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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Chandra Observations of Point Sources in Abell 2255

In our search for "hidden" AGN we present results from a Chandra observation of the nearby cluster Abell 2255. Eight cluster galaxies are associated with point-like X-ray emission, and we classify these galaxies based on their X-ray, radio, and optical properties. At least three are associated with active galactic nuclei (AGN) with no optical signatures of nuclear activity, with a further two being potential AGN. Of the potential AGN, one corresponds to a galaxy with a post-starburst optical spectrum. The remaining three X-ray detected cluster galaxies consist of two starbursts and an elliptical with luminous hot gas. Of the eight cluster galaxies five are associated with luminous (massive) galaxies and the remaining three lie in much lower luminosity systems. We note that the use of X-ray to optical flux ratios for classification of X-ray sources is often misleading, and strengthen the claim that the fraction of cluster galaxies hosting an AGN based on optical data is significantly lower than the fraction based on X-ray and radio data.

Davis, David S.↗
DOE OSTI2021

The large-scale environment of thermonuclear and core-collapse supernovae

ABSTRACT The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution of ∼3.8 Mpc, constrained by the 2M+ + galaxy survey. We limit our analysis to redshift z < 0.036, using samples of 498 thermonuclear and 782 core-collapse SNe from the Zwicky Transient Facility’s Bright Transient Survey and Census of the Local Universe catalogues. We detect clustering of SNe with high significance; the observed clustering of the two SNe populations is consistent with each other. Further, the clustering of SN hosts is consistent with that of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey DR12 spectroscopic galaxy sample in the same redshift range. Using a tidal shear classifier, we classify the LSS into voids, sheets, filaments, and knots. We find that both SNe and SDSS galaxies are predominantly found in sheets and filaments. SNe are significantly under-represented in voids and over-represented in knots compared to the volume fraction in these structures. This work opens the potential for using forthcoming wide-field deep SN surveys as a complementary LSS probe.

Astronomy & Astrophysics↗
DOE OSTI2024

Underwater unexploded ordnance discrimination based on intrinsic target polarizabilities – A case study

Seabed unexploded ordnance that resulted partly from the high failure rate among munitions from more than 80 years ago and from decades of military training and testing of weapons systems poses an increasing concern all around the world. Although existing magnetic systems can detect clusters of debris, they are not able to tell whether a munition is still intact requiring special removal (e.g. in situ detonation) or is harmless scrap metal. The marine environment poses unique challenges, and transferring knowledge and approaches from land to a marine environment has not been easy and straightforward. On land, the background soil conductivity is much lower than the conductivity of the unexploded ordnance and the electromagnetic response of a target is essentially the same as that in free space. For those frequencies required for target characterization in the marine environment, the seawater response must be accounted for and removed from the measurements. The system developed for this study uses fields from three orthogonal transmitters to illuminate the target and four three-component receivers to measure the signal arranged in a configuration that inherently cancels the system's response due to the enclosing seawater, the sea–bottom interface and the air–sea interface for shallow deployments. The system was tested as a cued system on land and underwater in San Francisco Bay – it was mounted on a simple platform on top of a support structure that extended 1 m below and allowed the diver to place metal objects to a specific location even in low-visibility conditions. The measurements were stable and repeatable. Furthermore, target responses estimated from marine measurements matched those from land acquisition, confirming that the seawater and air–sea interface responses were removed successfully. Thirty-six channels of normalized induction responses were used for the classification, which was done by estimating the target principal dipole polarizabilities. Our results demonstrated that the system can resolve the intrinsic polarizabilities of the target, with clear distinctions between those of symmetric intact unexploded ordnance and irregular scrap metal. The prototype system was able to classify an object based on its size, shape and metal content and correctly estimate its location and orientation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1981

IUE-Ultraviolet and optical chromospheric studies of late-type giants in the Hyades Cluster

