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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Mass and spatial distribution of carbonaceous component in Comet Halley

Cometary grains containing large amounts of carbon and/or organic matter were discovered by in situ measurements of cometary dust composition during VEGA and GIOTTO fly-by missions. In accordance with the classification for the data of PUMA-1 and PUMA-2 mass-spectrometers on board the VEGA spacecraft, particles with a ratio of C to any rock-forming element (Mg, Si, Fe, Ca etc.) greater than 10, were categorized as CHON. There are 464 such particles in PUMA-1 data and 51 in PUMA-2 data. Application of cluster analysis to these grains revealed several distinct compositional classes, namely: (H,C,N,O), (H,C,N), (H,C), (H,C,O), (C,N), (C,O), (C,N,O), and (C). Similar classes were identified among particles analyzed by PIA. Also, about a third of all particles fell into groups (H) and (O) characterized by abundances of these elements beyond chemically reasonable limits.

Fomenkova, M.↗
NASA NTRS1993

Investigation of cloud properties and atmospheric stability with MODIS

The work accomplished with the MAS (MODIS Airborne Simulator) during the TOGA-COARE (Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment) from January through June 1993 included cloud investigations with longwave CO2 channels (out to 13.9 microns) that reconfigured spectral channels. The comparison data was used with HIRS (high resolution Infrared Radiation Sounder) data from FIRE (First ISSCP Regional Experiment), CEPEX, and SCAR (Smoke Clouds, Aerosol and Radiation) data for the development of a two layer cloud CO2 slicing algorithm and the development of multi-spectral cloud detection algorithms (specifically tri-spectral) for cloud identification. Regarding the latter, a clustering analysis was added to improve cloud identification within the scatter diagram of tri-spectral (8, 11, and 12 microns) brightness temperatures. Via the regressions of the 8 - 11 and the 11 - 12 micron brightness temperature differences versus precipitable water, the problem of clear sky identification in the scatter diagram was further addressed. Comparison of the tri-spectral technique and visible channel reflectance ratioing indicate the tri-spectral infrared method distinguishes cloud phase more consistently in mixed cloud scenes rather than single phase cloud scenes where visible ratioing performs best.

Menzel, Paul↗
NASA NTRS1993

On evaluating the accuracy of SAR sea-ice classification using multifrequency polarimetric AIRSAR data

We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.

Drinkwater, Mark R.↗
NASA NTRS1993

An information model for use in software management estimation and prediction

This paper describes the use of cluster analysis for determining the information model within collected software engineering development data at the NASA/GSFC Software Engineering Laboratory. We describe the Software Management Environment tool that allows managers to predict development attributes during early phases of a software project and the modifications we propose to allow it to develop dynamic models for better predictions of these attributes.

Li, Ningda R.↗
NASA NTRS1994

Modeling ozone episodes in the Baltimore-Washington region

Surface ozone (O3) concentrations in excess of the National Ambient Air Quality Standard (NAAQS) continue to occur in metropolitan areas in the United States despite efforts to control emissions of O3 precursors. Future O3 control strategies will be based on results from modeling efforts that have just begun in many areas. Two initial questions that arise are model sensitivity to domain-specific conditions and the selection of episodes for model evaluation and control strategy development. For the Baltimore-Washington region (B-W), the presence of the Chesapeake Bay introduces a number of issues relevant to model sensitivity. In this paper, the specific questions of the determination of model volume (mixing height) for the Urban Airshed Model (UAM) is discussed and various alternative methods compared. For the latter question, several analytic approaches, Cluster Analysis and classification and Regression Tree (CART) analysis are undertaken to determine meteorological conditions associated with severe O3 events in the B-W domain.

