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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Space station ECLSS integration analysis: Simplified General Cluster Systems Model, ECLS System Assessment Program enhancements

The data base verification of the ECLS Systems Assessment Program (ESAP) was documented and changes made to enhance the flexibility of the water recovery subsystem simulations are given. All changes which were made to the data base values are described and the software enhancements performed. The refined model documented herein constitutes the submittal of the General Cluster Systems Model. A source listing of the current version of ESAP is provided in Appendix A.

Ferguson, R. E.↗
NASA NTRS1980

Optical properties of Morgan's poor clusters

The galaxy density, spiral content, and richness of the 23 poor clusters of galaxies cataloged by Morgan and co-workers are determined and compared with those of Abell clusters. It is found that Morgan's clusters generally represent a smooth continuation of the galaxy clustering spectrum from the rich Abell clusters. This continuity in optical properties implies a corresponding continuity in X-ray properties. The extended X-ray emission recently detected from several of Morgan's clusters is consistent with the amount of thermal bremsstrahlung emission expected on the basis of the present optical observations and previous correlations of X-ray-optical cluster properties. The fraction of cluster galaxies that are spirals is a sensitive function of the galaxy surface density, N(-)0.

Bahcall, N. A.↗
NASA NTRS1995

ROSAT HRI images of Abell 85 and Abell 496: Evidence for inhomogeneities in cooling flows

We present ROSAT high-resolution images of two clusters of galaxies with cooling flows, Abell 496 and Abell 85. In these clusters, X-ray emission on small scales above the general cluster emission is significant at the 3 sigma level. There is no evidence for optical counterparts. If real, the enhancements may be associated with clumps of gas at a lower temperature and higher density than the ambient medium, or hotter, denser gas perhaps compressed by magnetic fields. These observations can be used to test models of how thermal instabilities form and evolve in cooling flows.

Prestwich, Andrea H.↗
NASA NTRS1994

ROSAT HRI images of Abell 85 and Abell 496: Evidence for inhomogeneities in cooling flows

We present ROSAT HRI images of two clusters of galaxies with cooling flows, Abell 496 and Abell 85. In these clusters, x-ray emission on small scales above the general cluster emission is significant at the 3 sigma level. There is no evidence for optical counterparts. The enhancements may be associated with lumps of gas at a lower temperature and higher density than the ambient medium, or hotter, denser gas perhaps compressed by magnetic fields. These observations can be used to test models of how thermal instabilities form and evolve in cooling flows.

Prestwich, Andrea H.↗
NASA NTRS1993

Two generalizations of Kohonen clustering

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

Bezdek, James C.↗
NASA NTRS2004

Clustering with Missing Values: No Imputation Required

Clustering algorithms can identify groups in large data sets, such as star catalogs and hyperspectral images. In general, clustering methods cannot analyze items that have missing data values. Common solutions either fill in the missing values (imputation) or ignore the missing data (marginalization). Imputed values are treated as just as reliable as the truly observed data, but they are only as good as the assumptions used to create them. In contrast, we present a method for encoding partially observed features as a set of supplemental soft constraints and introduce the KSC algorithm, which incorporates constraints into the clustering process. In experiments on artificial data and data from the Sloan Digital Sky Survey, we show that soft constraints are an effective way to enable clustering with missing values.

constraints↗
NASA NTRS1982

X-ray-imaging observations of clusters of galaxies

Einstein X-ray imaging observations, made to illustrate the variety of phenomena that can be considered through X-ray image analysis, are presented. Attention is given to general cluster properties and intracluster gas. Individual clusters are discussed (considering classification and dynamical evolution), and X-ray images are used to determine cluster mass distribution and to examine distant clusters. X-ray observations have contributed information in regard to processes affecting galaxies, the intracluster medium, and the cluster itself. Analyses have traced massive halos around dominant galaxies in unevolved clusters, and have helped define the cluster gravitational potential. In addition, multi-component double clusters have been discovered, and material which has been ram-pressure stripped from a hot corona around the M86 galaxy in Virgo was observed. Finally, quantitative estimates of the fractions of young and evolved clusters and determinations of total cluster mass are possible using X-ray observations.

Forman, W.↗
NASA NTRS1980

Analysis of SETI data collected in the parasitic mode

A system for performing SETI observations continuously as part of non-SETI observations at a radio observatory is presented, and the analysis of results obtained by the parasitic system is discussed. The system, designated SERENDIP, is a real-time microprocessor-controlled spectrum analyzer with algorithms for performing statistical operations and recording those spectra with characteristics presumed to be typical of intelligent rather than astrophysical origin. Programs also exist for the post-acquisition analysis of signal autocorrelation, power spectra, time behavior and positional coordinates, and for a generalized cluster analysis to detect clusters of signal detections. In a recent run of 35 days, the SERENDIP system detected 4000 narrowband spectra exceeding a preset threshold, of which 98% were determined to be of instrumental origin. The remaining class of detections is also believed to be instrumental, although not as well organized as the first signals, and means are currently being sought for eliminating them.