Ultraviolet and optical observations of four bright, late-type giants in the Hyades cluster detected with IUE are presented in order to study chromospheric and coronal activity in stars of the same age. Two of the giants, 77 Tau and gamma Tau, clearly exhibit emission in the high temperature ions such as N V, C IV, and Si IV at levels several times larger than the upper limits for the other two giants, delta Tau and epsilon Tau. Comparison of the Mg II h and k fluxes and the Ca II K emission strengths shows that 77 Tau and gamma Tau have larger chromospheric radiative losses than delta Tau, epsilon Tau, and beta Gem, a field giant which also displays low upper limits to emission from high temperature ions. Coronal X-ray emission indicates that the surface flux in X-rays is an order of magnitude brighter in 77 Tau than in delta Tau. The results indicate that a parameter other than age, temperature, gravity or metallicity determines the amount of chromospheric and coronal emission in late-type giants.

Baliunas, S. L.↗
NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗
NASA NTRS1993

Automated System for Early Breast Cancer Detection in Mammograms

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

Bankman, Isaac N.↗
NASA NTRS2002

Determining the Cosmic Distance Scale from Interferometric Measurements of the Sunyaev-Zel'Dovich Effect

The distances to eighteen galaxy clusters are determined, with redshifts ranging from z approx. 0.14 to z approx. 0.78 from a maximum likelihood joint analysis of 30 GHz interferometric Sunyaev-Zel'dovich effect (SZE) and X-ray observations. We model the intracluster medium (ICM) using a spherical isothermal beta model. We quantify the statistical and systematic uncertainties inherent to these direct distance measurements, and we determine constraints on the Hubble parameter for three different cosmologies. These distances imply a Hubble constant of 60((sup +4+13)(sub -4-18)) km s(exp -1) megaparsec(exp -1) for an Omega(sub M) = 0.3, Omega(sub Lambda) = 0.7 cosmology, where the uncertainties correspond to statistical followed by systematic at 68% confidence. With a sample of eighteen clusters, systematic uncertainties clearly dominate. The systematics are observationally approachable and will be addressed in the coming years through the current generation of X-ray satellites (Chandra & XMIM-Newton) and radio observatories (OVRO (Owens Valley Radio Observatory), BIMA (Berkeley Illinois Maryland Association), & VLA (Very Large Array)). Analysis of high redshift clusters detected in future SZE and X-ray surveys will allow a determination of the geometry of the universe from SZE determined distances.

Reese, Erik D.↗
NASA NTRS2002

Determining the Cosmic Distance Scale from Interferometric Measurements of the Sunyaev-Zeldovich Effect

We determine the distances to 18 galaxy clusters with redshifts ranging from z approximately 0.14 to 0.78 from a maximum likelihood joint analysis of 30 GHz interferometric Sunyaev-Zeldovich effect (SZE) and X-ray observations. We model the intracluster medium (ICM) using a spherical isothermal Beta model. We quantify the statistical and systematic uncertainties inherent to these direct distance measurements, and we determine constraints on the Hubble parameter for three different cosmologies. These distances imply a Hubble constant of 60(sup+4+13)(sub-4-18)km s(exp -1)Mpc(exp -1) for an omega(sub Mu)= 0.3,omega(sub Lambda)=0.7 cosmology, where the uncertainties correspond to statistical followed by systematic at 68% confidence. With a sample of 18 clusters, systematic uncertainties clearly dominate. The systematics are observationally approachable and will be addressed in the coming years through the current generation of X-ray satellites (Chandra and XMM-Newton) and radio observatories (Owens Valley Radio Observatory, Berkeley-Illinois-Maryland Association, and Very Large Array). Analysis of high-redshift clusters detected in future SZE and X-ray surveys will allow a determination of the geometry of the universe from SZE-determined distances.

