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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Feasibility of vibration monitoring of small rotating machines for the environmental control and life support systems (ECLSS) of the NASA advanced space craft

The application of vibration monitoring to the rotating machinery typical of ECLSS components in advanced NASA spacecraft was studied. It is found that the weighted summation of the accelerometer power spectrum is the most successful detection scheme for a majority of problem types. Other detection schemes studied included high-frequency demodulation, cepstrum, clustering, and amplitude processing.

Milner, G. Martin↗
NASA NTRS1989

Iron, magnesium, and silicon in dust from Comet Halley

The highest-quality impact mass spectrometer data from the Vega-1 and Giotto spacecraft are presently used to study the Mg, Si, and Fe composition of dust grains in Comet Halley. The results thus obtained are in general agreement with previously reported data, but differ with respect to ion ratio dispersions. A lack of sharp clustering in the data indicates that none of the detected particles can be characterized as single mineral grains; an abundant glass content in the solids may be indicated. The best match of the distribution of Fe/(Fe+Mg) is with interplanetary particles containing high temperature, Mg-rich silicates dominated by anhydrous minerals, so that Comet Halley may be a mixture of ice and high-temperature anhydrous minerals.

Lawler, Mark E.↗
NASA NTRS1990

H I absorption toward cooling flows in clusters of galaxies

An H I survey of 14 cooling flow clusters and two noncooling flow clusters was conducted, and H I absorption features were detected against the nuclear radio continuum sources of two cooling flow dominant (CFD) galaxies, 2A 0335 + 096 and MKW3s. The absorption features are broad and redshifted with respect to the stellar absorption-line velocity of the CFDs by 90-225 km/s. This indicates that the H I is falling onto, and is probably gravitationally bound to, the CFDs. The kinematics of the H I clouds suggest a possible kinematic link between the warm and cold phases of the intracluster medium. The clouds are orders of magnitude smaller in radius and mass and larger in density than Galactic H I clouds. The detected CFDs have mass-accretion rates that are about 2.5 times larger than the CFDs that were not detected.

Mcnamara, Brian R.↗
NASA NTRS1999

The Low-Mass X-Ray Binary X1832-330 in the Globular Cluster NGC 6652: A Serendipitous ASCA Observation

The Low Mass X-ray Binary (LMXB) X1832-330 in NGC 6652 is one of about 10 bright X-ray sources to have been discovered in Globular Clusters. We report on a serendipitous ASCA observation of this Globular Cluster LMXB, during which a Type I burst was detected and the persistent, non-burst emission of the source was at its brightest level recorded to date. No orbital modulation was detected, which argues against a high inclination for the X1832-330 system. The spectrum of the persistent emission can be fit with a power law plus a partial covering absorber, although other models are not ruled out. Our time-resolved spectral analysis through the burst shows, for the first time, clear evidence for spectral cooling from kT = 2.4 +/- 0.6 keV to kT = 1.0 +/- 0.1 keV during the decay. The measured peak flux during the burst is approximately 10% of the Eddington luminosity for a 1.4 Solar Mass neutron star. These are characteristic of a Type I burst, in the context of the relatively low quiescent luminosity of X1832-330.

Mukai, Koji↗
NASA NTRS2017

Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016. Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2. The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core. These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.

Monsoon↗
NASA NTRS2018

Low-Power, Chip-Scale, Carbon Dioxide Gas Sensors for Spacesuit Monitoring

N5 Sensors, Inc. through a Small Business Technology Transfer (STTR) contract award has been developing ultra-small, low-power carbon dioxide (CO2) gas sensors, suited for monitoring CO2 levels inside NASA spacesuits. Due to the unique environmental conditions within the spacesuits, such as high humidity, large temperature swings, and operating pressure swings, measurement of key gases relevant to astronaut's safety and health such as(CO2), is quite challenging. Conventional non-dispersive infrared absorption based CO2 sensors present challenges inside the spacesuits due to size, weight, and power constraints, along with the ability to sense CO2 in a high humidity environment. Unique chip-scale, nanoengineered chemiresistive gas-sensing architecture has been developed for this application, which can be operated in a typical space-suite environmental conditions. Unique design combining the selective adsorption properties of the nanophotocatalytic clusters of metal-oxides and metals, provides selective detection of CO2 in high relative humidity conditions. All electronic design provides a compact and low-power solution, which can be implemented for multipoint detection of CO2 inside the spacesuits. This paper will describe the sensor architecture, development of new photocatalytic material for better sensor response, and advanced structure for better sensitivity and shorter response times.

