Data information system at the National Space Science Data Center
Integrated information system to support data handling activities of National Science Data Center
Karlow, N.↗
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Results for “active data”
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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Uncertainty Quantification of Activation Due to Cross Section Data in Neutron Shielding Calculation
Quantification of activation in structure materials around the nuclear reactor through calculation is necessary before start of decommissioning. Then a neutron shielding calculation is carried out to estimate activation of structural materials. Neutron shielding calculation is performed out for spatially large regions around a reactor through deep penetration calculation, calculation result would have significant uncertainty. In order to minimize total amount of structure materials treated as radioactive waste, quantitative estimation on uncertainty of structural activation and its reduction is important. The uncertainties due to calculation arises from that of input data and that of calculation method. Examples of uncertainty of input data is those for nuclear reaction cross section and atom density of the nuclide in the structure. In this study, we focus on the uncertainty of cross section, which would be one of the dominant uncertainties, and try to estimate uncertainty of activation due to cross section data in a neutron shielding calculation. The random sampling method (RS) is used as the uncertainty quantification method. With the RS method, uncertainty estimation can be carried out without modification of computer codes for a neutron shielding calculation. (authors)
36 MATERIALS SCIENCE↗
Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
97 MATHEMATICS AND COMPUTING↗
Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to a deterministic data communications network through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and the deterministic data communications network; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
97 MATHEMATICS AND COMPUTING↗
Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing
Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.
Brenner, Martin J.↗
Investigation of multi-dimensional algorithms using active and passive microwave data for ice concentration determination
A discussion is presented concerning the effect of variations in ice surface characteristics on the concentration calculations, in order to ascertain how active and passive microwave data can be optimally combined. Attention is given to dual-polarized, multifrequency passive microwave sensors and to single-channel SAR, in virtue of their availability in the near future. An examination of SAR intensity data at both 1 and 10 GHz indicates that the latter are much less sensitive to ice type and surface condition variations such as wetness and ridging. The Advanced Multichannel Microwave Radiometer is discussed.
Cavalieri, Donald J.↗
Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center
The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.
Moroni, David F.↗
Enhanced Hanford Low-Activity Waste Glass Property Data Development: Phase 5 and Phase 6
This report summarizes the data collected on two test matrices of low-activity waste (LAW) glass compositions intended to expand the composition-property database: Low-Activity Waste (LAW) Phase 5: Expansion of LAW Glass Composition Boundaries and LAW Phase 6: High PCT and VHT Response Glass Matrix. Both matrix glass compositions were statistically designed to expand the LAW glass composition region. The analyses performed on these glasses include chemical composition (for target compositional verification), density, viscosity, electrical conductivity, crystal fraction, container centerline cooling with crystal identification, the product consistency test (PCT) response, the vapor hydration test (VHT) response, and sulfur solubility. Because of the slightly different scope of the two matrices, not all methods were applied to both matrices. Specifically, the following measurements were taken only on the LAW Phase 5: Expansion of LAW Glass Composition Boundaries glasses: crystal fraction as a function of temperature, density (ρ), viscosity (η), and electrical conductivity (EC, e). Combined, these data contribute a significant amount, 51 glasses, to the database for high LAW loaded enhanced waste glasses. Most of these data are focused near the boundaries of acceptable PCT and VHT responses, where prediction uncertainties are most impactful.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Hazard-Based Model of Activity Generation Using Vehicle Trajectory Data
Travel behavior modeling suffers from lack of longitudinal data due to the high cost of procurement and difficulty with ensuring data quality. In the recent years ubiquitous data intercepted from social media, cell detail record, GPS traces are increasingly being explored to analyze human mobility. However, these data lack key demographic information which limits their use for developing causal models of traveler behavior. The primary contribution of the paper lies in using vehicle trajectory data from Ann Arbor along with multiple other data sources for developing a hazard-based activity generation model. The different category of data used in the analysis include (i) vehicle trajectory data (VTD), (ii) American Census Survey (ACS), (iii) land use data, (iv) household travel survey (HTS) data, and (v) smart location data from Environmental Protection Agency (EPA). Home and work are identified as the two most frequently visited locations from the VTD and validated against land use categories of the region. Next a random utility-based model is developed using HTS data to identify other activity purposes as a function of the polynomials of distance from home, activity duration and departure time. The developed model is then applied to identify the non-home activity purposes in the VTD. Demographic and accessibility information are appended to the VTD from ACS and smart location databases respectively. The fmal database is then used to develop a hazard-based activity generation model. (C) 2020 The Authors. Published by Elsevier B.V.
activity generation↗
Global Change Data Center: Mission, Organization, Major Activities, and 2001 Highlights
Rapid efficient access to Earth sciences data is fundamental to the Nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase further and missions with constellations of satellites start to appear. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink. The Global Change Data Center's (GCDC) mission is to provide systems, data products, and information management services to maximize the availability and utility of NASA's Earth science data. The specific objectives are (1) support Earth science missions be developing and operating systems to generate, archive, and distribute data products and information; (2) develop innovative information systems for processing, archiving, accessing, visualizing, and communicating Earth science data; and (3) develop value-added products and services to promote broader utilization of NASA Earth Sciences Enterprise (ESE) data and information. The ultimate product of GCDC activities is access to data and information to support research, education, and public policy.
Wharton, Stephen W.↗
Significant applications of ERTS-1 data to resource management activities at the state level in Ohio
Described are techniques utilized and the progress made in applying ERTS-1 data to (1) detecting, inventorying, and monitoring surface mining activities, particularly in relation to recently passed strip mine legislation in Ohio; (2) updating current land use maps at various scales for multiagency usage, and (3) solving other real-time problems existing throughout the various Ohio governmental agencies. General conclusions regarding current user views as to the opportunities and limitations of operationally using ERTS-1 data at the state level are also noted.
