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At least 1,243 records · Page 69

Atomic electron tomography in three and four dimensions

Atomic electron tomography (AET) has become a powerful tool for atomic-scale structural characterization in three and four dimensions. It provides the ability to correlate structures and properties of materials at the single-atom level. With recent advances in data acquisition methods, iterative three-dimensional (3D) reconstruction algorithms, and post-processing methods, AET can now determine 3D atomic coordinates and chemical species with sub-Angstrom precision, and reveal their atomic-scale time evolution during dynamical processes. In this work, we review the recent experimental and algorithmic developments of AET and highlight several groundbreaking experiments, which include pinpointing the 3D atom positions and chemical order/disorder in technologically relevant materials and capturing how atoms rearrange during early nucleation at four-dimensional atomic resolution.

30 DIRECT ENERGY CONVERSION↗

OGLE-2018-BLG-0567Lb and OGLE-2018-BLG-0962Lb: Two Microlensing Planets through the Planetary-caustic Channel

We present the analyses of two microlensing events, OGLE-2018-BLG-0567 and OGLE-2018-BLG-0962. In both events, the short-lasting anomalies were densely and continuously covered by two high-cadence surveys. The light-curve modeling indicates that the anomalies are generated by source crossings over the planetary caustics induced by planetary companions to the hosts. The estimated planet/host separation (scaled to the angular Einstein radius θ {sub E}) and mass ratio are (s, q × 10{sup 3}) = (1.81 ± 0.02, 1.24 ± 0.07) and (s, q × 10{sup 3}) = (1.25 ± 0.03, 2.38 ± 0.08), respectively. From Bayesian analyses, we estimate the host and planet masses as (M{sub h},M{sub p})=(0.25{sub −0.13}{sup +0.27} M{sub ⊙},0.32{sub −0.17}{sup +0.34} M{sub J}) and (M{sub h},M{sub p})=(0.54{sub −0.28}{sup +0.33} M{sub ⊙},1.34{sub −0.70}{sup +0.82} M{sub J}), respectively. These planetary systems are located at a distance of 7.06{sub −1.15}{sup +0.93} kpc for OGLE-2018-BLG-0567 and 6.50{sub −1.75}{sup +1.06} kpc for OGLE-2018-BLG-0962, suggesting that they are likely to be near the Galactic bulge. The two events prove the capability of current high-cadence surveys for finding planets through the planetary-caustic channel. We find that most published planetary-caustic planets are found in Hollywood events in which the source size strongly contributes to the anomaly cross-section relative to the size of the caustic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ice-shelf ocean boundary layer dynamics from large-eddy simulations

Abstract. Small-scale turbulent flow below ice shelves is regionally isolated and difficult to measure and simulate. Yet these small-scale processes, which regulate heat and salt transfer between the ocean and ice shelves, can affect sea-level rise by altering the ability of Antarctic ice shelves to “buttress” ice flux to the ocean. In this study, we improve our understanding of turbulence below ice shelves by means of large-eddy simulations at sub-meter resolution, capturing boundary layer mixing at scales intermediate between laboratory experiments or direct numerical simulations and regional or global ocean circulation models. Our simulations feature the development of an ice-shelf ocean boundary layer through dynamic ice melting in a regime with low thermal driving, low ice-shelf basal slope, and strong shear driven by the geostrophic flow. We present a preliminary assessment of existing ice-shelf basal melt parameterizations adopted in single component or coupled ice-sheet and ocean models on the basis of a small parameter study. While the parameterized linear relationship between ice-shelf melt rate and far-field ocean temperature appears to be robust, we point out a little-considered relationship between ice-shelf basal slope and melting worthy of further study.

54 ENVIRONMENTAL SCIENCES↗

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

A note on the problem of jet stream formation

It is noted that the formation of 'jet streams', or narrow ringlike structures of small particles, in early planetary and satellite systems cannot result solely from inelastic collisions among the small particles. The possibility is considered that gravitational encounters between the particles will perturb them into more eccentric orbits and thus maintain the orbital coupling between particles (or jet streams) in neighboring orbits. It is found that when the gravitational effect of the particles is taken into account, the average eccentricity of the particles increases as agglomeration due to inelastic collisions proceeds. With respect to jet-stream formation, it is suggested that the ever-increasing orbital eccentricity of the particles will aid in coupling together the different 'sub-jet streams', so that large-scale orbital focusing toward the center of the whole system can continue. Alternative mechanisms leading to planetary accretion are briefly discussed.

Ip, W.-H.↗

Need for active structures in future large IR and sub-mm telescopes

The potential of active structures technology for future IR and sub-mm telescopes deployed in space is discussed. A space infrared telescope with an aperture of at least 8 m, operating at about 50 k with surface precision better that 0.5 microns is required for future work in space IR and sub-mm astronomy. Telescope parameters, noise, and sensitivity are discussed. The effects of large scale figure errors are examined and conceptual designs of future space IR and sub-mm telescopes are presented. Possible uses of active structures technology and feedback control in future IR and sub-mm space observatories are suggested.

