Search NASA⌕ Search

SEARCH · Search NASA

Results for “historic data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gupta-et-al_2024_EarthsFuture

Results from Gupta et al. submitted to Earth's Future. All code to reproduce the experiment and make the figures can be found here: https://github.com/rg727/Gupta-etal_2024_EarthsFuture The data provided in this repository are (1) Weather Regime Data , (2) Hydroclimate Data, and (3) CALFEWS output. In (1), there are Markov chains of daily weather regimes generated over the 600-year paleo-period. In (2), there are three sets of data: Historical daily CDEC data for 12 input locations into CALFEWS, 600-year long daily paleo data (streamflow and snow) for each input location, and (3) 600-year long daily climate-change data (4 degree temperature increase + 7% precipitation scaling applied to (2)) which serves as the "climate change scenario" in the study. Please reference the GitHub repository on how to use these data to reproduce the results. The CALFEWS output for the Paleo and Climate Change scenarios is stored in (3). More information can be found in the Gupta-et-al_2024_EarthsFuture-README file.

Gupta, Rohini↗
DOE OSTI2020

DEPRECATED - Sharing the Sun Community Solar Project Data (May 2020)

This data set is no longer current - The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of May 2020. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2020

DEPRECATED - Sharing the Sun Community Solar Project Data (June 2020)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of June 2020. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2021

DEPRECATED - Sharing the Sun Community Solar Project Data (Dec 2020, Revision)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2020. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top. The revision dataset included projects with a total installed capacity in 2020 under the state-level program but missing the project level details.

14 SOLAR ENERGY↗
DOE OSTI2022

DEPRECATED - Sharing the Sun Community Solar Project Data (December 2021)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2021. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2022

DEPRECATED - Sharing the Sun Community Solar Project Data (June 2022)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of June 2022. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2023

DEPRECATED - State Policies and Programs for Community Solar (2022)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nlr.gov/submissions/249 The purpose of this dataset is to summarize current community solar policies and low-income stipulations by the state in the United States as of December 2022. The "State_Program" sheet summarizes the key policy details for each state. This dataset is associated with the National Renewable Energy Laboratory (NREL) publication "Expanding Solar Access: State Community Solar Landscape (2022)." https://www.nlr.gov/docs/fy23osti/84247.pdf This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. Please submit updates, additions, or corrections please find contact information on the current data set page linked above.

14 SOLAR ENERGY↗
DOE OSTI2023

DEPRECATED - Sharing the Sun Community Solar Project Data (December 2022)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2022. In addition, this dataset updated the low-income (LI) and low- and moderate-income (LMI) provisions for both complete and pending projects, based on the most recent program data we collected as of July 2023. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2024

DEPRECATED - Sharing the Sun Community Solar Project Data (December 2023)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of Dec 2023. In addition, this dataset updated the low-income (LI) and low- and moderate-income (LMI) provisions for both complete and pending projects, based on the most recent program data we collected as of March 2024. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗
DOE OSTI2024

DEPRECATED - State Policies and Programs for Community Solar (2024 Q2 Update)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/249 The purpose of this dataset is to summarize current community solar policies and low-income stipulations by the state in the United States as of April 2024. This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. To submit updates, additions, or corrections please find contact information on the current data set page linked above.

14 SOLAR ENERGY↗
DOE OSTI2024

DEPRECATED - State Policies and Programs for Community Solar (2024 Q3 Update)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nlr.gov/submissions/249 The purpose of this dataset is to summarize current community solar policies and low-income stipulations by state in the United States as of June 2024. The "State_Program" sheet summarizes the key policy details for each state. This list has been reviewed, but errors may exist, and the list may not be comprehensive. NREL invites input to update or add to the database. To submit updates, additions, or corrections please find contact information on the current data set page linked above.

14 SOLAR ENERGY↗
NASA NTRS2000

Observations and Modeling of the Transient General Circulation of the North Pacific Basin

Because of recent progress in satellite altimetry and numerical modeling and the accumulation and archiving of long records of hydrographic and meteorological variables, it is becoming feasible to describe and understand the transient general circulation of the ocean (i.e., variations with spatial scales larger than a few hundred kilometers and time scales of seasonal and longer-beyond the mesoscale). We have carried out various studies in investigation of the transient general circulation of the Pacific Ocean from a coordinated analysis of satellite altimeter data, historical hydrographic gauge data, scatterometer wind observations, reanalyzed operational wind fields, and a variety of ocean circulation models. Broadly stated, our goal was to achieve a phenomenological catalogue of different possible types of large-scale, low-frequency variability, as a context for understanding the observational record. The approach is to identify the simplest possible model from which particular observed phenomena can be isolated and understood dynamically and then to determine how well these dynamical processes are represented in more complex Oceanic General Circulation Models (OGCMs). Research results have been obtained on Rossby wave propagation and transformation, oceanic intrinsic low-frequency variability, effects of surface gravity waves, pacific data analyses, OGCM formulation and developments, and OGCM simulations of forced variability.

McWilliams, James C.↗
NASA NTRS2015

High Altitude Long Endurance UAV Analysis Model Development and Application Study Comparing Solar Powered Airplane and Airship Station-Keeping Capabilities

There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on-site capability than either airship concept, and 2) the airship concepts can attain higher levels of energy collection and storage than the airplane concept; however, attaining these energy benefits requires adverse design trades of reduced performance (small airship) or excessive solar array area (large airship).

