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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Analysis of defect structure in silicon. Characterization of SEMIX material. Silicon sheet growth development for the large area silicon sheet task of the low-cost solar array project

Statistically significant quantitative structural imperfection measurements were made on samples from ubiquitous crystalline process (UCP) Ingot 5848 - 13C. Important correlation was obtained between defect densities, cell efficiency, and diffusion length. Grain boundary substructure displayed a strong influence on the conversion efficiency of solar cells from Semix material. Quantitative microscopy measurements gave statistically significant information compared to other microanalytical techniques. A surface preparation technique to obtain proper contrast of structural defects suitable for quantimet quantitative image analyzer (QTM) analysis was perfected and is used routinely. The relationships between hole mobility and grain boundary density was determined. Mobility was measured using the van der Pauw technique, and grain boundary density was measured using quantitative microscopy technique. Mobility was found to decrease with increasing grain boundary density.

Natesh, R.↗
NASA NTRS1984

Applications of model structure determination to flight test data

Several statistical and information criteria need to be considered when selecting an adequate model. Incorrect stability and control derivates result from inadequate aerodynamic model structure. Stepwise regression is used to determine the structure for an adequate model. Flight data which covers a nonlinear aerodynamic model range may be analyzed as a single data set or partitioned into several distinct sets. Stepwise regression for model structure detemination and parameter estimation was successfully applied to three aircraft types (single engine general aviation, unaugmented modern jet fighter, jet transport).

Batterson, J. G.↗
NASA NTRS1990

Distributed simulation of network protocols

Simulations of high speed network protocols are very CPU intensive operations requiring very long run times. Very high speed network protocols (Gigabit/sec rates) require longer simulation runs in order to reach a steady state, while at the same time requiring additional CPU processing for each unit of time because of the data rates for the traffic being simulated. As protocol development proceeds and simulations provide insights into any problems associated with the protocol, the simulation model often must be changed to generate additional or finer statistical performance information. Iterating on this process is very time consuming due to the required run times for the simulation models. The results of the efforts to distribute a high speed ring network protocol, Carrier Sensed Multiple Access/Ring Network (CSMA/RN), are presented.

Paterra, Frank↗
NASA NTRS1993

Threshold effects on V/V(max) for gamma-ray bursts

The interpretation of the observed gamma-ray burst V/V(max) statistic in terms of spatial distributions is model-dependent. Detection of gamma-ray bursts requires the counting rate in one or more detectors to exceed a threshold C(lim) determined from a time-dependent background rate B(t). The sampling depth of the burst detector is thus time-dependent, and, if burst sources are nonuniform in space, the observed V/V(max) distribution will be affected by B(t). We demonstrate this effect with a simple geometric distribution of standard candles and argue that V/V(max) statistic without information on threshold variations is insufficient for rigorous data analysis. Peak count rates and threshold values must be given separately for all events in order to facilitate a meaningful comparison of observations with theoretical distribution models.

Hartmann, D. H.↗
NASA NTRS2001

Pluto and Triton: Interactions Between Volatiles and Dynamics

Volatiles moving across the surfaces of Pluto and Triton can give rise to interesting dynamical consequences. Conversely, measurement of dynamical states can help constrain the movement of volatiles and interior structure of both bodies. Polar wander may theoretically occur on both Triton and Pluto. Triton's obliquity is low, so that the equatorial regions receive more insolation than the poles. Hence there is a tendency for nitrogen ice to sublime at the equator and condense at the poles, creating polar caps. If the nitrogen supply is large enough, then these caps could move in approximately 10(exp 5) years the global equivalent of 200 m of ice to the poles. At this point the equatorial moment of inertia becomes larger than the moment of inertia measured about the rotation axis, so that Triton overbalances and becomes dynamically unstable. The satellite then undergoes polar wander, restoring stability when the new equator contains the excess matter. Hence the pole may be continually wandering. Neptune raises a permanent tidal bulge on Triton, so that the satellite's surface is elongated like a football, with the long axis pointing at Neptune. This is expected to be the axis about which the pole wanders. Volatile migration would resurface the satellite to some depth and wandering would disturb leading side/trailing side crater statistics. Additional information is contained in the original extended abstract.

