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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Process modelling for materials preparation experiments

The main goals of the research under this grant consist of the development of mathematical tools and measurement techniques for transport properties necessary for high fidelity modelling of crystal growth from the melt and solution. Of the tasks described in detail in the original proposal, two remain to be worked on: development of a spectral code for moving boundary problems, and development of an expedient diffusivity measurement technique for concentrated and supersaturated solutions. We have focused on developing a code to solve for interface shape, heat and species transport during directional solidification. The work involved the computation of heat, mass and momentum transfer during Bridgman-Stockbarger solidification of compound semiconductors. Domain decomposition techniques and preconditioning methods were used in conjunction with Chebyshev spectral methods to accelerate convergence while retaining the high-order spectral accuracy. During the report period we have further improved our experimental setup. These improvements include: temperature control of the measurement cell to 0.1 C between 10 and 60 C; enclosure of the optical measurement path outside the ZYGO interferometer in a metal housing that is temperature controlled to the same temperature setting as the measurement cell; simultaneous dispensing and partial removal of the lower concentration (lighter) solution above the higher concentration (heavier) solution through independently motor-driven syringes; three-fold increase in data resolution by orientation of the interferometer with respect to diffusion direction; and increase of the optical path length in the solution cell to 12 mm.

Rosenberger, Franz↗
NASA NTRS1972

An evaluation of random analysis methods for the determination of panel damping

An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.

Bhat, W. V.↗
NASA NTRS1982

Spectral estimates of intercepted solar radiation by corn and soybean canopies

Attention is given to the development of methods for combining spectral and meteorological data in crop yield models which are capable of providing accurate estimates of crop condition and yields throughout the growing season. The present investigation is concerned with initial tests of these concepts using spectral and agronomic data acquired in controlled experiments. The data were acquired at the Purdue University Agronomy Farm, 10 km northwest of West Lafayette, Indiana. Data were obtained throughout several growing seasons for corn and soybeans. Five methods or models for predicting yields were examined. On the basis of the obtained results, it is concluded that estimating intercepted solar radiation using spectral data is a viable approach for merging spectral and meteorological data in crop yield models.

Gallo, K. P.↗
NASA NTRS1985

Calibration of AIS Data Using Ground-based Spectral Reflectance Measurements

Present methods of correcting airborne imaging spectrometer (AIS) data for instrumental and atmospheric effects include the flat- or curved-field correction and a deviation-from-the-average adjustment performed on a line-by-line basis throughout the image. Both methods eliminate the atmospheric absorptions, but remove the possibility of studying the atmosphere for its own sake, or of using the atmospheric information present as a possible basis for theoretical modeling. The method discussed here relies on use of ground-based measurements of the surface spectral reflectance in comparison with scanner data to fix in a least-squares sense parameters in a simplified model of the atmosphere on a wavelength-by-wavelength basis. The model parameters (for optically thin conditions) are interpretable in terms of optical depth and scattering phase function, and thus, in principle, provide an approximate description of the atmosphere as a homogeneous body intervening between the sensor and the ground.

Conel, J. E.↗
NASA NTRS2009

Improving 3D Wavelet-Based Compression of Hyperspectral Images

Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a manner similar to that of a baseline hyperspectral- image-compression method. The mean values are encoded in the compressed bit stream and added back to the data at the appropriate decompression step. The overhead incurred by encoding the mean values only a few bits per spectral band is negligible with respect to the huge size of a typical hyperspectral data set. The other method is denoted modified decomposition. This method is so named because it involves a modified version of a commonly used multiresolution wavelet decomposition, known in the art as the 3D Mallat decomposition, in which (a) the first of multiple stages of a 3D wavelet transform is applied to the entire dataset and (b) subsequent stages are applied only to the horizontally-, vertically-, and spectrally-low-pass subband from the preceding stage. In the modified decomposition, in stages after the first, not only is the spatially-low-pass, spectrally-low-pass subband further decomposed, but also spatially-low-pass, spectrally-high-pass subbands are further decomposed spatially. Either method can be used alone to improve the quality of a reconstructed image (see figure). Alternatively, the two methods can be combined by first performing modified decomposition, then subtracting the mean values from spatial planes of spatially-low-pass subbands.

