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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Localization of an experimental ecological unit in the Maradi region of Nigeria

A detailed topographical and geomorphological description of a specific ecological unit in the Maradi region of the Sahel in the Niger Republic is presented. Sandy structures are classified into active dunes and covered dunes and an extensives vocabulary is developed to describe sub-categories. The descriptions are based on meteorological data (anemometric and rainfall) from local weather stations, ground observations, aerial photographs and LANDSAT pictures. The problem of dune reactivation and desertification is discussed both from the standpoint of causes and possible counter measures.

Mainguet, M.↗
NASA NTRS1997

Gamma-Ray Burst Arrival Time Localizations: Simultaneous Observations by Mars Observer, Compton Gamma Ray Observatory and Ulysses

Between 1992 October 4 and 1993 August 1, concurrent coverage by the Compton Gamma Ray Observatory (CGRO), Mars Observer (MO), and Ulysses spacecraft was obtained for 78 gamma-ray bursts (GRBs). Although most of these were below the MO and Ulysses thresholds, nine were positively detected by all three spacecraft, with data quality adequate for quantitative localization analysis. All were localized independently to approximately 2 deg accuracy by the CGRO Burst and Transient Source Experiment (BATSE). We computed arrival-time error boxes with larger dimensions ranging from a few arcminutes to the diameters of the BATSE-only boxes and with smaller dimensions in the arcminute range. Three events are of particular interest: GB 930704 (BATSE 2428) has been described as a possible repeater. The arrival-time information is consistent with that hypothesis, but only just so. The GB 930706 (2431) box, at approximately 1 min x 4 min, is the only one this small obtained since Pioneer Venus Orbiter (PVO) entered the Venusian atmosphere in 1992 October. Sensitive radio and optical observations of this location were made within 8 and 9 days of the burst, but no counterpart candidates were identified. GB 930801 (2477) is the first GRB that had its localization improved by taking into account BATSE Earth occultation.

Laros, J. G.↗
DOE OSTI2026

Particle Filter Based Inference Testing

The primary intent of PAR-FIT (Particle Filter based Inference Testing) is to provide hard inductive evidence that a machine learning model is capable and proven for an individual test input. By examining training data used to form the underlying model functional correlation, an estimate of the reliability that a model will make the correct prediction can be made. The Sequential Probability Ratio Test is used to derive a qualitative evaluation for reliability based on hypothesis testing. The PAR-FIT framework achieves this by implementing a particle filter and the sequential probability ratio test algorithms on the machine learning model training data to determine relevancy of new individual test samples to the training dataset. The kernel function evaluates the local proximity and density of training data used to derive a prediction outcome. Particles are used to probabilistically determine which training data to evaluate for proximity. For test samples that are within a close proximity to and surrounded by multiple training data points, the evaluated reliability of the prediction is high. For test samples that are anomalies not represented by the training dataset, in low density data clusters, or are far from existing data points, the evaluated reliability is low as insufficient training evidence exists to suggest the model is capable of making the correct prediction. Sequential Probability Ratio Test is further used to determine when a hypothesis on whether a signal can be rejected or accepted for use. The ratio test collects sequence information from the particle filter to test whether the signal is anomalous or normal via hypothesis testing of the underlying distributions.

Chen, Edward [Idaho National Laboratory (INL), Ida↗
DOE OSTI2024

Subsurface Energy Systems Mapping Inquiry Tool (MapIT)

The Subsurface Energy Systems Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration for subsurface energy exploration and characterization efforts for resource identification (e.g. critical minerals, hydrocarbons, geothermal) as well as injection of geologic sequestration of carbon dioxide (e.g. enhanced oil recovery, saline storage, etc.). Modules within the tool curate data related to geology, faults, fractures, injection and confining zones, hydrologic information, groundwater, groundwater wells, geomechanical and petrophysical data, and geochemical data. User documentation on how to use the tool is also provided. Data have been collected from authoritative national, state, and local sources and made available in this tool. The data is also available as a data catalog and Esri Geodatabase at: https://edx.netl.doe.gov/dataset/mapit-database Disclaimer: There is no guarantee of completeness or appropriateness for individual user’s requirements. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer). This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. https://www.netl.doe.gov/home/disclaimer

Carbon Sequestration↗
NASA NTRS1977

Flight-test evaluation of two electronic display formats for approach to landing under instrument conditions

The results of a flight evaluation of two electronic display formats for the approach to landing under instrument conditions are presented. The evaluation was conducted for a base-line electronic display format and for the same format with runway symbology and track information added. The evaluation was conducted during 3 deg, manual straight-in approaches with and without initial localizer offsets. Flight path tracking performance data and pilot subjective comments were examined with regard to the pilot's ability to capture and maintain localizer and glide slope by using both display formats.

