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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
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 NTRS2015

Feasibility of Rayleigh Scattering Flow Diagnostics in the National Transonic Facility

Laser-based Rayleigh light scattering (RLS) was performed in the National Transonic Facility (NTF) at NASA Langley Research Center. The goal was to determine if the free-stream flow undergoes clustering (early stage of condensation from gas to liquid) or remains in a pure diatomic molecular phase. Data indicate that clusters are not observable down to levels of 10% of the total light scatter for a variety of total pressures at one N2 cryogenic-mode total temperature (Tt = -50 F = 227 K) and one air-mode temperature (Tt = +130 F = 327 K). Thus RLS appears viable as a qualitative or quantitative diagnostic for flow density in NTF in the future. Particles are distinguished from optically unresolvable clusters because they are much larger and individually resolvable in the laser beam image with Mie scattering. The same RLS apparatus was also used, without modification, to visualize naturally occurring particles entrained in the flow for both cryogenic and air-modes. Estimates of the free-stream particle flux are presented, which may be important for interpretation of laminar-to-turbulent boundary-layer transition studies. 1

Herring, Gregory C.↗
DOE OSTI2021

A Taxonomic Classification Approach for Global Spatio-temporal Data

The World Bank, World Health Organization, and other major vendors collectively provide thousands of global time series datasets that focus on issues of the environment, public health, economics, violence, education, and national security. Sorting these data into meaningful information requires the use of data mining techniques to cluster trends into an orderly and manageable number of cases. The World SpatioTemporal Analytics and Mapping (WSTAMP) project database (wstamp.ornl.gov) was developed to spatiotemporally harmonize global vendor data (23,300+ attributes, 200+ locations, 50+ years). Within the WSTAMP analytical environment, Dynamic Time Warping (DTW) has been a highly effective data-driven approach for clustering and mapping these time series into national spatiotemporal behavior maps. Two significant properties have surfaced from this work. First, several recognizable cluster patterns have emerged and persist across a range of locations, attributes, and time frames (e.g., increasing, decreasing, rebounding, peak, oscillating). Secondly, practitioners engaging WSTAMP have noted the explanatory and anticipatory value of these patterns and articulated particular interest in detecting them within the spatiotemporal cube. This need was addressed by shifting DTW-based clustering from an open ended, data-driven implementation to a taxonomic pattern matching approach. This paper presents the method including implementation strategies for visualization and human computer interaction and applies the approach to a sample data set and concludes with next steps.

Stewart, Robert↗
DOE OSTI2022

Data used in Wainwright, H.M. et al. 2021, “Watershed zonation through hillslope clustering for tractably quantifying above- and belowground watershed heterogeneity and functions”

This data package contains spatial data layers and processing scripts used in Wainwright, H.M. et al. 2021, “Watershed zonation approach for tractably quantifying above-and- belowground watershed heterogeneity and functions”. The purpose of the data and paper is to develop a watershed zonation approach for characterizing watershed organization and function in a tractable manner by applying clustering methods to multiple spatial data layers. The data package contains the geotiff files of spatial data layers, and the processed data values corresponding to the figures in the paper. The Data_description file describe each file in details. The spatial data sets (geotiff) are included in the zip files.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Recurrent brief X-ray bursts from the globular cluster NGC 6624

Observational data are presented on ten brief X-ray bursts, recurrent at nearly equal time intervals, recorded during a two-day observation of 3U 1820-30 in the globular cluster NGC 6624 with the wide-field modulation collimator detectors on the SAS-3 X-ray observatory. The occurrence times were fitted by least squares to a linear sequence with an rms deviation of 621 sec, corresponding to a phase jitter of 3.9%. The bursts were observed in two energy channels. For a sequence of five of the most clearly observed bursts, the 2-6 keV rate rose to its peak value in about 1 sec and then decayed to preburst level in about 10 sec. The 6-11 keV rate rose more slowly and decayed similarly. The smooth decay of their averaged light curve suggests the temporal evolution may have a geometrical origin, where Compton scattering in a surrounding cloud of hot plasma stretches the pulse out and causes a progressive hardening of the spectrum.

