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NASA NTRS2001

Deep Asca Campaign to Probe one Typical Broad Absorption Line Qso

We present a deep ASCA observation of a broad absorption line quasar (BALQSO) PG 0946+301. The source was clearly detected in one of the gas imaging spectrometers, but not in any other detector. If BALQSOs have intrinsic X-ray spectra similar to normal radio-quiet quasars, our observations imply that there is Thomson thick X-ray absorption (NH(1024 per square centimeter) toward PG 0946+301. This is the largest column density estimated so far toward a BALQSO. The absorber must be at least partially ionized and may be responsible for attenuation in the optical and UV. If the Thomson optical depth toward BALQSOs is close to 1, as inferred here, then spectroscopy in hard X-rays with large telescopes like XMM would be feasible.

Green, P.↗

NASA NTRS1997

Fault Detection of Rotating Machinery using the Spectral Distribution Function

The spectral distribution function is introduced to characterize the process leading to faults in rotating machinery. It is shown to be a more robust indicator than conventional power spectral density estimates, but requires only slightly more computational effort. The method is illustrated with examples from seeded gearbox transmission faults and an analytical model of a defective bearing. Procedures are suggested for implementation in realistic environments.

Davis, Sanford S.↗

NASA NTRS2001

The Statistical Consulting Center for Astronomy (SCCA)

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Akritas, Michael↗

NASA NTRS2003

Modeling and Visualizing Uncertainty in Continuous Variables Predicted using Remotely Sensed Data

The use of remotely sensed images to map continuous biophysical variables, such as those related to terrestrial vegetation amount, sea surface temperature, and many other targets of NASA s Earth Observing System (EOS), includes variable, parametric, positional, spatial support and structural sources of uncertainty. A complete description of uncertainty will lead to a probability distribution at each location, allowing the exploration of the spatial dimension of uncertainty, that is, where the field is not well quantified. To achieve this purpose, convenient visualization tools are required. We have produced such a tool, called PDFVis, that facilitates the display of probability density functions (pdfs) on a per-grid-cell basis. The density estimate from Monte-Carlo generated realizations is interactively displayed as well as parametric and non-parametric summaries of the pdf field (such as mean, median, quartiles, standard deviation, number of modes, and locations of modes). Shaded surface renderings of pdfs along a transect can also be projected onto a plane. This tool will become more useful as richer descriptions of spatial uncertainty become available.

Dungan, Jennifer L.↗

NASA NTRS2004

Earth GRAM-99 and Trace Constituents

Global Reference Atmospheric Model (GRAM-99) is an engineering-level model of Earth's atmosphere. It provides both mean values and perturbations for density, temperature, pressure, and winds, as well as monthly- and geographically-varying trace constituent concentrations. From 0-27 km, GRAM thermodynamics and winds are based on National Oceanic and Atmospheric Administration Global Upper Air Climatic Atlas (GUACA) climatology. Above 120 km, GRAM is based on the NASA Marshall Engineering Thermosphere (MET) model. In the intervening altitude region, GRAM is based on Middle Atmosphere Program (MAP) climatology that also forms the basis of the 1986 COSPAR International Reference Atmosphere (CIRA). Atmospheric composition is represented in GRAM by concentrations of both major and minor species. Above 120 km, MET provides concentration values for N2, O2, Ar, O, He, and H. Below 120 km, species represented also include H2O, O3, N2O, CO, CH4, and CO2. At COSPAR 2002 a comparison was made between GRAM constituents below 120 km and those provided by Naval Research Laboratory (NRL) climatology. No current need to update GRAM constituent climatology in that height range was identified. This report examines GRAM (MET) constituents between 100 and 1000 km altitudes. Discrepancies are noted between GRAM (MET) constituent number densities and mass density or molecular weight. Near 110 km altitude, there is up to about 25% discrepancy between MET number density and mass density (with mass density being valid and number densities requiring adjustment). Near 700 km altitude there is also up to about 25% discrepancy between MET number density and mean molecular weight (with molecular weight requiring adjustment). In neither case are MET mass density estimates invalidated. These discrepancies have been traced to MET subroutines SLV (which affects 90-170 km height range) and SLVH (which affects helium above 440 km altitude). With these discrepancies corrected, results are presented to illustrate GRAM (MET) constituent mole fractions in terms of height-latitude cross sections from 100 to 1000 km altitude, and latitude-longitude 'maps' at 450 km (approximate height of International Space Station). Plans are discussed for an update of MET (and GRAM) to correct these constituent inconsistencies and to incorporate several new thermospheric model features.

