Search NASA⌕ Search

SEARCH · Search NASA

Results for “cluster methods”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

An improved reconstruction method for cosmological density fields

This paper proposes some improvements to existing reconstruction methods for recovering the initial linear density and velocity fields of the universe from the present large-scale density distribution. We derive the Eulerian continuity equation in the Zel'dovich approximation and show that, by applying this equation, we can trace the evolution of the gravitational potential of the universe more exactly than is possible with previous approaches based on the Zel'dovich-Bernoulli equation. The improved reconstruction method is tested using N-body simulations. When the Zel'dovich-Bernoulli equation describes the formation of filaments, then the Zel'dovich continuity equation also follows the clustering of clumps inside the filaments. Our reconstruction method recovers the true initial gravitational potential with an rms error about 3 times smaller than previous methods. We examine the recovery of the initial distribution of Fourier components and find the scale at which the recovered phases are scrambled with respect their true initial values. Integrating the Zel'dovich continuity equation back in time, we can improve the spatial resolution of the reconstruction by a factor of about 2.

Gramann, Mirt↗
NASA NTRS2004

Using Fuzzy Clustering for Real-time Space Flight Safety

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Lee, Charles↗
NASA NTRS1993

The protonation of N2O reexamined - A case study on the reliability of various electron correlation methods for minima and transition states

The protonation of N2O and the intramolecular proton transfer in N2OH(+) are studied using various basis sets and a variety of methods, including second-order many-body perturbation theory (MP2), singles and doubles coupled cluster (CCSD), the augmented coupled cluster (CCSD/T/), and complete active space self-consistent field (CASSCF) methods. For geometries, MP2 leads to serious errors even for HNNO(+); for the transition state, only CCSD/T/ produces a reliable geometry due to serious nondynamical correlation effects. The proton affinity at 298.15 K is estimated at 137.6 kcal/mol, in close agreement with recent experimental determinations of 137.3 +/- 1 kcal/mol.

Martin, J. M. L.↗
NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗
NASA NTRS2026

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗
NASA NTRS1984

The prediction of tropopause height from clusters of brightness temperatures and its application in the stratified regression temperature retrievals using microwave and infrared satellite measurements

A total of 1575 radiosondes and the corresponding simulated brightness temperatures were used in an effort to derive a temperature retrieval based on the clusters of brightness temperatures. The 8 simulated channels, namely, 3 MSU and 5 IR of the TIROS-N satellite are used by the GLAS temperature retrieval method. The 3 MSU and 5 IR brightness temperatures were clustered into 17 cluster groups and a regression for the prediction of the tropopause height in mb was generated. The overall r.m.s. for the tropopause prediction is excellent, namely, around 16 mb for the summer and 23 mb for the winter. The correct cluster of brightness temperatures can be identified 98% of the time by the method of discriminatory classification if it is approximately a normal distribution or, in general, by the method of the nearest neighbor.

Munteanu, M. J.↗
NASA NTRSDate not supplied

Congruence of Clusters Defined By Whole Genome Sequencing and MALDI-TOF for Bacteria Isolated From Cleanrooms

Introduction: Oligotrophic conditions can render cleanrooms inhospitable to microbes. Despite these constraints, fungi and bacteria are frequently isolated from surfaces in astromaterials cleanrooms at the Johnson Space Center. Bacillus species are of particular concern because endospores belonging to this genus are resilient and can affect astromaterials. Current monitoring programs rely on 16S rRNA sequencing and the VITEK2 Compact system. These methods have limited power to resolve Bacillus species. Matrix-assisted laser desorption - time of flight mass spectrometry (MALDI-TOF MS), provides a rapid, low cost, method of identifying bacterial isolates and has a higher resolution than 16S rRNA sequencing, particularly for Bacillus species; however, few studies have compared this method to the industry gold standard, whole genome sequencing (WGS). Methods: Based on 16S rRNA classification, we selected 14 isolates for analysis with MALDI-TOF and WGS. Mass spectra were generated with MALDI-TOF MS and processed with custom scripts to identify clusters of closely related isolates and calculate a matrix of pairwise cosine similarity scores. Hybrid Illumina and Nanopore sequencing were used to generate draft genomes. Pairwise similarity scores were calculated from these genomes based on the average amino acid identity (AAI) predicted from single copy core genes. Congruence of clustering between these methods, was assessed by calculating adjusted Rand and Wallace coefficients. Results: Clusters of species generated from MALDI-TOF MS showed good agreement of phylotypes generated with WGS. Pairs of strains that were > 94% similar to each other in terms of predicted amino acid sequences consistently showed cosine similarities of mass spectra > 0.65 and, of the 9 clusters identified with WGS, 8 were identical with MALDI-TOF. This corresponds to an adjusted Rand index of 0.95 and a 95% confidence interval of 0.80 – 1.00 for adjusted Wallace coefficients. The only discordance was for a pair of isolates that were classified as Paenibacillus species. This pair showed relatively high similarity (0.84) in terms of MALDI-TOF MS but only 85% similarity in terms of AAI. Conclusion: This study shows that MALDI-TOF and WGS exhibit a similar ability to delineate Bacillus species isolated from cleanrooms and taxonomic units described by these two methods are consistent with one another. Since MALDI-TOF MS is low in cost and high in throughput, this approach appears to be an ideal option for routine microbial monitoring and identifying Bacillus species.

