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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Overview of the OECD-NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established in 1989 to facilitate collaboration in nuclear data activities. Over its thirty year history, different Subgroups have been created to address topics in nearly every aspect of nuclear data, including: experimental measurements, evaluation, validation, model development, quality assurance of databases and the development of software tools. WPEC has recently completed activities on fission yield evaluation, the general nuclear database structure (GNDS) to replace the ENDF-6 format, methods to provide feedback to evaluation, studies of specific capture cross sections, new methods in thermal scattering kernel evaluation and the Collaborative International Evaluated Library Organisation (CIELO) Pilot Project. Ongoing activities in GNDS application programming interface (API) development, methods for covariance evaluation and quality assurance in nuclear data validation using the International Criticality Safety Benchmark Evaluation Project (ICSBEP) database are complemented by the work of two Expert Groups that oversee the High-Priority Request List (HPRL) for Nuclear Data and the continuous development of the GNDS. New activities on the use of integral experiments for nuclear data validation and adjustment, as well as the use of the Shielding Integral Benchmark Archive and Database (SINBAD) for validation have begun and will be coordinated alongside future Subgroups. After three decades we will review the status of WPEC, how it integrates other collections and activities organised by the NEA and how it dovetails with the initiatives of the IAEA and other bodies to effectively coordinate international activities in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

[New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data]

Below is the 1st year progress report for NAG5-13435 "New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data". Activity on this project has been coordinated with our NASA DB project NAG5-9604. For your convenience, this report has six sections and an Appendix. Sections I - III discuss specific activities undertaken during the past year to analyze/use MODIS data. Section IV formally states our intention to no longer pursue any research using JAXA's (formerly NASDA's) GLI instrument which catastrophically failed very early after launch (also see the Appendix). Section V provides some indications of directions for second year activities based on our January 2004 telephone discussions and email exchanges. A brief summary is given in Section VI.

Dodge, James C.↗
NASA NTRS1973

ERTS image data compression technique evaluation

The author has identified the following significant results. Tapes of compressed ERTS data were obtained to permit later reconstruction and to prove that in general four ERTS MSS tapes can be put onto a single compressed tape. A compressed tape was reconstructed and imagery made. The data were compressed using the essentially information preserving SSDIAM algorithm, with mappings of from 1 to 3 levels and imagery was made of the result. This imagery shows that no visual degradation results from the one level mapping while compression is significantly increased. Mappings of up to three levels shows negligible deterioration in areas of moderate to high data activity, but contouring is noticeable in areas of uniform data such as the plains region.

Spencer, D. J.↗
NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗
NASA NTRS1980

Thermal metamorphism of primitive meteorites. XI - The enstatite meteorites: Origin and evolution of a parent body

The neutron activation data for Ag, As, Bi, Cd, Co, Cs, Cu, Ga, In, Rb, Se, Te, Tl, and Zn were obtained in samples of Abee heated to 1000-1400 C at low pressures. In addition, these elements were reported in nine enstatite achondrites and in the silicate part of the Mt. Egerton stony-iron. The data show trace element losses above 1000 C by diffusion-controlled processes with apparent activation energies of 8 to 55 kcal/mol; these data together with abundances of aubrites, Mt. Egerton, and E4-6 chondrites, and isotopic results link all enstatite meteorites to a common parent body. The data also indicate that aubrites and the Mt. Egerton material reflect fractional crystallization of a magma produced from enstatite chondrite-like parent material (E6) and the late introduction of chalcophiles and mobile elements transported by an FeS-Fe eutectic from an E4-6 region undergoing open-system metamorphism.

Biswas, S.↗
NASA NTRS2002

Visual Inference Programming

The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

Wheeler, Kevin↗
NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗
NASA NTRS1980

Glucose metabolism in different regions of the rat brain under hypokinetic stress influence

Glucose metabolism in rats kept under long term hypokinetic stress was studied in 7 brain regions. Determination was made of the regional levels of glucose, lactate, glutamate, glutamine, aspartate, gamma-aminobutyrate and the incorporation of C-14 from plasma glucose into these metabolites, in glycogen and protein. From the content and activity data the regional glucose flux was approximated quantitatively. Under normal conditions the activity gradient cortex and frontal pole cerebellum, thalamus and mesencephalon, hypothalamus and pons and medulla is identical with that of the regional blood supply (measured with I131 serum albumin as the blood marker). Within the first days of immobilization a functional hypoxia occurred in all brain regions and the utilization of cycle amino acids for protein synthesis was strongly diminished. After the first week of stress the capillary volumes of all regions increased, aerobic glucose metabolism was enhanced (factors 1.3 - 2.0) and the incorporation of glucose C-14 via cycle amino acids into protein was considerably potentiated. The metabolic parameters normalized between the 7th and 11th week of stress. Blood supply and metabolic rate increased most in the hypothalamus.

