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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Experimental Investigation of Rotorcraft Outwash in Ground Effect

The wake characteristics of a rotorcraft are affected by the proximity of a rotor to the ground surface, especially during hover. Ground effect is encountered when the rotor disk is within a distance of a few rotor radii above the ground surface and results in an increase in thrust for a given power relative to that same power condition with the rotor out of ground effect. Although this phenomenon has been highly documented and observed since the beginning of the helicopter age, there is still a relatively little amount of flow-field data existing to help understand its features. Joint Army and NASA testing was conducted at NASA Langley Research Center using a powered rotorcraft model in hover at various rotor heights and thrust conditions in order to contribute to the complete outwash data set. The measured data included outwash velocities and directions, rotor loads, fuselage loads, and ground pressures. The researchers observed a linear relationship between rotor height and percent download on the fuselage, peak mean outwash velocities occurring at radial stations between 1.7 and 1.8 r/R regardless of rotor height, and the measurement azimuthal dependence of the outwash profile for a model incorporating a fuselage. Comparisons to phase-locked PIV data showed similar contours but a more contracted wake boundary for the PIV data. This paper describes the test setup and presents some of the averaged results.

Tanner, Philip E.↗
NASA NTRS2016

Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.

Green, Lawrence L.↗
NASA NTRS2020

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

Quantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year−1 (1Tg = 1012 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH4 year−1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of −34 to −46 Tg CH4 year−1, we estimated that the global net land methane emissions are 149–176 Tg CH4 year−1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

wetland methane emission↗
NASA NTRSDate not supplied

Isokinetic Probe Total Water Content Measurements in the NASA Icing Research Tunnel with Supercooled Large Drop Conditions

An Isokinetic Total Water Content Evaporator (IKP2) was used to measure liquid water content (LWC) in the NASA Icing Research Tunnel (IRT) with spray conditions that ranged in LWC and cloud drop size spectra as characterized by the median volumetric diameter (MVD). The IKP2 measurements were made as part of an international collaborative effort to investigate the measurement of supercooled large drop (SLD) conditions in several icing wind tunnels. This report focuses on the IKP2 and background water vapor (BWV) measurements made within the NASA IRT during the October 2017 test entry. The IKP2 TWC results are compared to the IRT LWC calibration values for a range of LWC and MVD values. The IRT LWC calibration is based on measurements from a multi-element hot-wire probe. In general, the IKP2 TWC values were approximately 9% greater than the IRT LWC calibration values over a range of LWC from 0.4 g/m3 to 3.0 g/m3. The ratio of IKP2 TWC to IRT LWC calibration ranged from approximately 0.9 to 1.27 over a range of MVD from 15µm to 460 µm. Comparisons of this data set to IKP2 data from a 2014 IRT test entry show similar results in the regions where overlaps occurred. The results support the theory and observations of water mass loss from hot-wire TWC sensors when subjected to large MVD conditions.

Icing cloud instruments↗
NASA NTRSDate not supplied

Isokinetic Probe Total Water Content Measurements in the NASA Icing Research Tunnel with Supercooled Large Drop Conditions

An Isokinetic Total Water Content Evaporator (IKP2) was used to measure liquid water content (LWC) in the NASA Icing Research Tunnel (IRT) with spray conditions that ranged in LWC and cloud drop size spectra as characterized by the median volumetric diameter (MVD). The IKP2 measurements were made as part of an international collaborative effort to investigate the measurement of supercooled large drop (SLD) conditions in several icing wind tunnels. This report focuses on the IKP2 and background water vapor (BWV) measurements made within the NASA IRT during the October 2017 test entry. The IKP2 TWC results are compared to the IRT LWC calibration values for a range of LWC and MVD values. The IRT LWC calibration is based on measurements from a multi-element hot-wire probe. In general, the IKP2 TWC values were approximately 9% greater than the IRT LWC calibration values over a range of LWC from 0.4 g/m3 to 3.0 g/m3. The ratio of IKP2 TWC to IRT LWC calibration ranged from approximately 0.9 to 1.27 over a range of MVD from 15m to 460 m. Comparisons of this data set to IKP2 data from a 2014 IRT test entry show similar results in the regions where overlaps occurred. The results support the theory and observations of water mass loss from hot-wire TWC sensors when subjected to large MVD conditions.

o Aircraft Icing↗
NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗
NASA NTRS2021

Isokinetic Probe Total Water Content Measurements in the NASA Icing Research Tunnel with Supercooled Large Drop Conditions

