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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Fluidized bed combustor modeling

A general mathematical model for the prediction of performance of a fluidized bed coal combustor (FBC) is developed. The basic elements of the model consist of: (1) hydrodynamics of gas and solids in the combustor; (2) description of gas and solids contacting pattern; (3) kinetics of combustion; and (4) absorption of SO2 by limestone in the bed. The model is capable of calculating the combustion efficiency, axial bed temperature profile, carbon hold-up in the bed, oxygen and SO2 concentrations in the bubble and emulsion phases, sulfur retention efficiency and particulate carry over by elutriation. The effects of bed geometry, excess air, location of heat transfer coils in the bed, calcium to sulfur ratio in the feeds, etc. are examined. The calculated results are compared with experimental data. Agreement between the calculated results and the observed data are satisfactory in most cases. Recommendations to enhance the accuracy of prediction of the model are suggested.

Horio, M.↗
NASA NTRS1983

The structure and emission of a non-radiative shock

Observational data and the capabilities of current models for observed filament and shock features of supernova remnants are considered. The filaments emit Balmer lines originating in nonthermal shocks. Models of the generation mechanisms must account for the shock structure and the possibilities of electron thermal precursors to the shock and plasma turbulence, as well as equilibration processes for electron and ion temperatures. It is not yet known if a Maxwellian velocity distribution fits the electrons and ions. An assumption of Coulombic equilibration of ions and electrons has agreed well with some observed forbidden line intensities in the Cygnus Loop, while other lines require detailed radiative transfer calculations.

Raymond, J. C.↗
NASA NTRS1986

Parameter estimation and error analysis in environmental modeling and computation

A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.

Kalmaz, E. E.↗
NASA NTRS1995

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗
NASA NTRS2010

Abundances of Jupiter's Trace Hydrocarbons from Voyager and Cassini. Data Tables: Cassini CIRS Observations Planetary and Space Science, Forthcoming 2010

The following six tables give the retrieved temperatures and volume mixing ratios of C2H2 and C2H6 and the formal errors on these results from the retrieval, as described in the manuscript. These are in the form of two-dimensional tables, specified on a latitudinal and vertical grid. The first column is the pressure in bar, and the second column gives the altitude in kilometers calculated from hydrostatic equilibrium, and applies to the equatorial profile only. The top row of the table specifies the planetographic latitude.

Cassini CIRS observations↗
NASA NTRS2019

Status of the Post Flight MMOD Inspection Campaign for the SpaceX Cargo Dragon

The SpaceX Cargo Dragon has been flying supply missions for NASA to the International Space Station (ISS) since 2012. At the time of this writing, SpaceX has completed 14 missions to ISS with each returning to Earth via water landing. After each mission, a team from the NASA Johnson Space Center performs an inspection of the exterior surfaces of the Cargo Dragon spacecraft for hypervelocity impact damage features. Data from these inspections are collected into a database that includes impact feature dimensions as well as the location on the vehicle. Additional details on the type and size of particle that produced the damage site are pro-vided when sampling data and definitive spectroscopic analysis results are available. Observation data can be compared with impact estimates from risk assessment codes as a check on the micro-meteoroid and orbital debris (MMOD) environment predictions.

Hyde, James L.↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

State of the art astronomical simulations have provided datasets which enabled the training of novel deep learning techniques for constraining cosmological parameters. However, differences in subgrid physics implementation and numerical approximations among simulation suites lead to differences in simulated datasets, which pose a hard challenge when trying to generalize across diverse data domains and ultimately when applying models to observational data. Recent work reveals deep learning algorithms are able to extract more information from complex cosmological simulations than summary statistics like power spectra. We introduce Domain Adaptive Graph Neural Networks (DA-GNNs), trained on CAMELS data, inspired by CosmoGraphNet (Villanueva-Domingo et al 2023). By utilizing GNNs, we can capitalize on their capacity to capture both astrophysical and topological features of galaxy distributions. Mixing these capabilities with domain adaptation techniques such as Maximum Mean Discrepancy (MMD), which enable extraction of domain-invariant features, our framework demonstrates enhanced accuracy and robustness. We present experimental results, including the alignment of distributions across domains through data visualization. These findings suggest that DA-GNNs are an efficient way of extracting domain independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

