing of Northern Hemispheric precipitation data, in order to fill in the transition seasons to provide a continuous 40 year data base on the variability of continental precipitation; (2) comparison of seasonally averaged fields of sea surface temperature obtained from ship observations in the North Atlantic and North Pacific in 1970 with the corresponding fields inferred from satellite observations; (3) estimation of seasonal average of total precipitable water at those admittedly few oceanic stations where repeated vertical soundings were made in 1970 and comparison with corresponding values inferred from satellite measurements; (4) comparison of seasonally averaged evaporation fields determined from ground based observations in 1970 with the field of divergence of the seasonal total horizontal water vapor flux inferred from satellite total water measurements and NMC wind data for the lower troposphere; (5) examination of meaning of convection-inversion index.

Middleton, J. W.↗
NASA NTRS2012

Psychophysiological Assessment of Fatigue in Commercial Aviation Operations

The overall goal of this study is to improve our understanding of crew work hours, workload, sleep, fatigue, and performance, and the relationships between these variables on actual flight deck performance. Specifically, this study will provide objective measures of physiology and performance, which may benefit investigators in identifying fatigue levels of operators in commercial aviation and provide a way to better design strategies to limit crew fatigue. This research was supported by an agreement between NASA Ames Research Center and easyJet Airline Company, Ltd., Luton, UK. Twenty commercial pilots volunteered to participant in the study that included 15 flight duty days. Participants wore a Zephyr Bioharness ambulatory physiological monitor each flight day, which measured their heart rate, respiration rate, skin temperature, activity and posture. In addition, pilots completed sleep log diaries, self-report scales of mood, sleepiness and workload, and a Performance Vigilance Task (PVT). All data were sent to NASA researchers for processing and analyses. Heart rate variability data of several subjects were subjected to a spectral analysis to examine power in specific frequency bands. Increased power in low frequency band was associated with reports of higher subjective sleepinesss in some subjects. Analyses of other participants data are currently underway.

Hernandez, Norma↗
NASA NTRS1992

SeaWiFS Technical Report Series. Volume 7: Cloud screening for polar orbiting visible and infrared (IR) satellite sensors

Methods for detecting and screening cloud contamination from satellite derived visible and infrared data are reviewed in this document. The methods are applicable to past, present, and future polar orbiting satellite radiometers. Such instruments include the Coastal Zone Color Scanner (CZCS), operational from 1978 through 1986; the Advanced Very High Resolution Radiometer (AVHRR); the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), scheduled for launch in August 1993; and the Moderate Resolution Imaging Spectrometer (IMODIS). Constant threshold methods are the least demanding computationally, and often provide adequate results. An improvement to these methods are the least demanding computationally, and often provide adequate results. An improvement to these methods is to determine the thresholds dynamically by adjusting them according to the areal and temporal distributions of the surrounding pixels. Spatial coherence methods set thresholds based on the expected spatial variability of the data. Other statistically derived methods and various combinations of basic methods are also reviewed. The complexity of the methods is ultimately limited by the computing resources. Finally, some criteria for evaluating cloud screening methods are discussed.

Darzi, Michael↗
DOE OSTI2023

Bayesian merging of numerical modeling and remote sensing for saltwater intrusion quantification in the Vietnamese Mekong Delta

Saltwater intrusion has become one of the most concerning issues in the Vietnamese Mekong Delta (VMD) due to its increasing impacts on agriculture and food security of Vietnam. Reliable estimation of salinity plays a crucial role to mitigate the impacts of saltwater intrusion. Here, this study developed a hybrid technique that merges satellite imagery with numerical simulations to improve the estimation of salinity in the VMD. The salinity derived from Landsat images and by numerical simulations was fused using the Bayesian inference technique. The results indicate that our technique significantly reduces the uncertainties and improves the accuracy of salinity estimates. The Nash–Sutcliffe coefficient is 0.74, which is much higher than that of numerical simulation (0.63) and Landsat estimation (0.6). The correlation coefficient between the ensemble and measured salinity is relatively high (0.88). The variance of the ensemble salinity errors (5.0 ppt 2 ) is lower than that of Landsat estimation (10.4 ppt 2 ) and numerical simulations (9.6 ppt 2 ). The proposed approach shows a great potential to combine multiple data sources of a variable of interest to improve its accuracy and reliability wherever these data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NGEE Arctic Phase 4 Plant Functional Type Framework for Pan-Arctic Vegetation

