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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗
DOE OSTI2021

Point-spread Function Deconvolution of the IFU Data and Restoration of Galaxy Stellar Kinematics

We present a performance test of the point-spread function (PSF) deconvolution algorithm applied to astronomical integral field unit (IFU) spectroscopy data for restoration of galaxy kinematics. We deconvolve the IFU data by applying the Lucy–Richardson algorithm to the 2D image slice at each wavelength. We demonstrate that the algorithm can effectively recover the true stellar kinematics of the galaxy, by using mock IFU data with a diverse combination of surface brightness profile, signal-to-noise ratio, line-of-sight geometry, and line-of-sight velocity distribution (LOSVD). In addition, we show that the proxy of the spin parameter ${\lambda }_{{R}_{e}}$ can be accurately measured from the deconvolved IFU data. We apply the deconvolution algorithm to the actual SDSS-IV MaNGA IFU survey data. The 2D LOSVD, geometry, and ${\lambda }_{{R}_{e}}$ measured from the deconvolved MaNGA IFU data exhibit noticeable differences compared to the ones measured from the original IFU data. The method can be applied to any other regular-grid IFU data to extract the PSF-deconvolved spatial information.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Accounting for the Influence of Decorrelation in Microphone Phased Array Deconvolution Methods

Microphone phased arrays are a common tool for use in aeroacoustic wind tunnel testing. The analysis of acquired array data is known to suffer from decorrelation effects, where the coherence of an acoustic wave measured by a pair of microphones is degraded as the wave passes through a turbulent free shear layer or boundary layer. This paper describes, in detail, how to mitigate the influence of decorrelation effects when processing array data with deconvolution methods. This is done using the DAMAS algorithm as an example, applied to recent airframe noise test data acquired in the NASA Langley 14- by 22-Foot Subsonic Tunnel. Two ways of handling the turbulent propagation modeling, both assuming plane wave propagation, are described. Results show that while turbulence model fit parameters may differ, both methods output extremely similar deconvolution results. Further improvements likely require more accurate mean shear layer data prior to developing more involved turbulence models.

microphone array↗
DOE OSTI2018

Electrospray Ionization with High-Resolution Mass Spectrometry as a Tool for Lignomics: Lignin Mass Spectrum Deconvolution

The capability to characterize lignin, lignocellulose, and their degradation products is essential for the development of new renewable feedstocks. Electrospray ionization high-resolution time-of-flight mass spectrometry (ESI-HR TOF-MS) method was developed expanding the lignomics toolkit while targeting the simultaneous detection of low and high molecular weight (MW) lignin species. The effect of a broad range of electrolytes and various ionization conditions on ion formation and ionization effectiveness was studied using a suite of mono-, di-, and triarene lignin model compounds as well as kraft alkali lignin. Contrary to the previous studies, the positive ionization mode was found to be more effective for methoxy-substituted arenes and polyphenols, i.e., species of a broadly varied MW structurally similar to the native lignin. For the first time, we report an effective formation of multiply charged species of lignin with the subsequent mass spectrum deconvolution in the presence of 100 mmol L{sup −1} formic acid in the positive ESI mode. The developed method enabled the detection of lignin species with an MW between 150 and 9000 Da or higher, depending on the mass analyzer. The obtained M{sub n} and M{sub w} values of 1500 and 2500 Da, respectively, were in good agreement with those determined by gel permeation chromatography. Furthermore, the deconvoluted ESI mass spectrum was similar to that obtained with matrix-assisted laser desorption/ionization (MALDI)-HR TOF-MS, yet featuring a higher signal-to-noise ratio. The formation of multiply charged species was confirmed with ion mobility ESI-HR Q-TOF-MS. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TH-AB-209-03: Overcoming Resolution Limitations of Diffuse Optical Signals in X-Ray Induced Luminescence (XIL) Imaging Via Selective Plane Illumination and 2D Deconvolution

Purpose: To evaluate the resolution and sensitivity of XIL imaging using a surface radiance simulation based on optical diffusion and maximum likelihood expectation maximization (MLEM) image reconstruction. XIL imaging seeks to determine the distribution of luminescent nanophosphors, which could be used as nanodosimeters or radiosensitizers. Methods: The XIL simulation generated a homogeneous slab with optical properties similar to tissue. X-ray activated nanophosphors were placed at 1.0 cm depth in the tissue in concentrations of 10{sup −4} g/mL in two volumes of 10 mm{sup 3} with varying separations between each other. An analytical optical diffusion model determined the surface radiance from the photon distributions generated at depth in the tissue by the nanophosphors. The simulation then determined the detected luminescent signal collected with a f/1.0 aperture lens and back-illuminated EMCCD camera. The surface radiance was deconvolved using a MLEM algorithm to estimate the nanophosphors distribution and the resolution. To account for both Poisson and Gaussian noise, a shifted Poisson imaging model was used in the deconvolution. The deconvolved distributions were fitted to a Gaussian after radial averaging to measure the full width at half maximum (FWHM) and the peak to peak distance between distributions was measured to determine the resolving power. Results: Simulated surface radiances for doses from 1mGy to 100 cGy were computed. Each image was deconvolved using 1000 iterations. At 1mGy, deconvolution reduced the FWHM of the nanophosphors distribution by 65% and had a resolving power is 3.84 mm. Decreasing the dose from 100 cGy to 1 mGy increased the FWHM by 22% but allowed for a dose reduction of a factor of 1000. Conclusion: Deconvolving the detected surface radiance allows for dose reduction while maintaining the resolution of the nanophosphors. It proves to be a useful technique in overcoming the resolution limitations of diffuse optical imaging in tissue. C. S. acknowledges support from the NIH National Institute of General Medical Sciences (Award number R25GM109439, Project Title: University of Chicago Initiative for Maximizing Student Development, IMSD). B. Q. and P. L. acknowledge support from NIH grant R01EB017293.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Transient recovery problem in acoustics: A multichannel model-based deconvolution approach

