Search NASA⌕ Search

SEARCH · Search NASA

Results for “local group”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Steepening of kinetic magnetosonic waves into shocklets - Simulations and consequences for planetary shocks and comets

The generation and the nonlinear evolution of oblique low-frequency electromagnetic (kinetic magnetosonic) waves which were observed upstream of planetary bow shocks and at the Giacobini-Zinner comet, and referred to as shocklets, were investigated using an electromagnetic hybrid code. The observations show that the waves, which have a sinusoidal form when their amplitude is small, become steepened and linearly polarized as they grow in amplitude. The results of simulations show the original small-amplitude elliptically polarized wave grows and steepens, so that its polarization changes and becomes somewhat linear. The steepening process is associated with the coherent generation of a broad spectrum of waves on the magnetosonic whistler branch, which propagate at various phase and group velocities. It is shown that the presence of shocklets upstream of a planetary bow shock can modify its local structure by changing the solar wind Mach number and temperature, or by colliding with the shock.

Omidi, N.↗
NASA NTRS1994

AutoClass: A Bayesian Approach to Classification

We describe a Bayesian approach to the untutored discovery of classes in a set of cases, sometimes called finite mixture separation or clustering. The main difference between clustering and our approach is that we search for the "best" set of class descriptions rather than grouping the cases themselves. We describe our classes in terms of a probability distribution or density function, and the locally maximal posterior probability valued function parameters. We rate our classifications with an approximate joint probability of the data and functional form, marginalizing over the parameters. Approximation is necessitated by the computational complexity of the joint probability. Thus, we marginalize w.r.t. local maxima in the parameter space. We discuss the rationale behind our approach to classification. We give the mathematical development for the basic mixture model and describe the approximations needed for computational tractability. We instantiate the basic model with the discrete Dirichlet distribution and multivariant Gaussian density likelihoods. Then we show some results for both constructed and actual data.

Stutz, John↗
NASA NTRS2000

Redistribution of annexin in gravistimulated pea plumules

We used immunocytochemistry to investigate the effects of gravistimulation on annexin localization in etiolated pea plumule shoots. In longitudinal sections, an asymmetric annexin immunostaining pattern was observed in a defined group of cells located just basipetal to apical meristems at the main shoot apex and at all of the axillary buds, an area classically referred to as the leaf gap. The pattern was observed using both protein-A-purified anti-annexin and affinity-purified anti-annexin antibodies for the immunostaining. A subset of the cells with the annexin staining also showed an unusually high level of periodic acid Schiff (PAS) staining in their cell walls. Prior to gravistimulation, the highest concentration of annexin was oriented toward the direction of gravity along the apical end of these immunostained cells. In contrast, both at 15 and 30 min after gravistimulation, the annexin immunostain became more evenly distributed all around the cell and more distinctly cell peripheral. The asymmetry along the lower wall of these cells was no longer evident. In accord with current models of annexin action, we interpret the results to indicate that annexin-mediated secretion in the leaf gap area is preferentially toward the apical meristem prior to gravistimulation, and that gravistimulation results in a redirection of this secretion. These data are to our knowledge the first to show a correlation between the vector of gravity and the distribution of annexins in the cells of flowering plants. c 2000 Editions scientifiques et medicales Elsevier SAS.

Non-NASA Center↗
NASA NTRS1999

Managing Personal and Group Collections of Information

The internet revolution has dramatically increased the amount of information available to users. Various tools such as search engines have been developed to help users find the information they need from this vast repository. Users often also need tools to help manipulate the growing amount of useful information they have discovered. Current tools available for this purpose are typically local components of web browsers designed to manage URL bookmarks. They provide limited functionalities to handle high information complexities. To tackle this have created DIAMS, an agent-based tool to help users or groups manage their information collections and share their collections with other. the main features of DIAMS are described here.

Wolfe, Shawn R.↗
NASA NTRS1985

Modulational development of nonlinear gravity-wave groups

Observations of the development of nonlinear surface gravity-wave groups are presented, and the amplitude and phase modulations are calculated using Hilbert-transform techniques. With increasing propagation distance and wave steepness, the phase modulation develops local phase reversals whose locations correspond to amplitude minima or nodes. The concomitant frequency modulation develops jumps or discontinuities. The observations are compared with recent similar results for wavetrains. The observations are modelled numerically using the cubic nonlinear Schroedinger equation. The motivation is twofold: to examine quantitatively the evolution of phase as well as amplitude modulation, and to test the inviscid predictions for the asymptotic behavior of groups versus long-time observations. Although dissipation rules out the recurrence, there is a long-time coherence of the groups. The phase modulation is found to distinguish between dispersive and soliton behavior.