Morello, S. A.↗
NASA NTRS1988

Data traffic reduction schemes for sparse Cholesky factorizations

Load distribution schemes are presented which minimize the total data traffic in the Cholesky factorization of dense and sparse, symmetric, positive definite matrices on multiprocessor systems with local and shared memory. The total data traffic in factoring an n x n sparse, symmetric, positive definite matrix representing an n-vertex regular 2-D grid graph using n (sup alpha), alpha is equal to or less than 1, processors are shown to be O(n(sup 1 + alpha/2)). It is O(n(sup 3/2)), when n (sup alpha), alpha is equal to or greater than 1, processors are used. Under the conditions of uniform load distribution, these results are shown to be asymptotically optimal. The schemes allow efficient use of up to O(n) processors before the total data traffic reaches the maximum value of O(n(sup 3/2)). The partitioning employed within the scheme, allows a better utilization of the data accessed from shared memory than those of previously published methods.

Naik, Vijay K.↗
NASA NTRS1994

Monolithic Optical-To-Electronic Receiver

Monolithic optoelectronic integrated circuit converts multiplexed digital optical signals into electrical signals, separates, and distributes them to intended destinations. Developed to deliver phase and amplitude commands to monolithic microwave integrated circuits (MMIC's) at elements of millimeter-wave phased-array antenna from single optical fiber driven by external array controller. Also used in distribution of high-data-rate optical communications in local-area networks (LAN's). Notable features include options for optical or electrical clock inputs; outputs for raw data, addresses, and instructions for diagnosis; and optical-signal-detection circuit used to reduce power consumption by 80 percent between data-transmission times. Chip fabricated by processes available at many major semiconductor foundries. Distribution of digital signals in aircraft, automobiles, and ships potential application.

Kunath, Richard↗
NASA NTRS2003

Transmitting Data from Space at Higher Speeds

The CICT Program's Space Communications (SC) Project is responsible for developing technologies that deliver data quickly between Earth and space, and directly to users. To achieve this ambitious goal. the SC Project is providing technologies for building the Space Internet, which will require back-bone networks that pass data from one infrastructure to another. These infrastructures include the Earth-based wide-area and local-area networks. NASAs Tracking and Data Relay Satellite System (TDRSS) that provides links between low-earth orbiting spacecraft, and the ground planetary networks, and the Deep Space Network (DSN).

Laufenberg, Lawrence↗
DOE OSTI2017

Improved treatment of exact exchange in Quantum ESPRESSO

Here, we present an algorithm and implementation for the parallel computation of exact exchange in Quantum ESPRESSO (QE) that exhibits greatly improved strong scaling. QE is an open-source software package for electronic structure calculations using plane wave density functional theory, and supports the use of local, semi-local, and hybrid DFT functionals. Wider application of hybrid functionals is desirable for the improved simulation of electronic band energy alignments and thermodynamic properties, but the computational complexity of evaluating the exact exchange potential limits the practical application of hybrid functionals to large systems and requires efficient implementations. We demonstrate that existing implementations of hybrid DFT that utilize a single data structure for both the local and exact exchange regions of the code are significantly limited in the degree of parallelization achievable. We present a band-pair parallelization approach, in which the calculation of exact exchange is parallelized and evaluated independently from the parallelization of the remainder of the calculation, with the wavefunction data being efficiently transformed on-the-fly into a form that is optimal for each part of the calculation. For a 64 water molecule supercell, our new algorithm reduces the overall time to solution by nearly an order of magnitude.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

An extended JBN method of determining unsteady-state two-phase relative permeability

