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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

X-ray Spectra of Distant Clusters

The masses of galaxy clusters are dominated by dark matter, and a robust determination of their temperatures and 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 ASCA and 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 12 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 measurements are made close to the central core, where optical and Xray 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.

Ellingson, E.↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
DOE OSTI2021

Using action space clustering to constrain the recent accretion history of Milky Way-like galaxies

ABSTRACT In the currently favoured cosmological paradigm galaxies form hierarchically through the accretion of satellites. Since a satellite is less massive than the host, its stars occupy a smaller volume in action space. Actions are conserved when the potential of the host halo changes adiabatically, so stars from an accreted satellite would remain clustered in action space as the host evolves. In this paper, we identify recently disrupted accreted satellites in three Milky Way-like disc galaxies from the cosmological baryonic FIRE-2 simulations by tracking satellites through simulation snapshots. We try to recover these satellites by applying the cluster analysis algorithm Enlink to the orbital actions of accreted star particles in the z = 0 snapshot. Even with completely error-free mock data we find that only 35 per cent (14/39) satellites are well recovered while the rest (25/39) are poorly recovered (i.e. either contaminated or split up). Most (10/14 ∼70 per cent) of the well-recovered satellites have infall times <7.1 Gyr ago and total mass >4 × 108M⊙ (stellar mass more than 1.2 × 106 M⊙, although our upper mass limit is likely to be resolution dependent). Since cosmological simulations predict that stellar haloes include a population of in situ stars, we test our ability to recover satellites when the data include 10–50 per cent in situ contamination. We find that most previously well-recovered satellites stay well recovered even with 50 per cent contamination. With the wealth of 6D phase space data becoming available we expect that cluster analysis in action space will be useful in identifying the majority of recently accreted and moderately massive satellites in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

STAR CLUSTERS IN M31. IV. A COMPARATIVE ANALYSIS OF ABSORPTION LINE INDICES IN OLD M31 AND MILKY WAY CLUSTERS

We present absorption line indices measured in the integrated spectra of globular clusters both from the Galaxy and from M31. Our samples include 41 Galactic globular clusters, and more than 300 clusters in M31. The conversion of instrumental equivalent widths into the Lick system is described, and zero-point uncertainties are provided. Comparison of line indices of old M31 clusters and Galactic globular clusters suggests an absence of important differences in chemical composition between the two cluster systems. In particular, CN indices in the spectra of M31 and Galactic clusters are essentially consistent with each other, in disagreement with several previous works. We reanalyze some of the previous data, and conclude that reported CN differences between M31 and Galactic clusters were mostly due to data calibration uncertainties. Our data support the conclusion that the chemical compositions of Milky Way and M31 globular clusters are not substantially different, and that there is no need to resort to enhanced nitrogen abundances to account for the optical spectra of M31 globular clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Beyond – ΛCDM constraints from the full shape clustering measurements from BOSS and eBOSS

We analyse the full shape of anisotropic clustering measurements from the extended Baryon Oscillation Spectroscopic Survey quasar sample together with the combined galaxy sample from the Baryon Oscillation Spectroscopic Survey. We obtain constraints on the cosmological parameters independent of the Hubble parameter h for the extensions of the Lambda cold dark matter (ΛCDM) models, focusing on cosmologies with free dark energy equation of state parameter w. We combine the clustering constraints with those from the latest cosmic microwave background data from Planck to obtain joint constraints for these cosmologies for w and the additional extension parameters – its time evolution w a , the physical curvature density ω K and the neutrino mass sum Σm ν . Our joint constraints are consistent with a flat ΛCDM cosmological model within 68 per cent confidence limits. We demonstrate that the Planck data are able to place tight constraints on the clustering amplitude today, σ 12 , in cosmologies with varying w and present the first constraints for the clustering amplitude for such cosmologies, which is found to be slightly higher than the ΛCDM value. Additionally, we show that when we vary w and allow for non-flat cosmologies and the physical curvature density is used, Planck prefers a curved universe at 4σ significance, which is ~2σ higher than when using the relative curvature density Ω K . Finally, when w is varied freely, clustering provides only a modest improvement (of 0.021 eV) on the upper limit of Σm ν .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Dynamics of the Wide-angle Tailed (WAT) Galaxy Cluster A562

