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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Automatic electronic fish tracking system

A newly developed electronic fish tracking system to automatically monitor the movements and migratory habits of fish is reported. The system is aimed particularly at studies of effects on fish life of industrial facilities which use rivers or lakes to dump their effluents. Location of fish is acquired by means of acoustic links from the fish to underwater Listening Stations, and by radio links which relay tracking information to a shore-based Data Base. Fish over 4 inches long may be tracked over a 5 x 5 mile area. The electronic fish tracking system provides the marine scientist with electronics which permit studies that were not practical in the past and which are cost-effective compared to manual methods.

Osborne, P. W.↗
NASA NTRS1981

Comparison of forward fuselage to Space Shuttle Orbiter flight pressure data to wind tunnel and analytical results in the hypersonic Mach number range

The Space Transportation System (STS) test program is unique in that it combines flight testing with operational flights using the first operational orbital vehicle (OV-102). The Space Shuttle Orbiter was instrumented to obtain various types of flight data. The instrumentation, designated Development Flight Instrumentation (DFI) includes pressure transducers, thermocouples, calorimeters, and accelerometers. A comparison is conducted between orbiter DFI forward fuselage flight pressure data obtained from OV-102 during the STS-1 reentry, and ground facility data obtained utilizing a 0.04 scale Orbiter forebody model. The comparisons are used to validate the existing experimental data base, optimize the pressure modeling technique, and make possible the refinement of error analysis relative to both. The obtained results indicate, in general, good agreement between flight and ground-based data.

Bradley, P. F.↗
NASA NTRS1985

Cloud-drift wind estimates during PGGE

Cloud drift winds constitute an important component of the First Global Atmospheric Research Program Experiment data base. Data was generated by far different centers, using somewhat different procedures. Image data transformation to wind vectors is discussed. Emphasis is placed on the differences between the processing techniques employed in each system. The use of cloud drift data by global data assimulation systems is reviewed, including quality control and relative weighting.

Mcpherson, R. D.↗
NASA NTRS1991

Information logistics: A production-line approach to information services

Logistics can be defined as the process of strategically managing the acquisition, movement, and storage of materials, parts, and finished inventory (and the related information flow) through the organization and its marketing channels in a cost effective manner. It is concerned with delivering the right product to the right customer in the right place at the right time. The logistics function is composed of inventory management, facilities management, communications unitization, transportation, materials management, and production scheduling. The relationship between logistics and information systems is clear. Systems such as Electronic Data Interchange (EDI), Point of Sale (POS) systems, and Just in Time (JIT) inventory management systems are important elements in the management of product development and delivery. With improved access to market demand figures, logisticians can decrease inventory sizes and better service customer demand. However, without accurate, timely information, little, if any, of this would be feasible in today's global markets. Information systems specialists can learn from logisticians. In a manner similar to logistics management, information logistics is concerned with the delivery of the right data, to the ring customer, at the right time. As such, information systems are integral components of the information logistics system charged with providing customers with accurate, timely, cost-effective, and useful information. Information logistics is a management style and is composed of elements similar to those associated with the traditional logistics activity: inventory management (data resource management), facilities management (distributed, centralized and decentralized information systems), communications (participative design and joint application development methodologies), unitization (input/output system design, i.e., packaging or formatting of the information), transportations (voice, data, image, and video communication systems), materials management (data acquisition, e.g., EDI, POS, external data bases, data entry) and production scheduling (job, staff, and project scheduling).

Adams, Dennis↗
NASA NTRS1993

Space plasma physics research

During the course of this grant, work was performed on a variety of topics and there were a number of significant accomplishments. A summary of these accomplishments is included. The topics studied include empirical model data base, data reduction for archiving, semikinetic modeling of low energy plasma in the inner terrestrial magnetosphere and ionosphere, O(+) outflows, equatorial plasma trough, and plasma wave ray-tracing studies. A list of publications and presentations which have resulted from this research is also included.

