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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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At least 181 records · Page 10

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NASA NTRS1976

The quantitative properties of three soft X-ray flare kernels observed with the AS&E X-ray telescope on Skylab

The physical parameters for the kernels of three solar X-ray flare events have been deduced using photographic data from the S-054 X-ray telescope on Skylab as the primary data source and 1-8 and 8-20 A fluxes from Solrad 9 as the secondary data source. The kernels had diameters of about 5-7 seconds of arc and in two cases electron densities at least as high as 0.3 trillion per cu cm. The lifetimes of the kernels were 5-10 min. The presence of thermal conduction during the decay phases is used to argue: (1) that kernels are entire, not small portions of, coronal loop structures, and (2) that flare heating must continue during the decay phase. We suggest a simple geometric model to explain the role of kernels in flares in which kernels are identified with emerging flux regions.

Kahler, S. W.↗

NASA NTRS1979

Colorimetry and magnitudes of asteroids

In the present paper, 1500 UBV observations are analyzed by a new rather general multiple scattering theory which provided clear insight into previously poorly-recognized optical nature of asteroid surfaces. Thus, phase curves are shown to consist of a surface-texture controlled component, due to singly scattered light, and a component due to multiple scattering. Phase curve shapes can be characterized by a single parameter, the multiple scattering factor, Q. As Q increases, the relative importance of the opposition effect diminishes. Asteroid surfaces are particulate and strikingly similar to texture, being moderately porous and moderately rough on a scale greater than the wavelength of light. In concequence, Q (and also the phase coefficient) correlate well with geometric albedo, and there exists a purely photometric means of determining albedos and diameters.

Bowell, E.↗

NASA NTRS1984

Interlaminar fracture of random short-fiber SMC composite

In the experimental phase of the present study of the interlaminar fracture behavior of a randomly oriented short fiber sheet molding compound (SMC) composite, the double cantilever beam fracture test is used to evaluate the mode I interlaminar fracture toughness of different composite thicknesses. In the analytical phase of this work, a geometrically nonlinear analysis is introduced in order to account for large deflections and nonlinear load deflection curves in the evaluation of interlaminar fracture toughness. For the SMC-R50 material studied, interlaminar toughness is an order of magnitude higher than that of unreinforced neat resin, due to unusual damage mechanisms ahead of the crack tip, together with significant fiber bridging across crack surfaces. Composite thickness effects on interlaminar fracture are noted to be appreciable, and a detailed discussion is given on the influence of SMC microstructure.

Wang, S. S.↗

NASA NTRS1985

Dynamic Thermophysical Measurements in Space

The objective is to develop techniques for the dynamic measurement of selected thermophysical properties (e.g., heat of fusion, heat capacity, electrical resistivity) of solids and liquids at temperatures above 2000 K in a near zero-gravity environment. The first phase involves establishing the stability (geometrical) limits of specimens when rapidly heated to temperatures beyond their melting point. A test equipment package was designed and constructed for this purpose, consisting of removable specimen cartridge cells, a battery-bank power supply, a high-speed framing camera, a single-wavelength pyrometer, and electronic switching and control equipment. The operation of the equipment package was tested in the laboratory in preparation for near zero-gravity experiments to be performed during a KC-135 flight in September, 1984.

Cezairliyan, A.↗

NASA NTRS1988

Precise orbit determination for NASA's Earth Observing System using GPS

A precision orbit determination technique for NASA's Earth Observing System (EOS) is discussed. The technique exploits the redundant geometric information from GPS carrier phase and P-code pseudorange measurements and minimizes the requirements for precision dynamical modeling. Performance estimates for the application of the technique to the orbit geometry planned for the EOS platforms show that decimeter accuracies of orbit position may be obtained. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and earth gravity are presented.

Williams, Bobby G.↗

NASA NTRS2011

Properties of a Variable-Delay Polarization Modulator

We investigate the polarization modulation properties of a variable-delay polarization modulator (VPM). The VPM modulates polarization via a variable separation between a polarizing grid and a parallel mirror. We find that in the limit where the wavelength is much larger than the diameter of the metal wires that comprise the grid, the phase delay derived from the geometric separation between the mirror and the grid is sufficient to characterize the device. However, outside of this range, additional parameters describing the polarizing grid geometry must be included to fully characterize the modulator response. In this paper, we report test results of a VPM at wavelengths of 350 micron and 3 mm. Electromagnetic simulations of wire grid polarizers were performed and are summarized using a simple circuit model that incorporates the loss and polarization properties of the device.

