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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Where have all the sources gone?

In the continuing quest for an understanding of the cosmic x-ray background, the most difficult technical barrier remains the mismatch between the wavelength band in which the discrete source populations are best characterized (0.1 to 3.5 keV), and the band in which the spectrum of the background is well determined and the bulk of the energy density resides (3.5 to 50 keV). A progress report in an attempt to resolve this conundrum using the Einstein Imaging Proportional Counter (IPC) database and analysis system is presented. The IPC data base is described and how it can be used to search both for missing clusters of galaxies and highly obscured active galactic nuclei is addressed. All 4083 imaging proportional counter observations were examined after flat fielding and editing to optimize sensitivity for diffuse emission on various size scales ranging up to 10 feet. A '2 sigma source' catalog which, when filtered by matching with source catalogs from other wavelength regimes, is shown to reveal new source classes which may be significant contributors to the cosmic x-ray background is being constructed. Optimization techniques are described and the source catalogs which result are presented. Limits on the contributions both classes of sources make to resolving the discrepancy with the higher energy observations are set.

Helfand, D. J.↗
NASA NTRS1997

Does the Ultraviolet Imager on Polar Detect Cometesimals?

The Earth's dayglow images obtained by the Ultraviolet Imager (UVI) on Polar should show darkened pixels if cometesimals bombard Earth. This darkening occurs because the UV emissions are absorbed by water between the altitude where the dayglow emissions are produced and the Polar spacecraft. We have asked: (1) Does the UVI detect darkened pixels? (2) If so, what are their characteristics? (3) What can the UVI say about the presence/absence of cometesimals? The UVI does see dark pixels, which tend to be clustered. But the calibration data obtained from the same instrument just before the instrument was launched show similarly darkened pixel clusters. After a though statistical analysis of these images, we conclude that the darkened pixels are instrumental artifacts. Therefore, the UVI does not provide evidence for the existence of the cometesimals.

Parks, G. K.↗
NASA NTRS1998

Galaxy Cluster Masses at Moderate Redshifts

The masses of galaxy clusters are dominated by dark matter, and a robust determination of their masses has the potential of indicating how much dark matter exists on large scales in the universe, and the cosmological parameter Omega. X-ray observations of galaxy clusters provide a direct measure of both the gas mass in the intra-cluster medium, and also the total gravitating mass of the cluster. We used new and archival ROSAT observations to measure these quantities for a sample of intermediate redshift clusters which have also been subject to intensive dynamical studies, in order to compare the mass estimates from different methods. We used data from 14 of the CNOC cluster sample at 0.18 less than z less than 0.55 for this study. A direct comparison of dynamical mass estimates from Carlberg, Yee & Ellingson (1997) yielded surprisingly good results. The X-ray/dynamical mass ratios have a mean of 0.96+/- 0.10, indicating that for this sample, both methods are probably yielding very robust mass estimates. Comparison with mass estimates from gravitational lensing studies from the literature showed a small systematic with weak lensing estimates, and large discrepancies with strong lensing estimates. This latter is not surprising, given that these measurement are made close to the central core, where optical and X-ray estimates are less certain, and where substructure and the effects of individual galaxies will be more pronounced. These results are presented in Lewis, Ellingson, Morris/Carlberg, 1998, submitted to the Astrophysical Journal. (Note that Lewis is Ellingson's Ph.D. thesis, who received direct support from this grant and is using this investigation as part of his thesis.) Three additional papers are in preparation. The first provides a comparison of the mass profiles as measured in X- rays and in galaxy dynamics. These profiles are difficult to determine for individual clusters, and are subject to asphericity and other individual quirks of each cluster. However, a composite profile for each method will allow us to test our assumptions of hydrostatic/dynamical equilibrium in the sample as a whole. A second paper provides a more detailed look at the cluster MS0906+11, which is a merging system. A third paper authord with J. Mohr at U. Chicago will invetigate the size-temoerature relationship for intermediate redshift clusters and its impications on cluster formation and cosmology. Future work on these data will include comparisons of the cluster galaxy populations and the extent of the intra-cluster medium, and a more homogeneous analysis of gravitational lensing.

Ellingson, E.↗
NASA NTRS1999

An Intercomparison of Ground, Airborne, and Space Instrumentation Definitions of the Lightning Element

For the past century, scientists have made quantitative measurements of lightning discharges. In the process, they refined the definition of a lightning unit, or basic quantum of lightning, in order to base it on observable parameters. In this paper, we will use cluster analysis to derive a basic spatial and temporal definition or scale length for the unit of lightning. We will use data from three different systems that detected pulses from the same storm complex over Central Oklahoma during June, 1998. Since the different instruments detect lightning in different ways with different resolutions, there may not be a single definition of the unit of lightning that can be applied to all three systems. However, common components can be found since all instrumentation are detecting aspects of the same phenomenon.