Sweet, D. C.↗
Dynamics-A explorer RIMS data analysis
Activities of the RIMS instrument during the extended mission are planned. The modes of operation for RIMS to achieve the science requirements utilizing the new and exciting information on the composition and dynamics of the low energy (0-50eV) ions in the Earth's ionosphere and magnetosphere are determined. The specific science problems and the required RIMS operational modes needed to acquire the desired data are identified. The analysis was performed on the RIMS data to achieve the science results and this new information was used in determining RIMS operations during the latter part of the mission. Necessary sensitivity tests of RIMS operating modes and instrument performance was suggested. The inflight results was compared with theoretical models.
Banks, P. M.↗
Experimental Observations of the Topology of Convolutional Neural Network Activations
Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.
topological data analysis, deep learning↗
Understanding Subsurface Fracture Evolution Dynamics Using Time‐Lapse Full Waveform Inversion of Continuous Active‐Source Seismic Monitoring Data
Abstract Predicting the behavior, geometry, and flow properties of subsurface fractures remains a challenging problem. Seismic models that can characterize fractures usually suffer from low spatiotemporal resolution. Here, we develop a correlative double‐difference time‐lapse full waveform inversion of continuous active source seismic monitoring data for determining high‐spatiotemporal‐resolution time‐lapse V p models of in‐situ fracture evolution at a shallow contamination site in Wyoming, USA. Assisted by rock physics modeling, we find that (a) rapidly increasing pore pressure initializes and grows the fracture, increasing the porosity slightly (from ∼13.7% to ∼14.6%) in the tight clay formation, thus decreasing V p (∼50 m/s); (b) the fluid injection continues decreasing V p , likely through the introduction of gas bubbles in the injectate; and (c) final V p reductions reach over ∼150 m/s due to a posited ∼4.5% gas saturation. Our results demonstrate that high‐resolution V p changes are indicative of mechanical and fluid changes within the fracture zone during hydrofracturing.
58 GEOSCIENCES↗
Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles
Aerosol extinction profiles are derived from backscatter data by constraining the retrieval with column aerosol optical thickness (AOT), for example from coincident MODIS observations and without reliance on a priori assumptions about aerosol type or optical properties. The backscatter data were acquired with the NASA Langley High Spectral Resolution Lidar (HSRL). The HSRL also simultaneously measures extinction independently, thereby providing an ideal data set for evaluating the constrained retrieval of extinction from backscatter. We will show constrained extinction retrievals using various sources of column AOT, and examine comparisons with the HSRL extinction measurements and with a similar retrieval using data from the CALIOP lidar on the CALIPSO satellite.
Burton, S. P.↗
ESIP Information Quality Cluster (IQC)
The Information Quality Cluster (IQC) within the Federation of Earth Science Information Partners (ESIP) was initially formed in 2011 and has evolved significantly over time. The current objectives of the IQC are to: 1. Actively evaluate community data quality best practices and standards; 2. Improve capture, description, discovery, and usability of information about data quality in Earth science data products; 3. Ensure producers of data products are aware of standards and best practices for conveying data quality, and data providers distributors intermediaries establish, improve and evolve mechanisms to assist users in discovering and understanding data quality information; and 4. Consistently provide guidance to data managers and stewards on how best to implement data quality standards and best practices to ensure and improve maturity of their data products. The activities of the IQC include: 1. Identification of additional needs for consistently capturing, describing, and conveying quality information through use case studies with broad and diverse applications; 2. Establishing and providing community-wide guidance on roles and responsibilities of key players and stakeholders including users and management; 3. Prototyping of conveying quality information to users in a more consistent, transparent, and digestible manner; 4. Establishing a baseline of standards and best practices for data quality; 5. Evaluating recommendations from NASA's DQWG in a broader context and proposing possible implementations; and 6. Engaging data providers, data managers, and data user communities as resources to improve our standards and best practices. Following the principles of openness of the ESIP Federation, IQC invites all individuals interested in improving capture, description, discovery, and usability of information about data quality in Earth science data products to participate in its activities.
data products↗
Global Change Data Center: Mission, Organization, Major Activities, and 2003 Highlights
Rapid, efficient access to Earth sciences data from satellites and ground validation stations is fundamental to the nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase from current levels to terabytes per day. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink.The Global Change Data Center's (GCDC) mission is to develop and operate data systems, generate science products, and provide archival and distribution services for Earth science data in support of the U.S. Global Change Program and NASA's Earth Sciences Enterprise. The ultimate product of the GCDC activities is access to data to support research, education, and public policy.
FROM↗
Enhanced Hanford Low-Activity Waste Glass Property Data Development: Phase 2
This report summarizes and analyzes the data collected on a second test matrix of 42 low-activity waste (LAW) glass compositions intended to expand the LAW glass composition region over which glass property-composition models are valid. The 42 LAW glass compositions were selected using a statistical layered experimental design approach to explore a new glass composition region that overlaps and expands beyond the previously explored LAW glass composition region. The layered design of 42 LAW glasses consisted of 21 outer-layer glasses, 15 inner-layer glasses, a center glass (three replicates), and two glasses previously tested at another laboratory. The outer-layer glass compositions include extrema based on current projections of the LAW feeds and melter operating temperatures. One of the outer-layer compositions was eliminated due to the inability to form a glass. Therefore, only 41 glasses were analyzed. The analyses performed on these glasses include chemical composition (for target compositional verification), density, viscosity, electrical conductivity, crystal fraction, canister centerline cooling with crystal identification, the Product Consistency Test, sulfur solubility, and the Vapor Hydration Test. This report discusses in depth the results obtained from this testing.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