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At least 271 records · Page 15

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NASA NTRS2008

Efficient Kriging via Fast Matrix-Vector Products

Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrixvector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.

Memarsadeghi, Nargess↗

NASA NTRS2008

The Wide-Field Imaging Interferometry Testbed (WIIT): Recent Progress and Results

Continued research with the Wide-Field Imaging Interferometry Testbed (WIIT) has achieved several important milestones. We have moved WIIT into the Advanced Interferometry and Metrology (AIM) Laboratory at Goddard, and have characterized the testbed in this well-controlled environment. The system is now completely automated and we are in the process of acquiring large data sets for analysis. In this paper, we discuss these new developments and outline our future research directions. The WIIT testbed, combined with new data analysis techniques and algorithms, provides a demonstration of the technique of wide-field interferometric imaging, a powerful tool for future space-borne interferometers.

Rinehart, Stephen A.↗

NASA NTRS2008

Parametric-Studies and Data-Plotting Modules for the SOAP

"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.

Source record↗

NASA NTRS2007

A Fast Implementation of the Isodata Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to IsoDATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Memarsadeghi, Nargess↗

NASA NTRS2009

Characterizing Space Environments with Long-Term Space Plasma Archive Resources

A significant scientific benefit of establishing and maintaining long-term space plasma data archives is the ready access the archives afford to resources required for characterizing spacecraft design environments. Space systems must be capable of operating in the mean environments driven by climatology as well as the extremes that occur during individual space weather events. Long- term time series are necessary to obtain quantitative information on environment variability and extremes that characterize the mean and worst case environments that may be encountered during a mission. In addition, analysis of large data sets are important to scientific studies of flux limiting processes that provide a basis for establishing upper limits to environment specifications used in radiation or charging analyses. We present applications using data from existing archives and highlight their contributions to space environment models developed at Marshall Space Flight Center including the Chandra Radiation Model, ionospheric plasma variability models, and plasma models of the L2 space environment.

Minow, Joseph I.↗

NASA NTRS2010

A Case Study: Using Delmia at Kennedy Space Center to Support NASA's Constellation Program

The presentation examines the use of Delmia (Digital Enterprise Lean Manufacturing Interactive Application) for digital simulation in NASA's Constellation Program. Topics include an overview of the Kennedy Space Center (KSC) Design Visualization Group tasks, NASA's Constellation Program, Ares 1 ground processing preliminary design review, and challenges and how Delmia is used at KSC, Challenges include dealing with large data sets, creating and maintaining KSC's infrastructure, gathering customer requirements and meeting objectives, creating life-like simulations, and providing quick turn-around on varied products,

Kickbusch, Tracey↗

NASA NTRS2004

GPS FOM Chimney Analysis using Generalized Extreme Value Distribution

Many a time an objective of a statistical analysis is to estimate a limit value like 3-sigma 95% confidence upper limit from a data sample. The generalized Extreme Value Distribution method can be profitably employed in many situations for such an estimate. . .. It is well known that according to the Central Limit theorem the mean value of a large data set is normally distributed irrespective of the distribution of the data from which the mean value is derived. In a somewhat similar fashion it is observed that many times the extreme value of a data set has a distribution that can be formulated with a Generalized Distribution. In space shuttle entry with 3-string GPS navigation the Figure Of Merit (FOM) value gives a measure of GPS navigated state accuracy. A GPS navigated state with FOM of 6 or higher is deemed unacceptable and is said to form a FOM 6 or higher chimney. A FOM chimney is a period of time during which the FOM value stays higher than 5. A longer period of FOM of value 6 or higher causes navigated state to accumulate more error for a lack of state update. For an acceptable landing it is imperative that the state error remains low and hence at low altitude during entry GPS data of FOM greater than 5 must not last more than 138 seconds. I To test the GPS performAnce many entry test cases were simulated at the Avionics Development Laboratory. Only high value FoM chimneys are consequential. The extreme value statistical technique is applied to analyze high value FOM chimneys. The Maximum likelihood method is used to determine parameters that characterize the GEV distribution, and then the limit value statistics are estimated.

Ott, Rick↗

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 NTRS2011

Tool for Rapid Analysis of Monte Carlo Simulations

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Restrepo, Carolina↗

NASA NTRS2012

Automated and Manual Rocket Crater Measurement Software

An update has been performed to software designed to do very rapid automated measurements of craters created in sandy substrates by rocket exhaust on liftoff. The previous software was optimized for pristine lab geometry and lighting conditions. This software has been enhanced to include a section for manual measurements of crater parameters; namely, crater depth, crater full width at half max, and estimated crater volume. The tools provide a very rapid method to measure these manual parameters to ease the burden of analyzing large data sets. This software allows for rapid quantization of the rocket crater parameters where automated methods may not work. The progress of spreadsheet data is continuously saved so that data is never lost, and data can be copied to clipboards and pasted to other software for analysis. The volume estimation of a crater is based on the central max depth axis line, and the polygonal shape of the crater is integrated around that axis.

Metzger, Philip↗

NASA NTRS2011

Provenance Challenges for Earth Science Dataset Publication

Modern science is increasingly dependent on computational analysis of very large data sets. Organizing, referencing, publishing those data has become a complex problem. Published research that depends on such data often fails to cite the data in sufficient detail to allow an independent scientist to reproduce the original experiments and analyses. This paper explores some of the challenges related to data identification, equivalence and reproducibility in the domain of data intensive scientific processing. It will use the example of Earth Science satellite data, but the challenges also apply to other domains.