Mach, Douglas↗
NASA NTRS2006

Probabilistic Classification Using Elemental Abundance Distributions and Lossless Image Compression in Apollo 17 Lunar Dust Samples from Mare Serenitatis

We have previously outlined a strategy for the detection of fossils [Storrie-Lombardi and Hoover, 2004] and extant microbial life [Storrie-Lombaudi and Hoover, 20051 during robotic missions to Mars using co-registered structural and chemical signatures. Data inputs included image lossless compression indices to estimate relative textural complexity and elemental abundance distributions. Two exploratory classification algorithms (principal component analysis and hierarchical cluster analysis) provide an initial tentative classification of all targets. Nonlinear stochastic neural networks are then trained to produce a Bayesian estimate of algorithm classification accuracy. The strategy previously has been successful in distinguishing regions of biotic and abiotic alteration of basalt glass from unaltered samples. [Storrie-Lombardi and Fisk, 2004; Storrie-Lombardi and Fisk, 2004] Such investigations of abiotic versus biotic alteration of terrestrial mineralogy on Earth are compromised by .the difficulty finding mineralogy completely unaffected by the ubiquitous presence of microbial life on the planet. The renewed interest in lunar exploration offers an opportunity to investigate geological materials that may exhibit signs of aqueous alteration, but are highly unlikely to contain contaminating biological weathering signatures. We here present an extension of our earlier data set to include lunar dust samples obtained during the Apollo 17 mission. Apollo 17 landed in the Taurus-Littrow Valley in Mare Serenitatis. Most of the rock samples from this region of the lunar highlands are basalts comprised primarily of plagioclase and pyroxene and selected examples of orange and black volcanic glass. SEM images and elemental abundances (C6, N7, O8, Na11, Mg12, Al13, Si14, P15, S16, Cll7, K19, Ca20, Fe26) for a series of targets in the lunar dust samples are compared to the extant cyanobacteria, fossil trilobites, Orgueil meteorite, and terrestrial basalt targets previously discussed. The data set provides a first step in producing a quantitative probabilistic methodology for geobiological analysis of returned lunar samples or in situ exploration.

Storrie-Lombardi, Michael C.↗
NASA NTRS1998

High Performance Parallel Architectures

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operational. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, aimed at concentrating the vital information and discarding redundant data. One such transformation, which is widely used in remote sensing, is the Principal Components Analysis (PCA). This report summarizes our progress on the development of a parallel PCA and its implementation on two Beowulf cluster configuration; one with fast Ethernet switch and the other with a Myrinet interconnection. Details of the implementation and performance results, for typical sets of multispectral and hyperspectral NASA remote sensing data, are presented and analyzed based on the algorithm requirements and the underlying machine configuration. It will be shown that the PCA application is quite challenging and hard to scale on Ethernet-based clusters. However, the measurements also show that a high- performance interconnection network, such as Myrinet, better matches the high communication demand of PCA and can lead to a more efficient PCA execution.

El-Ghazawi, Tarek↗
NASA NTRS2018

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a piloting an aircraft, where activities with distinct visual signatures might be things like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as delta. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration delta, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to integer counts by multiplying by delta divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. The method has been applied to approximately 100 hours of eye movement data collected from pilots in a high-fidelity B747 flight simulator, and the results have been compared to synthetic data in which the each activity is represented as first-order Markov process with random probabilities assigned to the AOIs. Randomly-generated synthetic activities can require thousands of fixations to be discriminated with statistical significance, while the human data can be clustered using averaging windows of some 10's of seconds, suggesting that the actual activities are much more narrowly focused than random Markov models.

activity analysis↗
NASA NTRS2003

Physics of Galaxy Clusters and How it Affects Cosmological Tests

We have worked on the analysis of the Chandra observations of the distant clusters of galaxies, and on exploring new ways to obtain cosmological constraints from the cluster data. Some of the scientific results are discussed below: (1) Evolution of the cluster scaling relations at z is approximately 0.5; (2) Using gas mass as a proxy for the total cluster mass.