Clark, G. W.↗
DOE OSTI2017

Light and Heavy Element Abundance Variations in the Outer Halo Globular Cluster NGC 6229

NGC 6229 is a relatively massive outer halo globular cluster that is primarily known for exhibiting a peculiar bimodal horizontal branch morphology. Given the paucity of spectroscopic data on this cluster, we present a detailed chemical composition analysis of 11 red giant branch members based on high resolution (R ≈ 38,000), high S/N (>100) spectra obtained with the MMT-Hectochelle instrument. We find the cluster to have a mean heliocentric radial velocity of −138.1{sub −1.0}{sup +1.0} km s{sup −1}, a small dispersion of 3.8{sub −0.7}{sup +1.0} km s{sup −1}, and a relatively low (M/L{sub V}){sub ⊙}=0.82{sub −0.28}{sup +0.49}. The cluster is moderately metal-poor with 〈[Fe/H]〉=−1.13 dex and a modest dispersion of 0.06 dex. However, 18% (2/11) of the stars in our sample have strongly enhanced [La, Nd/Fe] ratios that are correlated with a small (∼0.05 dex) increase in [Fe/H]. NGC 6229 shares several chemical signatures with M75, NGC 1851, and the intermediate metallicity populations of ω Cen, which lead us to conclude that NGC 6229 is a lower mass iron-complex cluster. The light elements exhibit the classical (anti-)correlations that extend up to Si, but the cluster possesses a large gap in the O–Na plane that separates first and second generation stars. NGC 6229 also has unusually low [Na, Al/Fe] abundances that are consistent with an accretion origin. A comparison with M54 and other Sagittarius clusters suggests that NGC 6229 could also be the remnant core of a former dwarf spheroidal galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗
NASA NTRS2005

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Sullivan, Dana↗
DOE OSTI2016

CLASH-VLT: testing the nature of gravity with galaxy cluster mass profiles

We use high-precision kinematic and lensing measurements of the total mass profile of the dynamically relaxed galaxy cluster MACS J1206.2-0847 at z=0.44 to estimate the value of the ratio η=Ψ/Φ between the two scalar potentials in the linear perturbed Friedmann-Lemaitre-Robertson-Walker metric. An accurate measurement of this ratio, called anisotropic stress, could show possible, interesting deviations from the predictions of the theory of General Relativity, according to which Ψ should be equal to Φ. Complementary kinematic and lensing mass profiles were derived from exhaustive analyses using the data from the Cluster Lensing And Supernova survey with Hubble (CLASH) and the spectroscopic follow-up with the Very Large Telescope (CLASH-VLT). Whereas the kinematic mass profile tracks only the time-time part of the perturbed metric (i.e. only Φ), the lensing mass profile reflects the contribution of both time-time and space-space components (i.e. the sum Φ+Ψ). We thus express η as a function of the mass profiles and perform our analysis over the radial range 0.5 Mpc≤ r≤ r{sub 200}=1.96 Mpc. Using a spherical Navarro-Frenk-White mass profile, which well fits the data, we obtain η(r{sub 200})=1.01 {sub −0.28}{sup +0.31} at the 68% C.L. We discuss the effect of assuming different functional forms for mass profiles and of the orbit anisotropy in the kinematic reconstruction. Interpreting this result within the well-studied f(R) modified gravity model, the constraint on η translates into an upper bound to the interaction length (inverse of the scalaron mass) smaller than 2 Mpc. This tight constraint on the f(R) interaction range is however substantially relaxed when systematic uncertainties in the analysis are considered. Our analysis highlights the potential of this method to detect deviations from general relativity, while calling for the need of further high-quality data on the total mass distribution of clusters and improved control on systematic effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

clustering, k-means, power grid, graphs↗
DOE OSTI2015

A NEW REDUCTION OF THE BLANCO COSMOLOGY SURVEY: AN OPTICALLY SELECTED GALAXY CLUSTER CATALOG AND A PUBLIC RELEASE OF OPTICAL DATA PRODUCTS