Tilmes, Curt↗

NASA NTRS2012

Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis

MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.

Duffy, Daniel Q.↗

NASA NTRS2012

Space Shuttle Orbiter Digital Outer Mold Line Scanning

The Space Shuttle Orbiters Discovery and Endeavor have been digitally scanned to produce post-flight configuration outer mold line surfaces. Very detailed scans of the windward side of these vehicles provide resolution of the detailed tile step and gap geometry, as well as the reinforced carbon carbon nose cap and leading edges. Lower resolution scans of the upper surface provide definition of the crew cabin windows, wing upper surfaces, payload bay doors, orbital maneuvering system pods and the vertical tail. The process for acquisition of these digital scans as well as post-processing of the very large data set will be described.

Campbell, Charles H.↗

NASA NTRS2013

Tool for Rapid Analysis of Monte Carlo Simulations

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

Restrepo, Carolina↗

NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗

NASA NTRS2012

Improving the Automatic Inversion of Digital Alouette/ISIS Ionogram Reflection Traces into Topside Electron Density Profiles

The topside sounders of the International Satellites for Ionospheric Studies (ISIS) program were designed as analog systems. The resulting ionograms were displayed on 35 mm film for analysis by visual inspection. Each of these satellites, launched between 1962 and 1971, produced data for 10 to 20 years. A number of the original telemetry tapes from this large data set have been converted directly into digital records. Software, known as the Topside Ionogram Scalar With True-Height (TOPIST) algorithm, has been produced and used for the automatic inversion of the ionogram reflection traces on more than 100,000 ISIS-2 digital topside ionograms into topside vertical electron density profiles Ne(h). Here we present some topside ionospheric solar cycle variations deduced from the TOPIST database to illustrate the scientific benefit of improving and expanding the topside ionospheric Ne(h) database. The profile improvements will be based on improvements in the TOPIST software motivated by direct comparisons between TOPIST profiles and profiles produced by manual scaling in the early days of the ISIS program. The database expansion will be based on new software designed to overcome limitations in the original digital topside ionogram database caused by difficulties encountered during the analog-to-digital conversion process in the detection of the ionogram frame sync pulse and/or the frequency markers. This improved and expanded TOPIST topside Ne(h) database will greatly enhance investigations into both short- and long-term ionospheric changes, e.g., the observed topside ionospheric responses to magnetic storms, induced by interplanetary magnetic clouds, and solar cycle variations, respectively.

Benson, Robert F.↗

NASA NTRS2013

Shape-induced Gravitational Sorting of Saharan Dust During Transatlantic Voyage: Evidence from CALIOP Lidar Depolarization Measurements

Motivated by the physical picture of shape-dependent air resistance and, consequently, shape-induced differential sedimentation of dust particles, we searched for and found evidence of dust particle asphericity affecting the evolution and distribution of dust-scattered light depolarization ratio (delta). Specifically, we examined a large data set of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of Saharan dust from June to August 2007. Observing along a typical transatlantic dust track, we find that (1) median delta is uniformly distributed between 2 and 5 km altitudes as the elevated dust leaves the west coast of Africa, thereby indicating uniformly random mixing of particle shapes with height; (2) vertical homogeneity of median delta breaks down during the westward transport: between 2 and 5 km delta increases with altitude and this increase becomes more pronounced with westward progress; (3) delta tends to increase at higher altitude (greater than 4 km) and decrease at lower altitude (less than 4 km) during the westward transport. All these features are captured qualitatively by a minimal model (two shapes only), suggesting that shape-induced differential settling and consequent sorting indeed contribute significantly to the observed temporal evolution and vertical stratification of dust properties. By implicating particle shape as a likely cause of gravitational sorting, these results will affect the estimates of radiative transfer through Saharan dust layers.

CALIPSO↗

NASA NTRS2015

Kinematic and Microphysical Control of Lightning Flash Rate over Northern Alabama

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to examine the relationship between deep convection and the production of nitrogen oxides (NO (sub x)) via lightning (LNO (sub x)). A critical step in estimating LNO (sub x) production in a cloud-resolving model (CRM) without explicit lightning is to estimate the flash rate from available model parameters that are statistically and physically correlated. As such, the objective of this study is to develop, improve and evaluate lightning flash rate parameterizations in a variety of meteorological environments and storm types using radar and lightning mapping array (LMA) observations taken over Northern Alabama from 2005-2012, including during DC3. UAH's Advanced Radar for Meteorological and Operational Research (ARMOR) and the Weather Surveillance Radar - 1988 Doppler (WSR 88D) located at Hytop (KHTX) comprises the dual-Doppler and polarimetric radar network, which has been in operation since 2004. The northern Alabama LMA (NA LMA) in conjunction with Vaisala's National Lightning Detection Network (NLDN) allow for a detailed depiction of total lightning during this period. This study will integrate ARMOR-KHTX dual Doppler/polarimetric radar and NA LMA lightning observations from past and ongoing studies, including the more recent DC3 results, over northern Alabama to form a large data set of 15-20 case days and over 20 individual storms, including both ordinary multicell and supercell convection. Several flash rate parameterizations will be developed and tested, including those based on 1) graupel/small hail volume; 2) graupel/small hail mass, and 3) convective updraft volume. Sensitivity of the flash rate parameterizations to storm intensity, storm morphology and environmental conditions will be explored.

Carey, Lawrence D.↗