Reese, Erik D.↗
NASA NTRS2004

An Algorithm for Converting Static Earth Sensor Measurements into Earth Observation Vectors

An algorithm has been developed that converts penetration angles reported by Static Earth Sensors (SESs) into Earth observation vectors. This algorithm allows compensation for variation in the horizon height including that caused by Earth oblateness. It also allows pitch and roll to be computed using any number (greater than 1) of simultaneous sensor penetration angles simplifying processing during periods of Sun and Moon interference. The algorithm computes body frame unit vectors through each SES cluster. It also computes GCI vectors from the spacecraft to the position on the Earth's limb where each cluster detects the Earth's limb. These body frame vectors are used as sensor observation vectors and the GCI vectors are used as reference vectors in an attitude solution. The attitude, with the unobservable yaw discarded, is iteratively refined to provide the Earth observation vector solution.

Harman, R.↗
DOE OSTI2021

One of These Things IS Like the Other: Pursuing a New Taxonomy of Industry for Improved Energy System Modeling

Industrial processes drive the exchange of materials, energy, and currency throughout the economy. These processes are powered by electricity and direct combustion, with variation in their operation even within the same industry. This heterogeneity makes it difficult for large models, including the National Energy Modeling System (US), to project their energy use while remaining tractable. Decarbonization and ensuing changes to the energy system require changes to industrial processes while offering opportunities for process innovation, but the extent and nature of changes are difficult to model with current classification schemes and corresponding data. The North American Industrial Classification (NAICS) is an economic taxonomy of industries, but its categories are less meaningful from an energy and material flow perspective. For example, a facility that makes steel from iron ore in a blast furnace/basic oxygen furnace is categorized under the same NAICS code as a facility that makes steel from scrap in an electric arc furnace despite the scale, use of recycled scrap versus iron ore, and energy use differences in the two facility types. Exploratory analysis is performed on a large dataset used for plant-level energy assessment in order to detect clusters that can aid in better modeling of industry for energy analysis in an evolving system with breakthrough technologies.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2023

Detection of open cluster rotation fields from Gaia EDR3 proper motions

Context: Most stars from in groups which with time disperse, building the field population of their host galaxy. In the Milky Way, open clusters have been continuously forming in the disk up to the present time, providing it with stars spanning a broad range of ages and masses. Observations of the details of cluster dissolution are, however, scarce. One of the main difficulties is obtaining a detailed characterisation of the internal cluster kinematics, which requires very high-quality proper motions. For open clusters, which are typically loose groups with tens to hundreds of members, there is the additional difficulty of inferring kinematic structures from sparse and irregular distributions of stars. Aims: Here, we aim to analyse internal stellar kinematics of open clusters, and identify rotation, expansion, or contraction patterns. Methods: We use Gaia Early Data Release 3 (EDR3) astrometry and integrated nested Laplace approximations to perform vector-field inference and create spatio-kinematic maps of 1237 open clusters. The sample is composed of clusters for which individual stellar memberships were already known, thus minimising contamination from field stars in the velocity maps. Projection effects were corrected using EDR3 data complemented with radial velocities from Gaia Data Release 2 and other surveys. Results: We report the detection of rotation patterns in eight open clusters. Nine additional clusters display possible rotation signs. We also observe 14 expanding clusters, with 15 other objects showing possible expansion patterns. Contraction is evident in two clusters, with one additional cluster presenting a more uncertain detection. In total, 53 clusters are found to display kinematic structures. Within these, elongated spatial distributions suggesting tidal tails are found in five clusters. These results indicate that the approach developed here can recover kinematic patterns from noisy vector fields, as those from astrometric measurements of open clusters or other stellar or galactic populations, thus offering a powerful probe for exploring the internal kinematics and dynamics of these types of objects.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Detection of Galaxy Cluster Motions with the Kinematic Sunyaev-Zel'dovich Effect

Using high-resolution microwave sky maps made by the Atacama Cosmology Telescope, we for the first time detect motions of galaxy clusters and groups via microwave background .temperature distortions due to the kinematic Sunyaev.Zel'dovich effect. Galaxy clusters are identified by their constituent luminous galaxies observed by the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. The mean pairwise momentum of clusters is measured. at a statistical. significance of 3.8 sigma, and the signal is consistent with the growth of cosmic structure in the standard model of cosmology

