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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗
NASA NTRS1992

Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data

A radiative transfer algorithm is combined with digital elevation and satellite reflectance data to model spatial variability in net solar radiation at fine spatial resolution. The method is applied to the tall-grass prairie of the 16 x 16 sq km FIFE site (First ISLSCP Field Experiment) of the International Satellite Land Surface Climatology Project. Spectral reflectances as measured by the Landsat Thematic Mapper (TM) are corrected for atmospheric and topographic effects using field measurements and accurate 30-m digital elevation data in a detailed model of atmosphere-surface interaction. The spectral reflectances are then integrated to produce estimates of surface albedo in the range 0.3-3.0 microns. This map of albedo is used in an atmospheric and topographic radiative transfer model to produce a map of net solar radiation. A map of apparent net solar radiation is also derived using only the TM reflectance data, uncorrected for topography, and the average field-measured downwelling solar irradiance. Comparison with field measurements at 10 sites on the prairie shows that the topographically derived radiation map accurately captures the spatial variability in net solar radiation, but the apparent map does not.

Dubayah, R.↗
NASA NTRS1989

Low-altitude signatures of the cusp and flux transfer events

Cusp-like ion injection was studied using DE-2 satellite data obtained during strongly southward IMF. Although magnetosheath ion injection signatures are detected, the satellite motion and convection are opposed, and it is suggested that the observed falling energy dispersion of the precipitating ions may have arisen from a static moving or growing source. The spatial scale of the flux is found to be typical of that of a flux transfer event (FTE). A simple model of the ionospheric signature of an FTE is able to reproduce the observed electric and magnetic field perturbations. Precipitating electrons with peak energies of about 100 eV lie on the predicted boundary of the newly opened tube and are similar to those noted on the edges of FTEs at the magnetopause.

Lockwood, Mike↗
NASA NTRS2011

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Davis, Bruce↗
DOE OSTI2020

Metal Halide Scintillators with Fast and Self‐Absorption‐Free Defect‐Bound Excitonic Radioluminescence for Dynamic X‐Ray Imaging

Abstract Scintillators for radiation detection are of great significance in medical imaging, security, and nondestructive inspection. The current challenge for scintillators is to simultaneously achieve high scintillation light yield, fast radioluminescence, simple film fabrication, large X‐ray attenuation efficiency as well as stable and nontoxic compositions; no previous scintillators fulfill all the above requirements. Here, metal halide Rb 2 AgBr 3 , possessing defect‐bound excitonic radioluminescence, is shown as efficient and fast scintillators. This nontoxic and stable scintillator emits from excitons bound to neutral bromine vacancies, enjoying an efficient and spin‐allowed fast emission with minimized self‐absorption. Rb 2 AgBr 3 thus has a high light yield (25 600 photons MeV −1 ), fast scintillation decay time (5.31 ns), and a record value of light yield versus decay time (4821 photons MeV −1 ns −1 ). The close‐space sublimation method is developed for fast and scalable fabrication of oriented Rb 2 AgBr 3 films. The scintillator film is further integrated with commercial flat‐panel imagers, and the spatial resolution reaches 10.2 line pairs per millimeter at the modulation transfer function of 0.2, doubling the resolution of conventional CsI:Tl flat‐panel detectors. The dynamic X‐ray imaging and its use to real‐time monitoring of bone movement without ghosting effect is also demonstrated.

Zhang, Muyi↗
DOE OSTI2022

Enhanced deep neural networks with transfer learning for distribution LMP considering load and PV uncertainties

As the flexibility of generation and demand increases in distribution systems, the residential loads are emerging as a promising means to participate in demand response and the transactive energy market. Market pricing is an instrumental mechanism for the distribution system operator to exploit the full potential of the flexible resources. The distribution locational marginal price (DLMP) can be used to guide the residential load consumption. This type of market signal helps the distribution system operator to optimize the scheduling of all resources while satisfying related network constraints through a day-ahead market. However, solving the optimization problem for large-scale systems can be computationally expensive. To address the scalability and practicability limitations of the DLMP framework, a learning-based approach is proposed in this paper to complement the day-ahead distribution market framework. Here, the proposed approach combines long short-term memory and transfer learning to develop deep neural network that can capture the spatial–temporal correlation of the input data. The model can determine the optimal DLMP for each node in a distribution system without the system parameters required to formulate the optimization problem. Testing results on IEEE 33-bus and 123-bus systems show that the proposed approach can generate a comparable DLMP against the optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Polarity Asymmetries in Rocket‐Triggered Lightning

Abstract The dissonant development of positive and negative lightning leaders is a central question in atmospheric electricity. It is also the likely root cause of other reported asymmetries between positive and negative lightning flashes, including the ones regarding: stroke multiplicity, recoil activity, leader velocities, and emission of energetic radiation. In an effort to contrast lightning leaders of different polarities, we highlight the staggering differences between two rocket‐triggered lightning flashes. The flash beginning with upward positive leaders exhibits an initial continuous current stage followed by multiple sequences of dart leaders and return strokes. On the other, in its opposite‐polarity counterpart, the upward development of negative leaders is by itself the entire flash. As a result, the flash with negative leaders is faster, briefer, transfers less charge to the ground, has lower currents, and smaller spatial extent. We conclude by presenting a discussion on the three fundamental leader propagation modes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Synergy of semiempirical models and machine learning in computational chemistry

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort—design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Measuring the growth of Alfvén wave parametric decay instability using counter-propagating waves: Theory and simulations