Rapp, Donald↗

Fully Coupled Micro/Macro Deformation, Damage, and Failure Prediction for SiC/Ti-15-3 Laminates

The deformation, failure, and low cycle fatigue life of SCS-6/Ti-15-3 composites are predicted using a coupled deformation and damage approach in the context of the analytical generalized method of cells (GMC) micromechanics model. The local effects of inelastic deformation, fiber breakage, fiber-matrix interfacial debonding, and fatigue damage are included as sub-models that operate on the micro scale for the individual composite phases. For the laminate analysis, lamination theory is employed as the global or structural scale model, while GMC is embedded to operate on the meso scale to simulate the behavior of the composite material within each laminate layer. While the analysis approach is quite complex and multifaceted, it is shown, through comparison with experimental data, to be quite accurate and realistic while remaining extremely efficient.

Bednarcyk, Brett A.↗

Estimation of Length-Scales in Soils by MRI

Soil can be best described as an unconsolidated granular media that forms porous structure. The present macroscopic theory of water transport in porous media rests upon the continuum hypothesis that the physical properties of porous media can be associated with continuous, twice-differentiable field variables whose spatial domain is a set of centroids of Representative Elementary Volume (REV) elements. MRI is an ideal technique to estimate various length-scales in porous media. A 0.267 T permanent magnet at NASA GRC was used for this study. A 2D or 3D spatially-resolved porosity distribution were obtained from the NMR signal strength from each voxel and the spin-lattice relaxation time. A classical spin-warp imaging with Multiple Spin Echos (MSE) was used to evaluate proton density in each voxel. Initial resolution of 256 x 256 was subsequently reduced by averaging neighboring voxels and the porosity convergence was observed. A number of engineered "space candidate" soils such as Isolite(trademark), Zeoponics(trademark), Turface(trademark), and Profile(trademark) were used. Glass beads in the size range between 50 microns to 2 mm were used as well. Initial results with saturated porous samples have shown a good estimate of the average porosity consistent with the gravimetric porosity measurement results. For Profile(trademark) samples with particle sizes ranging between 0.25 to 1 mm and characteristic interparticle pore size of 100 microns the characteristic Darcy scale was estimated to be about delta(sub REV) = 10 mm. Glass beads porosity show clear convergence toward a definite REV which stays constant throughout homogeneous sample. Additional information is included in the original extended abstract.

N E Daidzic↗

Large-Aperture Wide-Bandwidth Anti-Reflection-Coated Silicon Lenses for Millimeter Wavelengths

The increasing scale of cryogenic detector arrays for sub-millimeter and millimeter wavelength astrophysics has led to the need for large aperture, high index of refraction, low loss, cryogenic refracting optics. Silicon with n = 3.4, low loss, and relatively high thermal conductivity is a nearly optimal material for these purposes, but requires an antireflection (AR) coating with broad bandwidth, low loss, low reflectance, and a matched coffecient of thermal expansion. We present an AR coating for curved silicon optics comprised of subwavelength features cut into the lens surface with a custom three axis silicon dicing saw. These features constitute a metamaterial that behaves as a simple dielectric coating. We have fabricated and coated silicon lenses as large as 33.4 cm in diameter with coatings optimized for use between 125-165 GHz. Our design reduces average reflections to a few tenths of a percent for angles of incidence up to 30 deg. with low cross-polarization. We describe the design, tolerance, manufacture, and measurements of these coatings and present measurements of the optical properties of silicon at millimeter wavelengths at cryogenic and room temperatures. This coating and lens fabrication approach is applicable from centimeter to sub-millimeter wavelengths and can be used to fabricate coatings with greater than octave bandwidth.

millimeter wavelength astrophysics↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllectorPrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methaneoxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO(sub 2) is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a H(sub 2)CO(sub 2) recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO(sub 2) hr for 14 hr, (3) the testing of the CO(sub 2) freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH(sub 4) hr and 71.3 g H(sub 2)O hr along with verification of their purity. The resulting 2.22 kg of CH(sub 2)O(sub 2) propellant per 14 hr day (including O(sub 2) from electrolysis of water recovered from regolith, which also supplies the H(sub 2) for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASAs new Mars exploration plans will be discussed.

waste treatment↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllector/PrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methaneoxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (approx. 8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO(sub 2) is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a H(sub 2)CO(sub 2) recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO(sub 2) hr for 14 hr, (3) the testing of the CO(sub 2) freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH(sub 4) hr and 71.3 g H(sub 2)O hr along with verification of their purity. The resulting 2.22 kg of CH(sub 2)O(sub 2) propellant per 14 hr day (including O(sub 2) from electrolysis of water recovered from regolith, which also supplies the H(sub 2) for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASAs new Mars exploration plans will be discussed.

hydrocarbon fuel production↗

Erasing the Milky Way: New Cleaning Technique Applied to GBT Intensity Mapping Data

We present the first application of a new foreground removal pipeline to the current leading HI intensity mapping dataset, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h field data of the GBT observations previously presented in Masui et al. (2013) and Switzer et al. (2013), covering about 41 square degrees at 0.6 less than z is less than 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point source contamination using an independent component analysis technique (fastica), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that fastica is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps is dominated by instrumental noise on small scales which fastica, as a conservative sub-traction technique of non-Gaussian signals, can not mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the Singular Value Decomposition (SVD) method, and confirm that foreground subtraction with fastica is robust against 21cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and fastica are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping datasets.

