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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

The first Earth Resources Technology Satellite - Nearly two years of operation

A brief status report is given of the ERTS-1 satellite system as of June, 1974, and some applications of the ERTS-1 images are discussed. The multispectral images make it possible to identify or measure the quality and composition of water, the potential water content of snow, the moisture and possible composition of soils, the types and state of vegetation cover, and factors relating to stresses on the environment. The orthographic view of the earth provided by the satellite makes it possible to rapidly produce thematic maps, on a scale of 1:250,000, of most areas of the world. The regular, repetitive coverage provided by ERTS-1 every 18 days is important in areas such as water-supply and flood-damage studies. The use of ERTS-1 imagery for land-use planning, wetlands surveying, assessing marine resources, and observing processes such as desertification in the African Sahel is discussed.

Nordberg, W.↗
DOE OSTI2025

DFAT: A web-based toolkit for estimating demand flexibility in building-to-grid integration

Demand Flexibility Assessment Tool (DFAT) is an open source web-based tool that estimates the demand flexibility potential of common control strategies in commercial buildings. The toolkit features a demand flexibility estimation tool that contains two calculators, basic and advanced, based on the level of input of customer data. The basic version calculates demand shed metrics for the control strategy “global temperature adjustment” and “cycle on/off compressors” using customer building information, local weather data, and electrical meter data. The advanced version, which uses detailed HVAC equipment data, calculates demand flexibility metrics for control strategies such as static pressure reset, global temperature adjustment, and cycle on/off compressors. In addition to the demand flexibility estimation tool, this toolkit offers a benchmarking tool that helps facility operators, aggregators, and utility resource managers assess demand flexibility opportunities, quantify/verify performance, and compare their performance against that of their peers.

Leong, Michael↗
NASA NTRS2002

CRM Assessment: Determining the Generalization of Rater Calibration Training. Summary of Research Report: Gold Standards Training

The extent to which pilot instructors are trained to assess crew resource management (CRM) skills accurately during Line-Oriented Flight Training (LOFT) and Line Operational Evaluation (LOE) scenarios is critical. Pilot instructors must make accurate performance ratings to ensure that proper feedback is provided to flight crews and appropriate decisions are made regarding certification to fly the line. Furthermore, the Federal Aviation Administration's (FAA) Advanced Qualification Program (AQP) requires that instructors be trained explicitly to evaluate both technical and CRM performance (i.e., rater training) and also requires that proficiency and standardization of instructors be verified periodically. To address the critical need for effective pilot instructor training, the American Institutes for Research (AIR) reviewed the relevant research on rater training and, based on "best practices" from this research, developed a new strategy for training pilot instructors to assess crew performance. In addition, we explored new statistical techniques for assessing the effectiveness of pilot instructor training. The results of our research are briefly summarized below. This summary is followed by abstracts of articles and book chapters published under this grant.

Baker, David P.↗
DOE OSTI2012

Assessment and Mapping of the Riverine Hydrokinetic Resource in the Continental United States

This report describes the methodology and results of the most rigorous assessment to date of the riverine hydrokinetic energy resource in the contiguous 48 states and Alaska, excluding tidal waters. The assessment provides estimates of the gross, naturally available resource, termed the theoretical resource, as well as estimates, termed the technically recoverable resource, that account for selected technological factors affecting capture and conversion of the theoretical resource. The technically recoverable resource does not account for all technical constraints on energy capture and conversion.

hydrokinetic↗
DOE OSTI2013

Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

17 WIND ENERGY↗
DOE OSTI2018

Assessment of Error Sources in the Modeling of POA Irradiance Under Clear-Sky Conditions: Preprint

A new physics-based model, the Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), accurately computes plane-of-array (POA) irradiances in both narrow- and broad wavelength bands within the solar region. The evaluation studies suggest that the new model provides increased accuracy than a model assuming isotropic diffuse solar radiation and an empirical model linking the POA irradiances with long-term surface observations at selected locations. This study anlyzes the surface observations used by FARMS-NIT and is intended to understand the error sources under clear-sky conditions as well as their impact to the performance of FARMS-NIT.