Klimesh, Matthew↗
NASA NTRS2018

Cloud Atlas: Rotational Modulations in the L/T Transition Brown Dwarf Companion HN Peg B

Time-resolved observations of brown dwarfs' rotational modulations provide powerful insights into the properties of condensate clouds in ultra-cool atmospheres. Multi-wavelength light curves reveal cloud vertical structures, condensate particle sizes, and cloud morphology, which directly constrain condensate cloud and atmospheric circulation models. We report results from Hubble Space Telescope/Wide Field Camera 3 (WFC3) near-infrared G141 taken in six consecutive orbits observations of HNPeg B, an L/T transition brown dwarf companion to a G0V type star. The best-fit sine wave to the 1.1 to 1.7 micron broadband light curve has the amplitude of and period of hour. The modulation amplitude has no detectable wavelength dependence except in the 1.4 micron water absorption band, indicating that the characteristic condensate particle sizes are large (greater than 1 micron). We detect significantly (4.4 sigma) lower modulation amplitude in the 1.4 micron water absorption band, and find that HN Peg B's spectral modulation resembles those of early T type brown dwarfs. We also describe a new empirical interpolation method to remove spectral contamination from the bright host star. This method may be applied in other high-contrast time-resolved observations with WFC3.

brown dwarf↗
NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗
NASA NTRS1987

A well-posed optimal spectral element approximation for the Stokes problem

A method is proposed for the spectral element simulation of incompressible flow. This method constitutes in a well-posed optimal approximation of the steady Stokes problem with no spurious modes in the pressure. The resulting method is analyzed, and numerical results are presented for a model problem.

Maday, Y.↗
NASA NTRSDate not supplied

Optimizing spectroheliogram deconvolution methods : MaGIXS - A case study

Over the past five years, new methods to reconstruct spectrally pure maps of the Sun from spectroheliogram data have emerged. In particular, with the rebirth of long-abandoned slitless imaging spectroscopy, one may obtain both spatial and spectral information over a large field of view simultaneously. Yet, depending on the size of the extended source combined with the extent of spectral dispersion, there will be locations in the focal plane where spectral lines from different spatial locations overlap and must be deconvolved. An unfolding method has been successfully developed and demonstrated on the recent rocket flight MaGIXS, which observed several strong emission lines (9 to 30$\AA$) from different portions of two active regions. In the work we are going to present, we conduct a systematic investigation of the parameters that controls and optimizes the inversion method to unfold overlappogram data. We also demonstrate a derived method of the inversion that does not require previous assumptions on the thermal and ionization equilibrium and abundance state of the plasma.

Spectroheliogram↗
NASA NTRS2011

Micro spectrometer for parallel light and method of use

A spectrometer system includes an optical assembly for collimating light, a micro-ring grating assembly having a plurality of coaxially-aligned ring gratings, an aperture device defining an aperture circumscribing a target focal point, and a photon detector. An electro-optical layer of the grating assembly may be electrically connected to an energy supply to change the refractive index of the electro-optical layer. Alternately, the gratings may be electrically connected to the energy supply and energized, e.g., with alternating voltages, to change the refractive index. A data recorder may record the predetermined spectral characteristic. A method of detecting a spectral characteristic of a predetermined wavelength of source light includes generating collimated light using an optical assembly, directing the collimated light onto the micro-ring grating assembly, and selectively energizing the micro-ring grating assembly to diffract the predetermined wavelength onto the target focal point, and detecting the spectral characteristic using a photon detector.

Park, Yeonjoon↗
NASA NTRS1990

Numerical investigation of the spreading of self-excited stratified jets

The structure and evolution of self-excited subsonic periodic arrays of jets of constant and variable density are studied using spectral-element direct numerical simulations. The governing equation of motion is presented, and a method based on spectral element discretizations appropriate for simulating arbitrarily complex geometry jets and large density variations for subsonic flows is developed. Variable density fields are found to be more unstable than the corresponding uniform density fields with much higher rms values; as a result, their spreading is also considerably larger. There is a dramatic increase in spreading after a few pairings occur. Findings presented for low and high side-momentum flux reveal a shifting of the origin of instability from the near-field to the far-field, respectively, and suggest possible routes of stabilization.