Wolz, L.↗

Studying Diurnal Variations of Aerosols with NASA MERRA-2 Reanalysis Data

Aerosols play an important role in atmospheric dynamics, climate variations, and Earth's energy cycle by altering the radiation balance in the atmosphere through interaction with clouds, providing fertilizer for forests and canopy, and as a supply of iron to the ocean over long time periods. Studies suggest that much of the feedback between dust aerosols and dynamics is associated with diurnal and synoptic scale variability. However, the lack of sub-daily resolution of aerosols from satellite observations makes it difficult to study the diurnal characteristics, especially over tropical and subtropical regions. Investigation of this topic utilizes over 37 years of simulated global aerosol products from NASA atmospheric reanalysis, in the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data set, available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). MERRA-2 covers the period 1980-present, and is continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using data from MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated using the MERRA-2 aerosol model, which interacts directly with radiation parameterization, and is radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Hourly, monthly, and monthly diurnal data are available at spatial resolution of 0.5o x 0.625o (latitude x longitude). By using MERRA-2 hourly and monthly diurnal products, different aerosol diurnal variabilities are observed over North America, Africa, Asia, and Australia, that may be due to different meteorological conditions and aerosol sources. The presentation will also provide an overview of MERRA-2 data services at GES DISC, such as how to find and download data, and how to quickly visualize and analyze data online with Giovanni.

aerosol↗

Sub-Kelvin Cooling Systems for Quantum Computers

Future large-scale quantum processors (i.e. 100s of qubits), especially those based on superconducting circuits, will require large cooling powers (~10s of microW) at very low temperatures (<50 mK) with stringent temperature stabilities to avoid quantum decoherence and thus guarantee successful operation of such systems. One attractive option for providing this cooling is through Continuous Adiabatic Demagnetization Refrigerators (CADR). Scalable state-of-the-art CADRs at NASA's Goddard Space Flight Center have successfully shown to lift 6 W of heat at 50 mK with a 1 K temperature stability while rejecting its heat to a cryocooler at 4K. Carefully planned and proper heat sinking of cables, attenuators, and microwave components at various temperature stages (between 4K and base temperature) is critical in the cooling architecture of quantum computers and can be provided through proper staging of each unit within the CADR system. As an alternative method of cooling, dilution refrigerators with the potential to meet cooling requirements of emerging large-scale quantum processors are also discussed.

quantum cooling↗

Advanced Materials Development under NASA’s Hybrid Thermally Efficient Core (HyTEC) Project

The Hybrid Thermally Efficient Core (HyTEC) project aims to develop small core turbofan engine technologies that will enable fuel burn reductions, additional use of electric airplane systems through power extraction, and to advance engine operability and compatibility with sustainable aviation fuels. As such, a portfolio of technologies that contribute to raising the pressure, temperature and efficiency of turbofan engine cores needs developed. Included in HyTEC’s technology portfolio to enable these advancements are enhanced combustor liner materials and higher temperature capable turbine blades and vanes manufactured using ceramic matrix composites (CMCs) and environmental barrier coatings (EBCs). These technologies are being developed and tested in laboratory-scale relevant environments to advance the technology readiness level (TRL) to 4 or 5, before moving into an engine core demonstrator to raise the TRL to 6. A new natural gas/oxygen burner rig facility will be used to simulate turbine engine relevant environments at the laboratory/coupon scale. In addition, improvements to enable sub-element, and more complex component testing in NASA Glenn’s combustor facility (CE-5) will be presented.

Ceramic Matrix Composites (CMCs)↗

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗

Enabling Seamless Integration of EV Charging Infrastructure with Weak Electric Grids

Widespread adoption of Electric Vehicles (EVs) for light, medium, and heavy duty (LD, MD, and HD) applications has gained significant interest. Based on ownership and user preferences, LD and local delivery MD EVs are typically connected to grid distribution networks whereas larger MD and HD EVs will be connected to distribution or even sub-transmission networks. Challenges with at-scale EVs and charging infrastructure supporting it include interoperability, distribution network upgrades, demand charges, power quality, voltage stability, etc. Based on real-world data, steady-state and dynamic assessments of LD EV adoption for weak distribution grids is presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Systems Level Fuel Cycle Modeling in TMAP8 - A Demonstration

The tritium migration analysis program (TMAP) has been used for tritium inventory tracking and analysis for several years, and the Multiphysics Object Oriented Simulation Environment (MOOSE)-based TMAP8 has several improvements over TMAP4 and TMAP7, such as support for multiple dimensions and non-cartesian coordinate systems, as well as interoperability with sub-apps at higher and lower length scales. We demonstrate that TMAP8 has the additional capacity to solve systems-level problems using zero-dimensional ordinary differential equations by reproducing a literature model which describes a systems-level fuel-cycle of tritium inventory in a hypothetical fusion power plant. The capacity to run several coupled multi-scale physics calculations as part of a single package will be necessary for accurate blanket and fuel-cycle design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