Comfort, Richard H.↗
NASA NTRS1991

Clouds as calibration targets for AVHRR reflected-solar channels - Results from a two-year study at NOAA/NESDIS

NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) and associated ground-based data have been collected at NOAA/NESDIS, on a daily basis and for 600 days, using five stations within the continental United States in the NOAA solar radiation (SOLRAD) monitoring network. The data have been filtered to include only uniformly overcast conditions and analyzed along the lines described by Paris and Justus (1988). Results from this first long-term pilot operational application of the method are presented. The method is potentially useful for establishing yearly-averaged trends in the radiometric gain of AVHRR Channels. The relatively small data base examined here suggests a precision in the 600 day mean gain of 5 percent or worse, with a significant part of this uncertainty being driven by poor knowlege of the bidirectional reflectance properties of clouds. The results suggest that the method in its present formulation has insufficient precision to be used as a primary method for the measurement of in-orbit gains of reflected-solar radiometers aboard polar orbiting satellites. Intrinsic limitations to the precision and time resolution of the method are discussed, and suggestions are offered for improving the precision of future results.

Abel, Peter↗
NASA NTRS1994

Integration of remote sensing and hydrologic modeling through multi-disciplinary semiarid field campaigns: Moonsoon 1990, Walnut Gulch 1992, and SALSA-MEX

A research and modeling strategy is presented for development of distributed hydrologic models given by a combination of remotely sensed and ground based data. In support of this strategy, two experiments Moonsoon'90 and Walnut Gulch'92 were conducted in a semiarid rangeland southeast of Tucson, Arizona, (U.S.) and a third experiment, the SALSA-MEX (Semi Arid Land Surface Atmospheric Mountain Experiment) was proposed. Results from the Moonsoon'90 experiment substantially advanced the understanding of the hydrologic and atmospheric fluxes in an arid environment and provided insight into the use of remote sensing data for hydrologic modeling. The Walnut Gulch'92 experiment addressed the seasonal hydrologic dynamics of the region and the potential of combined optical microwave remote sensing for hydrologic applications. SALSA-MEX will combine measurements and modeling to study hydrologic processes influenced by surrounding mountains, such as enhanced precipitation, snowmelt and recharge to ground water aquifers. The results from these experiments, along with the extensive experimental data bases, should aid the research community in large scale modeling of mass and energy exchanges across the soil-plant-atmosphere interface.

Moran, M. S.↗
NASA NTRS2017

Assessment of State-of-the-Art Dust Emission Scheme in GEOS

The GEOS modeling system has been extended with state of the art parameterization of dust emissions based on the vertical flux formulation described in Kok et al 2014. The new dust scheme was coupled with the GOCART and MAM aerosol models. In the present study we compare dust emissions, aerosol optical depth (AOD) and radiative fluxes from GEOS experiments with the standard and new dust emissions. AOD from the model experiments are also compared with AERONET and satellite based data. Based on this comparative analysis we concluded that the new parameterization improves the GEOS capability to model dust aerosols originating from African sources, however it lead to overestimation of dust emissions from Asian and Arabian sources. Further regional tuning of key parameters controlling the threshold friction velocity may be required in order to achieve more definitive and uniform improvement in the dust modeling skill.

Darmenov, Anton↗
DOE OSTI2022

Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference

Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will increase that number by 1-2 orders of magnitude. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. To leverage the increased statistical power of the lenses that will be discovered through upcoming surveys, automated lens analysis techniques are necessary. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate the successful application of Neural Posterior Estimation (NPE) to automate the inference of a 12-parameter lens mass model for DES-like ground-based imaging data. We compare our NPE constraints to a Bayesian Neural Network (BNN) and find that it outperforms the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1987

Conceptual information processing: A robust approach to KBS-DBMS integration

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing.

Lazzara, Allen V.↗
DOE OSTI2023

AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) v1.0.0

The AmeriFlux BASE Flux/Met Data QA/QC and Processing (AMF-BASE-QAQC) code provides tools to review and prepare continuous flux/met data submitted to the AmeriFlux Management Project for publication as the AmeriFlux BASE data product. The code provides 3 core functionalities: Format QA/QC assesses submitted data files for compliance with the required submission format; Data QA/QC assesses the data quality; BASE Publish prepares the data for publication.