Chereskin, T. K.↗
NASA NTRS1992

The local properties of ocean surface waves by the phase-time method

A new approach using phase information to view and study the properties of frequency modulation, wave group structures, and wave breaking is presented. The method is applied to ocean wave time series data and a new type of wave group (containing the large 'rogue' waves) is identified. The method also has the capability of broad applications in the analysis of time series data in general.

Huang, Norden E.↗
NASA NTRS1977

An operational, multistate, earth observation data management system

State, local, and regional agencies involved in natural resources management were investigated as potential users of satellite remotely sensed data. This group's needs are assessed and alternative data management systems serving some of those needs are outlined. It is concluded that an operational earth observation data management system will be of most use to these user agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

Eastwood, L. F., Jr.↗
NASA NTRS1987

Study of pre-storm environment by using rawinsonde and satellite observations

Rawinsonde and satellite remote sensing data were utilized to examine the prestorm environment and mechanisms for the initiation of four groups of severe storms. The storms in Altus, Oklahoma, Pampas, Texas, Bennett, Colorado, and Red River Valley, Oklahoma are described. The geographical distributions of the areas of high moisture concentration and variations of tropopause heights for the storm groups are analyzed. It is detected that in the area of a low-level high concentration of moisture, the local tropopause height is lowest at the time of the storm cloud formation and development, and the potential energy storage per unit areas for the overshootiong clouds penetrating above the tropopause is related to the intensity of the storms produced. Numerical cloud modeling was performed for the storms. The model data are compared with the satellite and rawinsonde observations, and it is noted that the data correlate well.

Hung, R. J.↗
NASA NTRS2006

Marshall Space Flight Center Propulsion Systems Department (PSD) KM Initiative

NASA Marshall Space Flight Center s Propulsion Systems Department (PSD) is four months into a fifteen month Knowledge Management (KM) initiative to support enhanced engineering decision making and analyses, faster resolution of anomalies (near-term) and effective, efficient knowledge infused engineering processes, reduced knowledge attrition, and reduced anomaly occurrences (long-term). The near-term objective of this initiative is developing a KM Pilot project, within the context of a 3-5 year KM strategy, to introduce and evaluate the use of KM within PSD. An internal NASA/MSFC PSD KM team was established early in project formulation to maintain a practitioner, user-centric focus throughout the conceptual development, planning and deployment of KM technologies and capabilities with in the PSD. The PSD internal team is supported by the University of Alabama's Aging Infrastructure Systems Center Of Excellence (AISCE), Intergraph Corporation, and The Knowledge Institute. The principle product of the initial four month effort has been strategic planning of PSD KM implementation by first determining the "as is" state of KM capabilities and developing, planning and documenting the roadmap to achieve the desired "to be" state. Activities undertaken to support the planning phase have included data gathering; cultural surveys, group work-sessions, interviews, documentation review, and independent research. Assessments and analyses have been performed including industry benchmarking, related local and Agency initiatives, specific tools and techniques used and strategies for leveraging existing resources, people and technology to achieve common KM goals. Key findings captured in the PSD KM Strategic Plan include the system vision, purpose, stakeholders, prioritized strategic objectives mapped to the top ten practitioner needs and analysis of current resource usage. Opportunities identified from research, analyses, cultural/KM surveys and practitioner interviews include: executive and senior management sponsorship, KM awareness, promotion and training, cultural change management, process improvement, leveraging existing resources and new innovative technologies to align with other NASA KM initiatives (convergence: the big picture). To enable results based incremental implementation and future growth of the KM initiative, key performance measures have been identified including stakeholder value, system utility, learning and growth (knowledge capture, sharing, reduced anomaly recurrence), cultural change, process improvement and return-on-investment. The next steps for the initial implementation spiral (focused on SSME Turbomachinery) have been identified, largely based on the organization and compilation of summary level engineering process models, data capture matrices, functional models and conceptual-level systems architecture. Key elements include detailed KM requirements definition, KM technology architecture assessment, evaluation and selection, deployable KM Pilot design, development, implementation and evaluation, and justifying full implementation (estimated Return-on-Investment). Features identified for the notional system architecture include the knowledge presentation layer (and its components), knowledge network layer (and its components), knowledge storage layer (and its components), User Interface and capabilities. This paper provides a snapshot of the progress to date, the near term planning for deploying the KM pilot project and a forward look at results based growth of KM capabilities with-in the MSFC PSD.