Uncertainties in climate data sets

Climate diagnostics are constructed from either analyzed fields or from observational data sets. Those that have been commonly used are normally considered ground truth. However, in most of these collections, errors and uncertainties exist which are generally ignored due to the consistency of usage over time. Examples of uncertainties and errors are described in NMC and ECMWF analyses and in satellite observational sets-OLR, TOVS, and SMMR. It is suggested that these errors can be large, systematic, and not negligible in climate analysis.

Mcguirk, James P.↗
NASA NTRS2006

Time Relevance of Convective Weather Forecast for Air Traffic Automation

The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

Chan, William N.↗
DOE OSTI2026

CHESS 2025: Location data for field observations and sampling

This dataset represents geolocation data associated with field observations and sampling from the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Location data were collected using Trimble DA2 Global Navigation Satellite System (GNSS) receivers with Trimble Catalyst 2 centimeter (cm) positioning service and the Environmental Systems Research Institute (Esri) Field Maps mobile app. Files in this data package include meadow site polygons, shrub site polygons, tree site polygons and stem point locations, and Leaf Area Index (LAI) plot polygons (.geojson). The geojson files can be opened with open-source GIS software (e.g, QGIS). A csv file is also provided with point coordinates for all locations. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRSDate not supplied

SpaceX Dragon Spacecraft Post Flight MMOD Inspection Campaign

The SpaceX Dragon spacecraft performed 20 resupply flights to the International Space Station (ISS) between 2012 and 2020. After each mission, a team led by the NASA Johnson Space Center Hypervelocity Impact Technology (HVIT) Group inspected each Dragon vehicle exterior for hypervelocity impact damage. A general description of the inspected vehicle areas is provided as well as mission details such as exposure duration and launch dates. This paper documents the general inspection procedure for collection of data and the post inspection data analysis process. It also provides details of the observation data collected in addition to the spectroscopic analysis results of intact samples collected to discern the source of the impacting particle. A comparison between observed impacts and the expected number of damage features calculated by Bumper 3 with the latest micrometeoroid and orbital debris (MMOD) environments are also presented. Statistics on the >300 impact features documented in the database will provide insight into the depth to diameter ratios and other relationships. The quality of the comparison between the observations and code predictions are dependent on several factors. The paper provides details of each of these variables.

orbital debris↗
NASA NTRS1982

The origin and evolution of the coordinated data analysis workshop process

During the planning stage for the International Magnetospheric Study (IMS), it was stressed that coordinated observations among various satellites and among satellite, ground-based, balloon, and rocket (GBR) experiments were essential in obtaining the required observational data base. In the course of operating the Satellite Situation Center (SSC), it was found to be desirable to assemble a problem-oriented digital data base, consisting of a large number of physical parameters obtained from satellite and GBR sensors, in a computer system which would permit a large number of scientists to manipulate, display, discuss, study and analyze the data together in a coordinated manner. It was felt that such a process might shorten the time required to gain full scientific understanding of the observations. This approach was called the Coordinated Data Analysis Workshop (CDAW) process. Attention is given to the preliminary concept, the the initial implementation of the CDAW process, and aspects of subsequent evolution.