Justus, C. G.↗

NASA NTRS2004

Symmetric normal mixtures

We consider mixture density estimation under the symmetry constraint x = Az for an orthogonal matrix A. This distributional constraint implies a corresponding constraint on the mixture parameters. Focusing on the gaussian case, we derive an expectation-maximization (EM) algorithm to enforce the constraint and show results for modeling of image feature vectors.

symmetry constraint↗

NASA NTRS2006

Learning User Preferences for Sets of Objects

Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

preferences↗

NASA NTRS2008

The Atmospheric Dynamics of Alpha Tau (K5 III) -- Clues to Understanding the Magnetic Dynamo

Using HST/GHRS, HST/STIS and FUSE archival data for (alpha) Tau and the CHIANTI spectroscopic code, we have derived line shifts, volumetric emission measures, and plasma density estimates, and calculated filling factors for a number of UV lines forming between 10,000 K and 300,000 K in the outer atmosphere of this red giant star. The data suggest the presence of low-temperature extended regions and high-temperature compact regions, associated with magnetically open and closed structures in the stellar atmosphere, respectively. The signatures of UV lines from Alpha Tau can be consistently understood via a model of upward-traveling Alfven waves in a gravitationally stratified atmosphere. These wakes cause non-thermal broadening in UV lines due to unresolved wave motions and downward plasma motions in compact magnetic loops heated by resonant .4lf\en wave heating. We discuss implications of this interpretation for understanding the nature of magnetic dynamos operating in late-type giants.

Carpenter Kenneth G.↗

NASA NTRS2008

The Atmospheric Dynamics of alpha Tau (K5 III) - Clues to Understanding the Magnetic Dynamo in Late-Type Giant Stars

Using HST/GHRS, HST/STIS and FUSE archival data for alpha Tau and the CHIANTI spectroscopic code, we have derived line shifts, volumetric emission measures, and plasma density estimates, and calculated filling factors for a number of UV lines forming between 10,000 K and 300,000 K in the outer atmosphere of this red giant star. The data suggest the presence of low-temperature extended regions and high-temperature compact regions, associated with magnetically open and closed structures in the stellar atmosphere, respectively. The signatures of UV lines from alpha Tau can be consistently understood via a model of upward-traveling Alfven waves in a gravitationally stratified atmosphere. These waves cause non-thermal broadening in UV lines due to unresolved wave motions and downward plasma motions in compact magnetic loops heated by resonant Alfven wave heating.

Carpenter, Kenneth G.↗

NASA NTRS2008

The Atmospheric Dynamics of alpha Tau (K5 III) - Clues to Understanding the Magnetic Dynamo in Late-Type Giant Stars

Carpenter, Kenneth G.↗

NASA NTRS2009

Elastomer Reinforced with Carbon Nanotubes

Elastomers are reinforced with functionalized, single-walled carbon nanotubes (SWNTs) giving them high-breaking strain levels and low densities. Cross-linked elastomers are prepared using amine-terminated, poly(dimethylsiloxane) (PDMS), with an average molecular weight of 5,000 daltons, and a functionalized SWNT. Cross-link densities, estimated on the basis of swelling data in toluene (a dispersing solvent) indicated that the polymer underwent cross-linking at the ends of the chains. This thermally initiated cross-linking was found to occur only in the presence of the aryl alcohol functionalized SWNTs. The cross-link could have been via a hydrogen-bonding mechanism between the amine and the free hydroxyl group, or via attack of the amine on the ester linage to form an amide. Tensile properties examined at room temperature indicate a three-fold increase in the tensile modulus of the elastomer, with rupture and failure of the elastomer occurring at a strain of 6.5.

Hudson, Jared L.↗

NASA NTRS2010

Using CTX Image Features to Predict HiRISE-Equivalent Rock Density

Methods have been developed to quantitatively assess rock hazards at candidate landing sites with the aid of images from the HiRISE camera onboard NASA s Mars Reconnaissance Orbiter. HiRISE is able to resolve rocks as small as 1-m in diameter. Some sites of interest do not have adequate coverage with the highest resolution sensors and there is a need to infer relevant information (like site safety or underlying geomorphology). The proposed approach would make it possible to obtain rock density estimates at a level close to or equal to those obtained from high-resolution sensors where individual rocks are discernable.