Caraccioli, Paul↗
NASA NTRS2006

Marshall Space Flight Center Propulsion Systems Department (PSD) Knowledge Management (KM) Initiative

NASA Marshall Space Flight Center's Propulsion Systems Department (PSD) is four months into a fifteen month Knowledge Management (KM) initiative to support enhanced engineering decision making and analyses, faster resolution of anomalies (near-term) and effective, efficient knowledge infused engineering processes, reduced knowledge attrition, and reduced anomaly occurrences (long-term). The near-term objective of this initiative is developing a KM Pilot project, within the context of a 3-5 year KM strategy, to introduce and evaluate the use of KM within PSD. An internal NASA/MSFC PSD KM team was established early in project formulation to maintain a practitioner, user-centric focus throughout the conceptual development, planning and deployment of KM technologies and capabilities within the PSD. The PSD internal team is supported by the University of Alabama's Aging Infrastructure Systems Center of Excellence (AISCE), lntergraph Corporation, and The Knowledge Institute. The principle product of the initial four month effort has been strategic planning of PSD KNI implementation by first determining the "as is" state of KM capabilities and developing, planning and documenting the roadmap to achieve the desired "to be" state. Activities undertaken to suppo~th e planning phase have included data gathering; cultural surveys, group work-sessions, interviews, documentation review, and independent research. Assessments and analyses have beon pedormed including industry benchmarking, related local and Agency initiatives, specific tools and techniques used and strategies for leveraging existing resources, people and technology to achieve common KM goals. Key findings captured in the PSD KM Strategic Plan include the system vision, purpose, stakeholders, prioritized strategic objectives mapped to the top ten practitioner needs and analysis of current resource usage. Opportunities identified from research, analyses, cultural1KM surveys and practitioner interviews include: executive and senior management sponsorship, KM awareness, promotion and training, cultural change management, process improvement, leveraging existing resources and new innovative technologies to align with other NASA KM initiatives (convergence: the big picture). To enable results based incremental implementation and future growth of the KM initiative, key performance measures have been identified including stakeholder value, system utility, learning and growth (knowledge capture, sharing, reduced anomaly recurrence), cultural change, process improvement and return-on-investment. The next steps for the initial implementation spiral (focused on SSME Turbomachinery) have been identified, largely based on the organization and compilation of summary level engineering process models, data capture matrices, functional models and conceptual-level svstems architecture. Key elements include detailed KM requirements definition, KM technology architecture assessment, - evaluation and selection, deployable KM Pilot design, development, implementation and evaluation, and justifying full implementation (estimated Return-on-Investment). Features identified for the notional system architecture include the knowledge presentation layer (and its components), knowledge network layer (and its components), knowledge storage layer (and its components), User Interface and capabilities. This paper provides a snapshot of the progress to date, the near term planning for deploying the KM pilot project and a forward look at results based growth of KM capabilities with-in the MSFC PSD.

Caraccioli, Paul↗
NASA NTRS2006

Effectively Transforming IMC Flight into VMC Flight: An SVS Case Study

A flight-test experiment was conducted using the NASA LaRC Cessna 206 aircraft. Four primary flight and navigation display concepts, including baseline and Synthetic Vision System (SVS) concepts, were evaluated in the local area of Roanoke Virginia Airport, flying visual and instrument approach procedures. A total of 19 pilots, from 3 pilot groups reflecting the diverse piloting skills of the GA population, served as evaluation pilots. Multi-variable Discriminant Analysis was applied to three carefully selected and markedly different operating conditions with conventional instrumentation to provide an extension of traditional analysis methods as well as provide an assessment of the effectiveness of SVS displays to effectively transform IMC flight into VMC flight.

Glaab, Louis J.↗
NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗
NASA NTRS2014

Complete Decoding and Reporting of Aviation Routine Weather Reports (METARs)

Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.

METAR Decoder/Parser↗
NASA NTRS1981

Ionospsheric observation of enhanced convection-initiated gravity waves during tornadic storms

Atmospheric gravity waves associated with tornadoes, with locally severe storms occuring with tornadoes, and with hurricanes were studied through the coupling between the ionosphere and the troposphere. Reverse group ray tracing computations of gravity waves observed by an ionospheric Doppler sounder array were analyzed. The results of ray tracing computations and comparisons between the computed location of the wave sources and with conventional meteorological data indicate that the computed sources of the waves were near the touchdown of the tornadoes, near the eye of the hurricanes, and directly on the squall line of the severe thunderstorms. The signals excited occurred one hour in advance of the tornadoes and three hours in advance of the hurricanes. Satellite photographs show convective overshooting turrets occurring at the same locations and times the gravity waves were being excited. It is suggested that gravity wave observations, conventional meteorological data, and satellite photographs be combined to develop a remote sensing technique for detecting severe storms.