Critical acoustical systems operating in complex environments contaminated with disturbances and noise offer an extreme challenge when excited by out-of-the-ordinary, impulsive, transient events that can be undetected and seriously affect their overall performance. Transient impulse excitations must be detected, extracted, and evaluated to determine any potential system damage that could have been imposed; therefore, the problem of recovering the excitation in an uncertain measurement environment becomes one of multichannel deconvolution. Recovering a transient and its initial energy has not been solved satisfactorily, especially when the measurement has been truncated and only a small segment of response data is available. The development of multichannel deconvolution techniques for both complete and incomplete excitation data is discussed, employing a model-based approach based on the state-space representation of an identified acoustical system coupled to a forward modeling solution and a Kalman-type processor for enhancement and extraction. In conclusion, synthesized data are utilized to assess the feasibility of the various approaches, demonstrating that reasonable performance can be achieved even in noisy environments.

42 ENGINEERING↗
DOE OSTI2024

Deep learning-based temporal deconvolution for photon time-of-flight distribution retrieval

The acquisition of the time of flight (ToF) of photons has found numerous applications in the biomedical field. Over the last decades, a few strategies have been proposed to deconvolve the temporal instrument response function (IRF) that distorts the experimental time-resolved data. However, these methods require burdensome computational strategies and regularization terms to mitigate noise contributions. Herein, we propose a deep learning model specifically to perform the deconvolution task in fluorescence lifetime imaging (FLI). The model is trained and validated with representative simulated FLI data with the goal of retrieving the true photon ToF distribution. Its performance and robustness are validated with well-controlled in vitro experiments using three time-resolved imaging modalities with markedly different temporal IRFs. The model aptitude is further established with in vivo preclinical investigation. Overall, these in vitro and in vivo validations demonstrate the flexibility and accuracy of deep learning model-based deconvolution in time-resolved FLI and diffuse optical imaging.

Pandey, Vikas (ORCID:0000000154771095)↗
DOE OSTI2025

Beam Signal Recovery Using Wiener Deconvolution

This project explores the use of Wiener deconvolution to recover an original signal that has been distorted by a known transfer function and by noise. A simulated Gaussian pulse was used as the test signal, and a transfer function was applied in the frequency domain to model system distortion. Controlled noise was then introduced to approximate real-world signal degradation. A Wiener filter was implemented to reverse the effects of the transfer function while minimizing the influence of noise. The recovered signal was compared to the original pulse to evaluate the effectiveness of the filter. Results demonstrate that Wiener deconvolution offers a stable and effective approach to signal recovery, balancing complete transfer function inversion and noise suppression.

Campbell, Savanna [El Camino Coll.]↗
NASA NTRS1975

A digital algorithm for spectral deconvolution with noise filtering and peak picking: NOFIPP-DECON

Noise-filtering, peak-picking deconvolution software incorporates multiple convoluted convolute integers and multiparameter optimization pattern search. The two theories are described and three aspects of the software package are discussed in detail. Noise-filtering deconvolution was applied to a number of experimental cases ranging from noisy, nondispersive X-ray analyzer data to very noisy photoelectric polarimeter data. Comparisons were made with published infrared data, and a man-machine interactive language has evolved for assisting in very difficult cases. A modified version of the program is being used for routine preprocessing of mass spectral and gas chromatographic data.

Edwards, T. R.↗
NASA NTRS1978

Deconvolution estimation theory applied to Nimbus 6 ERB data

It is pointed out that the ERB (Earth Radiation Budget) Experiment aboard the Nimbus 6 spacecraft has provided nearly 3 years of data thus far from its wide field of view (WFOV) radiometers. Each data point is an integral of the irradiance from all points within the field of view of the WFOV sensor, which is an approximately 60 deg diameter circular region on the earth. House (1972) proposed that the data, being a convolution of the flux field at the top of the atmosphere, could be convoluted so as to enhance the resolution. The problem was solved by Smith and Green (1975-76) for the case of earth emitted radiation. A parameter estimation approach to the deconvolution problem was formulated. A description is presented of the deconvolution estimation concept and the results obtained by its application to the Nimbus 6 ERB WFOV data for earth emitted radiation for August 1975.