The Blanco Cosmology Survey is a four-band (griz) optical-imaging survey of ∼80 deg{sup 2} of the southern sky. The survey consists of two fields centered approximately at (R.A., decl.) = (23{sup h}, –55°) and (5{sup h}30{sup m}, –53°) with imaging sufficient for the detection of L {sub *} galaxies at redshift z ≤ 1. In this paper, we present our reduction of the survey data and describe a new technique for the separation of stars and galaxies. We search the calibrated source catalogs for galaxy clusters at z ≤ 0.75 by identifying spatial over-densities of red-sequence galaxies and report the coordinates, redshifts, and optical richnesses, λ, for 764 galaxy clusters at z ≤ 0.75. This sample, >85% of which are new discoveries, has a median redshift of z = 0.52 and median richness λ(0.4 L {sub *}) = 16.4. Accompanying this paper we also release full survey data products including reduced images and calibrated source catalogs. These products are available at http://data.rcc.uchicago.edu/dataset/blanco-cosmology-survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric Redshifts and Galaxy Clusters for DES DR2, DESI DR9, and HSC-SSP PDR3 Data

Photometric redshift (photoz) is a fundamental parameter for multi-wavelength photometric surveys, while galaxy clusters are important cosmological probes and ideal objects for exploring the dense environmental impact on galaxy evolution. We extend our previous work on estimating photoz and detecting galaxy clusters to the latest data releases of the Dark Energy Spectroscopic Instrument (DESI) imaging surveys, Dark Energy Survey (DES) and Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) imaging surveys and make corresponding catalogs publicly available for more extensive scientific applications. The photoz catalogs include accurate measurements of photoz and stellar mass for about 320, 293 and 134 million galaxies with r < 23, i < 24 and i < 25 in DESI DR9, DES DR2 and HSC-SSP PDR3 data, respectively. The photoz accuracy is about 0.017, 0.024 and 0.029 and the general redshift coverage is z < 1, z < 1.2 and z < 1.6, respectively for those three surveys. Furthermore, the uncertainty of the logarithmic stellar mass that is inferred from stellar population synthesis fitting is about 0.2 dex. With the above photoz catalogs, galaxy clusters are detected using a fast cluster-finding algorithm. A total of 532,810, 86,963 and 36,566 galaxy clusters with the number of members larger than 10 is discovered for DESI, DES and HSC-SSP, respectively. Their photoz accuracy is at the level of 0.01. The total mass of our clusters is also estimated by using the calibration relations between the optical richness and the mass measurement from X-ray and radio observations. The photoz and cluster catalogs are available at ScienceDB (https://www.doi.org/10.11922/sciencedb.o00069.00003) and PaperData Repository (https://doi.org/10.12149/101089).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Crustal influence in the generation of continental flood basalts

The suggestion that primordial undifferentiated material may exist in the earth's mantle has recently been revived on the strength of Nd isotope data for two types of young continental rocks - flood basalts and kimberlites. The limited published data show a clustering of Nd isotopic compositions close to those for meteorites with chondritic relative rare-earth (REE) abundance. In contrast, data are presented for samples from the Columbia flood basalt province of the northwestern United States which show large isotopic variability suggestive of mixing processes acting after the separation of the primary magmas from their mantle source.