Rubincam, D. P.↗
NASA NTRS2003

In-Flight Observations of Long-Term Single Event Effect(SEE)Performance on Orbview-2 and Xray Timing Explorer(XTE)Solid State Recorders (SSR)

This paper presents Single Event Effect (SEE) in-flight data on Solid State Recorders (SSR) that have been collected over a long period of time for two NASA spacecraft: Orbview-2 and XTE. SEE flight data on solid-state memories give an opportunity to study the behavior in space of SEE sensitive commercial devices. The actual Single Event Upset (SEU) rates can be compared with the calculated rates based on environment models and ground test data. The SEE mitigation schemes can also be evaluated in actual implementation. A significant amount of data has already been published concerning observed SEE effects on memories in space. However, most of the data presented cover either a short period of time or a small number of devices. The data presented here has been collected on a large number of devices during several years. This allows statistically significant information about the effect of space weather fluctuations on SEU rates, and the effectiveness of SEE countermeasures used to be analyzed. Only Orbview-2 data is presented in this summary. XTE data will be included in the final paper.

Poivey, Christian↗
NASA NTRS2004

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↗
NASA NTRS2004

A Statistical Approach to Characterizing the Reliability of Systems Utilizing HBT Devices

This paper presents a statistical approach to characterizing the reliability of systems with HBT devices. The proposed approach utilizes the statistical reliability information of the HBT individual devices, along with the analysis on the critical paths of the system, to provide more accurate and more comprehensive reliability information about the HBT systems compared to the conventional worst-case method.

hetero bipolar transistors (HBTs)↗
NASA NTRS2017

Development of the Space Debris Sensor (SDS)

The Space Debris Sensor (SDS) is a NASA experiment scheduled to fly aboard the International Space Station (ISS) starting in 2018. The SDS is the first flight demonstration of the Debris Resistive/Acoustic Grid Orbital NASA-Navy Sensor (DRAGONS) developed and matured at NASA Johnson Space Center's Orbital Debris Program Office. The DRAGONS concept combines several technologies to characterize the size, speed, direction, and density of small impacting objects. With a minimum two-year operational lifetime, SDS is anticipated to collect statistically significant information on orbital debris ranging from 50 microns to 500 microns in size. This paper describes the features of SDS and how data from the ISS mission may be used to update debris environment models. Results of hypervelocity impact testing during the development of SDS and the potential for improvement on future sensors at higher altitudes will be reviewed.

Hamilton, J.↗
NASA NTRS2017

Development of the Space Debris Sensor

The Space Debris Sensor (SDS) is a NASA experiment scheduled to fly aboard the International Space Station (ISS) starting in 2017. The SDS is the first flight demonstration of the Debris Resistive/Acoustic Grid Orbital NASA-Navy Sensor (DRAGONS) developed and matured by the NASA Orbital Debris Program Office. The DRAGONS concept combines several technologies to characterize the size, speed, direction, and density of small impacting objects. With a minimum two-year operational lifetime, SDS is anticipated to collect statistically significant information on orbital debris ranging from 50 micron to 500 micron in size. This paper describes the SDS features and how data from the ISS mission may be used to update debris environment models. Results of hypervelocity impact testing during the development of SDS and the potential for improvement on future sensors at higher altitudes will be reviewed.

Hamilton, J.↗
NASA NTRS2019

Further Characterization of Aerosols Sampled on the International Space Station

Spacecraft cabin air quality is of fundamental importance to crew health, with concerns encompassing both gaseous contaminants and airborne particles. Quantification of spacecraft indoor aerosols will increase our understanding of crew exposure and cabin cleanliness. Aerosols on the International Space Station (ISS) have been sampled and brought back to Earth for analysis to characterize the airborne particulate matter in the cabin. Microscopic analyses have been performed to determine morphology and particle size information, and Energy Dispersive X-ray Spectroscopy (EDS) provides information on the chemical elements present in the particles. With the use of IntelliSEM software for computer-controlled scanning electron microscopy (CCSEM), this data provides particle size distribution information and statistics on particle materials. Many of the particles collected were made up of multiple elements and had uncommon morphologies compared to typical indoor aerosols on Earth. These characteristics are thought to be from unique formation mechanisms in the microgravity environment. Several notable particle types are examined further in this work. Bromine-containing particles and cadmium-containing particles are discussed as they constitute a health hazard to crew members. Humans in indoor living and working spaces are typically the single largest particle emission source, and this was observed in the sampled aerosols in ISS as well.