We present the first in-depth dynamical analysis of the archetypal wide-angle tailed (WAT) cluster A562. We have combined Gemini observations with archival data from the literature to form a sample of 76 cluster members and derived a mean redshift of 0.1088 ± 0.0004 and a velocity dispersion of 919 ± 116 km s{sup −1}. This relatively large velocity dispersion suggests either a very massive cluster (M {sub dyn} > 6.9 × 10{sup 14} M {sub ☉}) and/or a merger system. The merger model is supported by a non-Gaussian galaxy velocity distribution, an elongated spatial distribution of likely cluster members, and an elongated X-ray emitting gas. This scenario would generate the bulk flow motion of the intracluster medium that can exert enough ram pressure to bend the radio jets. Thus, our observations support the model in which a recent off-axis merger event produced the cluster wide conditions needed to shape the WAT in A562.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

IPC two-color analysis of x ray galaxy clusters

The mass distributions were determined of several clusters of galaxies by using X ray surface brightness data from the Einstein Observatory Imaging Proportional Counter (IPC). Determining cluster mass distributions is important for constraining the nature of the dark matter which dominates the mass of galaxies, galaxy clusters, and the Universe. Galaxy clusters are permeated with hot gas in hydrostatic equilibrium with the gravitational potentials of the clusters. Cluster mass distributions can be determined from x ray observations of cluster gas by using the equation of hydrostatic equilibrium and knowledge of the density and temperature structure of the gas. The x ray surface brightness at some distance from the cluster is the result of the volume x ray emissivity being integrated along the line of sight in the cluster.

White, Raymond E., III↗
NASA NTRS2004

Visual data mining for quantized spatial data

In previous papers we've shown how a well known data compression algorithm called Entropy-constrained Vector Quantization ( can be modified to reduce the size and complexity of very large, satellite data sets. In this paper, we descuss how to visualize and understand the content of such reduced data sets.

cluster analysis↗
DOE OSTI2015

MEASUREMENT OF GALAXY CLUSTER INTEGRATED COMPTONIZATION AND MASS SCALING RELATIONS WITH THE SOUTH POLE TELESCOPE

We describe a method for measuring the integrated Comptonization (Y {sub SZ}) of clusters of galaxies from measurements of the Sunyaev-Zel'dovich (SZ) effect in multiple frequency bands and use this method to characterize a sample of galaxy clusters detected in the South Pole Telescope (SPT) data. We use a Markov Chain Monte Carlo method to fit a β-model source profile and integrate Y {sub SZ} within an angular aperture on the sky. In simulated observations of an SPT-like survey that include cosmic microwave background anisotropy, point sources, and atmospheric and instrumental noise at typical SPT-SZ survey levels, we show that we can accurately recover β-model parameters for inputted clusters. We measure Y {sub SZ} for simulated semi-analytic clusters and find that Y {sub SZ} is most accurately determined in an angular aperture comparable to the SPT beam size. We demonstrate the utility of this method to measure Y {sub SZ} and to constrain mass scaling relations using X-ray mass estimates for a sample of 18 galaxy clusters from the SPT-SZ survey. Measuring Y {sub SZ} within a 0.'75 radius aperture, we find an intrinsic log-normal scatter of 21% ± 11% in Y {sub SZ} at a fixed mass. Measuring Y {sub SZ} within a 0.3 Mpc projected radius (equivalent to 0.'75 at the survey median redshift z = 0.6), we find a scatter of 26% ± 9%. Prior to this study, the SPT observable found to have the lowest scatter with mass was cluster detection significance. We demonstrate, from both simulations and SPT observed clusters that Y {sub SZ} measured within an aperture comparable to the SPT beam size is equivalent, in terms of scatter with cluster mass, to SPT cluster detection significance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Analysis of elastic scattering and breakup of {sup 11}li in collisions with protons using a dynamical two-cluster model

The {sup 11}Li scattering and breakup on protons is considered under the assumption that the {sup 11}Li nucleus consists of two interacting clusters, which are a c = {sup 9}Li core and a h = 2n dineutron halo. The single-particle density of the {sup 11}Li nucleus, amicroscopic optical potential, and the cross section for {sup 11}Li+p scattering for various choices of cluster shape are obtained and analyzed by folding the density distribution for either cluster with the probability density for the relative motion of two clusters. A comparison with experimental data of the scattering cross section at low, 60–75 MeV, and intermediate, 700 MeV, energies is performed. The momentum distribution of c fragments upon {sup 11}Li breakup is calculated and studied with a help of the obtained p + c and p + h microscopic optical potentials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Dose, LET, time and strain dependence of radiation-induced 53BP1 foci in 15 mouse strains ex vivo and associations to in vivo radiation susceptibility

