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At least 325 records · Page 18

Long-life assessment of graphite epoxy materials for Space Station Freedom pressure vessels

Graphite/epoxy composite overwrapped pressure vessels are being considered for use on Space Station Freedom because of their light weight and high efficiency. These composite pressure vessels weigh roughly one-third of comparable all-metal aluminum pressure vessels, and could result in a 15,000-lb weight saving for the propulsion and fluid management and distribution systems. These vessels must resist failures under sustained pressure loads for crew safety considerations and adequate protection of the space structure during their 30-yr life. Weibull statistical analysis techniques have been applied, and a model developed, for predicting long-term stress-rupture behavior based on published short-term test data on composite strands and pressure vessels. Graphite/epoxy materials are calculated to have a 99.99-percent probability of surviving stress rupture for 30 yr under a sustained load of 50 percent ultimate failure strength. Stress-rupture lifetimes are predicted to increase as the size of the pressure vessels increases in support of the viscoelastic load-transfer mechanism proposed for stress rupture of fiber/epoxy composite materials.

Thomas, Donald A.↗

Global ocean tide mapping using TOPEX/Poseidon altimetry

The investigation's main goals are to produce accurate tidal maps of the main diurnal, semidiurnal, and long-period tidal components in the world's deep oceans. This will be done by the application of statistical estimation techniques to long time series of altimeter data provided by the TOPEX/POSEIDON mission, with additional information provided by satellite tracking data. In the prelaunch phase, we will use in our simulations and preliminary work data supplied by previous oceanographic missions, such as Seasat and Geosat. These results will be of scientific interest in themselves. The investigation will also be concerned with the estimation of new values, and their uncertainties, for tidal currents and for the physical parameters appearing in the Laplace tidal equations, such as bottom friction coefficients and eddy viscosity coefficients. This will be done by incorporating the altimetry-derived charts of vertical tides as boundary conditions in the integration of those equations. The methodology of the tidal representation will include the use of appropriate series expansions such as ocean-basin normal modes and spherical harmonics. The results of the investigation will be space-determined tidal models of coverage and accuracy superior to that of the present numerical models of the ocean tides, with the concomitant benefits to oceanography and associated disciplinary fields.

Sanchez, Braulio V.↗

Analysis of Uranian radio emissions, Uranus Data Analysis Program (UDAP)

Progress under this grant has included identifying certain new radio emission components and determining the source location of both these and the two major Uranian radio emission (the SHF and bursty components) by a unique new statistical minimization technique. This new source location technique has subsequently also been applied at Neptune, with considerable success. New radio spectrograms have been prepared to clarify the behavior of such emissions, using both the usual 48-second, log-averaged data and the original 6-second PRA data, the latter showing a number of interesting new features. Also, a plasmasphere was discovered at Uranus, auroral plasma cavities were discovered at both Uranus and Neptune, and it was found that the currently-accepted rotation period for Uranus is in error by a small amount.

Calvert, W.↗

Statistical temperature profile retrievals in clear-air using passive 118-GHz O2 observations

The clean-air temperature profile accuracy yielded by a localized linear statistical retrieval operator applied to passive aircraft-based 118-GHz spectra is demonstrated. A comparison of the statistically and physically derived correlation coefficients of antenna temperature and kinetic temperature furnishes a physical justification of the statistical retrieval technique. The atmospheric temperature mean and covariance significantly depend on such geophysical parameters as latitude, longitude, local season, and time, as well as the prevailing meteorological state and orographic effects.

Gasiewski, A. J.↗

Forced unsteady deceleration of a turbulent boundary layer from a temporal perspective

The behavior of a turbulent boundary layer which has been subjected to a local ramp-like deceleration in the external velocity field, which leads to forced separation, has been studied experimentally. The data of this study are re-interpreted in light of more recent findings concerning the temporal nature of boundary layer turbulence in the presence of forced unsteady shear. In particular, the robustness of the near-wall turbulent motions to organized deformation is recognized. Their resilence during unsteady shearing action promotes continued efficient turbulent mixing and rapid redistribution of turbulent kinetic energy during forced transients. In aerodynamic problems, the rapid nature of the adjustment of the turbulence field to a new temporal boundary condition necessitates equally rapid remedial measures to be taken if means of control/prevention of forced unsteady separation are to be deployed to maximum effect. This requirement suggests exploration of the use of simple, real-time statistical forecasting techniques, based upon time-series analysis of easily-measurable features of the flow, to help assure timely deployment of mechanisms of boundary-layer control. This paper focuses upon the nature of turbulence in boundary layers undergoing forced deceleration which would lead to separation. A preliminary form of a forecasting model is presented and evaluated. Using observations of the previous two large eddies passing a detector, it forecasts the behavior of the future large eddy rather well.