Vikhlinin, Alexey↗
NASA NTRS2016

Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

In response to severe weather conditions, traffic management coordinators specify reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options would assist the traffic management coordinators in making more efficient rerouting decisions. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. Essentially, using previous information to inform future decisions. This paper describes the initial steps and methodology used towards this goal. A method to extract relevant features from the large volume of weather data to quantify the convective weather scenario during a particular time range is presented. Similar routes are clustered. A description of the algorithm to identify which cluster of reroute advisories were actually followed by pilots is described. Models built for fifteen of the top twenty most frequently used reroute clusters correctly predict the use of the cluster for over 60 of the test examples. Results are preliminary but indicate that the methodology is worth pursuing with modifications based on insight gained from this analysis.

machine learning↗
NASA NTRS2010

Kepler Science Operations Center Pipeline Framework

The Kepler mission is designed to continuously monitor up to 170,000 stars at a 30 minute cadence for 3.5 years searching for Earth-size planets. The data are processed at the Science Operations Center (SOC) at NASA Ames Research Center. Because of the large volume of data and the memory and CPU-intensive nature of the analysis, significant computing hardware is required. We have developed generic pipeline framework software that is used to distribute and synchronize the processing across a cluster of CPUs and to manage the resulting products. The framework is written in Java and is therefore platform-independent, and scales from a single, standalone workstation (for development and research on small data sets) to a full cluster of homogeneous or heterogeneous hardware with minimal configuration changes. A plug-in architecture provides customized control of the unit of work without the need to modify the framework itself. Distributed transaction services provide for atomic storage of pipeline products for a unit of work across a relational database and the custom Kepler DB. Generic parameter management and data accountability services are provided to record the parameter values, software versions, and other meta-data used for each pipeline execution. A graphical console allows for the configuration, execution, and monitoring of pipelines. An alert and metrics subsystem is used to monitor the health and performance of the pipeline. The framework was developed for the Kepler project based on Kepler requirements, but the framework itself is generic and could be used for a variety of applications where these features are needed.

Klaus, Todd C.↗
NASA NTRS1978

Buckling tests of structural elements applicable to large erectable space trusses

Detailed data on columns and center a joint for completeness is presented. Buckling data for a tripod arrangement of these columns using a cluster joint is also presented. The objectives of these test are: (1) to gain insight into joint requirements for truss structure; (2) to assess the structural qualities of the column and center joint designs; (3) to investigate the restraint provided by octetruss core members (tripod) to the cluster joints; (4) to provide insight into the level of analysis required to predict buckling behavior of Gr/E nestable columns both as simple columns and in a tripod arrangement; and (5) to provide a data base for Gr/E nestable columns.

Heard, W. L., Jr.↗
NASA NTRS1981

Skylab's Apollo telescope mount

A large part of the scientific knowledge provided by the Skylab mission was obtained from high resolution observations of the structure and behavior of the sun utilizing scientific instruments mounted in the Apollo Telescope Mount (ATM). The Skylab Attitude and Pointing Control System (APCS) provided three-axis attitude stabilization and maneuvering capability for the Skylab cluster as well as pointing control of the ATM experiment canister with the Experiment Pointing Control System. Based on an analysis of flight data, it can be concluded that the Skylab APCS successfully performed within design specifications and met or exceeded all imposed requirements.

Chubb, W. B.↗
NASA NTRSDate not supplied

Providing Long-term Solar and Meteorological Resource Information from NASA Research through the GIS-Enabled POWER Web Services Portal

Solar and other renewable energy systems are optimized using geophysical parameters describing information about the solar resource and meteorological environments and how those environments may be changing in time. The Prediction of Worldwide Renewable Energy Resource (POWER) team at the NASA LaRC Research Center deployed its first version of the revitalized POWER geophysical parameter website that employs Esri Geographic Information System (GIS) tools. This web application provides access to both time series and climatological data sets spanning from a few days behind real-time back to the early 1980’s with a spatial resolution of 0.5 x 0.5 degree, thus extending over 30 years. The GIS tools enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility to government agencies, industry and individuals. There is an API that provides data through a URL coding and can also invoked inside user software packages. Output data formats now include ASCII, CSV, geoTiff, JSON and .netCDF. Since May 2018, over 10.4 TB of data have been delivered to fulfill over 110 million data requests from 240,000 unique user IPs (https://power.larc.nasa.gov). This presentation provides an overview of this project and the current version of the new POWER web capabilities through to the end usage. Surface solar parameters are adapted from both the NASA/GEWEX (Global and Energy Water Cycle Exchange) SRB (Surface Radiation Budget) project and the CERES (Clouds and Earth’s Radiant Energy System) data products. The meteorological parameters are adapted from NASA’s MERRA-2 (Modern Era Retrospective-analysis for Research and Applications). We review uncertainty of various basic parameters using surface measurements. After the introduction, we specifically discuss various clusters of parameters for equator pointing tilted surfaces that provide for the estimation of optimal tilt angle by month and year. The discussion will emphasize a few examples of how solar and building engineers are using the data products. We will then preview the capabilities of Version 2 featuring examples of hourly solar and meteorological data products, customized user reports and expanded web mapping services from CERES data products. The web services provide a unique, expandable resource for renewable energy systems engineers to design, evaluate and optimize to environments worldwide.