14 SOLAR ENERGY↗
DOE OSTI2014

Assessment of Opportunities for New United States Pumped Storage Hydroelectric Plants Using Existing Water Features as Auxiliary Reservoirs

In this assessment of opportunities for new pumped storage hydroelectric plants performed in support of the U.S. Department of Energy Water Power Program, the characteristics of existing U.S. pumped storage hydroelectric plants (PSHs) are reviewed to define criteria for selecting candidate sites for new pumped storage plants. These characteristics are discussed and are presented in an appendix table. Candidate sites for new PSHs using existing U.S. hydroelectric plants, non-powered dams, greenfield hydroelectric plant sites, and natural waterbodies as base plant locations and natural waterbodies as auxiliary reservoirs are identified using criteria based on PSHs. Characteristics of the candidate sites are discussed and their characteristic features are provided in the appendix tables and spreadsheets.

13 HYDRO ENERGY↗
DOE OSTI2019

A Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT): Part II. The cloudy-sky model

The Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT) reported in Part I of this report is enhanced to include the requirements for cloudy-sky conditions. Surface radiances in 2002 narrow-wavelength bands from 0.28 to 4.0 um are analytically computed by solving the radiative transfer equation for five independent photon paths accounting for clear-sky absorption, Rayleigh scattering, and cloud absorption and scattering. The Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS) is used to show the optical thickness of the clear-sky atmosphere. Unlike Part I, which approximates the computation of aerosol scattering using the single-scattering phase function, the cloud transmittance and reflectance are efficiently retrieved from a comprehensive look-up table pre-computed by a 32-stream DIScrete Ordinates Radiative Transfer (DISORT) model for possible cloud conditions as well as solar and viewing geometries. A resolution assessment is performed to observe the optimal balance between the computational efficiency and accuracy in the development of the look-up table. Model simulations by DISORT and TMYSPEC are used to evaluate the performance of FARMS-NIT under cloudy-sky conditions. Compared to DISORT, FARMS-NIT yields 2-3% uncertainties on average, but it substantially reduces the computational time because of the independent computation of cloud properties and the implementation of the look-up table. In contrast to TMYSPEC, which uses successive steps to empirically compute plane-of-array (POA) irradiances and spectral irradiances, FARMS-NIT directly solves spectral radiances from the radiative transfer equation, which profoundly increases the accuracy in surface irradiances, especially over inclined photovoltaics (PV) panels.

14 SOLAR ENERGY↗
DOE OSTI2020

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Evaluation of Performance Variables to Accelerate the Deployment of Sustainable Aviation Fuels at a Regional Scale

An increase in jet fuel consumption and its associated emissions across the world have led to the need for alternative technologies to produce sustainable aviation fuels (SAF). One option to produce SAFs is to utilize waste or biomass-based feedstocks that has the potential to reduce greenhouse gas emissions by 50% or more compared to conventional jet fuel. However, there is a lack of understanding of how the synergistic effects of key performance variables could hinder or help the deployment of aviation fuels on a regional scale. Here, we assess the implications of key variables-including type and quantity of waste/biomass feedstock availability near the airport, cost of SAF production, life cycle greenhouse gas (GHG) emissions, policies, and fuel/infrastructure logistics-on the deployment of SAF at Chicago's O'Hare International Airport. We consider three ASTM International-approved SAF technologies (Hydroprocessed Esters and Fatty Acids, Fischer-Tropsch, and Alcohol to Jet) that can be blended up to 50% with petroleum-based jet fuel. Results from our analysis show that woody biomass-based Fischer-Tropsch technology has the lowest fuel production costs ($2.31-$2.81/gallon gasoline equivalent) of all pathways, and it reduces life cycle GHG emissions by 86% compared to conventional jet fuel despite the higher availability of crop residues compared to either woody biomass or fats, oils, and greases. Also, infrastructure is available at O'Hare International Airport to blend SAF with Jet A fuel through three terminals directly connected to the airport via pipelines. Our sensitivity analysis shows renewable fuel incentives and feedstock price to be key performance variables affecting the production cost and deployment of SAF.