Carlson, R. W.↗
DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

The thermodynamics of proton hydration and the electrochemical surface potential of water

The free energy change for transferring a single ion across the water liquid/vapor interface includes an electrochemical surface potential contribution. Since this potential is not directly accessible to thermodynamic measurement, several extra-thermodynamic approaches have been employed to infer its sign and magnitude, with a resulting wide spread of values. Here, we examine further the thermodynamics of proton hydration and the electrochemical surface potential of water along three directions: (1) a basic relation of interfacial electrostatics and experimental results on ion distributions near a water/organic interface are employed to infer a solvent contribution to the electrochemical surface potential, (2) a re-analysis is performed of the existing bulk and cluster ion hydration data, and (3) extensive computational modeling is conducted to examine the size dependence of hydration enthalpy differences for the NaF ion pair between the small cluster and the converged bulk limits. The computational studies include classical polarizable models and high-level quantum chemical methods. The new theoretical analysis of existing experimental data and the combined classical/quantum modeling lead to results consistent with our previously derived proton hydration quantities.

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

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: anisotropic galaxy clustering in Fourier space

We investigate the anisotropic clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 sample, which consists of 1198 006 galaxies in the redshift range 0.2 < z < 0.75 and a sky coverage of 10 252 deg 2 . We analyse this data set in Fourier space, using the power-spectrum multipoles to measure redshift-space distortions simultaneously with the Alcock–Paczynski effect and the baryon acoustic oscillation scale. We include the power-spectrum monopole, quadrupole and hexadecapole in our analysis and compare our measurements with a perturbation-theory-based model, while properly accounting for the survey window function. To evaluate the reliability of our analysis pipeline, we participate in a mock challenge, which results in systematic uncertainties significantly smaller than the statistical uncertainties. While the high-redshift constraint on fσ8 at z eff = 0.61 indicates a small (~1.4σ) deviation from the prediction of the Planck ΛCDM (Λ cold dark matter) model, the low-redshift constraint is in good agreement with Planck ΛCDM. This paper is part of a set that analyses the final galaxy clustering data set from BOSS. Lastly, the measurements and likelihoods presented here are combined with others in Alam et al. to produce the final cosmological constraints from BOSS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Investigation of Poorly Studied Open Cluster NGC 4337 Using Multicolor Photometric and Gaia DR2 Astrometric Data

We present a comprehensive analysis (photometric and kinematical) of the poorly studied open cluster NGC 4337 using 2MASS, WISE, APASS, and Gaia DR2 databases. By determining the membership probabilities of stars, we identified the 624 most probable members with membership probability higher than 50% by using proper motion and parallax data taken from Gaia DR2. The mean proper motion of the cluster is obtained as μ{sub x}=−8.83±0.01 and μ {sub y} = 1.49 ± 0.006 mas yr{sup −1}. We find the normal interstellar extinction toward the cluster region. The radial distribution of members provides a cluster radius of 7.′75 (5.63 pc). The estimated age of 1600 ± 180 Myr indicates that NGC 4337 is an old open cluster with a bunch of red giant stars. The overall mass function slope for main-sequence stars is found as 1.46±0.18 within the mass range 0.75−2.0 M{sub ⊙}, which is in fair agreement with Salpeter’s value (x = 1.35) within uncertainty. The present study demonstrates that NGC 4337 is a dynamically relaxed open cluster. Using the Galactic potential model, Galactic orbits are obtained for NGC 4337. We found that this object follows a circular path around the Galactic center. Under the kinematical analysis, we compute the apex coordinates (A, D) by using two methods: (i) the classical convergent point method and (ii) the AD-diagram method. The obtained coordinates are (A {sub conv}, D {sub conv}) = (96.°27 ± 0.°10, 13.°14 ± 0.°27) and (A {sub ◦}, D {sub ◦}) = (100.°282 ± 0.°10, 9.°577 ± 0.°323) respectively. We also computed the Velocity Ellipsoid Parameters, matrix elements (μ {sub ij}), direction cosines (l {sub j}, m {sub j}, n {sub j}), and the Galactic longitude of the vertex (l {sub 2}).

79 ASTRONOMY AND ASTROPHYSICS↗