Farnaz Mazhari↗
NASA NTRS1984

Seven poor clusters of galaxies

The measurement of 83 new redshifts from galaxies in the region of seven of the poor clusters of galaxies identified by Morgan et al (1975) and Albert et al (1977) has been followed by an estimation of cluster masses through the application of both the virial theorem and the projected mas method. For each system, these two estimates are consistent. For the two clusters with highest X-ray luminosities, the line-of-sight velocity dispersions are about 700 km/sec, while for the five other clusters, the dispersions are of the order of less than about 370 km/sec. The D or cD galaxy in each poor cluster is at the kinematic center of each system.

Beers, T. C.↗
NASA NTRS1980

The photometric properties of brightest cluster galaxies. I - Absolute magnitudes in 116 nearby Abell clusters

Two-color aperture photometry of the brightest galaxies in a complete sample of nearby Abell clusters is presented. The results are used to anchor the bright end of the Hubble diagram; essentially the entire formal error for this method is then due to the sample of distant clusters used. New determinations of the systematic trend of galaxy absolute magnitude with the cluster properties of richness and Bautz-Morgan type are derived. When these new results are combined with the Gunn and Oke (1975) data on high-redshift clusters, a formal value (without accounting for any evolution) of q sub 0 = -0.55 + or - 0.45 (1 standard deviations) is found.

Hoessel, J. G.↗
NASA NTRS2016

Improving and Expanding NASA Software Cost Estimation Methods

Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm.

Hihn, Jairus↗
NASA NTRS1996

IRAS Colors of the Pleiades

We present large scale images of the infrared emission of the region around the Pleiades using the ISSA data product from the IRAS mission. Residual Zodiacal background and a discontinuity in the image due to the scanning strategy of the satellite necessitated special background subtraction methods. The 60/100 color image clearly shows the heating of the ambient interstellar medium by the cluster. The 12/100 and 25/100 images peak on the cluster as expected for exposure of small dust grains to an enhanced UV radiation field; however, the 25/100 color declines to below the average interstellar value at the periphery of the cluster. Potential causes of the color deficit are discussed. A new method of identifying dense molecular material through infrared emission properties is presented. The difference between the 100 micron flux density and the 60 micron flux density scaled by the average interstellar 60/100 color ratio (Delta I(sub 100) is a sensitive diagnostic of material with embedded heating sources (Delta I(sub 100) less than 0) and cold, dense cores (Delta I(sub 100) greater than 0). The dense cores of the Taurus cloud complex as well as Lynds 1457 are clearly identified by this method, while the IR bright but diffuse Pleiades molecular cloud is virtually indistinguishable from the nearby infrared cirrus.

Carey, Sean J.↗
NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗
NASA NTRS1992

The void spectrum in two-dimensional numerical simulations of gravitational clustering

An algorithm for deriving a spectrum of void sizes from two-dimensional high-resolution numerical simulations of gravitational clustering is tested, and it is verified that it produces the correct results where those results can be anticipated. The method is used to study the growth of voids as clustering proceeds. It is found that the most stable indicator of the characteristic void 'size' in the simulations is the mean fractional area covered by voids of diameter d, in a density field smoothed at its correlation length. Very accurate scaling behavior is found in power-law numerical models as they evolve. Eventually, this scaling breaks down as the nonlinearity reaches larger scales. It is shown that this breakdown is a manifestation of the undesirable effect of boundary conditions on simulations, even with the very large dynamic range possible here. A simple criterion is suggested for deciding when simulations with modest large-scale power may systematically underestimate the frequency of larger voids.

Kauffmann, Guinevere↗
NASA NTRS1983

A new calibration of the extragalactic distance scale using Cepheids and RR Lyrae stars

Visual absolute magnitudes of classical Cepheids, metal-poor RR Lyrae stars and short-period type II Cepheids have been determined with very high precision by combining a large number of old and new astrophysical data. Five independent methods (four observational and one theoretical) have been successfully used: (1) secular and statistical parallaxes; (2) moving-group parallaxes; (3) cluster main-sequence fitting; (4) the Baade-Wesselink method and its modifications; and (5) light-curve and velocity-curve fitting (the theoretical method). With these five adopted methods, the zero point of the galactic and extragalactic distance scale can be set on a relatively firm and self-consistent basis. Classical Cepheids and RR Lyrae stars now provide essentially identical distances to nearby galaxies: the distance modulus to the Large Magellanic Cloud is 18.5 and to the Small Magellanic Cloud is 18.8, both with an uncertainty of 0.1. The distance to the center of our Galaxy is 8.6 plus or minus 0.5 kiloparsecs. The major uncertainty in these values lies in the correction for interstellar extinction.