Ryan, William F.↗
NASA NTRS1995

A study of various methods for calculating locations of lightning events

This article reports on the results of numerical experiments on finding the location of lightning events using different numerical methods. The methods include linear least squares, nonlinear least squares, statistical estimations, cluster analysis and angular filters and combinations of such techniques. The experiments involved investigations of methods for excluding fake solutions which are solutions that appear to be reasonable but are in fact several kilometers distant from the actual location. Some of the conclusions derived from the study are that bad data produces fakes, that no fool-proof method of excluding fakes was found, that a short base-line interferometer under development at Kennedy Space Center to measure the direction cosines of an event shows promise as a filter for excluding fakes. The experiments generated a number of open questions, some of which are discussed at the end of the report.

Cannon, John R.↗
NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗
NASA NTRS1994

Carbonaceous Components in the Comet Halley Dust

Cometary grains containing large amounts of carbon and/or organic matter (CHON) were discovered by in situ measurements of comet Halley dust composition during VEGA and GIOTTO flyby missions. In this paper, we report the classification of these cometary, grains by means of cluster analysis, discuss the resulting compositional groups, and compare them with substances observed or hypothesized in meteorites, interplanetary dust particles, and the interstellar medium. Grains dominated by carbon and/or organic matter (CHON grains) represent approx. 22% of the total population of measured cometary dust particles. They, usually contain a minor abundance of rock-forming elements as well. Grains having organic material are relatively more abundant in the vicinity of the nucleus than in the outer regions of the coma, which suggests decomposition of the organics in the coma environment. The majority of comet Halley organic particles are multicomponent mixtures of carbon phases and organic compounds. Possibly, the cometary CHON grains may be related to kerogen material of an interstellar origin in carbonaceous meteorites. Pure carbon grains, hydrocarbons and polymers of cyanopolyynes, and multi-carbon monoxides are present in cometary dust as compositionally simple and distinctive components among a variety of others. There is no clear evidence of significant presence of pure formaldehyde or HCN polymers in Halley dust particles. The diversity of types of cometary organic compounds is consistent with the inter-stellar dust model of comets and probably reflects differences in composition of precursor dust. Preservation of this heterogeneity among submicron particles suggest the gentle formation of cometary, nucleus by aggregation of interstellar dust in the protosolar nebula without complete mixing or chemical homogenization at the submicron level.

Fomenkova, M. N.↗
NASA NTRS1999

An Intercomparison of Ground, Airborne, and Space Instrumentation Definitions of the Lightning Element

For the past century, scientists have made quantitative measurements of lightning discharges. In the process, they refined the definition of a lightning unit, or basic quantum of lightning, in order to base it on observable parameters. In this paper, we will use cluster analysis to derive a basic spatial and temporal definition or scale length for the unit of lightning. We will use data from three different systems that detected pulses from the same storm complex over Central Oklahoma during June, 1998. Since the different instruments detect lightning in different ways with different resolutions, there may not be a single definition of the unit of lightning that can be applied to all three systems. However, common components can be found since all instrumentation are detecting aspects of the same phenomenon.

Mach, Douglas↗
NASA NTRS2000

Satellite Data Sets in the Polar Regions

We have generated about two decades of consistently derived geophysical parameters in the polar regions. The key parameters are sea ice concentration, surface temperature, albedo, and cloud cover statistics. Sea ice concentrations were derived from the Scanning Multichannel Microwave Radiometer (SMMR) data and the Special Scanning Cl Microwave Imager (SSM/I) data from several platforms using the enhanced Bootstrap Algorithm for the period 1978 through 1999. The new algorithm reduces the errors associated with spatial and temporal variations in the emissivity and surface temperatures of sea ice. Also, bad data at ocean/land interfaces are identified and deleted in an unsupervised manner. Surface ice temperature, albedo and cloud cover statistics are derived simultaneously from the Advanced Very High Resolution Radiometer (AVHRR) data from 1981 through 1999 and mapped at a higher resolution but the same format as the ice concentration data. The technique makes use these co-registered ice concentration maps to enable cloud masking to be done separately for open ocean, sea ice and land areas. The effect of inversion is minimized by taking into consideration the expected changes in the effect of inversion with altitude, especially in the Antarctic. A technique for ice type regional classification has also been developed using multichannel cluster analysis and a neural network. This provide a means to identify large areas of thin ice, first year ice, and older ice types. The data sets have been shown to be coherent with each other and provide a powerful tool for in depth studies of the currently changing Arctic and Antarctic environment.

