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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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Growth of Solid and Hollow Gold Particles through the Thermal Annealing of Nanoscale Patterned Thin Films
Through thermally annealing well-arrayed, circular, nanoscale thin films of gold, deposited onto [111] silicon/silicon dioxide substrates, both solid and hollow gold particles of different morphologies with controllable sizes were obtained. The thin film could form individual particle or clusters of particles by tuning the diameter of it. Hollow gold particles were featured by their large size whose diameter was larger than 500 nm and confirmed by a cross-section view. Hollow gold particles show greater plasmonic field enhancement under photoemission electron microscopy. Potential growth mechanisms for these structures are explored
Pattern recognition techniques to reduce backgrounds in the search for the {sup 136}Xe double beta decay with gaseous TPCs
The observation of the neutrinoless double beta decay may provide essential information on the nature of neutrinos. Among the current experimental approaches, a high pressure gaseous TPC is an attractive option for the search of double beta decay due to its good energy resolution and the detailed topological information of each event. We present in this talk a detailed study of the ionization topology of the {sup 136}Xe double beta decay events in a High Pressure Xenon TPC, as well as that of the typical competing backgrounds. We define some observables based on graph theory concepts to develop automated discrimination algorithms. Our criteria are able to reduce the background level by about three orders of magnitude in the region of interest of the {sup 136}Xe Q{sub ββ} for a signal acceptance of 40%. This result provides a quantitative assessment of the benefit of topological information offered by gaseous TPCs for double beta decay search, and proves that it is a promising feature in view of future experiments in the field. Possible ideas for further improvement in the discrimination algorithms and the dependency of these results with the gas diffusion and readout granularity will be also discussed.
The software peculiarities of pattern recognition in track detectors
The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.
Modeling of the L-shell copper X-pinch plasma produced by the compact generator of Ecole polytechnique using pattern recognition
Principal component analysis is applied and compared with the line ratios of special Ne-like transitions for investigating the electron beam effects on the L-shell Cu synthetic spectra. The database for the principal component extraction is created over a non Local Thermodynamic Equilibrium (non-LTE) collisional radiative L-shell Copper model. The extracted principal components are used as a database for Artificial Neural Network in order to estimate the plasma electron temperature, density, and beam fractions from a representative time-integrated spatially resolved L-shell Cu X-pinch plasma spectrum. The spectrum is produced by the explosion of 25-μm Cu wires on a compact LC (40 kV, 200 kA, and 200 ns) generator. The modeled plasma electron temperatures are about T{sub e} ∼ 150 eV and N{sub e} = 5 × 10{sup 19} cm{sup −3} in the presence of the fraction of the beams with f ∼ 0.05 and a centered energy of ∼10 keV.
Energy and stochasticity: the yin and yang of dislocation patterning
Not Available
Active microrheology and dynamic phases for pattern-forming systems with competing interactions
We consider the driven dynamics of a probe particle moving through an assembly of particles with competing long-range repulsive and short-range attractive interactions, which form crystal, stripe, labyrinth, and bubble states as the ratio of attraction to repulsion is varied. We show that the probe particle exhibits a depinning-like threshold from an elastic regime, where the probe particle is trapped by interactions with the other particles, to a plastic flow regime, where the probe particle can break bonds in the surrounding medium. For a fixed particle density, the depinning threshold and sliding velocity of the probe particle vary nonmonotonically as the attraction term is increased. A velocity minimum appears near the crystal to stripe crossover, and there is a significant increase in the depinning threshold in the bubble regime when the probe particle is strongly confined inside the bubbles. For fixed attractive interaction but increasing particle density, the behavior is also nonmonotonic, and there are jumps and drops in the velocity and depinning threshold corresponding to points at which the system transitions between different structures. There are also several distinct flow states that can be characterized by the amount of plastic deformation induced by the probe particle in the surrounding medium. Each flow state generates a different amount of effective drag on the probe particle, and there can be jumps in the velocity-force curve at transitions between the states. In conclusion, we also find that when oriented stripes are present, the probe particle can move along the stripe in an edge transport state that has a finite Hall angle.
Generating Information-Diverse Microwave Speckle Patterns Inside a Room at a Single Frequency With a Dynamic Metasurface Aperture
Not Available
Machine Learning Pattern Recognition Algorithm With Applications to Coherent Laser Combination
Herein we analyze a new kind of machine learning algorithm designed to feedback stabilize coherently combined lasers. This algorithm learns differential, rather than absolute, values of action in phase space, in order to facilitate learning on initially unstable systems. Experiments have shown that this approach can control small-scale spatial beam combination with high stability. In this paper we analyze the algorithm's performance and limitations in depth, showing that it can continuously learn during operation in order to track changes. Using simulation, we extend the application to temporal combination, and show that it scales to more complex instances by combining 81 beams.
Surface pattern of a Si Mini-Pad sensor for the PHENIX MPC-EX and damage caused by ionizing radiation
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Revealing Occupancy Patterns in Office Buildings Through the use of Annual Occupancy Sensor Data
Energy simulation programs like DOE-2 and EnergyPlus are tools that have been proven to aid with energy calculations to predict energy use in buildings. Some inputs to energy simulation models are relatively easy to find, including building size, orientation, construction materials, and HVAC system size and type. Others vary with time (e.g. weather and occupancy) and some can be a challenge to estimate in order to create an accurate simulation. In this paper, the analysis of occupancy sensor data for a large commercial, multi-tenant office building is presented. It details occupancy diversity factors for private offices and summarizes the same for open offices, hallways, conference rooms, break rooms, and restrooms in order to better inform energy simulation parameters. Long-term data were collected allowing results to be presented to show variations of occupancy diversity factors in private offices for time of day, day of the week, holidays, and month of the year. The diversity factors presented differ as much as 46% from those currently published in ASHRAE 90.1 2004 energy cost method guidelines, a document referenced by energy modelers regarding occupancy diversity factors for simulations. This may result in misleading simulation results and may introduce inefficiencies in the final equipment and systems design.
Magnetically stimulated fluid flow patterns
Sandia National Laboratories' Jim Martin and Kyle Solis explain research on the effects of magnetic fields on fluid flows and how they stimulate vigorous flows. Fluid flow is a necessary phenomenon in everything from reactors to cooling engines in cars.
Mobility Patterns Informing V2X Research Projects: Eco-Routing and Electrified Roadway Project Examples
Presentation given at an 'Expert Workshop on V2X Enabled Electric Vehicles' hosted at NREL on behalf of the International Energy Agency (IEA) Hybrid and Electric Vehicle Implementing Agreement for Task 28: Home Grids and V2X Technologies.
Large Aperture Orientation-Patterned Gallium Arsenide for High Power Frequency Conversion
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Final Technical Report: Flexible Low-cost Platform for Beam Pattern Optimization
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Model performance in spatiotemporal patterns of precipitation: New methods for identifying value added by a regional climate model: Value added by a regional climate model
Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, and time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.