alcohol-to-jet↗
NASA NTRS1987

Continental land cover assessment using Landsat MSS data

A statistical procedure to assess level-II continental resources using Landsat MSS digital data is presented. The statistical procedure involves a two-stage cluster sample within a stratified random sample. The utility of this procedure is assessed by using it to estimate the areal extent of the conifer and hardwood resources of the continental U.S. National estimates of conifer and hardwood derived using this sampling procedure were within 3 percent of U.S. Forest Service (USFS) figures. According to the Landsat-based study, 11 percent of the country is conifer forest and 12 percent is hardwood. The corresponding USFS figures are 13 and 15 percent, respectively. Comparison of the MSS classification products and airphotos showed that the conifer cover class was correctly identified 74 percent of the time and hardwood 80 percent of the time. The average classification accuracy countrywide for the four cover types considered (conifer, hardwood, water, and 'other') is 74 percent, and the overall accuracy is 85 percent. The statistical procedure provides a method of incorporating Landsat MSS digital data as a second state for level-II continental resource assessment. Alternate data sources, e.g., satellite and aircraft photographic imagery, may also be used in conjunction with this statistical model.

Nelson, Ross↗
DOE OSTI2016

Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information

Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.

58 GEOSCIENCES↗
DOE OSTI2018

Archie's Saturation Exponent for Natural Gas Hydrate in Coarse-Grained Reservoirs

Accurately quantifying the amount of naturally occurring gas hydrate in marine and permafrost environments is important for assessing its resource potential and understanding the role of gas hydrate in the global carbon cycle. Electrical resistivity well logs are often used to calculate gas hydrate saturations, S h , using Archie's equation. Archie's equation, in turn, relies on an empirical saturation parameter, n . Though n = 1.9 has been measured for ice–bearing sands and is widely used within the hydrate community, it is highly questionable if this n value is appropriate for hydrate–bearing sands. In this work, we calibrate n for hydrate–bearing sands from the Canadian permafrost gas hydrate research well, Mallik 5L–38, by establishing an independent downhole S h profile based on compressional–wave velocity log data. Using the independently determined S h profile and colocated electrical resistivity and bulk density logs, Archie's saturation equation is solved for n , and uncertainty is tracked throughout the iterative process. In addition to the Mallik 5L–38 well, we also apply this method to two marine, coarse–grained reservoirs from the northern Gulf of Mexico Gas Hydrate Joint Industry Project: Walker Ridge 313–H and Green Canyon 955–H. All locations yield similar results, each suggesting n ≈ 2.5 ± 0.5. Furthermore, for the coarse–grained hydrate bearing ( S h > 0.4) of greatest interest as potential energy resources, we suggest that n = 2.5 ± 0.5 should be applied in Archie's equation for either marine or permafrost gas hydrate settings if independent estimates of n are not available.

58 GEOSCIENCES↗
DOE OSTI2022

Limitations of reanalysis data for wind power applications

Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground). However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

17 WIND ENERGY↗
DOE OSTI2020

Lessons from the 2010 Deepwater Horizon Accident in the Gulf of Mexico

The 2010 Deepwater Horizon (DWH) accident in the Gulf of Mexico had many unique aspects to it not seen in previous marine spills. Indeed, research related to the DWH response phase, Natural Resource Damage Assessment, Gulf of Mexico Research Initiative (GoMRI), National Academy of Sciences, US agencies: NOAA, EPA, Fish & Wildlife, DOE, and Coast Guard have made this the most studied marine oil spill in the world. There are many oil biodegradation lessons learned from this experience and these will undoubtedly continue for many years.