Christianson, Danielle↗
NASA NTRS2021

Analysis of Aerosol Type and Fine- and Coarse-mode Aerosol Direct Radiative Forcing over Regions in East and Southeast Asia Based on AERONET Version 3 Data

Based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) values obtained for 1020 nm from Aerosol Robotic Network (AERONET) Version 3 Level 2.0 data collected in five regions, namely, northern China, Northwest Asia, the Tibetan Plateau, southern China and Southeast Asia, we classified seven types of aerosol (viz., purely dust, dust-dominated, pollution-dominated, non-absorbing [NA], weakly absorbing [WA], moderately absorbing [MA] and strongly absorbing [SA]) in order to assess the spatial and temporal distributions of their constituents and the radiative effects of their fine- and coarse-mode particles. The fine fraction dominated in northern China and also played a crucial role on the Tibetan Plateau and in southern China and Southeast Asia, whereas the coarse fraction prevailed in Northwest Asia. Furthermore, the fine-mode aerosol on the Tibetan Plateau exhibited its maximum radiative forcing efficiency (110.3 W m–2) during high concentrations of SA aerosol. Also, the lowest values for both the radiative forcing and the radiative forcing efficiency in southern China occurred during summer. Finally, the various aerosol constituents displayed distinct spatial and temporal distributions in Southeast Asia, with the SA aerosol contributing approximately 20% of the total aerosol on the Indochinese Peninsula and the NA and WA aerosol forming the largest percentages on the Malay Peninsula.

Particle linear depolarization ratio↗
DOE OSTI2018

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Stanfill, Bryan A.↗
DOE OSTI2021

Topological data analysis of task-based fMRI data from experiments on schizophrenia

We use methods from computational algebraic topology to study functional brain networks, in which nodes represent brain regions and weighted edges represent similarity of fMRI time series from each region. With these tools, which allow one to characterize topological invariants such as loops in high-dimensional data, we are able to gain understanding into low-dimensional structures in networks in a way that complements traditional approaches based on pairwise interactions. In the present paper, we analyze networks constructed from task-based fMRI data from schizophrenia patients, healthy controls, and healthy siblings of schizophrenia patients using persistent homology, which allows us to explore the persistence of topological structures such as loops at different scales in the networks. We use persistence landscapes, persistence images, and Betti curves to create output summaries from our persistent-homology calculations, and we study the persistence landscapes and images using k-means clustering and community detection. Based on our analysis of persistence landscapes, we find that the members of the sibling cohort have topological features (specifically, their 1-dimensional loops) that are distinct from the other two cohorts. From the persistence images, we are able to distinguish all three subject groups and to determine the brain regions in the loops (with four or more edges) that allow us to make these distinctions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1979

Multipurpose interactive NASA information system

Multipurpose Interactive NASA Information System (MINIS) is data management system capable of retrieving descriptive data from LANDSAT photos. General enough to be used with other user-defined data bases, interactive data management and information retrieval system was especially developed for small and medium-sized computers. It uses free-form data base that allows one to create entirely new and different data bases and to control format of output products.

Hill, J. M.↗
DOE OSTI2015

Performance analysis of data intensive cloud systems based on data management and replication: a survey

As we delve deeper into the ‘Digital Age’, we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis that originated from myriad of sources and applications including mobiledevices, sensors, individual archives, social networks, Internet of Things, enterprises, cameras, software logs, etc. Such ‘Data Explosions’ has led to one of the most challenging research issues of the current Information and Communication Technology era: how to optimally manage (e.g., store, replicated, filter, and the like) such large amount of data and identify new ways to analyze large amounts of data for unlocking information. It is clear that such large data streams cannot be managed by setting up on-premises enterprise database systems as it leads to a large up-front cost in buying and administering the hardware and software systems. Therefore, next generation data management systems must be deployed on cloud. The cloud computing paradigm provides scalable and elastic resources, such as data and services accessible over the Internet Every Cloud Service Provider must assure that data is efficiently processed and distributed in a way that does not compromise end-users’ Quality of Service (QoS) in terms of data availability, data search delay, data analysis delay, and the like. In the aforementioned perspective, data replication is used in the cloud for improving the performance (e.g., read and write delay) of applications that access data. Through replication a data intensive application or system can achieve high availability, better fault tolerance, and data recovery. In this paper, we survey data management and replication approaches (from 2007 to 2011) that are developed by both industrial and research communities. The focus of the survey is to discuss and characterize the existing approaches of data replication and management that tackle the resource usage and QoS provisioning with different levels of efficiencies. Moreover, the breakdown of both influential expressions (data replication and management) to provide different QoS attributes is deliberated. Furthermore, the performance advantages and disadvantages of data replication and management approaches in the cloud computing environments are analyzed. Open issues and future challenges related to data consistency, scalability, load balancing, processing and placement are also reported.

Malik, Saif Ur Rehman↗