We present a comparative analysis on the repair of radiation-induced DNA damage ex vivo in 15 strains of mice, including 5 inbred reference strains and 10 collaborative-cross strains, of both sexes. Non-immortalized primary skin fibroblasts derived from 76 mice were subjected to both low- and high-LET radiation (0.1, 1 and 4 Gy of X rays; 1.1 and 3 particles/100μm2 of 350 MeV/n 40Ar and 600 MeV/n 56Fe). Automated image quantification of 53BP1 radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET. Similarly to what we had previously reported for immortalized human cell lines [1], we observed a saturation of RIF number with dose at 4h post-irradiation, with more RIF/Gy for lower LET (X rays and 40Ar) compared to 56Fe. However at later time points (24h and above), the trend was inverted with more RIF/Gy for higher LET. Our data suggest that multiple DSBs cluster into RIF: as the linear density of DSBs increases with LET, so does the probability of having more DSBs per RIF, which makes it more difficult for cells to fully resolve high-LET-induced RIF, explaining the hypersensitivity to high-LET radiation despite a low number of RIF. Taking into account the amount of clustering at a given dose and LET, but also the kinetics of DNA damage repair, we introduced a novel mathematical formalism to evaluate the number of remaining RIF over time. We showed that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the repairable fraction of RIF measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk. In addition to the efficacy of repair and persistent RIF levels, even the amount of spontaneous foci without irradiation was shown to be strain dependent, indicating that these phenotypes are at least partially driven by genetics, and supporting their potential as indicators of individual radiation sensitivity. [1] Neumaier, T., et al., PNAS, 2012 (8) 109:443

Radiation, DNA damage, repair kinetics↗
DOE OSTI2021

ORCA: Outlier detection and Robust Clustering for Attributed graphs

Here, a framework is proposed to simultaneously cluster objects and detect anomalies in attributed graph data. Our objective function along with the carefully constructed constraints promotes interpretability of both the clustering and anomaly detection components, as well as scalability of our method. In addition, we developed an algorithm called Outlier detection and Robust Clustering for Attributed graphs (ORCA) within this framework. ORCA is fast and convergent under mild conditions, produces high quality clustering results, and discovers anomalies that can be mapped back naturally to the features of the input data. The efficacy and efficiency of ORCA is demonstrated on real world datasets against multiple state-of-the-art techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Development of Vocational Vehicle Drive Cycles and Segmentation

Under a collaborative interagency agreement between the U.S. Environmental Protection Agency and the U.S Department of Energy (DOE), the National Renewable Energy Laboratory (NREL) performed a series of in-depth analyses to characterize the on-road driving behavior including distributions of vehicle speed, idle time, accelerations and decelerations, and other driving metrics of medium- and heavy-duty vocational vehicles operating within the United States. As part of this effort, NREL researchers segmented U.S. medium- and heavy-duty vocational vehicle driving characteristics into three distinct operating groups or clusters using real world drive cycle data collected at 1 Hz and stored in NREL's Fleet DNA database. The Fleet DNA database contains millions of miles of historical real-world drive cycle data captured from medium- and heavy vehicles operating across the United States. The data encompass data from existing DOE activities as well as contributions from valued industry stakeholder participants. For this project, data captured from 913 unique vehicles comprising 16,250 days of operation were drawn from the Fleet DNA database and examined. The Fleet DNA data used as a source for this analysis has been collected from a total of 30 unique fleets/data providers operating across 22 unique geographic locations spread across the United States. This includes locations with topology ranging from the foothills of Denver, Colorado, to the flats of Miami, Florida. The range of fleets, geographic locations, and total number of vehicles analyzed ensures results that include the influence of these factors. While no analysis will be perfect without unlimited resources and data, it is the researchers understanding that the Fleet DNA database is the largest and most thorough publicly accessible vocational vehicle usage database currently in operation. This report includes an introduction to the Fleet DNA database and the data contained within, a presentation of the results of the statistical analysis performed by NREL, review of the logistic model developed to predict cluster membership, and a discussion and detailed summary of the development of the vocational drive cycle weights and representative transient drive cycles for testing and simulation. Additional discussion of known limitations and potential future work are also included in the report content.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

