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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Full Life-Cycle Defect Management Assessment: Initial Inspection Data Collection Results and Research Questions for Further Study

It is often the case in software projects that when schedule and budget resources are limited, the Verification and Validation (V&V) activities suffer. Fewer V&V activities can be afforded and moreover, short-term challenges can result in V&V activities being scaled back or dropped altogether. As a result, too often the default solution is to save activities for improving software quality until too late in the life-cycle, relying on late-term code inspections followed by thorough testing activities to reduce defect counts to acceptable levels. As many project managers realize, however, this is a resource-intensive way of achieving the required quality for software. The Full Life-cycle Defect Management Assessment Initiative, funded by NASA s Office of Safety and Mission Assurance under the Software Assurance Research Program, aims to address these problems by: Improving the effectiveness of early life-cycle V&V activities to make their benefits more attractive to team leads. Specifically, we focus on software inspection, a proven method that can be applied to any software work product, long before executable code has been developed; Better communicating this effectiveness to software development teams, along with suggestions for parameters to improve in the future to increase effectiveness; Analyzing the impact of early life-cycle V&V on the effectiveness and cost required for late life-cycle V&V activities, such as testing, in order to make the tradeoffs more apparent. This white paper reports on an initial milestone in this work, the development of a preliminary model of inspection effectiveness across multiple NASA Centers. This model contributes toward reaching our project goals by: Allowing an examination of inspection parameters, across different types of projects and different work products, for an analysis of factors that impact defect detection effectiveness. Allowing a comparison of this NASA-specific model to existing recommendations in the literature regarding how to plan effective inspections. Forming a baseline model which can be extended to incorporate factors describing: the numbers and types of defects that are missed by inspections; how such defects flow downstream through software development phases; how effectively they can be caught by testing activities in the late stages of development. The model has been implemented in a prototype web-enabled decision-support tool which allows developers to enter their inspection data and receive feedback based on a comparison against the model. The tool also allows users to access reusable materials (such as checklists) from projects included in the baseline. Both the tool itself and the model underlying it will continue to be extended throughout the remainder of this initiative. As results of analyzing inspection effectiveness for defect containment are determined, they can be shared via the tool and also via updates to existing training courses on metrics and software inspections. Moreover, the tool will help satisfy key CMMI requirements for the NASA Centers, as it will enable NASA to take a global view across peer review results for various types of projects to identify systemic problems. This analysis can result in continuous improvements to the approach to verification.

Shull, Forrest↗
DOE OSTI2020

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2000

BOREAS AFM-07 SRC Surface Meteorological Data

The Saskatchewan Research Council (SRC) collected surface meteorological and radiation data from December 1993 until December 1996. The data set comprises Suite A (meteorological and energy balance measurements) and Suite B (diffuse solar and longwave measurements) components. Suite A measurements were taken at each of ten sites, and Suite B measurements were made at five of the Suite A sites. The data cover an approximate area of 500 km (North-South) by 1000 km (East-West) (a large portion of northern Manitoba and northern Saskatchewan). The measurement network was designed to provide researchers with a sufficient record of near-surface meteorological and radiation measurements. The data are provided in tabular ASCII files, and were collected by Aircraft Flux and Meteorology (AFM)-7. The surface meteorological and radiation data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Osborne, Heather↗
NASA NTRS1971

A data acquisition system for marine and ecological research.

Description of a self-contained portable data acquisition system for use in marine and ecological research. The compact lightweight data acquisition system is capable of recording 14 variables in its present configuration and is suitable for use in either a boat, pickup truck, or light aircraft. This system will provide the acquisition of reliable data on the structure of the environment and the effect of man-made and natural activities on the observed phenomenon. Utilizing both self-contained analog recording and a telemetry transmitter for real-time digital readout and recording, the prototype system has undergone extensive testing. Currently undergoing component performance upgrading, the prototype system has been utilized in several environmental science investigations associated with air pollution investigations and weather modification and is currently being used for marine data acquisition.