Ozoroski, Thomas A.↗
NASA NTRSDate not supplied

Updating the Thermal Vacuum Chambers at the NASA Johnson Space Center

Chambers A and B are two large thermal vacuum chambers at Johnson Space Center which enable space simulation for unmanned and human-rated missions, respectively. With the resurgence in deep space missions for scientific research and various private commercial ventures, these chambers are expected to be used frequently for at least the next decade. For qualifying the James Webb Space Telescope, upgrades to Chamber A were performed which included the addition of a 12.5 kW refrigeration system with helium shrouds capable of simulating deep space environment and an efficient and reliable LN2 natural flow thermosiphon system for the thermal shield. Continuous improvements since then have focused on ensuring operational readiness by modernizing the data acquisition, recording, controls, and visualization systems for both chambers and clean room. These upgrades will be the focus of this paper. Controlling the Cryochambers was enhanced by moving from a 32-bit SCADA system to a 64-bit architected system. Infrastructural changes involved installing redundant power circuits, adding new servers, network switches, and including load balancing with fail-over between servers to minimize downtime. Instead of distributed servers, 3 redundant servers are used to share configurations. Configurations are now kept in a shared SQL instance making it easy to deploy and maintain. During this upgrade process many sub-systems (PLCs and NI PXI interfaces to sensors) were upgraded from the prior OPC-DA to the more secure OPC-UA protocol. Cryo-system PLCs were updated to allow Ganni cycle floating pressure calculations from any cold box to be sent to any compressor. During the project, the team recreated over 70,000 live data points, 50000 historical data points, and 4000 alarms. Finally, the graphical interfaces were upgraded to support HTML 5 in conjunction shared pages were implemented reducing the total number of webpages by over 75%. These system updates reinvigorated the previous SCADA system which had reached its end of life. The same look and feel was maintained while providing operators with an updated interface to control, troubleshoot, and record. The new system architecture is more robust and easier to maintain creating a path forward to address remaining problem points and implement additional features.

Cody Schaefer↗
NASA NTRSDate not supplied

Updating the Thermal Vacuum Chambers at the NASA Johnson Space Center

Chambers A and B are two large thermal vacuum chambers at Johnson Space Center which enable space simulation for unmanned and human-rated missions, respectively. With the resurgence in deep space missions for scientific research and various private commercial ventures, these chambers are expected to be used frequently for at least the next decade. For qualifying the James Webb Space Telescope, upgrades to Chamber A were performed which included the addition of a 12.5 kW refrigeration system with helium shrouds capable of simulating deep space environment and an efficient and reliable LN2 natural flow thermosiphon system for the thermal shield. Continuous improvements since then have focused on ensuring operational readiness by modernizing the data acquisition, recording, controls, and visualization systems for both chambers and clean room. These upgrades will be the focus of this paper. Controlling the Cryochambers was enhanced by moving from a 32-bit SCADA system to a 64-bit architected system. Infrastructural changes involved installing redundant power circuits, adding new servers, network switches, and including load balancing with fail-over between servers to minimize downtime. Instead of distributed servers, 3 redundant servers are used to share configurations. Configurations are now kept in a shared SQL instance making it easy to deploy and maintain. During this upgrade process many sub-systems (PLCs and NI PXI interfaces to sensors) were upgraded from the prior OPC-DA to the more secure OPC-UA protocol. Cryo-system PLCs were updated to allow Ganni cycle floating pressure calculations from any cold box to be sent to any compressor. During the project, the team recreated over 70,000 live data points, 50000 historical data points, and 4000 alarms. Finally, the graphical interfaces were upgraded to support HTML 5 in conjunction shared pages were implemented reducing the total number of webpages by over 75%. These system updates reinvigorated the previous SCADA system which had reached its end of life. The same look and feel was maintained while providing operators with an updated interface to control, troubleshoot, and record. The new system architecture is more robust and easier to maintain creating a path forward to address remaining problem points and implement additional features.

Cody Schaefer↗
DOE OSTI2021

Failure prediction and estimation of failure parameters

Machine-learning methods and apparatus are disclosed to determine frictional state or other parameters in an earthquake zone or other failing medium, using acoustic emission, seismic waves, or other detectable indicators of microscopic processes. Predictions of future failures are demonstrated in different regimes. A classifier is trained using time series of acoustic emission data along with historic data of frictional state or failure events. In disclosed examples, random forests and gradient boost trees are used, and grid-search or EGO procedures are used for hyperparameter tuning. Once trained, the classifier can be applied to testing or live data in order to assess a frictional state, assess seismic hazard, or make predictions regarding a future failure event. The technology has been developed in a double direct shear apparatus, but can be widely applied to seismic faults, other terrestrial failures, or failures in man-made structures. Variations are disclosed.

Johnson, Paul Allan↗
NASA NTRS2014

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Spruce, Joseph↗
NASA NTRS2001

A New Ensemble Canonical Correlation Prediction Scheme for Seasonal Precipitation

Department of Mathematical Sciences, University of Alberta, Edmonton, Canada This paper describes the fundamental theory of the ensemble canonical correlation (ECC) algorithm for the seasonal climate forecasting. The algorithm is a statistical regression sch eme based on maximal correlation between the predictor and predictand. The prediction error is estimated by a spectral method using the basis of empirical orthogonal functions. The ECC algorithm treats the predictors and predictands as continuous fields and is an improvement from the traditional canonical correlation prediction. The improvements include the use of area-factor, estimation of prediction error, and the optimal ensemble of multiple forecasts. The ECC is applied to the seasonal forecasting over various parts of the world. The example presented here is for the North America precipitation. The predictor is the sea surface temperature (SST) from different ocean basins. The Climate Prediction Center's reconstructed SST (1951-1999) is used as the predictor's historical data. The optimally interpolated global monthly precipitation is used as the predictand?s historical data. Our forecast experiments show that the ECC algorithm renders very high skill and the optimal ensemble is very important to the high value.

Kim, Kyu-Myong↗