Relative permeability is the reduction of permeability of porous media when subjected to multiphase flow and a key parameter in subsurface hydrology. The JBN method is a well-known method of obtaining relative permeability, which measures the overall pressure drop and the effluent phase ratio versus time during two-phase displacements. By assuming no capillary pressure or gravity, the JBN method obtains the relative permeabilities to both phases at the core outlet. Since data across a range of saturations are acquired in a relatively short time, this method is widely used. This work extends the JBN method by having (1) section-wise pressure drop measurements between the core inlet, four pressure taps on the core and the outlet, (2) local saturation measurements, and (3) local phase fluxes. With these data, the extended JBN method can determine relative permeabilities to both phases at each pressure tap of the core (not just at the core outlet). The JBN extension is shown using a data set where CO 2 invades a brine-filled core. From this it is found that the advantages of the extended JBN method over the regular JBN method are: (1) four times more data are obtained, and (2) data are more accurate because the capillary end effect is experimentally avoided. Avoiding the end effect results in tripling the saturation range, and obtaining relative permeabilities that are consistent with steady-state measurements and roughly 40% higher than those from the regular JBN method.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Implementation of Dynamic Extensible Adaptive Locally Exchangeable Measures (IDEALEM) v 0.1

Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable. One possible solution to reduce the storage of vast amounts of measured data is to store a random sample, such as one out of 1000 network packets. However, such static sampling methods (linear sampling) have drawbacks: (1) it is not scalable for high-rate streaming data, and (2) there is no guarantee of reflecting the underlying distribution. In this software, we implemented a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.

Sim, Alex↗
NASA NTRS1981

VISSR Atmospheric Sounder (VAS) simulation experiment for a severe storm environment

Radiance fields were simulated for prethunderstorm environments in Oklahoma to demonstrate three points: (1) significant moisture gradients can be seen directly in images of the VISSIR Atmospheric Sounder (VAS) channels; (2) temperature and moisture profiles can be retrieved from VAS radiances with sufficient accuracy to be useful for mesoscale analysis of a severe storm environment; and (3) the quality of VAS mesoscale soundings improves with conditioning by local weather statistics. The results represent the optimum retrievability of mesoscale information from VAS radiance without the use of ancillary data. The simulations suggest that VAS data will yield the best soundings when a human being classifies the scene, picks relatively clear areas for retrieval, and applies a "local" statistical data base to resolve the ambiguities of satellite observations in favor of the most probable atmospheric structure.

Chesters, D.↗
DOE OSTI2022

Predicting defects in laser powder bed fusion using in-situ thermal imaging data and machine learning

Variation in the local thermal history during the Laser Powder Bed Fusion (LPBF) process in Additive Manufacturing (AM) can cause micropore defects, which add to the uncertainty of the mechanical properties (e.g., fatigue life, tensile strength) of the built materials. In-situ sensing has been proposed for monitoring the AM process to minimize defects, but successful minimization requires establishing a quantitative relationship between the sensing data and the porosity, which is particularly challenging with a large number of variables (e.g., laser speed, power, scan path, powder property). Physics-based modeling can simulate such an in-situ sensing-porosity relationship, but it is computationally costly. In this work, we develop Machine Learning (ML) models that can use in-situ thermographic data to predict the micropore of LPBF stainless steel materials. This work considers two identified key features from the thermal histories: the time above the apparent melting threshold ($\tau$) and the maximum radiance ( T max ). These features are computed, stored for each voxel in the built material, and then used as inputs. The binary state of each voxel, either defective or normal, is the output. Different ML models are trained and tested for the binary classification task. In addition to using the thermal features of each voxel to predict its own state, the thermal features of neighboring voxels are also included as inputs. This is shown to improve the prediction accuracy, which is consistent with thermal transport physics around each voxel contributing to its final state. Among the models trained, the F1 scores on test sets reach above 0.96 for Random Forests. Feature importance analysis based on the ML models shows that T max is more important to the voxel state than $\tau$ . The analysis also finds that the thermal history of the voxels above the present voxel is more influential than those beneath it. Our study significantly extends the capability of using in-situ thermographic data to predict porosity in LPBF materials. Finally, since ML models are fast, they may play integral roles in the optimization and control of such AM technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Impact of a Locally Measured H {sub 0} on the Interpretation of Cosmic-chronometer Data