Serrano, Navid↗

NASA NTRS2008

The Atmospheric Dynamics of Alpha Tau (K5 III) - Clues to Understanding the Magnetic Dynamo in Late-Type Giant Stars

Using HST/GHRS, HST/STIS and FUSE archival data for a Tau and the CHIANTI spectroscopic code, we have derived line shifts, volumetric emission measures, and plasma density estimates, and calculated filling factors for a number of UV lines forming between 10,000 K and 300,000 K in the outer atmosphere of this red giant star. The data suggest the presence of low-temperature extended regions and high-temperature compact regions, associated with magnetically open and closed structures in the stellar atmosphere, respectively. The signatures of UV lines from a Tau can be consistently understood via a model of upward-traveling Alfv6n waves in a gravitationally stratified atmosphere. These waves cause nonthermal broadening in UV lines due to unresolved wave motions and downward plasma motions in compact magnetic loops heated by resonant Alfven wave heating.

Carpenter, Kenneth G.↗

NASA NTRS2006

X-Windows PVT Widget Class

The X-Windows Process Validation Table (PVT) Widget Class ( Class is used here in the object-oriented-programming sense of the word) was devised to simplify the task of implementing network registration services for Information Sharing Protocol (ISP) graphical-user-interface (GUI) computer programs. Heretofore, ISP PVT programming tasks have required many method calls to identify, query, and interpret the connections and messages exchanged between a client and a PVT server. Normally, programmers have utilized direct access to UNIX socket libraries to implement the PVT protocol queries, necessitating the use of many lines of source code to perform frequent tasks. Now, the X-Windows PVT Widget Class encapsulates ISP client server network registration management tasks within the framework of an X Windows widget. Use of the widget framework enables an X Windows GUI program to interact with PVT services in an abstract way and in the same manner as that of other graphical widgets, making it easier to program PVT clients. Wrapping the PVT services inside the widget framework enables a programmer to treat a PVT server interface as though it were a GUI. Moreover, an alternate subclass could implement another service in a widget of the same type. This program was written by Matthew R. Barry of United Space Alliance for Johnson Space Center. For further information, contact the Johnson Technology Transfer Office at (281) 483-3809. MSC-23582 Shuttle Data Center File- Processing Tool in Java A Java-language computer program has been written to facilitate mining of data in files in the Shuttle Data Center (SDC) archives. This program can be executed on a variety of workstations or via Web-browser programs. This program is partly similar to prior C-language programs used for the same purpose, while differing from those programs in that it exploits the platform-neutrality of Java in implementing several features that are important for analysis of large sets of time-series data. The program supports regular expression queries of SDC archive files, reads the files, interleaves the time-stamped samples according to a chosen output, then transforms the results into that format. A user can choose among a variety of output file formats that are useful for diverse purposes, including plotting, Markov modeling, multivariate density estimation, and wavelet multiresolution analysis, as well as for playback of data in support of simulation and testing.

Barry, Matthew R.↗

NASA NTRS2006

Shuttle Data Center File-Processing Tool in Java

A Java-language computer program has been written to facilitate mining of data in files in the Shuttle Data Center (SDC) archives. This program can be executed on a variety of workstations or via Web-browser programs. This program is partly similar to prior C-language programs used for the same purpose, while differing from those programs in that it exploits the platform-neutrality of Java in implementing several features that are important for analysis of large sets of time-series data. The program supports regular expression queries of SDC archive files, reads the files, interleaves the time-stamped samples according to a chosen output, then transforms the results into that format. A user can choose among a variety of output file formats that are useful for diverse purposes, including plotting, Markov modeling, multivariate density estimation, and wavelet multiresolution analysis, as well as for playback of data in support of simulation and testing.

Barry, Matthew R.↗

NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗

NASA NTRS2012

Particle Filtering for Model-Based Anomaly Detection in Sensor Networks

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.

Solano, Wanda↗

NASA NTRS2013

Autonomous Aerobraking Development Software: Phase 2 Summary

NASA has used aerobraking at Mars and Venus to reduce the fuel required to deliver a spacecraft into a desired orbit compared to an all-propulsive solution. Although aerobraking reduces the propellant, it does so at the expense of mission duration, large staff, and DSN coverage. These factors make aerobraking a significant cost element in the mission design. By moving on-board the current ground-based tasks of ephemeris determination, atmospheric density estimation, and maneuver sizing and execution, a flight project would realize significant cost savings. The NASA Engineering and Safety Center (NESC) sponsored Phase 1 and 2 of the Autonomous Aerobraking Development Software (AADS) study, which demonstrated the initial feasibility of moving these current ground-based functions to the spacecraft. This paper highlights key state-of-the-art advancements made in the Phase 2 effort to verify that the AADS algorithms are accurate, robust and ready to be considered for application on future missions that utilize aerobraking. The advancements discussed herein include both model updates and simulation and benchmark testing. Rigorous testing using observed flight atmospheres, operational environments and statistical analysis characterized the AADS operability in a perturbed environment.

Cianciolo, Alicia D.↗