The parametric decay instability (PDI) of Alfvén waves—where a pump Alfvén wave decays into a backward-propagating child Alfvén wave and a forward ion acoustic wave—is a fundamental nonlinear wave-wave interaction and holds significant implications for space and laboratory plasmas. However, to date there has been no direct experimental measurement of PDI. Here, we propose a novel and experimentally viable scheme to quantify the growth of Alfvén wave PDI on a linear device using a large pump Alfvén wave and a small counter-propagating seed Alfvén wave, with the seed-wave frequency tuned to match the backward Alfvén wave generated by standard PDI. Using hybrid simulations, we show that energy transfer from the pump to the seed reduces the latter's spatial damping. By comparing seed-wave amplitudes with and without the pump wave, this damping reduction can be used as a direct and reliable proxy for PDI growth. The method is validated in our simulations across a range of plasma and wave parameters and agrees well with theoretical predictions. Notably, the scheme exhibits no threshold for PDI excitation and is, in principle, readily implementable under current laboratory conditions. Finally, this scheme is a critical step toward solving the challenge of experimentally accessing Alfvén wave PDI and provides an elegant method that may be used to validate fundamental theories of parametric instabilities in controlled laboratory settings.

heliosphere↗
NASA NTRS1972

The liquid crystal light valve, an optical-to-optical interface device

A photoactivated liquid crystal light valve is described as an optical-to-optical interface device (OTTO) which is designed to transfer an optical image from a noncoherent light beam to a spatially coherent beam of light, in real time. Schematics of OTTO in use, the liquid cyrstal cell, and the liquid crystal structure are presented. Sensitivity characteristics and the principles of operation are discussed.

Jacobson, A. D.↗
NASA NTRS1983

LANDSAT-D investigations in snow hydrology

Progress on the registration of TM data to digital topographic data; on comparison of TM, MSS and NOAA meteorological satellite data for snowcover mapping; and on radiative transfer models for atmospheric correction is reported. Some methods for analyzing spatial contiguity of snow within the snow covered area were selected. The methods are based on a two-channel version of the grey level co-occurence matrix, combined with edge detection derived from an algorithm for computing slopes and exposures from digital terrain data.

Dozier, J.↗
NASA NTRS1982

Honeywell multispectral linear array (MLA) instrument design A system overview

In support of NASA's Experimental Land Observing System, a simple, reliable and relatively inexpensive multispectral linear array (MLA) instrument concept has been developed. The design satisfies requirements for multichannel radiometry and wide field imaging. A reflective off-axis anastigmat telescope is mounted in a highly strength-to-weight efficient truss structure, coupled to a solid beamsplitter assembly. Attention is given to the optical design of the MLA instrument, the telescope structure, the detector arrays, detector cooling, on-orbit calibration, signal processing electronics, the spacecraft interfaces, the modulation transfer function, the signal-to-noise ratio, radiometric accuracy, and spatial registration.

Eyring, D.↗
NASA NTRS1989

Radiative transfer theory for inhomogeneous media with random extinction and scattering coefficients

The small-angle scattering approximation of the scalar radiative transfer equation (RTE) is examined for the case where the extinction and scattering coefficients have a component that is a deterministic function of position along the propagation path and a component that is a random function of position transverse to the propagation direction. It is found that the resulting stochastic RTE can be reduced to a system of two stochastic integrodifferential equations for the average and fluctuating components of the radiant intensity. Two transfer equations are obtained describing the average radiant intensity and the spatial correlation function of the intensity fluctuations. The average intensity equation is then solved and applied to a simple propagation scenario. An approximate solution is also derived for the equation giving the correlation function. The developed equations can be applied to problems involving short wavelength electromagnetic wave propagation through media possessing the variable characteristics of turbulence and turbidity, such as plasmas, the atmosphere, and the ocean.

Manning, Robert M.↗
NASA NTRS1990

Diverter Decision Aiding for In-Flight Diversions

It was determined that artificial intelligence technology can provide pilots with the help they need in making the complex decisions concerning en route changes in a flight plan. A diverter system should have the capability to take all of the available information and produce a recommendation to the pilot. Phase three illustrated that using Joshua to develop rules for an expert system and a Statice database provided additional flexibility by permitting the development of dynamic weighting of diversion relevant parameters. This increases the fidelity of the AI functions cited as useful in aiding the pilot to perform situational assessment, navigation rerouting, flight planning/replanning, and maneuver execution. Additionally, a prototype pilot-vehicle interface (PVI) was designed providing for the integration of both text and graphical based information. Advanced technologies were applied to PVI design, resulting in a hierarchical menu based architecture to increase the efficiency of information transfer while reducing expected workload. Additional efficiency was gained by integrating spatial and text displays into an integrated user interface.

Rudolph, Frederick M.↗
NASA NTRS1996

The Effects of Dissipation and Coarse Grid Resolution for Multigrid in Flow Problems

The objective of this paper is to investigate the effects of the numerical dissipation and the resolution of the solution on coarser grids for multigrid with the Euler equation approximations. The convergence is accomplished by multi-stage explicit time-stepping to steady state accelerated by FAS multigrid. A theoretical investigation is carried out for linear hyperbolic equations in one and two dimensions. The spectra reveals that for stability and hence robustness of spatial discretizations with a small amount of numerical dissipation the grid transfer operators have to be accurate enough and the smoother of low temporal accuracy. Numerical results give grid independent convergence in one dimension. For two-dimensional problems with a small amount of numerical dissipation, however, only a few grid levels contribute to an increased speed of convergence. This is explained by the small numerical dissipation leading to dispersion. Increasing the mesh density and hence making the problem over resolved increases the number of mesh levels contributing to an increased speed of convergence. If the steady state equations are elliptic, all grid levels contribute to the convergence regardless of the mesh density.

Eliasson, Peter↗
NASA NTRS2003

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Taylor, Jaime R.↗
NASA NTRS2010

Optical Imaging and Radiometric Modeling and Simulation

OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge diffusion modulation transfer function (MTF).

Ha, Kong Q.↗