Many measurements in cosmology depend on the use of integrated distances or time, but galaxies evolving passively on a timescale much longer than their age difference allow us to determine the expansion rate H ( z ) solely as a function of the redshift–time derivative dz / dt . These model-independent “cosmic chronometers” can therefore be powerful discriminators for testing different cosmologies. In previous applications, the available sources strongly disfavored models (such as ΛCDM) predicting a variable acceleration, preferring instead a steady expansion rate over the redshift range 0 ≲ z ≲ 2. A more recent catalog of 30 objects appears to suggest non-steady expansion. In this paper, we show that such a result is entirely due to the inclusion of a high, locally inferred value of the Hubble constant H{sub 0} as an additional datum in a set of otherwise pure cosmic-chronometer measurements. This H {sub 0}, however, is not the same as the background Hubble constant if the local expansion rate is influenced by a Hubble Bubble. Used on their own, the cosmic chronometers completely reverse this conclusion, favoring instead a constant expansion rate out to z∼2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Can I solve my structure by SAD phasing? Planning an experiment, scaling data and evaluating the useful anomalous correlation and anomalous signal

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, we describe algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment. A simple theoretical framework [Terwilliger et al. (2016), Acta Cryst. D 72 , 346–358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. The phenix.plan_sad_experiment tool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. The phenix.scale_and_merge tool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and the phenix.anomalous_signal tool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Hera - The HEASARC's New Data Analysis Service

Hera is the new computer service provided by the HEASARC at the NASA Goddard Space Flight Center that enables qualified student and professional astronomical researchers to immediately begin analyzing scientific data from high-energy astrophysics missions. All the necessary resources needed to do the data analysis are freely provided by Hera, including: * the latest version of the hundreds of scientific analysis programs in the HEASARC's HEASOFT package, as well as most of the programs in the Chandra CIAO package and the XMM-Newton SAS package. * high speed access to the terabytes of data in the HEASARC's high energy astrophysics Browse data archive. * a cluster of fast Linw workstations to run the software * ample local disk space to temporarily store the data and results. Some of the many features and different modes of using Hera are illustrated in this poster presentation.

Pence, William↗
NASA NTRS2012

U.S. Government Open Internet Access to Sub-meter Satellite Data

The National Geospatial-Intelligence Agency (NGA) has contracted United States commercial remote sensing companies GeoEye and Digital Globe to provide very high resolution commercial quality satellite imagery to federal/state government agencies and those projects/people who support government interests. Under NextView contract terms, those engaged in official government programs/projects can gain online access to NGA's vast global archive. Additionally, data from vendor's archives of IKONOS-2 (IK-2), OrbView-3 (OB-3), GeoEye-1 (GE-1), QuickBird-1 (QB-1), WorldView-1 (WV-1), and WorldView-2 (WV-2), sensors can also be requested under these agreements. We report here the current extent of this archive, how to gain access, and the applications of these data by Earth science investigators to improve discoverability and community use of these data. Satellite commercial quality imagery (CQI) at very high resolution (< 1 m) (here after referred to as CQI) over the past decade has become an important data source to U.S. federal, state, and local governments for many different purposes. The rapid growth of free global CQI data has been slow to disseminate to NASA Earth Science community and programs such as the Land-Cover Land-Use Change (LCLUC) program which sees potential benefit from unprecedented access. This article evolved from a workshop held on February 23rd, 2012 between representatives from NGA, NASA, and NASA LCLUC Scientists discussion on how to extend this resource to a broader license approved community. Many investigators are unaware of NGA's archive availability or find it difficult to access CQI data from NGA. Results of studies, both quality and breadth, could be improved with CQI data by combining them with other moderate to coarse resolution passive optical Earth observation remote sensing satellites, or with RADAR or LiDAR instruments to better understand Earth system dynamics at the scale of human activities. We provide the evolution of this effort, a guide for qualified user access, and describe current to potential use of these data in earth science.

Neigh, Christopher S. R>↗
NASA NTRS2018

NASA Crew Earth Observations: A Long-Term Dataset for Earth System Research, Applications, and Education

Polar orbit; Sun-synchronous - designed for long term repeatability of data, Typically nadir viewing, crosses every point on Earth ~ 12-14 days near local solar noon/local midnight, Landsat series collecting data since 1972, Pointing capability, satellite constellations. Inclined Equatorial Orbit: ISS; Sun-asynchronous - similar illumination 3-4 days every 90 days, Nadir to highly oblique imagery possible from hand-held cameras, WORF, external sensors, Provides opportunity to collect unique datasets for scientific study, disaster response, Data is complementary to polar-orbiting satellite data.

Stefanov, William L.↗