The NGEE-Arctic research team identified a common set of hierarchical plant functional types (PFTs) for pan-arctic vegetation that we will use across our research activities. Interdisciplinary work within a large team requires agreement regarding levels of functional organization so that knowledge, data, and technologies can be shared and combined effectively. The team has identified plant functional types as a crucial area where such interoperability is needed. PFTs are used to represent plant pools and fluxes within models, summarize observational data, and map vegetation across the landscape. Within each of these applications, varying levels of PFT specificity are needed according to the specific scientific research goal, computational limitations, and data availability. By agreeing on a specific hierarchical framework for grouping variables in our vegetation data, we ensure the resulting research products will be robust, flexible, and scalable. In this document, we lay out the agreed upon PFT framework with definitions and references to existing literature. Table 1 included in the "NGA700_Phase4PFTFramework_about*" file outlines the relationship between NGEE-Arctic Phase 4, Tier 1 PFTs and the PFTs used within prominent arctic literature as well as publications by the NGEE-Arctic team during phases 1-3.This dataset consists of a table detailing a hierarchical PFT framework that spans 4 tiers with the most granular PFTs listed in tier 1 and the most general PFTs in tier 4. The PFTs within each tier has a single column in the dataset where the PFTs are named and a separate column where the characteristics used to define that PFT are listed. Grey fill of the cells is used to indicate where a given PFT starts to “lose” tier 1 details as you look from left to right. Note the excel file has merged cells to indicate grouping of PFTs across the Tiers- it will not translate into a delimited filetype (.csv, .txt, etc) without modification thus the hierarchical PFT framework table is available in three different file formats: 1) NGA700_Phase4PTS.xlsx – maintains the merged cells and grey fill; 2) NGA700_Phase4PTS.csv – merged cells are split, and grey fill is removed; 3) NGA700_Phase4PTS.pdf – image of the table with merged cells and grey fill. Metadata document included as a *.pdf and file-level metadata and data dictionary as *.csv files.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

OKeefe, Matthew↗
NASA NTRS1999

Temperature Variability Associated with the Middle Atmosphere Electrodynamics (MAE-1) Campaign

Meteorological rockets launched during the Middle Atmosphere Electrodynamics (MAE-1) Campaign in October 1980 from Andoya Rocket Range (ARR), Norway, exhibited large and unexpected temperature variability. Temperatures were found to vary as much as 20 C within a few hours and demonstrated a similar type of variability from one day to the next. Following examination of the reduced rocketsonde profiles the question was raised whether the observed variability was due to natural atmospheric variability or instrument malfunction. Small-scale variability, as observed, may result from one or multiple sources, e.g., intense storms upstream from the observing site, orography such as mountain waves off of the Greenland Plateau, convective activity, gravity waves, etc. Arranging the observations spaced over time showed that the perturbations moved downward. Prior to MAE-1 very few small rocketsonde measurements had been launched from ARR, thus the quality of the initial measurements in early October caused concern when the large variability was noted. We discuss the errors of the rocketsonde measurements, graphically review the nature of the variability observed, compare the data with other measurements, and postulate a possible cause for the variability.

Schmidlin, F. J.↗
NASA NTRS1984

Modular approach for satellite communication ground terminals

The trend in satellite communications is toward completely digital, time division multiple access (TDMA) systems with uplink and downlink data rates dictated by the type of service offered. Trunking terminals will operate in the 550 MBPS (megabit per second) region uplink and downlink, whereas customer premise service (CPS) terminals will operate in the 25 to 10 MBPS region uplink and in the 200 MBPS region downlink. Additional criteria for the ground terminals will be to maintain clock sychronization with the system and burst time integrity to within a matter of nanoseconds, to process required order-fire information, to provide adaptive data scrambing, and to compensate for variations in the user input output data rates, and for changes in range in the satellite communications links resulting from satellite perturbations in orbit. To achieve the required adaptability of a ground terminal to the above mentioned variables, programmable building blocks can be developed that will meet all of these requirements. To maintain system synchronization, i.e., all bursted data arriving at the satellite within assigned TDMA windows, ground terminal transmit data rates and burst timing must be maintained within tight tolerances. With a programmable synchronizer as the heart of the terminal timing generation, variable data rates and burst timing tolerances are achievable. In essence, the unit inputs microprocessor generated timing words and outputs discrete timing pulses.

Gould, G. R.↗
NASA NTRSDate not supplied

Deriving Climate Change Signal from Hyperspectral Sounders Using Spectral Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric temperature, water vapor and trace gas vertical profiles. We have developed a radiometrically consistent spectral fingerprinting method to derive climate change signals from Aqua AIRS/AMSU and S-NPP CrIS/ATMS data. The climate variables include temperature and water vapor profiles, cloud, trace gases, and surface skin temperature. The radiative kernels obtained via a single field of view physical retrieval algorithm under all-sky conditions. A key component to this work is a Principal Component-based Radiative Transfer Model (PCRTM). It is 4 orders of magnitude faster than a line-by-line radiative transfer model while keeping a similar accuracy (0.03 K RMS errors with close to zero bias). The PCRTM includes multiple scattering of clouds and non-thermodynamics equilibrium of CO2 in the RT calculations. Instead of quantifying the radiometric differences between AIRS/AMSU and CrIS/ATMS measurements directly using Simultaneous Nadir Overpass (SNO) or Double Difference Technique (DDT), we use the radiometric consistent fingerprinting scheme to derive two sets of space-time averaged anomalies from the Level 1 data of AIRS/AMSU and CrIS/ATMS. The derived anomalies in geophysical space will form a long-term, stable, and continuous climate data record. We can further infer the causes of any offset or drift by studying the differences between two overlapping data sets. For example, the offset in surface skin temperature anomaly time series will most likely caused by the Blackbody temperature calibration errors of the sounder instruments.

climate↗
NASA NTRS1989

NH3 column abundances over Lauder, New Zealand

Gaseous NH3 has been observed in the atmosphere over central New Zealand with infrared absorption spectra. The amount of NH3 shows marked variability, which is strongly correlated with time of day and season. The pattern is similar to data obtained in Denver, Colorado, but is much more variable than data from Hampton, Virginia. The rapid variability indicates a residence time of 8 hours in some cases.