Green, R. N.↗
NASA NTRS1979

Correction of instrumental distortion by analytical deconvolution of data

A general analytical theorem developed by van de Hulst (1946) for inverting the convolution integral is reviewed and illustrated both with synthetic data and with experimental data from time-of-flight measurements. If the undesired influence of an instrument used in an experimental measurement can be represented by the convolution integral, the original undistorted or true distribution may sometimes be recovered in postprocessing the data by means of deconvolution. Analytical deconvolution is achieved by using the coefficients from a power series representation of the distorted output distribution and a set of 'solving polynomials' which may be readily derived from the response function of the instrument.

Morton, D. C.↗
NASA NTRS1980

Deconvolution of gas chromatographic data

The use of deconvolution methods on gas chromatographic data to obtain an accurate determination of the relative amounts of each material present by mathematically separating the merged peaks is discussed. Data were obtained on a gas chromatograph with a flame ionization detector. Chromatograms of five xylenes with differing degrees of separation were generated by varying the column temperature at selected rates. The merged peaks were then successfully separated by deconvolution. The concept of function continuation in the frequency domain was introduced in striving to reach the theoretical limit of accuracy, but proved to be only partially successful.

Howard, S.↗
NASA NTRS1981

Deconvolution of wide field-of-view radiometer measurements of earth-emitted radiation. II - Analysis of first year of Nimbus 6 ERB data

The theory of deconvolution considered by Smith and Green (1981) is applied to Nimbus 6 data in order to interpret the data with the maximum obtainable resolution. Attention is given to the data sample, sun-contaminated measurements, the measurement model, the deconvolution, the degree variance, the spherical harmonic coefficients, the geographical distribution of longwave radiation, time histories of zonal coefficients, and the effect of a grid system. Degree variance plots for 12 months of longwave radiation data show that the limit for a spherical harmonic representation of the Nimbus 6 wide field-of-view longwave data is 12th degree. The degree variance plots also reveal that most of the power is in the lower degree terms. Contour maps of the radiation field show the geographical distribution of earth emitted radiant exitance for each month.

Bess, T. D.↗
NASA NTRS1982

Thorium concentrations in the lunar surface. V - Deconvolution of the central highlands region

The distribution of thorium in the lunar central highlands measured from orbit by the Apollo 16 gamma-ray spectrometer is subjected to a deconvolution analysis to yield improved spatial resolution and contrast. Use of two overlapping data fields for complete coverage also provides a demonstration of the technique's ability to model concentrations several degrees beyond the data track. Deconvolution reveals an association between Th concentration and the Kant Plateau, Descartes Mountain and Cayley plains surface formations. The Kant Plateau and Descartes Mountains model with Th less than 1 part per million, which is typical of farside highlands but is infrequently seen over any other nearside highland portions of the Apollo 15 and 16 ground tracks. It is noted that, if the Cayley plains are the result of basin-forming impact ejecta, the distribution of Th concentration with longitude supports an origin from the Imbrium basin rather than the Nectaris or Orientale basins. Nectaris basin materials are found to have a Th concentration similar to that of the Descartes Mountains, evidence that the latter may have been emplaced as Nectaris basin impact deposits.

Metzger, A. E.↗
NASA NTRS1986

Achieving improved frequency response of the rain structure from spaceborne radar altimeters by employing deconvolution methods

A technique is described for arriving at improved measurements of the rain structure near the earth's surface from satellite-borne radars. The method uses deconvolution and Fourier transform procedures and assumes a knowledge of the antenna beam pattern. As an example, the method is directed toward the application of future spaceborne radar altimeters that may contain additional range gates to permit the measurement of rain in the lower troposphere. Using a radar-measured rain reflectivity profile acquired at Wallops Island, VA, in a simulation example, it is specifically demonstrated that improved measurements of the spatial frequency spectrum of the rain structure may be deduced by means of deconvolution methods, as compared to the measured spectrum derived by beam averaging. Rain measurements are considered vital from the standpoint of providing a flag for altimeter data that may be corrupted by rain. Such measurement capabilities should also provide sorely needed data on rain over the oceans where few or no such data are available for the meteorologist or the communicator interested in space diversity communications.

Goldhirsh, J.↗
NASA NTRS1987

Spatial deconvolution of IRAS galaxies at 60 UM

Using IRAS in a slow scan observing mode to increase the spatial sampling rate and a deconvolution analysis to increase the spatial resolution, several bright galaxies were resolved at 60 micron. Preliminary results for M 82, NGC 1068, NGC 3079 and NGC 2623 show partially resolved emission from 10 to 26 arcsec., full width at half maximum, and extended emission from 30 to 90 arcsec. from the center. In addition, the interacting system, Arp 82, along with Mark 231 and Arp 220 were studied using the program ADDSCAN to average all available survey mode observations. The Arp 82 system is well resolved after deconvolution and its brighter component is extended; the two most luminous objects are not resolved with an upper limit of 15 arcsec. for Arp 220.

Low, Frank J.↗