Vette, J. I.↗
DOE OSTI2017

Testing averaged cosmology with type Ia supernovae and BAO data

An important problem in precision cosmology is the determination of the effects of averaging and backreaction on observational predictions, particularly in view of the wealth of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of averaged cosmologies which consist of a simple parametrized phenomenological two-scale backreaction model with decoupled spatial curvature parameters. We perform a Bayesian model selection analysis and find that this class of averaged phenomenological cosmological models is favored with respect to the standard ΛCDM cosmological scenario when a joint analysis of current SNe Ia and BAO data is performed. In particular, the analysis provides observational evidence for non-trivial spatial curvature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A New MHD-assisted Stokes Inversion Technique

We present a new method of Stokes inversion of spectropolarimetric data and evaluate it by taking the example of a Sunrise/IMaX observation. An archive of synthetic Stokes profiles is obtained by the spectral synthesis of state-of-the-art magnetohydrodynamics (MHD) simulations and a realistic degradation to the level of the observed data. The definition of a merit function allows the archive to be searched for the synthetic Stokes profiles that best match the observed profiles. In contrast to traditional Stokes inversion codes, which solve the Unno–Rachkovsky equations for the polarized radiative transfer numerically and fit the Stokes profiles iteratively, the new technique provides the full set of atmospheric parameters. This gives us the ability to start an MHD simulation that takes the inversion result as an initial condition. After a relaxation process of half an hour solar time we obtain physically consistent MHD data sets with a target similar to the observation. The new MHD simulation is used to repeat the method in a second iteration, which further improves the match between observation and simulation, resulting in a factor of 2.2 lower mean χ{sup 2} value. One advantage of the new technique is that it provides the physical parameters on a geometrical height scale. It constitutes a first step toward inversions that give results consistent with the MHD equations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

The role of FGGE data in the understanding and prediction of atmospheric planetary waves

The augmented observational data base provided by FGGE offers a unique opportunity to improve the understanding and prediction of atmospheric planetary waves. Substantial progress was made, but a number of problems remain. The research on planetary waves conducted thus far with FGGE data is reviewed. Areas of progress are summarized, and some remaining problems are discussed.

Baker, W. E.↗
NASA NTRS1992

Data analysis and interpretation of lunar dust exosphere

The lunar horizon glow observed by Apollo astronauts and captured on film during the Surveyor mission is believed to result from the scattering of sunlight off lunar fines suspended in a dust layer over the lunar surface. For scale heights on the order of tens of kilometers, it is anticipated that the size of the dust particles will be small enough to admit Rayleigh scattering. Such events would result in scattered light which is polarized to a degree which is a function of observation angle and produce spectra containing large high frequency components ('bluing'). Believing these signatures to be observable from ground based telescopes, observational data has been collected from McDonald Observatory and the task of reduction and analysis of this data is the focus of the present report.

Andrews, George A., Jr.↗
NASA NTRS1993

Data analysis and interpretation of lunar dust exosphere

The lunar horizon glow observed by Apollo astronauts and recorded during the Surveyor missions is believed to result from the scattering of sunlight off lunar fines suspended in a dust layer above the lunar surface. For scale heights of tens of kilometers, theory and astronaut's observations suggest that the size of the dust particles will be smaller than 0.1 microns in radius and will act as Rayleigh scatters. This means that the dust scattered light will be 100 percent polarized at a 90 degree scattering angle and will depend on wavelength to the inverse fourth power ('bluing'). Believing these signatures to be observable from ground based telescopes, observational data in the form of CCD images has been collected from McDonald Observatory's 36 in. telescope, and the reduction and analysis of this data is the focus of the present report.

Andrews, George A., Jr.↗
NASA NTRS2004

Objective Lightning Forecasting at Kennedy Space Center/Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily morning briefings. This information is used by personnel involved in determining the possibility of violating Launch Commit Criteria, evaluating Flight Rules for the Space Shuttle, and daily planning for ground operation activities on Kennedy Space Center (KSC)/CCAFS. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a lightning probability forecast tool based on statistical analysis of historical warm-season (May - September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local CCAFS 1000 UTC sounding was used to calculate stability parameters for equation predictors. The Cloud-to-Ground Lightning Surveillance System (CGLSS) data were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which uses multiple linear regression, and also persistence and climatology forecasts. Lericos et al. (2002) developed lightning distributions over the Florida peninsula based on specific flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS.

Lambert, Winifred↗