Rani, Asha↗
NASA NTRS2016

Discovery and Modelling of a Flattening of the Positive Cyclotron Line/luminosity Relation in GX 304-1 with RXTE

The Rossi X-ray Timing Explorer (RXTE) observed four outbursts of the accreting Xray binary transient source, GX 304−1 in 2010 and 2011. We present results of detailed 3-100 keV spectral analysis of 69 separate observations, and report a positive correlation between cyclotron line parameters, as well as other spectral parameters, with power-law flux. The cyclotron line energy, width and depth versus flux, and thus luminosity, correlations show a flattening of the relationships with increasing luminosity, which are well described by quasi-spherical or disc accretion that yield the surface magnetic field to be ∼5 × 1012 Gauss. Since HEXTE (High Energy X-ray Timing Experiment) cluster A was fixed aligned with the Proportional Counter Array field of view and cluster B was fixed viewing a background region 1. ◦ 5 off of the source direction during these observations near the end of the RXTE mission, the cluster A background was estimated from cluster B events using HEXTEBACKEST. This made possible the detection of the ∼55 keV cyclotron line and an accurate measurement of the continuum. Correlations of all spectral parameters with the primary 2-10 keV power-law flux reveal it to be the primary driver of the spectral shape. The accretion is found to be in the collisionless shock braking regime.

Rothschild, Richard E.↗
NASA NTRS2022

Technical Note: On Seasonal Variability of the M2 Tide

Seasonal variability of the M2 ocean tide can be detected at many ports, perhaps most. Examination of the cluster of tidal constituents residing within the M2 tidal group can shed light on the physical mechanisms underlying seasonality. In the broadest terms these are astronomical, frictional–advective interactions, and climate processes; some induce annual modulations and some semiannual, in amplitude, phase, or both. This note reviews how this occurs and gives an example from each broad category. Phase conventions and their relationship with causal mechanisms, as well as nomenclature, are also addressed.

Richard D Ray↗
NASA NTRS1994

The galactic globular cluster system

We explore correlations between various properties of Galactic globular clusters, using a database on 143 objects. Our goal is identify correlations and trends which can be used to test and constrain theoretical models of cluster formation and evolution. We use a set of 13 cluster parameters, 9 of which are independently measured. Several arguments suggest that the number of clusters still missing in the obscured regions of the Galaxy is of the order of 10, and thus the selection effects are probably not severe for our sample. Known clusters follow a power-law density distribution with a slope approximately -3.5 to -4, and an apparent core with a core radius approximately 1 kpc. Clusters show a large dynamical range in many of their properties, more so for the core parameters (which are presumably more affected by dynamical evolution) than for the half-light parameters. There are no good correlations with luminosity, although more luminous clusters tend to be more concentrated. When data are binned in luminosity, several trends emerge: more luminous clusters tend to have smaller and denser cores. We interpret this as a differential survival effect, with more massive clusters surviving longer and reaching more evolved dynamical states. Cluster core parameters and concentrations also correlate with the position in the Galaxy, with clusters closer to the Galactic center or plane being more concentrated and having smaller and denser cores. These trends are more pronounced for the fainter (less massive) clusters. This is in agreement with a picture where tidal shocks form disk or bulge passages accelerate dynamical evolution of clusters. Cluster metallicities do not correlate with any other parameter, including luminosity and velocity dispersion; the only detectable trend is with the position in the Galaxy, probably reflecting Zinn's disk-halo dichotomy. This suggests that globular clusters were not self-enriched systems. Velocity dispersions show excellent correlations with luminosity and surface brightness. Their origin is not well understood, but they may well reflect initial conditions of cluster formation, and perhaps even be used to probe the initial density perturbation spectrum on a approximately 10(exp 6) solar mass scale. Core radii and concentrations play a role of a 'second parameter' in these correlations. While a global manifold of cluster properties has a high statistical dimensionality (D greater than 4), a subset of structural, photometric, and dynamical parameters forms a statistically three-dimensional family, as expected from objects following King models; we propose to call this set of quantities the King Manifold. Some of the observed correlations may be usable as distance indicator relations for globular clusters.

