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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Blue clusters, populous clusters, and globulars

The introduction of new photometric techniques for faint objects has tremendously increased our understanding of the MC clusters, especially at the old end of the age spectrum. Many of the well-studied clusters of the past have gone through several transformations, starting as true globulars in 1960, becoming intermediate-age objects in the 1970's, but now returning to the true globular classification in the 1980's. LW 868 is an example of a cluster with such a history. Better photometric accuracy is also greatly improving our understanding of younger clusters, allowing detailed comparisons with theoretical evolutionary models, and a more reliable determination of the age-abundance relationship. The dynamical history of MC clusters can also be examined from the new data. The cluster formation rate, as well as the destruction rate, can be reconstructed from modern, deep cluster surveys.

Hodge, P. W.↗
NASA NTRS2008

A New Technique using Electron Velocity Data from the Four Cluster Spacecraft to Explore Magnetofluid Turbulence in the Solar Wind

It is now possible in certain circumstances to use velocity moments computed from the Plasma Electron and Current Experiment (PEACE) on the four Cluster spacecraft to determine a number of turbulence properties of the solar wind, including direct measurements of the vorticity and compressibility. Assuming that the four spacecraft are not co-planar and that there is only a linear variation of the plasma variables across the volume defined by the four satellites, one can estimate the curl of the fluid velocity, i.e., the vorticity. From the vorticity it is possible to explore directly intermittent regions in the solar wind where dissipation is likely to be enhanced. In addition, one can estimate directly the Taylor microscale.

Goldstein, Melvyn L.↗
DOE OSTI2016

Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data

An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion

Robust Subspace Recovery (RoSuRe) algorithm was recently introduced as a principled and numerically efficient algorithm that unfolds underlying Unions of Subspaces (UoS) structure, present in the data. The union of Subspaces (UoS) is capable of identifying more complex trends in data sets than simple linear models. In this work, we build on and extend RoSuRe to prospect the structure of different data modalities individually. We propose a novel multi-modal data fusion approach based on group sparsity which we refer to as Robust Group Subspace Recovery (RoGSuRe). Relying on a bi-sparsity pursuit paradigm and non-smooth optimization techniques, the introduced framework learns a new joint representation of the time series from different data modalities, respecting an underlying UoS model. We subsequently integrate the obtained structures to form a unified subspace structure. The proposed approach exploits the structural dependencies between the different modalities data to cluster the associated target objects. The resulting fusion of the unlabeled sensors’ data from experiments on audio and magnetic data has shown that our method is competitive with other state of the art subspace clustering methods. The resulting UoS structure is employed to classify newly observed data points, highlighting the abstraction capacity of the proposed method.

47 OTHER INSTRUMENTATION↗
NASA NTRS1981

An image-data-compression algorithm

Cluster Compression Algorithm (CCA) preprocesses Landsat image data immediately following satellite data sensor (receiver). Data are reduced by extracting pertinent image features and compressing this result into concise format for transmission to ground station. This results in narrower transmission bandwidth, increased data-communication efficiency, and reduced computer time in reconstructing and analyzing image. Similar technique could be applied to other types of recorded data to cut costs of transmitting, storing, distributing, and interpreting complex information.

Hilbert, E. E.↗
NASA NTRS1988

The globular cluster system of M31

Previous data on globular cluster candidates in M31 have been studied in order to identify a large sample of clusters with reliable UBV photometry and independent reddening estimates. The distribution of the intrinsic colors of the M31 globular clusters is similar to that of the Galactic globulars. While the flattening and kinematics of the system of metal-rich clusters suggest a disk, the more metal-poor clusters reveal little evidence for rotation. It is noted that the flattening of the system of metal-poor and intermediate clusters resembles that of the M31 spheroid, and that the effective radius of the intermediate system also resembles that of the spheroid.

Elson, Rebecca A.↗
DOE OSTI2021

Simple and Scalable Streaming: The GRETA Data Pipeline

The Gamma Ray Energy Tracking Array (GRETA) is a state of the art gamma-ray spectrometer being built at Lawrence Berkeley National Laboratory to be first sited at the Facility for Rare Isotope Beams (FRIB) at Michigan State University. A key design requirement for the spectrometer is to perform gamma-ray tracking in near real time. To meet this requirement we have used an inline, streaming approach to signal processing in the GRETA data acquisition system, using a GPU-equipped computing cluster. The data stream will reach 480 thousand events per second at an aggregate data rate of 4 gigabytes per second at full design capacity. We have been able to simplify the architecture of the streaming system greatly by interfacing the FPGA-based detector electronics with the computing cluster using standard network technology. A set of highperformance software components to implement queuing, flow control, event processing and event building have been developed, all in a streaming environment which matches detector performance. Prototypes of all high-performance components have been completed and meet design specifications.

