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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 469 records · Page 26

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NASA NTRS1972

The farfield structure of aircraft wake turbulence.

Detailed mean flow measurements were obtained at stations up to thirty chordlengths downstream in an airfoil trailing vortex using a yawhead pressure probe in the Virginia Tech Six-Foot Subsonic Tunnel. Mass injection at the wingtip was shown to hasten the vortex decay. A theoretical method has been developed to show the effect of wing circulation distribution on the structure of the outer portion of the vortex and excellent agreement with the experimental data is demonstrated. Experimental results indicate a much slower decay and higher tangential velocities than previously expected.

Mason, W. H.↗

NASA NTRS1983

Droplet sizes and velocities in vaporizing sprays

A pulse height laser Doppler anemometer particle sizing technique has been refined to permit simultaneous particle size and velocity measurements in sprays. The improvements include (1) the use of a specially tailored 'top hat' light distribution, to provide unambiguous particle diameter-signal amplitude relations, (2) the use of back scattered light collection, and (3) the utilization of Mie theory to compute the relations between signal amplitude and particle diameter, in the backscatter mode. Twin-fluid atomized kerosene sprays have been investigated using the new technique. In these sprays distributions have been mapped of mean droplet diameters, droplet size distributions, and the local correlations between droplet diameters and velocities. The data show the variation of spray structure with atomizer input parameters, the preferential vaporization of smaller droplets, and the differing trajectories of the large and small droplets.

Yule, A. J.↗

NASA NTRS1991

Version 0 EOSDIS - An overview

Attention is given to NASA's Earth Observing System Data and Information System (EOSDIS), which is to be a single, distributed but internally consistent evolutionary system to support the planning and execution of EOS data acquisitions and to process, archive, and distribute EOS data products and selected non-EOS data to enable interdisciplinary studies of the earth. V0 EOSDIS, a logical step in this evolutionary process, is to address both technical and managerial challenges. Technical challenges include developing a multidiscipline, distributed system for searching and ordering data in a heterogeneous environment, and standardizing data formats and distribution techniques among differing communities and organizations. Managerial challenges include establishing and maintaining a structure consisting of geographically distributed entities such that cooperative development is carried out effectively despite organizational differences, maintaining interactions with the scientific community to ensure its close involvement despite its size and diversity, and keeping the expectations for V0 consistent with its schedules and resources.

Ramapriyan, H. K.↗

NASA NTRS1992

Experiment/facility requirements document for the Space Station Furnace Facility. Section 1: Integrated configuration

The function of the Space Station Furnace Facility (SSFF) is to support materials research into the crystal growth and solidification processes of electronic and photonic materials, metals and alloys, and glasses and ceramics. To support this broad base of research requirements, the SSFF will employ a variety of furnace modules which will be operated, regulated, and supported by a core of common subsystems. Furnace modules may be reconfigured or specifically developed to provide unique solidification conditions for each set of experiments. The SSFF modular approach permits the addition of new or scaled-up furnace modules to support the evolution of the facility as new science requirements are identified. The SSFF Core is of modular design to permit augmentation for enhanced capabilities. The fully integrated configuration of the SSFF will consist of three racks with the capability of supporting up to two furnace modules per rack. The initial configuration of the SSFF will consist of two of the three racks and one furnace module. This Experiment/Facility Requirements Document (E/FRD) describes the integrated facility requirements for the Space Station Freedom (SSF) Integrated Configuration-1 (IC1) mission. The IC1 SSFF will consist of two racks: the Core Rack, with the centralized subsystem equipment; and the Experiment Rack-1, with Furnace Module-1 and the distributed subsystem equipment to support the furnace. The SSFF support functions are provided by the following Core subsystems: power conditioning and distribution subsystem (SSFF PCDS); data management subsystem (SSFF DMS); thermal control Subsystem (SSFF TCS); gas distribution subsystem (SSFF GDS); and mechanical structures subsystem (SSFF MSS).

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NASA NTRS2001

Extrapolation of the dna fragment-size distribution after high-dose irradiation to predict effects at low doses

The patterns of DSBs induced in the genome are different for sparsely and densely ionizing radiations: In the former case, the patterns are well described by a random-breakage model; in the latter, a more sophisticated tool is needed. We used a Monte Carlo algorithm with a random-walk geometry of chromatin, and a track structure defined by the radial distribution of energy deposition from an incident ion, to fit the PFGE data for fragment-size distribution after high-dose irradiation. These fits determined the unknown parameters of the model, enabling the extrapolation of data for high-dose irradiation to the low doses that are relevant for NASA space radiation research. The randomly-located-clusters formalism was used to speed the simulations. It was shown that only one adjustable parameter, Q, the track efficiency parameter, was necessary to predict DNA fragment sizes for wide ranges of doses. This parameter was determined for a variety of radiations and LETs and was used to predict the DSB patterns at the HPRT locus of the human X chromosome after low-dose irradiation. It was found that high-LET radiation would be more likely than low-LET radiation to induce additional DSBs within the HPRT gene if this gene already contained one DSB.