Sampling↗
NASA NTRS2020

Data Science for Weather Impacts on Crop Yield

Private businesses in sectors, such as food, energy, and retail, as well as public sector and federal agencies are interested in the predictive understanding of weather impacts on crop yield, which is an important aspect of food security. Scientific literature has mainly examined how crop yield is impacted by growing season-averaged weather indices. Although a few studies did consider weather extremes in their analysis, their scope was either restricted to measuring their conditional relationship with yield or the extreme event types considered were limited. Selection of regression models, whether the more commonly used linear approaches or nonlinear methods, have not been appropriately justified in this context. Here, we develop data-driven methods to examine two inter-related hypotheses for improved scientific understanding and enhanced predictive modeling. The first hypothesis, that extreme weather indices have a statistically significant information content in them is found to be valid based on linear and nonlinear methods for pairwise dependence. The second hypothesis, examines the value addition of nonlinear regression methods, and suggests that linear approaches may not alone be adequate. The results of this study can inform scientific understanding, generation and relevance of indices and end-to-end risk assessment systems in the context of climate impacts on crop yield. An immediate application may be in the context of NASA Earth Exchange (NEX) which facilitates the generation and dissemination of impacts relevant weather data and indices using a multitude of satellite-derived data sets and model outputs.

Data mining, food security, weather impacts↗
NASA NTRS1997

A Categorization of Dynamic Analyzers

Program analysis techniques and tools are essential to the development process because of the support they provide in detecting errors and deficiencies at different phases of development. The types of information rendered through analysis includes the following: statistical measurements of code, type checks, dataflow analysis, consistency checks, test data,verification of code, and debugging information. Analyzers can be broken into two major categories: dynamic and static. Static analyzers examine programs with respect to syntax errors and structural properties., This includes gathering statistical information on program content, such as the number of lines of executable code, source lines. and cyclomatic complexity. In addition, static analyzers provide the ability to check for the consistency of programs with respect to variables. Dynamic analyzers in contrast are dependent on input and the execution of a program providing the ability to find errors that cannot be detected through the use of static analysis alone. Dynamic analysis provides information on the behavior of a program rather than on the syntax. Both types of analysis detect errors in a program, but dynamic analyzers accomplish this through run-time behavior. This paper focuses on the following broad classification of dynamic analyzers: 1) Metrics; 2) Models; and 3) Monitors. Metrics are those analyzers that provide measurement. The next category, models, captures those analyzers that present the state of the program to the user at specified points in time. The last category, monitors, checks specified code based on some criteria. The paper discusses each classification and the techniques that are included under them. In addition, the role of each technique in the software life cycle is discussed. Familiarization with the tools that measure, model and monitor programs provides a framework for understanding the program's dynamic behavior from different, perspectives through analysis of the input/output data.

Lujan, Michelle R.↗
NASA NTRS1972

Avoidance of Trailing Vortex Hazard by Airport Warning System

In an effort to improve airport traffic operation near jumbo jets, an airport trailing vortex warning system (ATVWS) was developed to predict trailing vortex turbulence. The ATVWS consists of a computer simulator which is compatible with a vortex sensor such as a laser Doppler velocimeter or an acoustic radar. A study of the traffic in one of the ten busiest airports, Atlanta Municipal Airport, provided information on traffic patterns of a statistical nature. With this information, airport traffic patterns can be studied and hazard statistics developed. Based on a careful study of this simulation model, requirements for the development and testing of an ATVWS can be accurately specified.

Rudland, R. S.↗
NASA NTRS1979

A study of possible sea state information in the sample and hold gate statistics for the GEOS-3 satellite altimeter

The statistical variations in the sample gate outputs of the GEOS-3 satellite altimeter were studied for possible sea state information. After examination of a large number of statistical characteristics of the altimeter waveforms, it was found that the best sea predictor for H-1/3 in the range of 0 to 3 meters was the 75th percentile of sample and hold gate number 11.

Wells, W. T.↗