Bowyer, S.↗
NASA NTRS1987

Extrapolation of velocity for inviscid solid boundary conditions

The present examination of an extrapolation of velocity along an arbitrary direction in the case of inviscid solid boundary conditions demonstrates the error associated with the arbitrary direction and establishes that the most appropriate procedure lies in the extrapolation of the velocity components that are tangential to the body surface. It is noted that, in a typical calculation, mesh lines generally cluster together and are therefore parallel or nearly parallel to the body surface.

Hung, Ching-Mao↗
NASA NTRS1993

The coronae of main-sequence A stars

We have undertaken a deep X-ray imaging survey of single, normal, mid-to-late-A- and early-F-type main-sequence stars using the ROSA T PSPC. Eight of the nine such stars in our fields went undetected at very weak emission levels, with upper limits on the normalized X-ray flux in each case of better than log R(x) below -6.3. The only A-F star we detected was 83 Tau, a member of the Hyades that we now belatedly recognize as a possible binary star, whose emission may come from an unidentified companion. Our observations reveal a systematic decline in coronal X-ray brightness with increasing effective temperature, which we attribute to the presence of strong coronal winds. These new results add further weight to earlier suggestions that single A and early-F stars in the field and in nearby older open clusters generally have intrinsically faint coronae.

Simon, Theodore↗
NASA NTRS2003

Constraints on the Energy Content of the Universe from a Combination of Galaxy Cluster Observables

We demonstrate that constraints on cosmological parameters from the distribution of clusters as a function of redshift (dN/dz) are complementary to accurate angular diameter distance (D(sub A)) measurements to clusters, and their combination significantly tightens constraints on the energy density content of the Universe. The number counts can be obtained from X-ray and/or SZ (Sunyaev-Ze'dovich effect) surveys, and the angular diameter distances can be determined from deep observations of the intra-cluster gas using their thermal bremsstrahlung X-ray emission and the SZ effect. We combine constraints from simulated cluster number counts expected from a 12 deg(sup 2) SZ cluster survey and constraints from simulated angular diameter distance measurements based on the X-ray/SZ method assuming a statistical accuracy of 10% in the angular diameter distance determination of 100 clusters with redshifts less than 1.5. We find that Omega(sub m), can be determined within about 25%, Omega(sub lambda) within 20% and w within 16%. We show that combined dN/dz+(sub lambda) constraints can be used to constrain the different energy densities in the Universe even in the presence of a few percent redshift dependent systematic error in D(sub lambda). We also address the question of how best to select clusters of galaxies for accurate diameter distance determinations. We show that the joint dN/dz+ D(lambda) constraints on cosmological parameters for a fixed target accuracy in the energy density parameters are optimized by selecting clusters with redshift upper cut-offs in the range 0.55 approx. less than 1. Subject headings: cosmological parameters - cosmology: theory - galaxies:clusters: general

Molnar, Sandor M.↗
NASA NTRS2010

Trace Element Compositions of Pallasite Olivine Grains and Pallasite Origin

Pallasites are mixtures of metal with magnesian olivine. Most have similar metal compositions and olivine oxygen isotopic compositions; these are the main-group pallasites (PMG). The Eagle Station grouplet of pallasites (PES) have distinctive metal and olivine compositions and oxygen isotopic compositions. Pallasites are thought to have formed at the core-mantle boundary of their parent asteroids by mixing molten metal with solid olivine of either cumulatic or restitic origin. We have continued our investigation of pallasite olivines by doing in situ trace element analyses in order to further constrain their origin. We determined Al, P, Ca, Ga and first row transition element contents of olivine grains from suite of PMG and PES by LA-ICP-MS at JSC. Included in the PMG suite are some that have anomalous metal compositions (PMG-am) and atypically ferroan olivines (PMG-as). Our EMPA work has shown that there are unanticipated variations in olivine Fe/Mn, even within those PMG that have uni-form Fe/Mg. Manganese is homologous with Fe2+, and thus can be used the same way to investigate magmatic fractionation processes. It has an advantage for pallasite studies in that it is unaffected by redox exchange with the metal. PMG can be divided into three clusters on the basis of Mn/Mg; low, medium and high that can be thought of as less, typically and more fractionated in an igneous sense. The majority of PMG have medium Mn/Mg ratios. PMG-am occur in all three clusters; there does not seem to be any relationship between putative olivine igneous fractionation and metal composition. The PMG-as and one PMG-am make up the high Mn/Mg cluster; no PMG are in this cluster. The high Mn/Mg cluster ought to be the most fractionated (equivalent to the most Fe-rich in igneous suites), yet they have among the lowest contents of incompatible lithophile elements Al and Ti and the two PMG-as in this cluster also have low Ca and Sc contents. This is inconsistent with simple igneous fractionation on a single, initially homogeneous parent asteroid. For Al and Ti, the low and high Mn/Mg clusters have generally uniform contents, while the medium cluster has wide ranges. This is also true of analyses of duplicate grains from the medium cluster pallasites which can have very different Al and Ti contents. Those from the low and high clusters do not. These observations suggest that pallasite olivines are not cumulates, but rather are restites from high degrees of melting. The moderately siderophile elements P and Ga show wide ranges in the high Mn/Mg cluster, but very uniform compositions in the medium cluster, opposite the case for Al and Ti. There is no correlation of P or Ga and Fe/Mn as might be expected if redox processes controlled the contents of moderately siderophile elements in the olivines. The lack of correlation of P could reflect equilibration with phosphates, although there is no correlation of Ca with P as might be expected