An Isokinetic Total Water Content Evaporator (IKP2) was used to measure liquid water content (LWC) in the NASA Icing Research Tunnel (IRT) with spray conditions that ranged in LWC and cloud drop size spectra as characterized by the median volumetric diameter (MVD). The IKP2 measurements were made as part of an international collaborative effort to investigate the measurement of supercooled large drop (SLD) conditions in several icing wind tunnels. This report focuses on the IKP2 and background water vapor (BWV) measurements made within the NASA IRT during the October 2017 test entry. The IKP2 TWC results are compared to the IRT LWC calibration values for a range of LWC and MVD values. The IRT LWC calibration is based on measurements from a multi-element hot-wire probe. In general, the IKP2 TWC values were approximately 9% greater than the IRT LWC calibration values over a range of LWC from 0.4 g/m3 to 3.0 g/m3. The ratio of IKP2 TWC to IRT LWC calibration ranged from approximately 0.9 to 1.27 over a range of MVD from 15um to 460 um. Comparisons of this data set to IKP2 data from a 2014 IRT test entry show similar results in the regions where overlaps occurred. The results support the theory and observations of water mass loss from hot-wire TWC sensors when subjected to large MVD conditions.

o Aircraft Icing↗
NASA NTRSDate not supplied

Mars Sample Return Earth Entry System Woven Roughness Mach 6 Aeroheating Test

The Mars Sample Return Earth Entry System is the first entry vehicle designed for a NASA flagship mission to utilize a woven thermal protection system as well as a 52.5 degree sphere cone forebody geometry. As a result, no heritage aeroheating experimental data set exists to compare with computational predictions. In order to obtain a set of validation data for computational models, an extensive wind tunnel test campaign was funded by the Mars Sample Return Earth Entry System project. The first entry in the test campaign was completed in April of 2023, which was an investigation of turbulent heating augmentation due to woven thermal protection system roughness on the 52.5 degree Mars Sample Return - Earth Entry System vehicle forebody geometry. This test entry produced the first ever experimental aeroheating data on a 52.5 degree sphere-cone geometry as well as the first NASA experimental aeroheating data on a woven surface roughness pattern. Data obtained from this test campaign is being directly leveraged to support the NASA flight program, as experimental results are being utilized to validate the computational models which characterize the aeroheating environment that the vehicle experiences and predict turbulent surface heating levels and margins across the woven surface.

Jonathan S Cheatwood↗
NASA NTRSDate not supplied

Mars Sample Return Earth Entry System Woven Roughness Mach 6 Aeroheating Test

The Mars Sample Return Earth Entry System is the first entry vehicle designed for a NASA flagship mission to utilize a woven thermal protection system as well as a 52.5 degree sphere cone forebody geometry. As a result, no heritage aeroheating experimental data set exists to compare with computational predictions. In order to obtain a set of validation data for computational models, an extensive wind tunnel test campaign was funded by the Mars Sample Return Earth Entry System project. The first entry in the test campaign was completed in April of 2023, which was an investigation of turbulent heating augmentation due to woven thermal protection system roughness on the 52.5 degree Mars Sample Return - Earth Entry System vehicle forebody geometry. This test entry produced the first ever experimental aeroheating data on a 52.5 deg sphere-cone geometry as well as the first NASA experimental aeroheating data on a woven surface roughness pattern. Data obtained from this test campaign is being directly leveraged to support the NASA flight program, as experimental results are being utilized to validate the computational models which characterize the aeroheating environment that the vehicle experiences and predict turbulent surface heating levels and margins across the woven surface.

Jonathan Cheatwood↗
NASA NTRS1997

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height anomalies. Because of its potential for large scale synoptic coverage of the deep ocean, acoustic travel time data should be a natural complement to satellite altimetry. Satellite data give us vertical integrals associated with thermodynamic and dynamic processes.

Miller, Robert N.↗
NASA NTRS2000

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Raster Format

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites. The data are stored in binary, image format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2001

Validation of the galactic cosmic ray and geomagnetic transmission models

A very high-momentum resolution particle spectrometer called the Alpha Magnetic Spectrometer (AMS) was flown in the payload bay of the Space Shuttle in a 51.65 degrees x 380-km orbit during the last solar minimum. This spectrometer has provided the first high statistics data set for galactic cosmic radiation protons, and helium, as well as limited spectral data on carbon and oxygen nuclei in the International Space Station orbit. First measurements of the albedo protons at this inclination were also made. Because of the high-momentum resolution and high statistics, the data can be separated as a function of magnetic latitude. A related investigation, the balloon borne experiment with a superconducting solenoid spectrometer (BESS), has been flown from Lynn Lake, Canada and has also provided excellent high-resolution data on protons and helium. These two data sets have been used here to study the validity of two galactic cosmic ray models and the geomagnetic transmission function developed from the 1990 geomagnetic reference field model. The predictions of both the CREME96 and NASA/JSC models are in good agreement with the AMS data. The shape of the AMS measured albedo proton spectrum, up to 2 GeV, is in excellent agreement with the previous balloon and satellite observations. A new LIS spectrum was developed that is consistent with both previous and new BESS 3He observations. Because the astronaut radiation exposures onboard ISS will be highest around the time of the solar minimum, these AMS measurements and these models provide important benchmarks for future radiation studies. AMS-02 slated for launch in September 2003, will provide even better momentum resolution and higher statistics data. Published by Elsevier Science Ltd.