Cromaz, Mario↗
NASA NTRS1987

The surface-brightness-effective-size relation for elliptical galaxies in the cores of clusters

Surface photometry of 372 elliptical galaxies has been performed using CCD images of the centers of 97 nearby rich Abell clusters. The strong correlation between surface brightness and effective size, originally found by Kormendy (1977), is clear in the data. Brightest cluster galaxies show much less scatter about the mean relation defined by these data than do lower-luminosity cluster ellipticals, and the slope of the relation is shallower for the brightest galaxies; these two results are tentative, however, because of uncertain selection and environmental effects. When combined with published central velocity dispersions, the photometry yields a relation for brightest cluster galaxies that is in good agreement with the mean relation for elliptical galaxies found by Djorgovski and Davis (1987). Use of the surface-brightness/scale-length relation to measure the lookback luminosity evolution of the stellar content in galaxies is promising.

Hoessel, J. G.↗
NASA NTRS1977

The structure of eight globular clusters

Star counts on short-exposure plates are presented for eight globular clusters. The data are given to several limiting magnitudes for each cluster. Projected radial distributions are determined from the star counts; no significant segregation is observed among the distributions to various limiting magnitudes. The structural parameters of the clusters (core radii and concentration factors) are determined from best-fitting King curves to the observed distributions. The central densities, total masses, central escape velocities, and relaxation times are also calculated. NGC 6093 (M80) and NGC 7099 (M30) have dense compact stellar cores, similar to the established globular X-ray sources. Upper limits are given for the masses of possible central black holes in the eight clusters.

Bahcall, N. A.↗
NASA NTRS1973

Editing ERTS-1 data to exclude land aids cluster analysis of water targets

The author has identified the following significant results. It has been determined that an increase in the number of spectrally distinct coastal water types is achieved when data values over the adjacent land areas are excluded from the processing routine. This finding resulted from an automatic clustering analysis of ERTS-1 system corrected MSS scene 1002-18134 of 25 July 1972 over Monterey Bay, California. When the entire study area data set was submitted to the clustering only two distinct water classes were extracted. However, when the land area data points were removed from the data set and resubmitted to the clustering routine, four distinct groupings of water features were identified. Additionally, unlike the previous separation, the four types could be correlated to features observable in the associated ERTS-1 imagery. This exercise demonstrates that by proper selection of data submitted to the processing routine, based upon the specific application of study, additional information may be extracted from the ERTS-1 MSS data.

Erb, R. B.↗
NASA NTRS1972

3C 323.1 - A QSO in a rich cluster of galaxies.

The redshift and structural data on the compact cluster Zw Cl 1545.1+2104 have been determined from deep plates of the cluster region and from spectral scans of the central galaxy in the cluster. The cluster is of richness 1 on Abell's (1958) scale, and the redshift of its central galaxy agrees well with that of the quasar 3C 323.1 which lies at a projected distance of 6.5 sec from the center of the cluster. The data indicate that the quasar is a member of the cluster as opposed to the observed trend.

Oemler, A., Jr.↗
DOE OSTI2015

Big Data Analytics for Demand Response: Clustering Over Space and Time

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

The extended medium sensitivity survey distant cluster sample - X-ray data and interpretation of the luminosity evolution

The X-ray properties of a cluster of galaxies subsample of the Einstein Extended Medium Sensitivity Survey is described. A summary of this sample and its implication has been presented previously; this paper gives the full details. The cluster subsample is 98.4 percent identified and contains 93 X-ray-selected clusters to a redshift of 0.58. The cluster X-ray luminosity function at three cosmic epochs is derived. While the present luminosity function agrees with previous determinations at the lowest redshifts, it is found that the volume density of high-luminosity clusters is greater now than it was in the past. The normalization, shape, and time dependence of the luminosity function can be described by a simple hierarchical formation model with parameters which also describe the temperature function of an independent sample of low-redshift clusters. In this model the comoving hot gas density remains constant with time at least to redshifts of order 0.35.