NASA Discipline Radiation Health↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 6

Contents include the following: A Model for Multiple Populations of Presolar Diamonds. Characterization of Martian North Polar Geologic Units Using Mars Odyssey THEMIS Data. Effect of Flow on the Internal Structure of the Martian North Polar Layered Deposits. Elemental Abundance Distributions in Basalt Clays and Meteorites: Is It a Biosignature? Early Results on the Saturn System from the Composite Infrared Spectrometer. NanoSIMS D/H Imaging of Isotopically Primitive Interplanetary Dust Particles. Presolar (Circumstellar and Interstellar) Phases in Renazzo: The Effects of Parent Body Processing. Catastrophic Disruption of Hydrated Targets: Implications for the Hydrated Asteroids and for the Production of Interplanetary Dust Particles. Chemical and Mineralogical Analyses of Particles from the Stratospheric Collections Coinciding with the 2002 Leonid Storm and the 2003 Comet Grigg-Skjellerup Trail Passage. An Analysis of the Solvus in the CaS-MnS System. ESA s SMART-1 Mission at the Moon: First Results, Status and Next Steps. Europa Analog Ice-splitting Measurements and Experiments with Ice-Hunveyor on the Frozen Balaton-Lake, Hungary. Chromium on Eros: Further Evidence of Ordinary Chondrite Composition. Dust Devil Tracks on Mars: Observation and Analysis from Orbit and the Surface. Spatial Variation of Methane and Other Trace Gases Detected on Mars: Interpretation with a General Circulation Model. Mars Water Ice and Carbon Dioxide Seasonal Polar Caps: GCM Modeling and Comparison with Mars Express Omega Observations. Component Separation of OMEGA Spectra with ICA. Clathrate Formation in the Near-Surface Environment of Titan. Space Weathering: A Proposed Laboratory Approach to Explaining the Sulfur Depletion on Eros. Sample Collection from Small Airless Bodies: Examination of Temperature Constraints for the TGIP. Sample Collector for the Hera Near-Earth Asteroid Sample Return Mission. A Rugged Miniature Mass-Spectrometer for Measuring Aqueous Geochemistry on Mars. Martian and Lunar Pyroxene Microstructures Studied by Single-Crystal X-Ray Diffraction.

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NASA NTRS2011

Characterizing Vegetation Cover in Global Savannas with an Annual Foliage Clumping Index Derived from the MODIS BRDF Product

The global savanna biome is characterized by enormous diversity in the physiognomy and spatial structure of the vegetation. The foliage clumping index can be calculated from bidirectional reflectance distribution function (BRDF) data. It measures the response of the darkspot reflectance to increased shadow associated with clumped vegetation and is related to leaf area index. Clumping index theoretically declines with increasing woody cover until the tree canopy begins to become uniform. In this study, clumping index is calculated for Moderate Resolution Imaging Spectroradiometer BRDF data for the Australian tropical savanna, the tropical savannas of South America, and the tropical savannas of east, west and southern Africa and compared with site-based measurements of tree canopy cover, and with area-based classifications of land cover. There were differences in sensitivity of clumping index between red and near-infrared reflectance channels, and between savanna systems with markedly different woody vegetation physiognomy. Clumping index was broadly related to foliage cover from historical site data in Australia and in West Africa and Kenya, but not in Southern Africa nor with detailed site-based demographic data in the cerrado of Brazil. However, clumping index decreased with proportion of woody cover in land cover datasets for east Africa, Australia and the Colombian Llanos. There was overlap in the range of clumping index values for forest, cerrado and campo land covers in Brazil. Clumping index was generally negatively correlated with percentage tree cover from the MODIS Vegetation Continuous Fields product, but regional differences in the relationship were evident. There were large differences in the frequency distributions of clumping index from savanna, woody savanna and grassland land cover classes between global ecoregions. The clumping index shows differing sensitivity to savanna woody cover for red and NIR reflectance, and requires regional calibration for application as a universal indicator.