unmanned↗
NASA NTRS2016

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

aerosol optical depth↗
DOE OSTI2024

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

An improved model for the Earth's gravity field

An improved model for the Earth's gravity field, TEG-1, was determined using data sets from fourteen satellites, spanning the inclination ranges from 15 to 115 deg, and global surface gravity anomaly data. The satellite measurements include laser ranging data, Doppler range-rate data, and satellite-to-ocean radar altimeter data measurements, which include the direct height measurement and the differenced measurements at ground track crossings (crossover measurements). Also determined was another gravity field model, TEG-1S, which included all the data sets in TEG-1 with the exception of direct altimeter data. The effort has included an intense scrutiny of the gravity field solution methodology. The estimated parameters included geopotential coefficients complete to degree and order 50 with selected higher order coefficients, ocean and solid Earth tide parameters, Doppler tracking station coordinates and the quasi-stationary sea surface topography. Extensive error analysis and calibration of the formal covariance matrix indicate that the gravity field model is a significant improvement over previous models and can be used for general applications in geodesy.

Tapley, B. D.↗
NASA NTRS2000

BOREAS RSS-4 1994 Southern Study Area Jack Pine LAI and FPAR Data

The RSS-4 team collected several data sets related to leaf, plant, and stand physical, optical, and chemical properties. This data set contains leaf area indices and FPAR measurements that were taken at the three conifer sites in the BOREAS SSA during August 1993 and at the jack pine tower flux and a subset of auxiliary sites during July and August 1994. The measurements were made with LAI-2000 and Ceptometer instruments. The measurements were taken for the purpose of model parameterization and to test empirical relationships that were hypothesized between biophysical parameters and remotely sensed data. The data are stored in tabular ASCII files.

Hall, Forrest G.↗
DOE OSTI2020

SPRUCE Plot-Level Water Table Data Assessments for Absolute Elevations and Height with Respect to Mean Hollows Beginning in 2015

This data set provides a record of the half-hourly automated water table depth data collected for 12 SPRUCE plots (4, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 20, and 21) beginning during deep peat heating (DPH) in 2015 and continuing throughout the whole ecosystem warming (WEW) manipulations for the SPRUCE Project (Hanson et al. 2017). The data currently cover 2015-05-12 through 2024-12-31 and will be updated periodically throughout the duration of the SPRUCE project. Also provided are daily plot normalized data for water table depths with respect to mean hollow locations within each plot. The hollow referenced data provide the basis for the intercomparison of peat saturation or aeration across treatment plots. A limited data set for manual water table observations made periodically from 2015-2022 are also provided as a reference to the plot center automated observations. In August 2015, WEW was initiated at 5 warming levels (+0, +2. +4.5, +6.75 and +9 °C) with 2 plots per warming level. DPH measurements were underway before the initiation of WEW heating treatments and both are expected to operate through 2025. Elevated CO2 treatments were added in June 2016 (Enclosures 4, 10, 11, 16 and 19). All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This dataset contains three data files in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

HERO WEC V1.0 2024 - WEC-Sim Detailed Simulation Runs and Summary Data

This dataset includes results from simulations of NREL's hydraulic and electric reverse osmosis wave energy converter (HEREO WEC). Simulation runs include 135 wave cases that were based on the updated WEC-Sim model, which is linked below. The data represented in this repository is based on an updated WEC-Sim model using laboratory data to tune and refine the original WEC-Sim model for the V1.0 HERO WEC. The 135 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 3.75m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 100 second ramp time, a total simulation time of 3,100 seconds, and a simulation time-step of 0.005s. A reference table has been included to map each multi condition run (MCR) case with each wave condition. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the simulation runs, in the same increments. The following matrices are included: - Power Abs: The average absorbed power from the WEC (calculated from anchor reaction force and heave velocity) - Power Hyd: The average hydraulic power output at pump (calculated from pump output flow and pressure) - Power - Hyd ROi: The average hydraulic power measured at the RO system inlet (calculated from RO system pressure and flow (pre-accumulator)) - Flow - Pump out: The average flowrate measured at the pump outlet - Flow - Perm: The average permeate (clean water) production - Flow - RO (pre): The average flowrate measured at the inlet of the RO system before the accumulators - Flow - RO (post): The average flowrate measured after the accumulator bank in the RO system - Pressure - RO: The average pressure measured at the inlet of the RO system This data set has been developed by the National Renewable Energy Laboratory, operated by the Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