Hung, R. J.↗
NASA NTRS2016

Exploring X-Ray Binary Populations in Compact Group Galaxies With Chandra

We obtain total galaxy X-ray luminosities, LX, originating from individually detected point sources in a sample of 47 galaxies in 15 compact groups of galaxies (CGs). For the great majority of our galaxies, we find that the detected point sources most likely are local to their associated galaxy, and are thus extragalactic X-ray binaries (XRBs) or nuclear active galactic nuclei (AGNs). For spiral and irregular galaxies, we find that, after accounting for AGNs and nuclear sources, most CG galaxies are either within the +/-1σ scatter of the Mineo et al. LX-star formation rate (SFR) correlation or have higher LX than predicted by this correlation for their SFR. We discuss how these "excesses" may be due to low metallicities and high interaction levels. For elliptical and S0 galaxies, after accounting for AGNs and nuclear sources, most CG galaxies are consistent with the Boroson et al. LX-stellar mass correlation for low-mass XRBs, with larger scatter, likely due to residual effects such as AGN activity or hot gas. Assuming non-nuclear sources are low- or high-mass XRBs, we use appropriate XRB luminosity functions to estimate the probability that stochastic effects can lead to such extreme LX values. We find that, although stochastic effects do not in general appear to be important, for some galaxies there is a significant probability that high LX values can be observed due to strong XRB variability.

X-rays: binaries↗
NASA NTRSDate not supplied

PRESOLAR GRAIN ABUNDANCE VARIATION IN THE MILLER RANGE 090019 CO3.1 CHONDRITE

Presolar grains condensed in the outflows of evolved red giant stars and the ejecta of supernovae (SNe) and novae. These grains have greatly anomalous isotopic compositions compared to solar system material, reflecting their stellar origins [1]. They have been identified in primitive meteorites, interplanetary dust particles (IDPs), Antarctic micrometeorites, and comet Wild 2 samples returned by NASA’s Stardust mission. Presolar silicates are one of the most abundant presolar phases and their concentrations extend up to 1.5% in primitive IDPs believed to derive from comets [2]. These grains are highly susceptible to alteration and destruction by secondary processing in the interstellar medium, nebula, and asteroid or comet parent body. Presolarsilicate abundance variations between primitive meteorites and chemical and mineralogical studies provide indications of the extent of secondary hydrothermal alteration [3, 4]. The abundance of presolar SiC grains is generally consistent among chondrites, but lower abundances in some meteorites have been attributed to thermal alteration [5, 6]. Presolar grain abundance variations attributed to localized alteration have also been reported within different regions of a chondrite [e.g., 7].Carbonaceous chondrites from the CO and CR groups have the highest abundances of presolar silicates among meteorites, attesting to their primitive nature. The CO3 chondrite Dominion Range (DOM) 08006 has the highest presolar O-rich grain abundance of ~260 ppm [8, 9]. MillerRange (MIL) 090019 is classified as a CO3.1 chondrite and has affinities to Acfer 094, DOM 08004/6 and Allan Hills (ALH) 77307. These chondrites have high presolar silicate abundances and contain high abundances of various types of refractory inclusions. We previously conducted detailed studies of CAIs in MIL 090019 [10, 11]. Here we evaluate its presolar grain inventory to assess the degree of parent body alteration and compare to other chondrites

A. N. Nguyen↗
NASA NTRSDate not supplied

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗
NASA NTRS1992

Localized sources of propagating acoustic waves in the solar photosphere

A time series of Doppler measurements of the solar photosphere with moderate spatial resolution is described which covers a portion of the solar disk surrounding a small sunspot group. At temporal frequencies above 5.5 mHz, the Doppler field probes the spatial and temporal distribution of regions that emit acoustic energy. In the frequency range between 5.5 and 7.5 mHz, inclusive, a small fraction of the surface area emits a disproportionate amount of acoustic energy. The regions with excess emission are characterized by a patchy structure at spatial scales of a few arcseconds and by association (but not exact co-location) with regions having substantial magnetic field strength. These observations bear on the conjecture that most of the acoustic energy driving solar p-modes is created in localized regions occupying a small fraction of the solar surface area.

Brown, Timothy M.↗