Comiso, Josefino C.↗
NASA NTRS2002

Functional Groups Based on Leaf Physiology: Are they Spatially and Temporally Robust?

The functional grouping hypothesis, which suggests that complexity in function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species in fire maintained FL scrub function in terms of carbon, water and nitrogen dynamics. The suite of physiologic parameters measured to determine function included both instantaneous gas exchange measurements obtained from photosynthetic light response curves and integrated measures of function. Using cluster analysis, five distinct physiologically-based functional groups were identified. Using non-parametric multivariate analyses, it was determined that these five groupings were not altered by plot differences or by the three different management regimes; prescribed burn, mechanically treated and burn, and fire-suppressed. The physiological groupings also remained robust between the two years 1999 and 2000. In order for these groupings to be of use for scaling ecosystem processes, there needs to be an easy-to-measure morphological indicator of function. Life form classifications were able to depict the physiological groupings more adequately than either specific leaf area or leaf thickness. THe ability of life forms to depict the groupings was improved by separating the parasitic Ximenia americana from the shrub category.

Foster, Tammy E.↗
NASA NTRS2003

Objective Classification of Radar Profile Types, and Their Relationship to Lightning Occurrence

A cluster analysis technique is used to identify 16 "archetypal" vertical radar profile types from a large, globally representative sample of profiles from the TRMM Precipitation Radar. These include nine convective types (7 of these deep convective) and seven stratiform types (5 of these clearly glaciated). Radar profile classification provides an alternative to conventional deep convective storm metrics, such as 30 dBZ echo height, maximum reflectivity or VIL. As expected, the global frequency of occurrence of deep convective profile types matches satellite-observed total lightning production, including to very small scall local features. Each location's "mix" of profile types provides an objective description of the local convective spectrum, and in turn, is a first step in objectively classifying convective regimes. These classifiers are tested as inputs to a neural network which attempts to predict lightning occurrence based on radar-only storm observations, and performance is compared with networks using traditional radar metrics as inputs.

Boccippio, Dennis↗
NASA NTRS2004

The Tropical Convective Spectrum: Archetypal Vertical Structures - 1

A taxonomy of tropical convective vertical structures is constructed through cluster analysis of three years of Tropical Rainfall Measuring Mission [TRMM] Precipitation Radar [PR] vertical profiles, their surface rainfall and associated radar-based classifiers (convective/stratiform and bright band existence). archetypal profile types are identified. These include nine convective types, divided into warm, "just cold", midlevel, deep and deep/wet-growth categories, seven stratiform types, divided into warm, "just cold", midlevel and deep categories, three "mixed" types (deep profiles with low reflectivity aloft), and six fragment types (non-precipitating anvils and sheared deep convective profiles). The taxonomy allows for description of any storm or local Convective spectrum by the nine primary convective and stratiform types, a significant reduction over full three-dimensional radar data which nonetheless retains vertical structure information. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types is presented, demonstrating primary rainfall contribution by midlevel glaciated convection and similar depth decaying/stratiform stages. Close correspondence is found between deep convective profile frequency and annualized lightning production. Passive microwave and lightning properties associated with the profiles are reported, and cases presented illustrating known nonuniqueness problems with 85 and 37 GHz brightness temperature pairs (the same pairs corresponding to both convective and stratiform profiles), and how supplementary lightning information might be used to mitigate these problems.

