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At least 343 records · Page 19

Analyzing Fourier Transforms for NASA DFRC's Fiber Optic Strain Sensing System

This document provides a basic overview of the fiber optic technology used for sensing stress, strain, and temperature. Also, the document summarizes the research concerning speed and accuracy of the possible mathematical algorithms that can be used for NASA DFRC's Fiber Optic Strain Sensing (FOSS) system.

Fiechtner, Kaitlyn Leann↗

Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer

A document discusses a mechanism that uses flex-pivots in a parallelogram arrangement to provide frictionless motion with an unlimited lifetime. A voicecoil actuator drives the parallelogram over the required 5-cm travel. An optical position sensor provides feedback for a servo loop that keeps the velocity within 1 percent of expected value. Residual tip/tilt error is compensated for by a piezo actuator that drives the interferometer mirror. This mechanism builds on previous work that targeted ground-based measurements. The main novelty aspects include cryogenic and vacuum operation, high reliability for spaceflight, compactness of the design, optical layout compatible with the needs of an imaging FTS (i.e. wide overall field-of-view), and mirror optical coatings to cover very broad wavelength range (i.e., 0.26 to 15 m).

Blavier, Jean-Francois L.↗

MgB2-Based Bolometer Array for Far Infra-Red Thermal Imaging and Fourier Transform Spectroscopy Applications

The mid-superconducting critical temperature (T(sub c) approximately 39 K) of the simple binary, intermetallic MgB, [1] makes it a very good candidate for the development of the next generation of electrooptical devices (e.g. [2]). In particular, recent advances in thin film deposition teclmiques to attain higb quality polycrystalline thin film MgB, deposited on SiN-Si substrates, with T(sub c) approximately 38K [3] coupled with the low voltage noise performance of the film [4] makes it higbly desirable for the development of moderately cooled bolometer arrays for integration into future space-bourne far infra-red (FIR) spectrometers and thermal mappers for studying the outer planets, their icy moons and other moons of interest in the 17-250 micrometer spectral wavelength range. Presently, commercially available pyroelectric detectors operating at 300 K have specific detectivity, D(*), around 7 x 10(exp 8) to 2 x 10(exp 9) centimeters square root of Hz/W. However, a MgB2 thin film based bolometer using a low-stress (less than 140 MPa) SiN membrane isolated from the substrate by a small thermal conductive link, operating at 38 K, promises to have two orders of magnitude higher specific detectivity [5][6].

Lakew, B.↗

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Wemet, Mark P.↗

Programs for high-speed Fourier, Mellin and Fourier-Bessel transforms

Several FORTRAN program modules for performing one-dimensional and two-dimensional discrete Fourier transforms, Mellin, and Fourier-Bessel transforms are described along with programs that realize the algebra of high speed Fourier transforms on a computer. The programs can perform numerical harmonic analysis of functions, synthesize complex optical filters on a computer, and model holographic image processing methods.

Ikhabisimov, D. K.↗

A Linear-Complexity Tensor Butterfly Algorithm for Compressing High-Dimensional Oscillatory Integral Operators

This paper presents a multilevel tensor compression algorithm called tensor butterfly algorithm for efficiently representing large-scale and high-dimensional oscillatory integral operators, including Green's functions for wave equations and integral transforms such as Radon transforms and Fourier transforms. The proposed algorithm leverages a tensor extension of the so-called complementary low-rank property of existing matrix butterfly algorithms. The algorithm partitions the discretized integral operator tensor into subtensors of multiple levels and factorizes each subtensor at the middle level as a Tucker-type interpolative decomposition, whose factor matrices are formed in a multilevel fashion. For a d-dimensional (d > 1) integral operator discretized into a 2d-mode tensor with n2d entries, the overall CPU time and memory requirement scale as O(nd), in stark contrast to the O(nd log n) complexity of existing matrix algorithms such as matrix butterfly algorithms and fast Fourier transforms (FFTs), where n is the number of points per direction. When comparing with other tensor algorithms such as quantized tensor train (QTT), the proposed algorithm also shows superior CPU and memory performance for tensor contraction. Remarkably, the tensor butterfly algorithm can efficiently model high-frequency Green's function interactions between two unit cubes, each spanning 512 wavelengths per direction, which represents problems of scale over 512× larger than that existing butterfly algorithms can handle, with the same amount of computation resources. On the other hand, for a problem representing 64 wavelengths per direction, which is the largest size existing algebraic matrix algorithms can handle, our tensor butterfly algorithm exhibits 200x speedups and 30× memory reduction compared with existing ones. Moreover, the tensor butterfly algorithm also permits O(nd)-complexity FFTs and Radon transforms up to d = 6 dimensions.