Hand, Nick↗
NASA NTRS2008

Spectroscopic Confirmation of a Massive Red-sequence Selected Galaxy Cluster at Z=1.34 in the SpARCS-South Cluster Survey

The Spitzer Adaptation of the Red-sequence Cluster Survey (SpARCS) is a z'-passband imaging survey, consisting of deep (z' approx. 24 AB) observations made from both hemispheres using the CFHT 3.6m and CTIO 4m telescopes. The survey was designed with the primary aim of detecting galaxy clusters at z > 1. In tandem with pre-existing 3.6 micron observations from the Spitzer Space Telescope SWIRE Legacy Survey, SpARCS detects clusters using an infrared adaptation of the two-filter red-sequence cluster technique. The total effective area of the SpARCS cluster survey is 41.9 sq deg. In this paper, we provide an overview of the 13.6 sq deg Southern CTIO/MOSAICII observations. The 28.3 sq deg Northern CFHT/MegaCam observations are summarized in a companion paper by Muzzin et al. (2008a). In this paper, we also report spectroscopic confirmation of SpARCS J003550-431224, a very rich galaxy cluster at z = 1.335, discovered in the ELAIS-S1 field. To date, this is the highest spectroscopically confirmed redshift for a galaxy cluster discovered using the red-sequence technique. Based on nine confirmed members, SpARCS J003550-431224 has a preliminary velocity dispersion of 1050+/-230 km/s. With its proven capability for efficient cluster detection, SpARCS is a demonstration that we have entered an era of large, homogeneously-selected z > 1 cluster surveys.

Wilson, Gillian↗
NASA NTRS2016

System and Method for Outlier Detection via Estimating Clusters

An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

Iverson, David J.↗
DOE OSTI2024

Using Signal Clustering Similarity for Detecting CAN Masquerade Attacks

The computer code assumes that time series representing the physical signals of the vehicle have been extracted from the CAN bus. The main input of the computer code is the multivariate time series representation of the signals in the CAN bus. The computer code cluster these time series using agglomerative hierarchical clustering from benign and attack datasets. Based on this, it generates probability distributions from the similarity of the obtained clusters based in each scenario---benign and attack---using the CluSim method (https://github.com/Hoosier-Clusters/clusim). Finally, it compares how a new data collection compares with the previous distribution to provide and probability score for an intrusion.

Moriano, Pablo↗
DOE OSTI2022

Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with nearest neighbor distributions

ABSTRACT Distances to the k-nearest-neighbor (kNN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here, we present the first application of kNN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters (0.1 ≤ z ≤ 0.3) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of kNN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the k = 1, 2-NN CDFs of redMaPPer deviate significantly from the randoms’ across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to kNN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the χ2 distribution for both the kNN-CDFs and the two-point correlation function measured on the randoms peak at χ2 ∼ 50 (null hypothesis), whereas the kNN-CDFs (χ2 ∼ 300, p = 1.54 × 10−36) pick up a much more significant clustering signal than the two-point function (χ2 ∼ 100, p = 1.16 × 10−6) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted k = 3, 4-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, kNN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy–halo connection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Development of FRET clusters for CBRN Detection

Advanced sensor capabilities for the simultaneous on-site detection of specific chemical, biological, and radiological/nuclear (CBRN) threats is important to significantly limit the risk of exposure to personnel and allow the rapid collection of essential scientific data and critical evidence. Commercially available sensor capabilities are generally complex, and/or require highly specific and ultra-sensitive methods that are often power demanding or require offsite post-analysis for positive detection, leaving personnel vulnerable. The goal of this project is to develop a portable sensor capable of simultaneously detecting CBRN signatures using a multiplexed Förster Resonance Energy Transfer (FRET) based sensor. FRET sensors are tailorable, specific, and highly dependent on the donor-acceptor distance. In this project, nanoparticles were functionalized with aptamers that were designed for the detection of methylphosphonate, a sarin metabolite. FRET was measured between quantum dot donors and dye and metal nanoparticle acceptors using optical spectroscopy.

61 RADIATION PROTECTION AND DOSIMETRY↗