Chuss, David T.↗

DOE OSTI2020

Deep Learning-Based Queue-Aware Eco-Approach and Departure System for Plug-In Hybrid Electric Buses at Signalized Intersections: A Simulation Study

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency. Based on optimal solutions obtained from the graph-based trajectory planning algorithm (GTPA), a deep neural network (DNN) is developed to learn the optimal vehicle speed for the next time step given its current state. It is demonstrated that the trained DNN can provide energy-efficient trajectories with high computational efficiency and high flexibility adopting to dynamic changes in the surrounding environment. To address the impact of downstream traffic, a queue prediction model is further developed using data from radars and connected vehicles (CVs), as well as signal timing data from SPaT messages. A comprehensive simulation study in the microscopic traffic modeling software PTV VISSIM shows that the proposed DLQ-EAD can achieve 18.7%-24.0% energy efficiency improvements for a single PHEB on various traffic congestion levels. The proposed queue prediction model can be of practical significance even at low penetration rates of CVs. Specifically, additional energy savings of 2.0%-8.2% can be further achieved with 20% vehicles in the network.

Ye, Fei↗

DOE OSTI2025

Quantum geometry embedded in unitarity of evolution: Revealing its impacts as geometric oscillation and dephasing in spin resonance and crystal bands

Quantum Hall effects provide intuitive ways of revealing the topology in crystals, i.e., each quantized “step” represents a distinct topological state. Here, we seek a counterpart for “visualizing” quantum geometry, which is a broader concept. Here we show how geometry emerges in quantum as an intrinsic consequence of unitary evolution, composing a framework compatible with quantum metric and independent of specific details or approximations, suggesting quantum geometry may have widespread applicability. Indeed, we exemplify geometric observables, such as oscillation, dephasing, in magnetic resonance or band driving scenarios. Anomalies, supported by both analytic and numerical solutions, underscore the advantages of adopting a geometric perspective, potentially yielding distinguishable experimental signatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1988

Precise orbit determination for NASA's earth observing system using GPS (Global Positioning System)

An application of a precision orbit determination technique for NASA's Earth Observing System (EOS) using the Global Positioning System (GPS) is described. This technique allows the geometric information from measurements of GPS carrier phase and P-code pseudo-range to be exploited while minimizing requirements for precision dynamical modeling. The method combines geometric and dynamic information to determine the spacecraft trajectory; the weight on the dynamic information is controlled by adjusting fictitious spacecraft accelerations in three dimensions which are treated as first order exponentially time correlated stochastic processes. By varying the time correlation and uncertainty of the stochastic accelerations, the technique can range from purely geometric to purely dynamic. Performance estimates for this technique as applied to the orbit geometry planned for the EOS platforms indicate that decimeter accuracies for EOS orbit position may be obtainable. The sensitivity of the predicted orbit uncertainties to model errors for station locations, nongravitational platform accelerations, and Earth gravity is also presented.

Williams, B. G.↗

NASA NTRS1987

Detection of reflector surface error from near-field data: Effect of edge diffracted field

The surface accuracy of large reflector antennas must be maintained within certain tolerances if high gain/low sidelobe performance is to be achieved. Thus the measurement of the surface profile is an important part of the quality control procedure when constructing antennas of this type. An efficient method for surface profile measurement has been proposed, i.e., the reflector surface is calculated from the measured near-field phase data using the theory of geometric optics. For a surface profile calculation of this kind, it is necessary to know the margin of error built into the method of calculation. This will enable a specification of the tolerance from which the surface profile can be determined. When calculating the surface profile from near-field phase data, there are two main sources of error. The first is the measurement error in near-field phase data. The second arises from the edge diffracted fields that are superimposed on the reflected fields in the measured near-field data. The error in the calculated surface profile produced by the edge diffracted fields is examined.

Cherrette, Alan R.↗

DOE OSTI2022

Strain-tuning of transport gaps and semiconductor-to-conductor phase transition in twinned graphene

We show, through the use of the Landauer-Büttiker (LB) formalism and a tight-binding (TB) model, that the transport gap of twinned graphene can be tuned through the application of a uniaxial strain in the direction normal to the twin band. Remarkably, we find that the transport gap E gap bears a square-root dependence on the control parameter ϵ x – ϵ c , where ϵ x is the applied uniaxial strain and ϵ c ~ 19% is a critical strain. We interpret this dependence as evidence of criticality underlying a continuous phase transition, with ϵ x – ϵ c playing the role of control parameter and the transport gap E gap playing the role of order parameter. For ϵ x < ϵ c , the transport gap is non-zero and the material is semiconductor, whereas for ϵ x < ϵ c the transport gap closes to zero and the material becomes conductor, which evinces a semiconductor-to-conductor phase transition. The computed critical exponent of 1/2 places the transition in the meanfield universality class, which enables far-reaching analogies with other systems in the same class.

36 MATERIALS SCIENCE↗

NASA NTRS1987

On the theory of the synthesis of single and dual offset shaped reflector antennas

Two reflectors shaped so as to transforn a geometrical optics (GO) feed power pattern into a uniform amplitude and phase aperture distribution are indicated schematically. Single- and dual-shaped geometrical optics problems are solved via exact solutions obtained by progressive integration. It is concluded that an infinite set of such solutions exists.

