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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.↗

NASA NTRS2013

An Archival Chandra and XMM-Newton Survey of Type 2 Quasars

In order to investigate obscuration in high-luminosity type 2 active galactic nuclei (AGNs), we analyzed Chandra and XMM-Newton archival observations for 71 type 2 quasars detected at 0.05 < z < 0.73, which were selected based on their [O III] lambda5007 emission lines. For 54 objects with good spectral fits, the observed hard X-ray luminosity ranges from 2 × 10(exp 41) to 5.3 × 10(exp 44) erg s(exp −1), with a median of 1.1 × 10(exp 43) erg s(exp −1). We find that the means of the column density and photon index of our sample are log N(sub H) = 22.9 cm(exp −2) and gamma = 1.87, respectively. From simulations using a more physically realistic model, we find that the absorbing column density estimates based on simple power-law models significantly underestimate the actual absorption in approximately half of the sources. Eleven sources show a prominent Fe K alpha emission line (EW>100 eV in the rest frame) and we detect this line in the other sources through a joint fit (spectral stacking). The correlation between the Fe K alpha and [O III] fluxes and the inverse correlation of the equivalent width of the Fe Kα line with the ratio of hard X-ray and [O III] fluxes is consistent with previous results for lower luminosity Seyfert 2 galaxies. We conclude that obscuration is the cause of the weak hard X-ray emission rather than intrinsically low X-ray luminosities. We find that about half of the population of optically selected type 2 quasars are likely to be Compton thick. We also find no evidence that the amount of X-ray obscuration depends on the AGN luminosity (over a range of more than three orders of magnitude in luminosity).

quasars: general↗

NASA NTRS2015

Computational and Experimental Unsteady Pressures for Alternate SLS Booster Nose Shapes

Delayed Detached Eddy Simulation (DDES) predictions of the unsteady transonic flow about a Space Launch System (SLS) configuration were made with the Fully UNstructured Three-Dimensional (FUN3D) flow solver. The computational predictions were validated against results from a 2.5% model tested in the NASA Ames 11-Foot Transonic Unitary Plan Facility. The peak C(sub p,rms) value was under-predicted for the baseline, Mach 0.9 case, but the general trends of high C(sub p,rms) levels behind the forward attach hardware, reducing as one moves away both streamwise and circumferentially, were captured. Frequency of the peak power in power spectral density estimates was consistently under-predicted. Five alternate booster nose shapes were assessed, and several were shown to reduce the surface pressure fluctuations, both as predicted by the computations and verified by the wind tunnel results.

Braukmann, Gregory J.↗

NASA NTRS2015

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗

NASA NTRS2017

Evidence of Significant Energy Input in the Late Phase of A Solar Flare from NuSTAR X-Ray Observations

We present observations of the occulted active region AR 12222 during the third Nuclear Spectroscopic Telescope ARray (NuSTAR) solar campaign on 2014 December 11, with concurrent Solar Dynamics Observatory (SDO)/ AIA and FOXSI-2 sounding rocket observations. The active region produced a medium-size solar flare 1 day before the observations, at approximately 18 UT on 2014 December 10, with the post-flare loops still visible at the time of NuSTAR observations. The time evolution of the source emission in the SDO/AIA 335 Å channel reveals the characteristics of an extreme-ultraviolet late-phase event, caused by the continuous formation of new post-flare loops that arch higher and higher in the solar corona. The spectral fitting of NuSTAR observations yields an isothermal source, with temperature 3.8-4.6 MK, emission measure (0.3-1.8) × 1046 cm−3, and density estimated at (2.5-6.0) × 108 cm−3. The observed AIA fluxes are consistent with the derived NuSTAR temperature range, favoring temperature values in the range of 4.0-4.3 MK. By examining the post-flare loops' cooling times and energy content, we estimate that at least 12 sets of post-flare loops were formed and subsequently cooled between the onset of the flare and NuSTAR observations, with their total thermal energy content an order of magnitude larger than the energy content at flare peak time. This indicates that the standard approach of using only the flare peak time to derive the total thermal energy content of a flare can lead to a large underestimation of its value.

gamma rays↗