Djorgovski, S.↗
NASA NTRS2019

The Seismic Signatures of Recently Formed Impact Craters on Mars

We investigated the seismic signatures of recent impact crater clusters on Mars that would be recorded by the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight)seismometers. We used a database of 77 measured and dated impact sites, with craters with diameters between 2.1 and 33.8 m, along with inferred impact angle, bolide trajectory, and varying target material properties to empirically scale for the momentum, expected seismic source function, and radiation pattern of impacts. The impact source is simulated in a local 3‐Dfinite difference wave propagation code and coupled to teleseismic distances by scaling the spectra of 1‐D global synthetic seismograms. We use the InSight seismometer noise floors to estimate detectability of impact(s) across azimuth and distance. Our experiments reveal that impact clusters have a higher peak corner frequency resulting from energy contributed by smaller craters to the power spectrum. We also find that the time separation between individual impacts in a cluster is small (<10–15 ms) and requires a seismometer closely situated to the source (<10 km) and a high sampling rate (>100 Hz) to resolve individual impacts within the cluster. Two of the clusters in our database(>20‐m effective diameter) would have been detectable by InSight, with the assumptions that the Martian background noise and seismic attenuation are both low. Joint detection of surface changes from newly formed crater(s) in images and by InSight will provide precise source locations that are crucial for constraining the internal structure of Mars

N. C. Schmerra↗
NASA NTRS2004

Non-Thermal Hard X-Ray Emission in Galaxy Clusters Observed with the BeppoSAX PDS

We study the X-ray emission in a sample of galaxy clusters using the BeppoSAX PDS instrument in the 20-80 keV energy band. We estimate the nonthermal hard X-ray (HXR) cluster emission by modeling the thermal contribution from the cluster gas and the nonthermal contamination from the unobscured active galactic nuclei (AGNs) in the clusters. We also evaluate the systematic uncertainties due to the background fluctuations. Assuming negligible contamination from the obscured AGNs, the resulting nonthermal component is detected at a 2 sigma level in approx. 50% of the nonsignificantly AGN-contaminated clusters: A2142, A2199, A2256, A3376, Coma, Ophiuchus, and Virgo. The data are consistent with a scenario whereby relaxed clusters have no hard X-ray component of nonthermal origin, whereas merger clusters do, with a 20-80 keV luminosity of approx. 10(exp 43)-10(exp 44) h(sup -2 sub 50) ergs/s. The co-added spectrum of the above clusters indicates a power-law spectrum for the HXR emission with a photon index of 2.8(sup +0.3 sub -0.4) in the 12-115 keV band, and we find indication that it has extended distribution. These indications argue against significant contamination from obscured AGNs, which have harder spectra and a centrally concentrated distribution. These results are supportive of the assumption of the merger shock acceleration of electrons in clusters, which has been proposed as a possible origin of the nonthermal hard X-ray emission models. Assuming that the cosmic microwave background photons experience inverse Compton scattering from the merger-accelerated relativistic electrons and thus produce the observed HXR, the measured hard X-ray slope corresponds to a differential momentum spectra of the relativistic electrons with a slope of mu = 3.8-5.0. In presence of cluster magnetic fields this relativistic electron population produces synchrotron emission with a spectral index of 1.4-2.1, consistent with radio halo observations of merger clusters. Thus both hard X-ray and radio observations of merger clusters are consistent with the inverse Compton model.