Stothers, R. B.↗
NASA NTRS1994

Implications for gravitational lensing and the dark matter content in clusters of galaxies from spatially resolved x-ray spectra

A simple method for deriving well-behaved temperature solutions to the equation of hydrostatic equilibrium for intracluster media with X-ray imaging observations is presented and applied to a series of generalized models as well as to observations of the Perseus cluster and Abell 2256. In these applications the allowed range in the ratio of nonbaryons to baryons as a function of radius is derived, taking into account the uncertainties and crude spatial resolution of the X-ray spectra and considering a range of physically reasonable mass models with various scale heights. Particular attention is paid to the central regions of the cluster, and it is found that the dark matter can be sufficiently concentrated to be consistent with the high central mass surface densities for moderate-redshift clusters from their gravitational lensing properties.

Loewenstein, M.↗
NASA NTRS1983

An interactive Barnes objective map analysis scheme for use with satellite and conventional data

The Barnes (1973) objective map analysis scheme is employed to develop an interactive analysis package for assessing the impact of satellite-derived data on analyses of conventional meteorological data sets. The method permits modification of the values of input parameters in the objective analysis within objectively determined, internally set limits. The effects of the manipulations are rapidly displayed, and methods are included for assimilating the spatially clustered characteristics of satellite data and the various horizontal resolutions of the data types. Data sets from the SESAME rawinsonde wind data with uniform spatial distribution, with the same data set plus satellite cloud motion data, and a data set from the atmospheric sounder radiometer on the GOES satellite were analyzed as examples. The scheme is demonstrated to recover details after two iterations through the data.

Koch, S. E.↗
NASA NTRS1996

Self-Consistent Simulation of the Brownian Stage of Dust Growth

It is a widely accepted view that in proto-planetary accretion disks the collision and following sticking of dust particles embedded in the gas eventually leads to the formation of planetesimals (coagulation). For the smallest dust grains, Brownian motion is assumed to be the dominant source of their relative velocities leading to collisions between these dust grains. As the dust grains grow they eventually couple to the turbulent motion of the gas which then drives the coagulation much more efficiently. Many numerical coagulation simulations have been carried out to calculate the fractal dimension of the aggregates, which determines the duration of the ineffective Brownian stage of growth. Predominantly on-lattice and off-lattice methods were used. However, both methods require simplification of the astrophysical conditions. The aggregates found by those methods had a fractal dimension of approximately 2 which is equivalent to a constant, mass-independent friction time. If this value were valid for the conditions in an accretion disk, this would mean that the coagulation process would finally 'freeze out' and the growth of a planetesimal would be impossible within the lifetime of an accretion disk. In order to investigate whether this fractal dimension is model independent, we simulate self-consistently the Brownian stage of the coagulation by an N-particle code. This method has the advantage that no further assumptions about homogeneity of the dust have to be made. In our model, the dust grains are considered as aggregates built up of spheres. The equation of motion of the dust grains is based on the probability density for the diffusive transport within the gas atmosphere. Because of the very low number density of the dust grains, only 2-body-collisions have to be considered. As the Brownian stage of growth is very inefficient, the system is to be simulated over long periods of time. In order to find close particle pairs of the system which are most likely to undergo a collision, we use a particle-in-cell (PIC) method for the early stages of the simulation where the system is still very homogeneous and a tree method later when the particles are more clustered.

Kempf, S.↗
NASA NTRS1993

Statistics of Experiments on Cluster Formation and Transport in a Gravitational Field

Metastable state relaxation in a gravitational field is investigated in the case of non-critical binary solutions. A relaxation description is presented in terms of the time-dependent Ginzburg-Landau formalism for a non-conserved order parameter. A new ansatz for solution of the corresponding partial nonlinear stochastic differential equation is discussed. It is proved that, for the supersaturated solution under consideration, the metastable state relaxation in a gravitational field leads to formation of solute concentration gradients due to the sedimentation of subcritical solute clusters. The pure discussion of the possible methods to compare theoretical results and experimental data related to solute sedimentation in a gravitational field is presented. It is shown that in order to describe these experiments it is necessary to deal both with the value of the solute concentration gradient and with its formation rate. The stochastic nature of the sedimentation process is shown.

Izmailov, Alexander F.↗