Solar Resource↗
NASA NTRS2005

Jet-Intracluster Medium Interactions of the Head Tail Radio Galaxy 3C 129

The 50 ksec XMM observations of the galaxy cluster 3C 129 were taken as scheduled, and the data are of good quality. We analyzed the data in the following way. After standard cleaning, we flat-fielded the XMM surface brightness maps. Combining the data from the EPIC MOS and PN Camera CCDs, we performed a cross-correlation analysis of the X-ray surface brightness distribution with the 1.4 GHz VLA radio map. We found evidence for cavities in the X-ray emitting Intra-Cluster Medium (ICM) associated with the radio tail of the head-tail radio galaxy 3C 129. This discovery is very interesting as it excludes the presence of a large fraction of thermal plasma in the radio tail. Together with the observation of an apparent pressure mismatch between the radio plasma and the ICM, and an upper limit on the magnetic field inside the radio tail (from the radio spectral indices map) the observation implies that the tail pressure is dominated either by low-energy electrons/positrons, or, by relativistic protons. Furthermore, we studied the energy spectrum of an X-ray "hot-spot" associated with the head of the radio galaxy 3C 129. It seems likely that the X-ray hot-spot originates from shocked gas in front of the radio galaxy. , The analysis turned out to be much more difficult than anticipated. The main reason is the lack of a comprehensive, publicly available background model that is key for the analysis of extended sources. Small groups like our do not have the man-power to come up with a background model themselves. We used the model from Read & Ponman (A&A 409, 395, 2003). However, the background subtracted X-ray surface brightness maps show a bright ring in the outer 20% of the camera. We tried to get rid of this ring and contacted the XMM helpdesk and Read & Ponman, the authors of the background paper. However, up to this day, we did not entirely succeed to remove the brightness enhancement at the outer parts of the camera. Unfortunately, our results are somewhat sensitive to the uncertainty, as the radio galaxy 3C 129 is very large and occupies a rather large fraction of the XMM field of view. We are now working on a paper describing the results. The paper will include a detailed discussion of the uncertainties associated with the non- perfect background subtraction.

Krawczynski, Henric S. W.↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Transonic Truss-Braced Wing Aircraft: Part 2 – Acoustic Signature and Noise Source Identification

High-fidelity, time-dependent simulations of a Boeing-designed, transonic, truss-braced-wing aircraft in cruise (clean) and landing configurations are leveraged to generate synthetic microphone-phased-array data for airframe noise prediction and assessment. These data sets are used to compute source localization (beamform) maps to determine the location and strength of primary and secondary airframe noise sources associated with this unique configuration. The synthetic phased-array implementation mimics the setup of a flight test. As this study is ongoing, preliminary integrated far-field spectra for the cruise configuration obtained at multiple spatial resolutions revealed significant tonal content that lacked convergence with increased resolution. The origin of several of these tones and their unusual convergence behavior was traced to the larger-than-normal trailing-edge thickness of the “as-tested” cruise model being simulated. Reducing the trailing-edge thickness to more realistic values eliminated most of the tones at low to moderate frequencies and improved spectrum convergence significantly. Applying lessons learned from the cruise simulations, several modifications to the geometry of the landing configuration were made and are described in this work. Results from permeable and solid Ffowcs-Williams and Hawkings surfaces at two different spatial resolutions (coarse and medium) are used to illustrate the major noise sources and determine convergence of the CLEAN integrated noise levels for the entire aircraft as well as major subcomponents. We demonstrate that the low-frequency content of the far-field spectrum is dominated by noise generated from the main landing gear, while the medium- and high-frequency content is dominated by the wing-leading-edge Krueger flaps. Since analysis of the acoustic maps for the landing configuration revealed several clusters of multiple sources along the wing leading edge, “high resolution” processing of the array data was used to distinguish more accurately the locations of sources.

Transonic Truss-Braced Wing↗
NASA NTRS1974

An automated and repeatable data analysis procedure for remote sensing applications

A new multispectral data analysis procedure, based on LARSYS, has been developed which substantially reduces the influence of the analyst. The analysis is automated, including the interpretation of clustering results. The classification results obtained are repeatable and not biased by analyst subjectivity during the analysis.

Davis, B. J.↗
NASA NTRS1989

Analysis of ISEE-3/ICE solar wind data

Under the grant that ended November 11, 1988 work was accomplished in a number of areas, as follows: (1) Analysis of solar wind data; (2) Analysis of Giacobini/Zinner encounter data; (3) Investigation of solar wind and magnetospheric electron velocity distributions; and (4) Experimental investigation of the electronic structure of clusters. Reprints and preprints of publications resulting from this work are included in the appendices.

Coplan, Michael A.↗
NASA NTRS2016

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