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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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Probabilistic Inference of Model Parameters and Missing High-Dimensional Data Based on Summary Statistics.
Abstract not provided.
Studying the Geomagnetic Polarity Time Scale and Superchrons by Scalar Models and Feature Based Data Assimilation
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A CIM Based Data Integration Framework for Distribution Utilities
With the proliferation of distributed energy resources and advanced metering, modern electric power distribution systems are data rich and include advanced capabilities for distribution automation. Distribution utilities need applications for planning and operations that can integrate all the available data from the enterprise applications and may incorporate distributed approaches to operate and control. This paper describes a framework for standardizing and integrating the data available at different vendor specific applications in a utility utilizing the Common Information Model (CIM). Theframework incorporates the conversion of these the standardized CIM models into models compatible with GridLAB-D, an open source distribution system simulator, for developing advanced planning and operation strategies.
3D Model Visual Verification and Mesh-Based Data Analysis in Fulcrum
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GAN-based Data Mapping for Model Adaptation
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Realtime forecasting of CO2 flow using variational autoencoder with ensemble-based data assimilation.
Abstract not provided.
MINNION: Non-Linear Machine Learning based Data Reduction Software for High-Performance Computing
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An Open-source Based Data Management and Processing Framework on a Central Server for Electron Microscopy
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ADMS Test Bed: AMI Data-Based Grid Controls
Develop algorithms for leveraging existing AMI infrastructure to provide a foundational, pervasive secondary voltage monitoring network solution.
Automatically Recognizing Semantics of List-based Data Structures in Source Code
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Recent Monitoring of Suspended Sediment Patterns along Louisiana's Coastal Zone using ER-2 based MAS Data and Terra Based MODIS Data
The University nf Wisconsin and Louisiana State University have teamed to study the forcing of winter season cold frontal wind systems on sediment distribution patterns and geomorphology in the Louisiana coastal zone. Wind systems associated with cold fronts have been shown to model coastal circulation and resuspend sediments along the micro tidal Louisiana coast (Roberts et at. 1987, Moeller et al. 1993). Remote sensing data is being used to map and track sediment distribution patterns for various wind conditions. Suspended sediment is a building material for coastal progradation and wetlands renewal, but also restricts access to marine nursery environments and impacts oyster bed health. Transferring a suspended sediment concentration (SSC) algorithm to EOS MODerate resolution Imaging Spectroradiometer (MODIS; Barnes et al. 1998) observations may enable estimates of SSC globally.
Data encoding based on the shape of the ferroelectric domains produced by a scanning probe microscopy tip
Ferroelectric materials are broadly considered for information storage due to extremely high storage and information processing densities they enable. To date, ferroelectric based data storage has invariably relied on formation of cylindrical domains, allowing for binary information encoding. Here we demonstrate and explore the potential of high-density encoding based on domain morphology. We explore the domain morphogenesis during the tip-induced polarization switching by sequences of positive and negative pulses in a lithium niobate single-crystal and demonstrate the principal of information coding by shape and size of the domains. We applied cross-correlation and neural network approaches for recognition of the switching sequence by the shape of the resulting domains and establish optimal parameters for domain shape recognition. These studies both provide insight into the highly non-trivial mechanism of domain switching and potentially establish a new paradigm for multilevel information storage and content retrieval memories. Furthermore, this approach opens a pathway to exploration of domain switching mechanisms via shape analysis.
The evaluation of satellite-borne weather radar system designs using real ground-based radar data
The paper presents method of evaluating proposed satellite radar systems using real radar data, and discusses methods of displaying the results which will hopefully facilitate easy comparison of systems. A single pencil beam pulsed radar system is considered while the precipitation data base comes from six rain days observed by SPANDAR. The many additional factors that must be considered in the radar equation such as attenuation and scattering (Mie and Rayleigh) are discussed along with some indication where possible errors lie.
Phases and interfaces from real space atomically resolved data: Physics-based deep data image analysis
Advances in electron and scanning probe microscopies have led to a wealth of atomically resolved structural and electronic data, often with ~1–10 pm precision. However, knowledge generation from such data requires the development of a physics-based robust framework to link the observed structures to macroscopic chemical and physical descriptors, including single phase regions, order parameter fields, interfaces, and structural and topological defects. Here, we develop an approach based on a synergy of sliding window Fourier transform to capture the local analog of traditional structure factors combined with blind linear unmixing of the resultant 4D data set. This deep data analysis is ideally matched to the underlying physics of the problem and allows reconstruction of the a priori unknown structure factors of individual components and their spatial localization. We demonstrate the principles of this approach using a synthetic data set and further apply it for extracting chemical and physically relevant information from electron and scanning tunneling microscopy data. Furthermore, this method promises to dramatically speed up crystallographic analysis in atomically resolved data, paving the road toward automatic local structure–property determinations in crystalline and quasi-ordered systems, as well as systems with competing structural and electronic order parameters.
Assessment of NASA Airborne Laser Altimetry Data Using Ground-Based GPS Data near Summit Station, Greenland
A series of NASA airborne lidars have been used in support of satellite laser altimetry missions. These airbornelaser altimeters have been deployed for satellite instrument development, for spaceborne data validation, and to bridge the data gap between satellite missions. We used data from ground-based Global Positioning System (GPS) surveys of an 11 km long track near Summit Station, Greenland, to assess the surface elevation bias and measurement precision of three airborne laser altimeters including the Airborne Topographic Mapper (ATM), the Land, Vegetation, and Ice Sensor (LVIS), and the Multiple Altimeter Beam Experimental Lidar (MABEL). Ground-based GPS data from the monthly ground-based traverses, which commenced in 2006, allowed for the assessment of nine airborne lidar surveys associated with ATM and LVIS between 2007 and 2016. Surface elevation biases for these altimeters over the flat, ice-sheet interior are less than 0.12 m, while assessments of measurement precision are 0.09 m or better. Ground-based GPS positions determined both with and without differential post-processing techniques provided internally consistent solutions. Results from the analyses of ground-based and airborne data provide validation strategy guidance for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) elevation and elevation-change data products.