Johnson, R. A.↗
NASA NTRSDate not supplied

Bringing Research to New Heights: How CASEI Integrates Data Curation, Discovery, and Education in Earth and Atmospheric Science

A challenging aspect of any project is finding all the relevant data and information needed to address the research objective. Searching for data and its contextual metadata can become overwhelming for both undergraduate and graduate students, potentially hindering their work and affecting the scientific discoveries that could be made in the long run. To ease this, the NASA Airborne Data Management Group (ADMG), part of the Interagency Implementation and Advanced Concepts Team (IMPACT), has developed the new Catalog of Archived Suborbital Earth science Investigations (CASEI). CASEI includes a web portal that users, be they professionals or students, can use to search, browse, discover, and locate relevant observations associated with NASA’s airborne and field campaigns. Users are able to query data in a variety of ways (via keywords, locations, timeframe, etc) from one online portal, minimizing the amount of time needed to search. CASEI also allows access to key contextual metadata and data from a wide array of Earth and Atmospheric Science topics such as aerosols and boundary layer processes, as well as ice and glacial properties or processes. Users are able to access the data via DOI links to data set landing pages. This presentation will demonstrate how CASEI can be used for classwork and student research. Teachers can provide CASEI to their students as a tool for their studies, or use it to find data themselves while constructing their curriculums. Additionally, users can leverage CASEI to learn about NASA’s Earth and Atmospheric Science research efforts and to find data relevant for assignments or other research projects. The metadata in CASEI has been carefully curated, and highlights important information about the campaigns and their data. Students can explore and learn about the scientific objectives of the campaigns, as well as descriptions of the campaign’s best research days. Having access to contextual metadata in an easy to understand way can help plant the seeds of new ideas in students at any point in their academic journey. From class projects to theses/dissertations and other research, CASEI is a valuable emerging tool for data discovery, giving access to all users and guiding researchers to NASA’s unique airborne data to answer the burning Earth Science questions of our time.

education↗
DOE OSTI2023

GMT: A deep learning approach to generalized multivariate translation for scientific data analysis and visualization

In scientific visualization, despite the significant advances of deep learning for data generation, researchers have not thoroughly investigated the issue of data translation. We present a new deep learning approach called generalized multivariate translation (GMT) for multivariate time-varying data analysis and visualization. Like V2V, GMT assumes a preprocessing step that selects suitable variables for translation. However, unlike V2V, which only handles one-to-one variable translation during training and inference, GMT enables one-to-many and many-to-many variable translation in the same framework. We leverage the recent StarGAN design from multi-domain image-to-image translation to achieve this generalization capability. We experiment with different loss functions and injection strategies to explore the best choices and leverage pre-training for performance improvement. We compare GMT with other state-of-the-art methods (i.e., Pix2Pix, V2V, StarGAN). Furthermore, the results demonstrate the overall advantage of GMT in translation quality and generalization ability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Safeguards-Informed Hybrid Imagery Dataset [Poster]

Deep Learning computer vision models require many thousands of properly labelled images for training, which is especially challenging for safeguards and nonproliferation, given that safeguards-relevant images are typically rare due to the sensitivity and limited availability of the technologies. Creating relevant images through real-world staging is costly and limiting in scope. Expert-labeling is expensive, time consuming, and error prone. We aim to develop a data set of both realworld and synthetic images that are relevant to the nuclear safeguards domain that can be used to support multiple data science research questions. In the process of developing this data, we aim to develop a novel workflow to validate synthetic images using machine learning explainability methods, testing among multiple computer vision algorithms, and iterative synthetic data rendering. We will deliver one million images – both real-world and synthetically rendered – of two types uranium storage and transportation containers with labelled ground truth and associated adversarial examples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Research progress on disease data bank and DATACON systems

Developments and specific statistics for this reporting period are presented. The administration, community activities, funding, personnel, marketing and public relations, technical operations, information systems, and technology transfer are discussed.

Source record↗
NASA NTRS1983

Oceanographic and meteorological research based on the data products of SEASAT

De-aliased SEASAT SASS vector winds obtained during the GOASEX (Gulf of Alaska SEASAT Experiment) program were processed to obtain superobservations centered on a one degree by one degree grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. Each grid point of the synoptic field provides the mean synoptic east-west and north-south wind components plus estimates of the standard deviations of these means. These superobservations winds are then processed further to obtain synoptic scale vector winds stress fiels, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations for each grid point value. The resulting fields appear to be consistant over large distances and to agree with, for example, geostationary cloud images obtained concurrently. Their quality is far superior to that of analyses based on conventional data.