Brereton, G. J.↗

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Sabol, Donald E., Jr.↗

Analytical Fuselage and Wing Weight Estimation of Transport Aircraft

A method of estimating the load-bearing fuselage weight and wing weight of transport aircraft based on fundamental structural principles has been developed. This method of weight estimation represents a compromise between the rapid assessment of component weight using empirical methods based on actual weights of existing aircraft, and detailed, but time-consuming, analysis using the finite element method. The method was applied to eight existing subsonic transports for validation and correlation. Integration of the resulting computer program, PDCYL, has been made into the weights-calculating module of the AirCraft SYNThesis (ACSYNT) computer program. ACSYNT has traditionally used only empirical weight estimation methods; PDCYL adds to ACSYNT a rapid, accurate means of assessing the fuselage and wing weights of unconventional aircraft. PDCYL also allows flexibility in the choice of structural concept, as well as a direct means of determining the impact of advanced materials on structural weight. Using statistical analysis techniques, relations between the load-bearing fuselage and wing weights calculated by PDCYL and corresponding actual weights were determined.

Chambers, Mark C.↗

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗

[Compton GRO Cycle 7]

The goals of this project were to use the improved location accuracy of combined BATSE/Ulysses-IPN gamma-ray burst (GRB) data to search for small-angle clustering within the burst population and to search for possible correlations between bursts and catalogs of known astrophysical objects. The research was completed in several phases due to the length of time needed to process the basic BATSE/Ulysses data and to develop the appropriate analysis algorithms. In the first phase, BATSE/Ulysses data were gathered from their respective sources and processed to yield, final BATSE burst catalog locations and final BATSE/Ulysses IPN timing annuli. The final data are published. In the next phase, traditional statistical analysis techniques were used to search a subset of the data for small-angle clustering and. correlations, and to produce upper limits. Next, the unique analysis techniques and software described in the proposal were developed and,applied to the final set of data (corresponding to the 4B catalog). The final search did not find any significant self-clustering or correlations with supernovae, AGN, or near by galaxy clusters. The investigation ruled-out earlier findings that indicated (with marginal significance) such results, and. provided stringent limits on the allowable fraction of bursts that are self-clustered and associated with selected known objects. An added benefit of this research came in 1998 when it was suggested that some gamma-ray bursts may be associated with supernova (SN) explosions. We responded rapidly and applied the tools of this investigation to study this possibility. Using combined BATSE/Ulysses data, we were able to completely rule out any association between bright bursts and known supernovae, thereby questioning the validity of any GRB/SN association. If a GRB/SN association exists, it must be only with a small fraction of weak bursts.

Kippen, R. Marc↗

Estimating Vegetation Parameters from Interferometric and Polarimetric Radar Using Physical Scattering Models

Radar data from vegetated land surfaces depend on many structural and compositional parameters describing the terrain. Because early, noninterferometric radar systems usually constituted an insufficient observation set from which to estimate parameters of the terrain, statistical regression techniques were used which incorporated some level of apriori knowledge or field measurements. With the advent of radar interferometry and polarimetric interferometry, potentially at multiple baselines, the observation set is now approaching that required to quantitatively estimate the parameters describing a vegetated land surface. Quantitative estimation entails formulating a physical scattering model relating the radar observations to the vegetation and surface parameters on which they depend. This paper describes the physics of candidate scattering models, and shows how the models determine the estimable parameter set. It also indicates the measurement accuracy of parameters such as vegetation height, height-to-base-of-live-crown, and surface topography with multibaseline polarimetric interferometry.

Treuhaft, Robert N.↗

Disentangling Structures in the Cluster of Galaxies Abell 133

A dynamical analysis of the structure of the cluster of galaxies Abell 133 will be presented using multi-wavelength data combined from multiple space and earth based observations. New and familiar statistical clustering techniques are used in combination in an attempt to gain a fully consistent picture of this interesting nearby cluster of galaxies. The type of analysis presented should be typical of cluster studies in the future, especially those to come from the surveys like the Sloan Digital Sky Survey and the 2DF.