Hazen, Terry C.↗
DOE OSTI2022

Using groundwater noble gas measurements to confirm paleorecharge hypotheses at Pahute Mesa, Nevada National Security Site, Nevada, USA

Pahute Mesa (Nevada, USA) was the site of 85 underground nuclear tests between 1965 and 1992 whose residual radio-chemical inventory poses a contaminant threat to local groundwater resources. To assess the fate and transport of these radionuclides in groundwater, several geochemical studies, including this one, have been conducted to understand long-term groundwater flow patterns at, and downgradient of, Pahute Mesa. Groundwater samples from the Pahute Mesa area at the Nevada National Security Site were analyzed for noble gases ( 3 He/ 4 He isotopic ratio and He, Ne, Kr, Ar and Xe concentrations) to infer groundwater recharge temperatures and provide additional evidence in support of groundwater flow patterns and the presence of late-pluvial Pleistocene groundwater. These data confirm recent findings (based on groundwater geochemistry and isotope compositions) that most recharge in the area occurred under temperature conditions much cooler than are found today, except near major drainages where ephemeral run of continues to recharge shallow groundwater. These noble gas data indicate that noble gas recharge temperatures and terrigenic He components have been reset where groundwater has flowed upward over barriers formed by caldera margins, or near the regional discharge area (Oasis Valley) where shallow groundwater has interacted with shallow soil gas. This evidence from groundwater noble gas measurements, in combination with other isotopic and geochemical studies, supports the current understanding of the unusual hydrogeology and recharge history of Pahute Mesa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Kansas Energy Sources: A Geological Review

Kansas produces both conventional energy (oil, gas, and coal) and nonconventional (coalbed gas, wind, hydropower, nuclear, geothermal, solar, and biofuels) and ranks the 22nd in state energy production in the U.S. Nonrenewable conventional petroleum is the most important energy source with nonrenewable, nonconventional coalbed methane gas becoming increasingly important. Many stratigraphic units produce oil and/or gas somewhere in the state with the exception of the Salina Basin in north-central Kansas. Coalbed methane is produced from shallow wells drilled into the thin coal units in southeastern Kansas. At present, only two surface coal mines are active in southeastern Kansas. Although Kansas has been a major exporter of energy in the past (it ranked first in oil production in 1916), now, it is an energy importer.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Quantifying Uncertainties in Modeling Wind Resource Data from Different PBL Schemes in the WRF Model: A Case Study Over the Puerto Rico Region

This study examines the modeling uncertainty of wind resource data stemming from the use of various planetary boundary layer (PBL) parameterizations available in the Weather Research and Forecasting (WRF) model. WRF-based wind simulations spanning 20 years at 3-km resolution using 11 different PBL schemes are used to objectively investigate the uncertainty in modeling wind speed for land-based wind (LBW) and offshore wind (OSW) locations in Puerto Rico. The uncertainty in the wind modeling for the 20-year dataset is quantified using the spread index (SI) and standard deviation (SD). For virtual LBW and OSW sites, the SI and SD values are analyzed as calculated across various spatial and temporal scales. Because the PBL's atmospheric stability conditions can be characterized into two dominant categories, the study focuses on analyzing the SI and SD for daytime (mainly unstable PBL conditions) and nighttime (mainly stable PBL conditions). For wind shear (10 m-200 m) at the OSW and LBW sites, WRF-based numerical experiments indicate the following SI (or SD) ranges: 39%-94% (0.74 m/s-1.44 m/s) during the daytime for OSW, 50%-75% (0.68 m/s-1.19 m/s) during the daytime for LBW, 37%-60% (0.73 m/s-1.12 m/s) during the nighttime for OSW, and 57%-143 % (0.65 m/s-1.43 m/s) during the nighttime for LBW. While a high SI is observed when modeling LBW during the nighttime, there are notable modeling uncertainties during the daytime on the leeward side of the orographic barriers for Puerto Rico.

17 WIND ENERGY↗