Pierson, W. J.↗
NASA NTRS1985

Oceanographic and meteorological research based on the data products of SEASAT

Reservations were expressed concerning the sum of squares wind recovery algorithm and the power law model function. The SAS sum of squares (SOS) method for recovering winds from backscatter data leads to inconsistent results when V pol and H pol winds are compared. A model function that does not use a power law and that accounts for sea surface temperature is needed and is under study both theoretically and by means of the SASS mode 4 data. Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts are elaborated. The operational aspect of an intermittent assimilation scheme currently utilized for the specification of the initial value field is considered with focus on quantifying the absolute 12-hour linear displacement error of the movement of low centers.

Pierson, W. J., Jr.↗
NASA NTRS1987

A Jupiter Data Analysis Program (JDAP) research grant on wave accessibility and attributes

For more than thirty years the intense decametric radio emissions from Jupiter (DAM) and the corresponding auroral kilometric radiation from the Earth (AKR) have remained major radio science mysteries. Part of the problem, aside from their inherent complexity, has been the difficulty of measuring their source location and emission properties from limited observations. Progress has been made on this problem by locating the source directly, i.e., by analysis of the faraday rotation observed with Voyager as the wave path crossed the Io plasma torus, and indirectly by comparing the peak frequencies of the decametric emission with that at the foot of the Io flux tube. Progress was also made on the general question of how the emissions originate by finding properties of both the AKR and DAM which would imply emission by natural radio lasing.

Calvert, Wynne↗
NASA NTRS1987

Better understanding of intense and tornadic thunderstorms through research using geostationary satellite data

The use of satellite data to study convective storm behavior and better understand intense and tornadic storm development is discussed. The influence of terrain and cloud cover on thunderstorm development, the life cycle and dynamics of the arc cloud line, and the difference in the thermodynamic characteristics of the air into which it advances are examined. The properties of convective-scale interaction are outlined, and the way in which severe convective storms can be isolated using satellite imagery is described. Examples of studies of severe convective and tornadic storms using GOES imagery are presented.

Purdom, James F. W.↗
NASA NTRS1997

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

This final report has four sections. We first describe the actual scientific results attained by our research team, followed by a description of the high performance computing research enhancing those results and prompted by the scientific tasks being undertaken. Next, we describe our research in data and program visualization motivated by the scientific research and also enabling it. Last, we comment on the indirect effects this research effort has had on our work, in terms of follow up or additional funding, student training, etc.

Schwan, Karsten↗
NASA NTRS2000

Use of Maps, GTE and UARS-MLS Data in Understanding Tropospheric Processes Critical to Model Development

Two of the major problems in using meteorological models to explain observed tropospheric trace constituent distributions and thereby to understand the global budgets of the tracers are to properly define the vertical layered structure in the free atmosphere, and to understand the contribution of advection processes in generating horizontal inhomogeneities at all scales. We proposed to tackle these problems through the examination of an extensive collection of trace constituent data from research and commercial aircraft in conjunction with meteorological data from the European Center for Medium-Range Weather Forecasts. The physical mechanisms responsible for these advection and layering processes were explored and their implications for theories and models assessed. In addition, we calculated examples of how thin layers (not currently resolved by models) affect the radiative heating/cooling rates. We developed an improved algorithm for trace constituent layer detection, and used it to analyze over 100,000 km of ozone and humidity vertical profiles collected by instruments piggybacked on commercial aircraft. We have also performed radiative heating/cooling calculations on some observed layer structures, and have demonstrated that the sharp edges on humidity layers can have strong local effects of self-stabilization (dry layers) or destabilization (wet layers), and have suggested that clear-air turbulence might result from the latter case through convective instability. We also systematically analyzed the mesoscale variabilities, not only of the trace constituents, but also of the aircraft-measured dynamical variables.

Newell, Reginald E.↗