Konitzer, K.↗
NASA NTRS1990

MEASURE: An integrated data-analysis and model identification facility

The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.

Singh, Jaidip↗
DOE OSTI2023

Search for keV-scale sterile neutrinos with the first KATRIN data

In this work we present a keV-scale sterile-neutrino search with a low-tritium-activity data set of the KATRIN experiment, acquired in a commissioning run in 2018. KATRIN performs a spectroscopic measurement of the tritium β-decay spectrum with the main goal of directly determining the effective electron anti-neutrino mass. During this commissioning phase a lower tritium activity facilitated the measurement of a wider part of the tritium spectrum and thus the search for sterile neutrinos with a mass of up to 1.6 keV. We do not find a signal and set an exclusion limit on the sterile-to-active mixing amplitude of $\text {sin}^{2}\: \theta<5\times 10^{-4}\: (95\%\: $C.L) at a mass of 0.3 keV. This result improves current laboratory-based bounds in the sterile-neutrino mass range between 0.1 and 1.0 keV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Fission neutron activations of stainless steel and its corresponding elemental components

Characterizing neutron activation of stainless steel is a critical task for many applications, and yet little activation data is available for this alloy. To address the need, a series of neutron activation experiments have been performed using the Flattop critical assembly at the National Criticality Experiments Research Center. Several experimental conditions were probed for complete understanding of the neutron environment, including foil composition and position within the assembly. The experimental results reported here will aid in the production of stainless steel benchmarks for a range of nuclear data applications including those used in nuclear forensics analysis.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1983

Description of data base management activities

ARC's current and future data processing needs have been identified and defined. Requirements for improved data processing capabilities are listed: (1) Centralized control of system data files. Establish a DBA/data base administrator position with responsibility for management of the Centers numerous data bases; (2) Programmer tools to improve efficiency of performance; (3) Direct and timely access to information. Presently, the user submits query requests to the data processing department where they are prioritized with other queries and then batch processed using a report generator; (4) On line data entry. With the merger of the Dryden facility with ARC on line data entry, edit and updates have become mandatory for timely operation and reporting. A DBMS software package was purchased to meet the above requirements.

Source record↗
DOE OSTI2018

Standards and Protocols for Data Acquisition and Reporting for Studies of the Electrochemical Reduction of Carbon Dioxide

Objective evaluation of the performance of electrocatalysts for CO 2 reduction has been complicated by a lack of standardized methods for measuring and reporting activity data. In this perspective, we advocate that standardizing these practices can aid in advancing research efforts toward the development of efficient and selective CO 2 reduction electrocatalysts. Using information taken from experimental studies, we identify variables that influence the measured activity of CO 2 reduction electrocatalysts and propose procedures to account for these variables in order to improve the accuracy and reproducibility of reported data. We recommend that catalysts be measured under conditions which do not introduce artifacts from impurities, from either the electrolyte or counter electrode, and advocate the acquisition of data measured in the absence of mass transport effects. Furthermore, measured rates of electrochemical reactions should be normalized to both the geometric electrode area as well as the electrochemically active surface area to facilitate the comparison of reported catalysts with those previously known. We demonstrate that, when these factors are accounted for, the CO 2 reduction activities of Ag and Cu measured in different laboratories exhibit little difference. Furthermore, adoption of the recommendations presented in this perspective would greatly facilitate the identification of superior catalysts for CO 2 reduction arising solely from changes in their composition and pretreatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

High altitude aircraft remote sensing during the 1988 Yellowstone National Park wildfires

An overview is presented of the effects of the wildfires that occurred in the Yellowstone National Park during 1988 and the techniques employed to combat these fires with the use of remote sensing. The fire management team utilized King-Air and Merlin aircraft flying night missions with a thermal IR line-scanning system. NASA-Ames Research Center assisted with an ER-2 high altitude aircraft with the ability to down-link active data from the aircraft via a teledetection system. The ER-2 was equipped with a multispectral Thematic Mapper Simulator scanner and the resultant map data and video imagery was provided to the fire command personnel for field evaluation and fire suppression activities. This type of information proved very valuable to the fire control management personnel and to the continuing ecological research goals of NASA-Ames scientists analyzing the effects of burn type and severity on ecosystem recovery and development.

Ambrosia, Vincent G.↗
NASA NTRS1998

Long-Term Global Morphology of Gravity Wave Activity Using UARS Data

Progress in research into the global morphology of gravity wave activity using UARS data is described for the period March-June, 1998. Highlights this quarter include further progress in the analysis and interpretation of CRISTA temperature variances; model-generated climatologies of mesospheric gravity wave activity using the HWM-93 wind and temperature model; and modeling of gravity wave detection from space-based platforms. Preliminary interpretations and recommended avenues for further analysis are also described.

Eckermann, Stephen D.↗
DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