Mittlefehldt, David W.↗
NASA NTRS1987

Star formation in Carina OB1: Observations of a giant molecular cloud associated with the eta Carinae Nebula

A giant molecular cloud associated with the eta Carinae nebula was fully mapped in CO with the Columbia Millimeter-Wave Telescope at Cerro Tololo. The cloud comples has a mass of roughly 700,000 solar mass and extends about 140 pc along the Galactic plane, with the giant Carina HII region situated at one end of the complex. Clear evidence of interaction between the HII region and the molecular cloud is found in the relative motions of the ionized gas, the molecular gas, and the dust; simple energy and momentum considerations suggest that the HII region is responsible for the observed motion of a cloud fragment. The molecular cloud complex appears to be the parent material of the entire Car OB1 Association which, in addition to the young clusters in the Carine nebula, includes the generally older cluster NGC 3325, NGC 3293, and IC 2581. The overall star formation efficiency in the cloud complex is estimated to be approximately 0.02.

Grabelsky, D. A.↗
NASA NTRS2005

Small-Scale Drop Size Variability: Impact on Estimation of Cloud Optical Properties

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.

Knyazikhin, Y.↗
NASA NTRS1993

Robust root clustering for linear uncertain systems using generalized Lyapunov theory

Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

Yedavalli, R. K.↗
NASA NTRS1991

Fuzzy modeling based on generalized neural networks and fuzzy clustering objective functions

An approach to the formulation of fuzzy if-then rules based on clustering objective functions is proposed. The membership functions are then calibrated with the generalized neural networks technique to achieve a desired input-output mapping. The learning procedure is basically a gradient-descent algorithm. A Kalman filter algorithm is used to improve the overall performance.

Sun, Chuen-Tsai↗
NASA NTRS2011

A Multiple Sphere T-Matrix Fortran Code for Use on Parallel Computer Clusters

A general-purpose Fortran-90 code for calculation of the electromagnetic scattering and absorption properties of multiple sphere clusters is described. The code can calculate the efficiency factors and scattering matrix elements of the cluster for either fixed or random orientation with respect to the incident beam and for plane wave or localized- approximation Gaussian incident fields. In addition, the code can calculate maps of the electric field both interior and exterior to the spheres.The code is written with message passing interface instructions to enable the use on distributed memory compute clusters, and for such platforms the code can make feasible the calculation of absorption, scattering, and general EM characteristics of systems containing several thousand spheres.

Mackowski, D. W.↗
NASA NTRS2011

Determining the Optimal Number of Clusters with the Clustergram

Cluster analysis aids research in many different fields, from business to biology to aerospace. It consists of using statistical techniques to group objects in large sets of data into meaningful classes. However, this process of ordering data points presents much uncertainty because it involves several steps, many of which are subject to researcher judgment as well as inconsistencies depending on the specific data type and research goals. These steps include the method used to cluster the data, the variables on which the cluster analysis will be operating, the number of resulting clusters, and parts of the interpretation process. In most cases, the number of clusters must be guessed or estimated before employing the clustering method. Many remedies have been proposed, but none is unassailable and certainly not for all data types. Thus, the aim of current research for better techniques of determining the number of clusters is generally confined to demonstrating that the new technique excels other methods in performance for several disparate data types. Our research makes use of a new cluster-number-determination technique based on the clustergram: a graph that shows how the number of objects in the cluster and the cluster mean (the ordinate) change with the number of clusters (the abscissa). We use the features of the clustergram to make the best determination of the cluster-number.

Fluegemann, Joseph K.↗