Kielstra, P Michael↗

High resolution frequency analysis techniques with application to the redshift experiment

High resolution frequency analysis methods, with application to the gravitational probe redshift experiment, are discussed. For this experiment a resolution of .00001 Hz is required to measure a slowly varying, low frequency signal of approximately 1 Hz. Major building blocks include fast Fourier transform, discrete Fourier transform, Lagrange interpolation, golden section search, and adaptive matched filter technique. Accuracy, resolution, and computer effort of these methods are investigated, including test runs on an IBM 360/65 computer.

Decher, R.↗

Optical fiber dispersion characterization study

The theory, design, and results of optical fiber pulse dispersion measurements are considered. Both the hardware and software required to perform this type of measurement are described. Hardware includes a thermoelectrically cooled injection laser diode source, an 800 GHz gain bandwidth produce avalanche photodiode and an input mode scrambler. Software for a HP 9825 computer includes fast Fourier transform, inverse Fourier transform, and optimal compensation deconvolution. Test set construction details are also included. Test results include data collected on a 1 Km fiber, a 4 Km fiber, a fused spliced, eight 600 meter length fibers concatenated to form 4.8 Km, and up to nine optical connectors.

Geeslin, A.↗

Signal processing applications of massively parallel charge domain computing devices

The present invention is embodied in a charge coupled device (CCD)/charge injection device (CID) architecture capable of performing a Fourier transform by simultaneous matrix vector multiplication (MVM) operations in respective plural CCD/CID arrays in parallel in O(1) steps. For example, in one embodiment, a first CCD/CID array stores charge packets representing a first matrix operator based upon permutations of a Hartley transform and computes the Fourier transform of an incoming vector. A second CCD/CID array stores charge packets representing a second matrix operator based upon different permutations of a Hartley transform and computes the Fourier transform of an incoming vector. The incoming vector is applied to the inputs of the two CCD/CID arrays simultaneously, and the real and imaginary parts of the Fourier transform are produced simultaneously in the time required to perform a single MVM operation in a CCD/CID array.

Fijany, Amir↗

Vacuum Pyrolysis of Hybrid Poplar Milled Wood Lignin with Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Analysis of Feedstock and Products for the Elucidation of Reaction Mechanisms

The pyrolysis of lignocellulosic materials is a promising technique to produce fuels and chemicals. It is well known that the most abundant products of lignin pyrolysis are oligomeric molecules, known as pyrolytic lignin (PL). The chemical composition of PL has been extensively studied; however, there is still an important debate whether these oligomers are produced directly from the lignin or from the recombination of monomeric pyrolytic products. Existing theories are unable to describe the effect of vacuum on the distribution of pyrolysis products. Hybrid poplar milled wood lignin (MWL) was initially isolated and thoroughly characterized by Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS). Chemical formulas were assigned to each oligomeric compound detected. The MWL was also subjected to vacuum pyrolysis in a modified pyroprobe at 250, 750, and 1000 mbar (absolute pressure), and the resulting liquid products were analyzed by FT-ICR MS. A new strategy to assign structural representations to the oligomeric PL products is proposed, based on the plausible pyrolysis reaction mechanisms of depolymerization/fragmentation applied to original MWL oligomer formulas. Our results support the hypothesis that PL is formed from the removal of moieties from primary lignin pyrolysis products with between three and five aromatic rings. This depolymerization/fragmentation allows the oligomers to reduce their molecular weights to the point where they can be removed from the reaction zone by direct vaporization. Furthermore, this phenomenon highlights the importance of pressure on removal mechanisms and their impact on the molecular weight of the resulting products from lignin pyrolysis.

09 BIOMASS FUELS↗

Microstructural characterization and assessment of mechanical properties of concrete based on combined elemental analysis techniques and Fast-Fourier transform-based simulations

This paper presents a pixel-based modeling approach of concrete which combines an experimental characterization of concrete and the Fast-Fourier transform simulations. High-resolution phase maps created from experimental characterization by micro X-ray fluorescence, energy dispersive X-ray analysis, and X-ray diffraction contain 9 different phases, including 22.17 vol.% of hydrated cement paste, 54.21 vol.% of minerals, and 23.62 vol.% of interfaces. These phases provide the input for determining the effective elastic properties, coupled with Fast-Fourier transform-based simulation. The simulation results show that the effective range of Young’s modulus of concrete is comparable with the range of experimental values ~ 37 ± 4 GPa with the assumption of realistic properties of interfaces.

36 MATERIALS SCIENCE↗