Hill, Michael J.↗

NASA NTRS2018

Climatespark: an In-Memory Distributed Computing Framework for Big Climate Data Analytics

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple- dimensional, array-based datasets in various geoscience domains.

Hu, Fei↗

DOE OSTI2020

F2 extraction from Inclusive Cross Section Data at Large Bjorken x

While we have made significant progress in probing nuclear structure at low Bjorken x and high Q 2 , we still have gaps in our knowledge regarding the high Bjorken x and intermediate Q 2 kinematic region. This is not an accident, but instead due to the diffculty in assessing the non-perturbative region of nuclear physics. For this reason, the E12-10-002 experiment measured the H(e,e') and D(e,e') inclusive cross section in the resonance region. This will allow us to study both perturbative and non-perturbative physics in a kinematic region that lacks precision measurements. Measurements were made up to a Bjorken x of 0.99 and Q 2 up to 17 GeV 2 . These measurements are made using the independent HMS and SHMS spectrometers at the upgraded beam energy of 11 GeV in Hall C at Jefferson Lab. Further, we extract F 2 structure functions from the measured data and study the effect of their inclusion in a global Parton Distribution Function analysis.

Araiza Gonzalez, Fernando↗

DOE OSTI2020

Characterization of turbulence under different stability conditions using lidar scanning data

The spatiotemporal scales of turbulence in the boundary layer flow vary with the static stability of the atmosphere. For example, turbulence structures in unstable conditions are often found to be large and coherent, whereas the turbulent structures in stable conditions are relatively small and sporadic. To better understand the behavior of such turbulent structures under different atmospheric stability conditions in the lower atmosphere, herein, we use scanning lidar data collected over several months during the US Department of Energy's second Wind Forecast Improvement Project (WFIP 2) in 2016. The radial velocity data from scanning lidar were gathered along the horizontal plane (PPI mode) and were analyzed using proper orthogonal decomposition (POD) and spectral energy methods. The results from these analyses show that the turbulent structures in daytime unstable conditions are different from those present during nighttime stable conditions in terms of amount of energy and coherent structures. The POD energy is distributed more evenly in all the higher spatial modes in the daytime unstable case compared to the nighttime stable case. Besides characterizing the turbulence in the flow, the lidar data were also used to compare the simulated flow field generated from the WRF-LES framework (Weather Research and Forecasting - large-eddy simulation) with the scanning lidar data. The results from both simulated and lidar scanned data show similar structures orienting the streak-like structure along the mean wind. This indicates that the streak-like structures can exist in the real atmosphere during unstable atmospheric condition cases.

Rai, Raj K.↗

NASA NTRS1981

Moisture analysis from radiosonde and microwave spectrometer data

A method for analysis of the horizontal and vertical distributions of the moisture field utilizing satellite, upper air and surface data is proposed in this paper. A brief overview of the microwave sensors on board Nimbus 5 and 6 is also presented. A technique is provided utilizing the radiosonde data sets to calibrate the satellite field of total precipitable water. Next, the calibrated satellite-derived field is utilized along with ship and coastal reports of moisture, and a vertical structure function to generate vertical distribution of moisture and thus provide a mapping of specific humidity at several levels in the troposphere. Utilizing these procedures, analyses for several case studies were performed. The resultant maps show detailed distribution of specific humidity along with some interesting climatological features. A reasonable acceptance of the available aerological data sets by the analysis scheme is demonstrated.

Haydu, K. J.↗

DOE OSTI2026

Generative models on phase space

Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when the training data appears to be concentrated on a submanifold of the data embedding space. For high-energy physics data, consisting of collections of relativistic energy-momentum 4-vectors, this submanifold can enforce extremely strong physically-motivated priors, such as energy and momentum conservation. If these constraints are learned only approximately, rather than exactly, this can inhibit the interpretability and reliability of such generative models. To remedy this deficiency, we introduce generative models which are, by construction, confined at every step of their sampling trajectory to the manifold of massless N-particle Lorentz-invariant phase space in the center-of-momentum frame. In the case of diffusion models, the "pure noise" forward process endpoint corresponds to the uniform distribution on phase space, which provides a clear starting point from which to identify how correlations among the particles emerge during the reverse (de-noising) process. We demonstrate that our models are able to learn both few-particle and many-particle distributions with various singularity structures, paving the way for future interpretability studies using generative models trained on simulated jet data.