Henry, J. P.↗
DOE OSTI2020

Combinatorial Exploration and Mapping of Phase Transformation in a Ni–Ti–Co Thin Film Library

Combinatorial synthesis and high-throughput characterization of a Ni–Ti–Co thin film materials library are reported for exploration of reversible martensitic transformation. The library was prepared by magnetron co-sputtering, annealed in vacuum at 500 °C without atmospheric exposure, and evaluated for shape memory behavior as an indicator of transformation. Composition, structure, and transformation behavior of the 177 pads in the library were characterized using high-throughput wavelength dispersive spectroscopy (WDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and four-point probe temperature-dependent resistance (R(T)) measurements. A new, expanded composition space having phase transformation with low thermal hysteresis and Co > 10 at. % is found. Unsupervised machine learning methods of hierarchical clustering were employed to streamline data processing of the large XRD and XPS data sets. Through cluster analysis of XRD data, we identified and mapped the constituent structural phases. Finally, composition–structure–property maps for the ternary system are made to correlate the functional properties to the local microstructure and composition of the Ni–Ti–Co thin film library.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Geostatistical interpolation of streambed hydrologic attributes with addition of left censored data and anisotropy

Spatial geostatistical interpolation of point measurements of streambed attributes in the hyporheic zone may be constrained by the streambed anisotropy, and data density and spatial distribution may significantly impact the results. Spatial clustering and low spatial data density can be caused by bedrock outcropping at the streambed limiting installation of in-stream piezometers. This study examines parameter error variability of the geostatistical interpolation using anisotropic interpolation methods and increasing the data density by adding left censored values (i.e., data below measurement limit) to locations where measurements were limited by exposed bedrock lining the streambed. The reduction in relative standard error of the interpolation was determined for the spatial distributions of streambed attributes including hydraulic conductivity, seepage flux, and mercury solute flux measured in two different years along a study reach in East Fork Poplar Creek, Tennessee, USA. Here, two methods to impute the left censored values were compared including the conventional half the detection limit substitution method, and the Stochastic Approximation of Expectation-Maximization (SAEM) algorithm, which both had comparable results. Imputing left censored data increased the data density to recommended ranges, reduced data clustering, increased the spatial dependence for some attributes, and reduced the standard error for each of the three attributes. For the reach considered herein, addition of the left censored values resulted in a larger error reduction than the consideration of anisotropy within the interpolation, which confirms the benefit of data addition to increase data density within data-limited river corridors.

58 GEOSCIENCES↗
DOE OSTI2022

Serial crystallography with multi-stage merging of thousands of images

KAMO and BLEND provide particularly effective tools to automatically manage the merging of large numbers of data sets from serial crystallography. The requirement for manual intervention in the process can be reduced by extending BLEND to support additional clustering options such as the use of more accurate cell distance metrics and the use of reflection-intensity correlation coefficients to infer `distances' among sets of reflections. This increases the sensitivity to differences in unit-cell parameters and allows clustering to assemble nearly complete data sets on the basis of intensity or amplitude differences. If the data sets are already sufficiently complete to permit it, one applies KAMO once and clusters the data using intensities only. When starting from incomplete data sets, one applies KAMO twice, first using unit-cell parameters. In this step, either the simple cell vector distance of the original BLEND or the more sensitive NCDist is used. This step tends to find clusters of sufficient size such that, when merged, each cluster is sufficiently complete to allow reflection intensities or amplitudes to be compared. One then uses KAMO again using the correlation between reflections with a common hkl to merge clusters in a way that is sensitive to structural differences that may not have perturbed the unit-cell parameters sufficiently to make meaningful clusters. Many groups have developed effective clustering algorithms that use a measurable physical parameter from each diffraction still or wedge to cluster the data into categories which then can be merged, one hopes, to yield the electron density from a single protein form. Since these physical parameters are often largely independent of one another, it should be possible to greatly improve the efficacy of data-clustering software by using a multi-stage partitioning strategy. Here, one possible approach to multi-stage data clustering is demonstrated. The strategy is to use unit-cell clustering until the merged data are sufficiently complete and then to use intensity-based clustering. Using this strategy, it is demonstrated that it is possible to accurately cluster data sets from crystals that have subtle differences.

36 MATERIALS SCIENCE↗
NASA NTRS1993

The Galactic bulge and halo

The relationship between the Galactic halo and bulge is discussed, with reference to early results from a survey for K giants in a field 2 kpc from the Galactic center and Zinn's (1992) data on globular-cluster kinematics. The data are currently too meager to decide whether the inner halo shades gradually into the bulge, although there are some interesting kinematical similarities between bulge stars and Zinn's Old Halo clusters in the inner Galaxy. Useful observations that would help decide this matter are also discussed.

Morrison, Heather L.↗