Murcray, Frank J.↗
NASA NTRS1993

Postprocessing of satellite altimetry return signals for improved sea surface topography accuracy

Retracked southern ocean data from the first 34 repeat cycles of the Geosat Exact Repeat Mission are analyzed. The difference between the surface heights calculated from the retracked data and the original on-board estimate is less than 10 cm for significant wave heights (SWH) lower than 10 m but increases to about 1.0 m at an SWH of 18 m. The electromagnetic (EM) bias coefficient calculated using the retracked data is generally slightly less than that using the unretracked data and does not decrease as much with SWH as to the EM bias coefficients calculated from the unretracked data. A map of the sea surface height variability of the southern ocean created using the retracked data shows differences from variability maps created using the unretracked data in regions of high wave heights. This study shows that retracking will improve altimeter precision.

Brenner, A. C.↗
NASA NTRS1988

Toward an improved global network for determination of tropospheric ozone climatology and trends

Current data on ozone variability on daily, monthly, annual, and interannual time scales were used for a standard trend-prediction analysis. Using the results of this analysis, together with a quantitative theory that defines the 'effectively sampled region' for an observing station, a definition was developed for a global network capable of determining ozone climatology and ozone trends with uncertainties not above 1 percent per year at the 95 percent confidence level. The definition indicates a need for at least a doubling of the present number of stations; the areas where more stations are most needed include the oceans, most of Asia, Africa, and South America. It is pointed out that differential absorption lidar ozone instruments have the potential for far more frequent measurements of ozone vertical profiles and, hence, potentially more accurate climatology and trend determinations than the ozonesondes; however, the differential-absorption lidar ozone measurements may produce a biased data set above the cloud base.

Prinn, Ronald G.↗
DOE OSTI2026

Spatiotemporal Dynamics of the Relative Abundance of Soil Nutrient‐Degrading Enzyme‐Encoding Genes Across Continental US Ecoregions

Understanding the spatiotemporal patterns in the relative abundance of soil extracellular enzyme‐encoding genes is critical for predicting microbial responses to environmental change and their potential role in nutrient cycling. Yet, integrating novel metagenomic observations with spatiotemporal environmental gradients to infer regional patterns and future trajectories has remained unclear. To address this gap, we applied a machine learning (ML) approach, integrating soil metagenomic data with environmental variables—soil properties, topography, vegetation, and climate—to predict the relative abundance of enzyme‐encoding genes for soil carbon (C), nitrogen (N), and phosphorus (P) across surface soils of the continental United States. We assessed potential responses under future emission scenarios (SSP2‐4.5 and SSP5‐8.5) by comparing a baseline (1985–2014) to a future period (2071–2100). The ML model explained 57%–63% of baseline variation. Precipitation was identified as the most influential factor for the relative abundance of C‐ and N‐degrading enzyme‐encoding genes, while slope length, representing horizontal distance that water can travel downslope, was the primary driver for P‐degrading enzyme‐encoding genes abundance. Projections revealed spatially heterogeneous shifts across continental US ecoregions: the relative abundance of C‐ and N‐degrading enzyme‐encoding genes decreased in wetter ecoregions and increased in drier ecoregions under future climate, while P‐degrading enzyme‐encoding genes abundance decreased significantly in semiarid and Mediterranean ecoregions. This study demonstrates the utility of metagenomic data for mapping soil genetic potential and predicting its regional response to environmental change, to inform ecosystem management strategies.

extracellular enzyme-encoding genes↗
NASA NTRS2019

On the Calculation of Exact Cumulative Distribution Statistics for Burgers Equation

A mathematical procedure is presented for the calculation of exact cumulative distribution statistics for a viscosity-free variant of Burgers nonlinear partial differential equation (PDE) in one space dimension and time subject to sinusoidal initial data with uncertain (random variable) amplitude or phase shift. Analytical solutions of nonlinear PDEs with uncertain initial and/or boundary data are invaluable benchmarks in assessing approximate uncertainty quantification techniques. The Burgers equation solution with uncertain initial data results in nonsmooth solution behavior in both physical and random variable dimensions which provides a severe test for approximate uncertainty quantification techniques. Mathematical proofs are provided to verify that exact cumulative distribution statistics can be systematically and robustly obtained for all forward time.

Burgers↗