The Problem of Hipparcos Distances to Open Clusters: Constraints from Multicolor a Main-Sequence Fitting - Report 1

Parallax data from the Hipparcos mission allow the direct distance to open clusters to be compared with the distance inferred from main-sequence (MS) fitting. There are surprising differences between the two distance measurements. indicating either the need for changes in the cluster compositions or reddening, underlying problems with the technique of MS fitting, or systematic errors in the Hipparcos parallaxes at the 1 mas level. We examine the different possibilities, focusing on MS fitting in both metallicity-sensitive B-V and metallicity-insensitive V-I for five well-studied systems (the Hyades, Pleiades, alpha Per, Praesepe, and Coma Ber). The Hipparcos distances to the Hyades and alpha Per are within 1 sigma of the MS-fitting distance in B-V and V-I, while the Hipparcos distances to Coma Ber and the Pleiades are in disagreement with the MS-fitting distance at more than the 3 sigma level. There are two Hipparcos measurements of the distance to Praesepe; one is in good agreement with the MS-fitting distance and the other disagrees at the 2 sigma level. The distance estimates from the different colors are in conflict with one another for Coma but in agreement for the Pleiades. Changes in the relative cluster metal abundances, age related effects, helium, and reddening are shown to be unlikely to explain the puzzling behavior of the Pleiades. We present evidence for spatially dependent systematic errors at the 1 mas level in the parallaxes of Pleiades stars. The implications of this result are discussed.

Pinsonneault, Marc H.↗
DOE OSTI2015

Aberration‐Corrected Transmission Electron Microscopy and In Situ XAFS Structural Characterization of Pt/γ‐Al 2 O 3 Nanoparticles

Abstract Aberration‐corrected (AC) STEM, AC TEM and in situ X‐ray absorption fine structure spectroscopy (XAFS) were used to characterize the Pt clusters present on a 0.35 wt % Pt on γ‐alumina support after reduction in hydrogen at 700 °C. STEM high‐angle annular dark field imaging shows that cluster formation takes place at temperatures up to approximately 350 °C, and this is followed by gradual growth in cluster size for heat treatments in hydrogen up to 700 °C. The STEM data show that after 700 °C reduction the Pt clusters are present in a narrow size distribution centered at 0.88 nm, and using a method involving a redistribution of the Pt atoms using a high electron dosage in the STEM, it is shown that the clusters are present in two‐dimensional morphology. This conclusion is verified using intensity line scans. The in situ extended X‐ray absorption fine structure data are in good agreement with these observations. High‐resolution AC–TEM, which uses a broad coherent electron beam, and can thus offer advantages relative to STEM for structure determination of fine clusters, supported by image simulations of through‐focus series, were used to analyze the structures of Pt particles. The structures determined by using AC–TEM are consistent with STEM and EXAFS data in having a flat two‐dimensional morphology. Comparison of AC–STEM and AC TEM data for the same 700 °C reduced sample suggests that parallel‐beam TEM mode of imaging may be advantageous because of the less pronounced beam‐induced structural rearrangements that occur when imaging with a fine STEM probe.

Sinkler, Wharton↗
DOE OSTI2019

Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps

We present a novel visual representation and interface named the matrix of isosurface similarity maps (MISM) for effective exploration of large time-varying multivariate volumetric data sets. MISM synthesizes three types of similarity maps (i.e., self, temporal, and variable similarity maps) to capture the essential relationships among isosurfaces of different variables and time steps. Additionally, it serves as the main visual mapping and navigation tool for examining the vast number of isosurfaces and exploring the underlying time-varying multivariate data set. We present temporal clustering, variable grouping, and interactive filtering to reduce the huge exploration space of MISM. In conjunction with the isovalue and isosurface views, MISM allows users to identify important isosurfaces or isosurface pairs and compare them over space, time, and value range. More importantly, we introduce path recommendation that suggests, animates, and compares traversal paths for effectively exploring MISM under varied criteria and at different levels-of-detail. A silhouette-based method is applied to render multiple surfaces of interest in a visually succinct manner. We demonstrate the effectiveness of our approach with case studies of several time-varying multivariate data sets and an ensemble data set, and evaluate our work with two domain experts.

97 MATHEMATICS AND COMPUTING↗