Galindo-Israel, Victor↗

DOE OSTI2022

Accurate tight-binding model for twisted bilayer graphene describes topological flat bands without geometric relaxation

A major hurdle in understanding the phase diagram of twisted bilayer graphene is the roles of lattice relaxation and electronic structure on isolated band flattening near magic twist angles. Here in this work, the authors develop an accurate local environment tight-binding model fit to tight-binding parameters computed from ab initio density-functional theory calculations across many atomic configurations. With the accurate parametrization, it is found that the magic angle shifts to slightly lower angles than often quoted, from around 1.05° to around 0.99°, and that isolated flat bands appear for rigidly rotated graphene layers, with enhancement of the flat bands when the layers are allowed to distort. Study of the orbital localization supports the emergence of fragile topology in the isolated flat bands without the need for lattice relaxation.

36 MATERIALS SCIENCE↗

NASA NTRS2020

A Fast Evaluation of PDA Experimental Parameters Using Mie Scattering to Enhance the Measurement Accuracy of Droplet Size Distributions

The Phase Doppler technique (PDA) and its implementation generally relies on a geometric optics formulation for light scattering to estimate drop sizes from the measured phase differences between Doppler signals from two or more detectors. Although this limits experimental PDA scattering geometries to those where only one component of the geometric scatter is dominant, the calculations are relatively simple. This TM describes a fast method to evaluate PDA experimental parameters analytically using Mie scattering that provides a performance estimate of all possible configurations. The best configurations are fully tested using a Monte Carlo simulation to obtain a more accurate capability estimate for each one.

PDA↗

DOE OSTI2021

Phase‐Change‐Memory Process at the Limit: A Proposal for Utilizing Monolayer Sb 2 Te 3

Abstract One central task of developing nonvolatile phase change memory (PCM) is to improve its scalability for high‐density data integration. In this work, by first‐principles molecular dynamics, to date the thinnest PCM material possible (0.8 nm), namely, a monolayer Sb 2 Te 3 , is proposed. Importantly, its SET (crystallization) process is a fast one‐step transition from amorphous to hexagonal phase without the usual intermediate cubic phase. An increased spatial localization of electrons due to geometrical confinement is found to be beneficial for keeping the data nonvolatile in the amorphous phase at the 2D limit. The substrate and superstrate can be utilized to control the phase change behavior: e.g., with passivated SiO 2 (001) surfaces or hexagonal Boron Nitride, the monolayer Sb 2 Te 3 can reach SET recrystallization in 0.54 ns or even as fast as 0.12 ns, but with unpassivated SiO 2 (001), this would not be possible. Besides, working with small volume PCM materials is also a natural way to lower power consumption. Therefore, the proposed PCM working process at the 2D limit will be an important potential strategy of scaling the current PCM materials for ultrahigh‐density data storage.

2D limit↗

NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗

DOE OSTI2022

Non-magnetic ion site disorder effects on the quantum magnetism of a spin-1/2 equilateral triangular lattice antiferromagnet

Here, with the motivation to study how non-magnetic ion site disorder affects the quantum magnetism of Ba 3 CoSb 2 O 9 , a spin-1/2 equilateral triangular lattice antiferromagnet, we performed DC and AC susceptibility, specific heat, elastic and inelastic neutron scattering measurements on single crystalline samples of Ba 2.87 Sr 0.13 CoSb 2 O 9 with Sr doping on non-magnetic Ba 2+ ion sites. The results show that Ba 2.87 Sr 0.13 CoSb 2 O 9 exhibits (i) a two-step magnetic transition at 2.7 K and 3.3 K, respectively; (ii) a possible canted 120 degree spin structure at zero field with reduced ordered moment as 1.24 μ B /Co; (iii) a series of spin state transitions for both H∥ab-plane and H∥c-axis. For H∥ab-plane, the magnetization plateau feature related to the up–up–down phase is significantly suppressed; (iv) an inelastic neutron scattering spectrum with only one gapped mode at zero field, which splits to one gapless and one gapped mode at 9 T. All these features are distinctly different from those observed for the parent compound Ba 3 CoSb 2 O 9 , which demonstrates that the non-magnetic ion site disorder (the Sr doping) plays a complex role on the magnetic properties beyond the conventionally expected randomization of the exchange interactions. We propose the additional effects including the enhancement of quantum spin fluctuations and introduction of a possible spatial anisotropy through the local structural distortions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Non-equilibrium dynamics in geometrically frustrated spin glass Bi 2 Fe 3 GaO 9 with a Cairo lattice

We have explored the magnetic relaxation of the spin glass phase in Bi 2 Fe 3 GaO 9 , a geometrically frustrated magnet with a unique Cairo lattice made of pentagonal building blocks. Using dc magnetization measurements, we find the relaxation behavior in single crystals follows the Arrhenius law as a function of temperature but remains relatively constant under different magnetic fields. Through a carefully designed protocol, we observe significant rejuvenation and memory effects, reminiscent of classical dilute spin glasses rather than spin jamming systems. Our finding suggests that Bi 2 Fe 3 GaO 9 is probably located in the crossover between conventional spin glass and perfect spin jam and thus provides an excellent platform for investigating the evolution of underlying magnetic structure, paving the way for further neutron scattering research.

aging↗