Bogorad, Zachary [Fermilab]↗

DOE OSTI2020

A New Capability of E4D For 3D Parallel Joint Inversion of DC Resistivity And Traveltime Data on Unstructured Mesh

A major challenge in interpreting geophysical data is how to derive consistent three-dimensional (3D) earth models of different physical properties from spatially and temporally limited measurements. Joint inversion with cross-gradient constraints is an approach to find such models by imposing structural similarities between different physical parameters. We have developed a parallel distributed-memory joint inversion code for direct-current (DC) resistivity and traveltime data using the cross-gradient constraint on unstructured mesh. The code utilizes existing E4D framework for parallel forward simulation, distributed storage and computation of the Jacobian matrix of forward operator, and parallel execution of matrix-vector multiplication during inversion. Besides, the joint inversion is solved by nonlinear conjugate gradient algorithm parallelized for DC resistivity and traveltime data. The joint inversion capability of E4D was tested using synthetic data from cross-borehole DC resistivity and traveltime data. The results indicate that the shape and size of the anomalies from the joint inversion are more reliable than those from separate inversions.

58 GEOSCIENCES↗

NASA NTRS1993

NELS 2.0 - A general system for enterprise wide information management

NELS, the NASA Electronic Library System, is an information management tool for creating distributed repositories of documents, drawings, and code for use and reuse by the aerospace community. The NELS retrieval engine can load metadata and source files of full text objects, perform natural language queries to retrieve ranked objects, and create links to connect user interfaces. For flexibility, the NELS architecture has layered interfaces between the application program and the stored library information. The session manager provides the interface functions for development of NELS applications. The data manager is an interface between session manager and the structured data system. The center of the structured data system is the Wide Area Information Server. This system architecture provides access to information across heterogeneous platforms in a distributed environment. There are presently three user interfaces that connect to the NELS engine; an X-Windows interface, and ASCII interface and the Spatial Data Management System. This paper describes the design and operation of NELS as an information management tool and repository.

Smith, Stephanie L.↗

NASA NTRS1992

Structure in the COBE differential microwave radiometer first-year maps

Results of the first year of data from the differential microwave radiometers on the Cosmic Background Explorer are presented. Statistically significant structure that is well described as scale-invariant fluctuations with a Gaussian distribution is shown. The rms sky variation, smoothed to a total 10-deg FWHM Gaussian, is 30 +/-5 micro-K for Galactic latitude greater than 20-deg data with the dipole anisotropy removed. The rms cosmic quadrupole amplitude is 13 +/-4 micro-K. The angular autocorrelation of the signal in each radiometer channel and cross-correlation between channels are consistent and give a primordial fluctuation power-law spectrum with index of 1.1 +/-0.5, and an rms-quadrupole-normalized amplitude of 16 +/-4 micro-K. These features are in accord with the Harrison-Zel'dovich spectrum predicted by models of inflationary cosmology.

Smoot, G. F.↗

DOE OSTI2021

Importance of nuclear quantum effects on the hydration of chloride ion

Path-integral ab initio molecular dynamics (PI-AIMD) calculations have been employed to probe the nature of chloride ion solvation in aqueous solution. Nuclear quantum effects (NQEs) are shown to weaken hydrogen bonding between the chloride anion and the solvation shell of water molecules. As a consequence, the disruptive effect of the anion on the solvent water structure is significantly reduced compared to what is found in the absence of NQEs. Additionally, the chloride hydration structure obtained from PI-AIMD agrees well with information extracted from neutron scattering data. In particular, the observed satellite peak in the hydrogen-chloride-hydrogen triple angular distribution serves as a clear signature of NQEs. The present results suggest that NQEs are likely to play a crucial role in determining the structure of saline solutions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding

Over the last decade, scanning transmission electron microscopy (STEM) has emerged as a powerful tool for probing atomic structures of complex materials with picometer precision, opening the pathway toward exploring ferroelectric, ferroelastic, and chemical phenomena on the atomic scale. Analyses to date extracting a polarization signal from lattice coupled distortions in STEM imaging rely on discovery of atomic positions from intensity maxima/minima and subsequent calculation of polarization and other order parameter fields from the atomic displacements. Here, we explore the feasibility of polarization mapping directly from the analysis of STEM images using deep convolutional neural networks (DCNNs). In this approach, the DCNN is trained on the labeled part of the image (i.e., for human labelling), and the trained network is subsequently applied to other images. We explore the effects of the choice of the descriptors (centered on atomic columns and grid-based), the effects of observational bias, and whether the network trained on one composition can be applied to a different one. This analysis demonstrates the tremendous potential of the DCNN for the analysis of high-resolution STEM imaging and spectral data and highlights the associated limitations.

36 MATERIALS SCIENCE↗