Batcho, P. F.↗
DOE OSTI2023

On the Approximability of Random-Hypergraph MAX-3-XORSAT Problems with Quantum Algorithms

Constraint satisfaction problems are an important area of computer science. Many of these problems are in the complexity class NP which is exponentially hard for all known methods, both for worst cases and often typical. Fundamentally, the lack of any guided local minimum escape method ensures the hardness of both exact and approximate optimization classically, but the intuitive mechanism for approximation hardness in quantum algorithms based on Hamiltonian time evolution is poorly understood. We explore this question using the prototypically hard MAX-3-XORSAT problem class. We conclude that the mechanisms for quantum exact and approximation hardness are fundamentally distinct. We qualitatively identify why traditional methods such as quantum adiabatic optimization are not good approximation algorithms. We propose a new spectral folding optimization method that does not suffer from these issues and study it analytically and numerically. We consider random rank-3 hypergraphs including extremal planted solution instances, where the ground state satisfies an anomalously high fraction of constraints compared to truly random problems. We show that, if we define the energy to be $E = N_{unsat}-N_{sat}$, then spectrally folded quantum optimization will return states with energy $E \leq A E_{GS}$ (where $E_{GS}$ is the ground state energy) in polynomial time, where conservatively, $A \simeq 0.6$. We thoroughly benchmark variations of spectrally folded quantum optimization for random classically approximation-hard (planted solution) instances in simulation, and find performance consistent with this prediction. We do not claim that this approximation guarantee holds for all possible hypergraphs, though our algorithm's mechanism can likely generalize widely. These results suggest that quantum computers are more powerful for approximate optimization than had been previously assumed.

Kapit, Eliot↗
DOE OSTI2020

Real-space formulation of the stress tensor for O (N) density functional theory: Application to high temperature calculations

We present an accurate and efficient real-space formulation of the Hellmann–Feynman stress tensor for O (N) Kohn–Sham density functional theory (DFT). While applicable at any temperature, the formulation is most efficient at high temperature where the Fermi–Dirac distribution becomes smoother and the density matrix becomes correspondingly more localized. We first rewrite the orbital-dependent stress tensor for real-space DFT in terms of the density matrix, thereby making it amenable to O (N) methods. We then describe its evaluation within the O (N) infinite-cell Clenshaw–Curtis Spectral Quadrature (SQ) method, a technique that is applicable to metallic and insulating systems, is highly parallelizable, becomes increasingly efficient with increasing temperature, and provides results corresponding to the infinite crystal without the need of Brillouin zone integration. We demonstrate systematic convergence of the resulting formulation with respect to SQ parameters to exact diagonalization results and show convergence with respect to mesh size to the established plane wave results. Here, we employ the new formulation to compute the viscosity of hydrogen at 10 6 K from Kohn–Sham quantum molecular dynamics, where we find agreement with previous more approximate orbital-free density functional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Intelligent multi-spectral IR image segmentation

We present a neural network based multi-­‐spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. The neural net based segmentation method is compared with Wavelet-­‐threshold and Grab-­‐Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-­‐spectral IR images.

Torres, Gilbert↗
NASA NTRS1998

Spaceborne Simulations of Two Direct-Detection Doppler Lidar Techniques

Direct-detection (or incoherent) lidar is now a proven technique for measuring winds in the atmosphere. Over the last few years, several types of direct-detection lidar have evolved. These methods rely on Fabry-Perot interferometers(also termed etalons) or other narrow-passband filters to provide the required spectral resolution. One method, now called the edge (EDG) technique, uses a sharply-sloping filter and measures changes in the filter transmission caused by Doppler shifting of the laser wavelength. A variation of the EDG method, called the double-edge (DEDG) technique, uses two filters. The molecular DEDG method was first demonstrated by Chanin et al. for stratospheric measurements and more recently Korb et al. successfully demonstrated the aerosol DEDG through the troposphere. A second method, here termed the multi-channel (MC) technique, measures Doppler shifts by observing angular displacement of a Fabry-Perot fringe in a spatially resolving detector. The EDG technique thus employs the Fabry-Perot to convert the frequency shift into an amplitude signal, while the MC technique uses the Fabry-Perot to resolve the spectral signature which is then fitted to determine the centroid. The focus of this presentation is on the DEDG and MC methods because these are viewed as the current state of the art in direct-detection lidar. Successful ground-based demonstrations of direct-detection wind measurements have resulted in proposals for spaceborne systems. With this new emphasis on spaceborne systems comes the need for accurate prediction of spaceborne direct-detection Doppler lidar performance. Previously, the EDG and MC methods have been compared although only for aerosol Doppler systems. A recent paper by McGill and Spinhirne compares the DEDG and MC methods in a non-system specific manner for both the aerosol and molecular Doppler systems. The purpose of this presentation is to extend the previous work of McGill and Spinhirne to examine the performance of spaceborne profiling systems. Particular emphasis will be placed on the molecular systems, as these are viewed as the strength of direct-detection Doppler lidar.

McGill, Matthew J.↗