Way, Michael J.↗

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗

An Artificial Intelligence Classification Tool and Its Application to Gamma-Ray Bursts

Despite being the most energetic phenomenon in the known universe, the astrophysics of gamma-ray bursts (GRBs) has still proven difficult to understand. It has only been within the past five years that the GRB distance scale has been firmly established, on the basis of a few dozen bursts with x-ray, optical, and radio afterglows. The afterglows indicate source redshifts of z=1 to z=5, total energy outputs of roughly 10(exp 52) ergs, and energy confined to the far x-ray to near gamma-ray regime of the electromagnetic spectrum. The multi-wavelength afterglow observations have thus far provided more insight on the nature of the GRB mechanism than the GRB observations; far more papers have been written about the few observed gamma-ray burst afterglows in the past few years than about the thousands of detected gamma-ray bursts. One reason the GRB central engine is still so poorly understood is that GRBs have complex, overlapping characteristics that do not appear to be produced by one homogeneous process. At least two subclasses have been found on the basis of duration, spectral hardness, and fluence (time integrated flux); Class 1 bursts are softer, longer, and brighter than Class 2 bursts (with two second durations indicating a rough division). A third GRB subclass, overlapping the other two, has been identified using statistical clustering techniques; Class 3 bursts are intermediate between Class 1 and Class 2 bursts in brightness and duration, but are softer than Class 1 bursts. We are developing a tool to aid scientists in the study of GRB properties. In the process of developing this tool, we are building a large gamma-ray burst classification database. We are also scientifically analyzing some GRB data as we develop the tool. Tool development thus proceeds in tandem with the dataset for which it is being designed. The tool invokes a modified KDD (Knowledge Discovery in Databases) process, which is described as follows.

Hakkila, Jon↗

Radiation-induced gene expression in the nematode Caenorhabditis elegans

We used the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation in a simple animal model emphasizing the unique effects of charged particle radiation. Here we demonstrate by RT-PCR differential display and whole genome microarray hybridization experiments that gamma rays, accelerated protons and iron ions at the same physical dose lead to unique transcription profiles. 599 of 17871 genes analyzed (3.4%) showed differential expression 3 hrs after exposure to 3 Gy of radiation. 193 were up-regulated, 406 were down-regulated and 90% were affected only by a single species of radiation. A novel statistical clustering technique identified the regulatory relationships between the radiation-modulated genes and showed that genes affected by each radiation species were associated with unique regulatory clusters. This suggests that independent homeostatic mechanisms are activated in response to radiation exposure as a function of track structure or ionization density.

Non-NASA Center↗

PIE: A Dynamic Failure-Based Technique

This paper presents a dynamic technique for statistically estimating three program characteristics that affect a program's computational behavior: (1) the probability that a particular section of a program is executed, (2) the probability that the particular section affects the data state, and (3) the probability that a data state produced by that section has an effect on program output. These three characteristics can be used to predict whether faults are likely to be uncovered by software testing. Index Terms: Software testing, data state, fault, failure, testability. 1 Introduction

Voas, Jeffrey M.↗

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

NASA Discipline Cardiopulmonary↗

Registration and Fusion of Multiple Source Remotely Sensed Image Data

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

LeMoigne, Jacqueline↗

What Do Our Users Want? Perspectives on Understanding and Meeting User Needs for Multi-Mission Data Services

The Sun-Earth Connection Active Archive (SECAA) project of NASA's Space Physics Data Facility operates a range of unique and heavily used multi-mission data services in support of the large-scale science objectives of the Great Observatory, including services such as CDAWeb, the CDAWeb Plus client, SSCWeb, OMNIweb and the CDF data format. In developing and operating these services, we have encountered and continue to struggle with a wide range of issues such as balancing scope and functionality with simplicity and ease of use, understanding the effectiveness of our choices and identifying areas most important for further improvement. In this paper, we will review our key services and then discuss some of our observations and new approaches to understanding and meeting user data service requirements. Some observations are obvious but may still have substantial implications; e.g. functionality without information content is of little user interest, which has led to our recent emphasis on development of web services interfaces, so the content and functionality we already serve is readily and fully available as a building block for new services. Some observations require careful design and tradeoffs; e.g. users will complain when they are offered interfaces with limited options but users are also easily intimidated and become lost when offered extensive options for customization. Some observations remain highly challenging; e.g. a comprehensive multi-mission, multi-source view of all data and services available easily produces a daunting list, but a more selective view can easily lead users to overlook available and relevant data. It is often difficult to obtain and meaningfully interpret measures of true productive usage and overall user satisfaction, even with a variety of techniques including statistics, citations, case studies, user feedback and advisory committees. Most of these issues will apply to and may even be more acute for distributed implementation architectures.

McGuire, Robert E.↗