Boccippio, Dennis J.↗
NASA NTRS2004

Tropospheric Ozone Climatology over Irene, South Africa, From 1990-1994 and 1998-2002

This paper describes ozone profiles from sonde data during the period of NASA s TRACE-A and the more recent SHADOZ (Southern Hemisphere Additional Ozonesondes) period. The data were taken by the South African Weather Service at the Irene (25 deg.54 min S; 28 deg. 13 min. E) station near Pretoria, South Africa, an area that is a unique mixture of local industry, heavy biofuels use and importation of biomass burning ozone from neighboring countries to the north. The main findings are: (1) With its geographical position at the edge of the subtropical transition zone, mid- latitude dynamical influences are evident at Irene, predominantly in winter when upper tropospheric ozone is enhanced as a result of stratospheric-tropospheric exchange. (2) There has been an increase in the near-surface ozone amount between the early 1990s and a decade later, presumably due to an influx of rural population toward the Johannesburg-Pretoria area, as well as with industrial growth and development. (3) Most significant for developing approaches for satellite ozone profile climatologies, cluster analysis has enabled the delineation of a background and "most polluted" profile. Enhancements of at least 30% occur throughout the troposphere in spring and in certain layers increases of 100 % are observed.

Diab, R. D.↗
NASA NTRS1998

A comparative bear model for immobility-induced osteopenia

The National Institutes of Health (NIH) and the National Aeronautics and Space Administration (NASA) are seeking solutions to the human problem of osteopenia, or immobility-induced bone loss. Bears, during winter dormancy, appear uniquely exempted from the debilitating effects of immobility osteopenia. NIH and ESA, Inc. are creating a large database of metabolic information on human ambulatory and bedrest plasma samples for comparison with metabolic data obtained from bear plasma samples collected in different seasons. The database generated from NASA's HR113 human bedrest study showed a clear difference between plasma samples of ambulatory and immobile subjects through cluster analysis using compounds determined by high performance liquid chromatography with coulometric electrochemical array detection (HPLC-EC). We collected plasma samples from black bears (Ursus americanus) across 4 seasons and from 3 areas and subjected them to similar analysis, with particular attention to compounds that changed significantly in the NASA human study. We found seasonal differences in 28 known compounds and 33 unknown compounds. A final database contained 40 known and 120 unknown peaks that were reliably assayed in all bear and human samples; these were the primary data set for interspecies comparison. Six unidentified compounds changed significantly but differentially in wintering bears and immobile humans. The data are discussed in light of current theories regarding dormancy, starvation, and anabolic metabolism. Work is in progress by ESA Laboratories on a larger database to confirm these findings prior to a chemical isolation and identification effort. This research could lead to new pharmaceuticals or dietary interventions for the treatment of immobility osteopenia.

NASA Discipline Musculoskeletal↗
NASA NTRS2005

Lightning Contribution to Improvement of Passive Microwave Vertical Structure and Rainfall Estimation

Joint observations from the TRMM mission are used to examine the contribution which lightning observations can make towards estimation of vertical structure and rainfall from passive microwave data. Passive microwave (TMI) observations are binned into distinct vertical structure categories based on cluster analysis of radar (PR) vertical profiles and convective/stratiform (C/S) classifiers. TMI rain estimates are high-biased relative to radar for stratiform and mixed convective/stratiform vertical structures and low-biased relative to radar for convective structures. Significant ambiguity exists in the TMI brightness temperature space between midlevel stratiform and convective profile types which are primary contributors to tropical rainfall. The ambiguity is worst for convective profile types with radar echo tops within and just above the mixed-phase region. The ability of TMI data (including all low and high frequency polarized brightness temperatures; 19V, 19H, 21V, 37V, 37H, 85V, 85H) to predict vertical structure is assessed. The incremental benefit of including TMI convective/stratiform (C/S) classifiers (both 85 GHz polarization and 19, 37 and 85 GHz texture-based) and LZS lightning observations is then considered. The use of all parameters (brightness temperatures, TMI C/S classifiers, lightning data, predicted vertical structure) to reduce TMI/PR rainfall estimate scatter is demonstrated. For both vertical structure and rainfall estimation, inclusion of C/S classifiers and lightning observations provide statistical skill improvements but do not completely alleviate critical midlevel profile C/S ambiguity and related rain estimate errors.

Boccippio, Dennis↗
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
NASA NTRS2007

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Liu, Yi↗