Nevalainen, J.↗
NASA NTRS2002

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

Tilton, James C.↗
NASA NTRS1984

Preliminary Comparisons of the Information Content and Utility of TM Versus MSS Data

Comparisons were made between subscenes from the first TM scene acquired of the Washington, D.C. area and a MSS scene acquired approximately one year earlier. Three types of analyses were conducted to compare TM and MSS data: a water body analysis, a principal components analysis and a spectral clustering analysis. The water body analysis compared the capability of the TM to the MSS for detecting small uniform targets. Of the 59 ponds located on aerial photographs 34 (58%) were detected by the TM with six commission errors (15%) and 13 (22%) were detected by the MSS with three commission errors (19%). The smallest water body detected by the TM was 16 meters; the smallest detected by the MSS was 40 meters. For the principal components analysis, means and covariance matrices were calculated for each subscene, and principal components images generated and characterized. In the spectral clustering comparison each scene was independently clustered and the clusters were assigned to informational classes. The preliminary comparison indicated that TM data provides enhancements over MSS in terms of (1) small target detection and (2) data dimensionality (even with 4-band data). The extra dimension, partially resultant from TM band 1, appears useful for built-up/non-built-up area separation.

Markham, B. L.↗
NASA NTRS1985

A comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in lower Chesapeake Bay

LANDSAT Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery generated simultaneously over Guinea Marsh, Virginia, are assessed in the ability to detect submerged aquatic, bottom-adhering plant canopies (SAV). An unsupervised clustering algorithm is applied to both image types and the resulting classifications compared to SAV distributions derived from color aerial photography. Class confidence and accuracy are first computed for all water areas and then only shallow areas where water depth is less than 6 feet. In both the TM and MSS imagery, masking water areas deeper than 6 ft. resulted in greater classification accuracy at confidence levels greater than 50%. Both systems perform poorly in detecting SAV with crown cover densities less than 70%. On the basis of the spectral resolution, radiometric sensitivity, and location of visible bands, TM imagery does not offer a significant advantage over MSS data for detecting SAV in Lower Chesapeake Bay. However, because the TM imagery represents a higher spatial resolution, smaller SAV canopies may be detected than is possible with MSS data.

Ackleson, S. G.↗
NASA NTRS2003

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Tilton, James C.↗
NASA NTRS2016

Searching for the 3.5 keV Line in the Stacked Suzaku Observations of Galaxy Clusters

We perform a detailed study of the stacked Suzaku observations of 47 galaxy clusters, spanning a redshift range of 0.01-0.45, to search for the unidentified 3.5 keV line. This sample provides an independent test for the previously detected line. We detect a 2sigma-significant spectral feature at 3.5 keV in the spectrum of the full sample. When the sample is divided into two subsamples (cool-core and non-cool core clusters), the cool-core subsample shows no statistically significant positive residuals at the line energy. A very weak (approx. 2sigma confidence) spectral feature at 3.5 keV is permitted by the data from the non-cool-core clusters sample. The upper limit on a neutrino decay mixing angle of sin(sup 2)(2theta) = 6.1 x 10(exp -11) from the full Suzaku sample is consistent with the previous detections in the stacked XMM-Newton sample of galaxy clusters (which had a higher statistical sensitivity to faint lines), M31, and Galactic center, at a 90% confidence level. However, the constraint from the present sample, which does not include the Perseus cluster, is in tension with previously reported line flux observed in the core of the Perseus cluster with XMM-Newton and Suzaku.

dark matter↗
NASA NTRS2006

Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences

This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.

Budalakoti, Suratna↗
NASA NTRS1993

HI observations of dwarf galaxies out to a distance of 50 Mpc

Here we report our preliminary findings from an HI search for dwarf galaxies in three environmentally distinct regions of the sky: a galactic void, a galactic cluster, and an interaction field. This study is sensitive at the 5(sigma) level to hydrogen masses as low as 5 x 10(exp 5) solar mass. We have made three possible detections of previously uncatalogued objects: one in the void field, and two in the cluster field. Reduction of the interaction field is in progress.

Simpson, Caroline↗