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Results for “Deconvolution”

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
NASA NTRS1999

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Kumar, Rajendra↗
NASA NTRS2005

Deconvolution of Energy Spectra in the ATIC Experiment

The Advanced Thin Ionization Calorimeter (ATIC) balloon-borne experiment is designed to perform cosmic- ray elemental spectra measurements from below 100 GeV up to tens TeV for nuclei from hydrogen to iron. The instrument is composed of a silicon matrix detector followed by a carbon target, interleaved with scintillator tracking layers, and a segmented BGO calorimeter composed of 320 individual crystals totalling 18 radiation lengths, used to determine the particle energy. The technique for deconvolution of the energy spectra measured in the thin calorimeter is based on detailed simulations of the response of the ATIC instrument to different cosmic ray nuclei over a wide energy range. The method of deconvolution is described and energy spectrum of carbon obtained by this technique is presented.

Batkov, K. E.↗
NASA NTRS1996

An Optimal Deconvolution Method for Reconstructing Pneumatically Distorted Near-Field Sonic Boom Pressure Measurements

In-flight measurements of the SR-71 near-field sonic boom were obtained by an F-16XL airplane at flightpath separation distances from 40 to 740 ft. Twenty-two signatures were obtained from Mach 1.60 to Mach 1.84 and altitudes from 47,600 to 49,150 ft. The shock wave signatures were measured by the total and static sensors on the F-16XL noseboo. These near-field signature measurements were distorted by pneumatic attenuation in the pitot-static sensors and accounting for their effects using optimal deconvolution. Measurement system magnitude and phase characteristics were determined from ground-based step-response tests and extrapolated to flight conditions using analytical models. Deconvolution was implemented using Fourier transform methods. Comparisons of the shock wave signatures reconstructed from the total and static pressure data are presented. The good agreement achieved gives confidence of the quality of the reconstruction analysis. although originally developed to reconstruct the sonic boom signatures from SR-71 sonic boom flight tests, the methods presented here generally apply to other types of highly attenuated or distorted pneumatic measurements.

Whitmore, Stephen A.↗
NASA NTRS2018

Frequency-Domain Deconvolution for Flight Dynamics Applications

A deconvolution method is presented for estimating input data from measured output data and a model of the dynamic process involved. The method uses an optimal Wiener filter for separating the measured data into signal and noise components, and a high-accuracy Fourier transform for inverting the model dynamics in the frequency domain. The method is an extension of optimal Fourier smoothing, and uses a technique to enhance the contrast between the signal and noise spectra in designing the Wiener filter. The deconvolution method was applied to simulation and flight test data for the purposes of removing unwanted distortions introduced by signal-conditioning filters and sensor dynamics, and for reconstructing turbulence inputs from measured sensor data. Results indicated hat the method performs well given good signal-to-noise levels and accurate models of the dynamic process.

Grauer, Jared A.↗
DOE OSTI2025

Calorimeter Pileup Deconvolution for Online Trigger Primitives

In high energy physics experiment, as the luminosity increases, pile-up issues on detectors such as calorimeters become non-negligible. Deconvolution approaches with mathematic pre-assumptions such as Sparse Representation are developed for data analysis stage. For online computation tasks such as for trigger primitive creation, signal availability is significantly different as in offline data analysis stage, and therefore, different (yet simpler) algorithms should be explored. In this document, several approaches of deconvolution suitable for FPGA implementation are discussed.

Wu, Jin-yuan [Fermilab] (ORCID:0000000344329521)↗
DOE OSTI2025

Wiener Filter Deconvolution for Analog Signals

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 the 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 with the original pulse to evaluate the effectiveness of the filter. The results demonstrate that Wiener deconvolution offers a stable and effective approach to signal recovery, balancing complete transfer function inversion and noise suppression.

Campbell, Savanna [Fermilab]↗
NASA NTRS1993

Least-Squares Deconvolution of Compton Telescope Data with the Positivity Constraint

We describe a Direct Linear Algebraic Deconvolution (DLAD) approach to imaging of data from Compton gamma-ray telescopes. Imposition of the additional physical constraint, that all components of the model be non-negative, has been found to have a powerful effect in stabilizing the results, giving spatial resolution at or near the instrumental limit. A companion paper (Dixon et al. 1993) presents preliminary images of the Crab Nebula region using data from COMPTEL on the Compton Gamma-Ray Observatory.

COMPTEL↗
DOE OSTI2024

Deconvoluting Effects of Lithium Morphology and SEI Stability at Moderate Current Density Using Interface Engineering

Lithium (Li)-morphology and solid electrolyte interphase (SEI) are among the most significant performance regulators in Li-metal batteries (LMBs). While both Li-morphology and SEI composition play key roles in the cyclability of LMBs, less is understood about the individual contributions of each factor to overall Li reversibility, particularly at a practical current density (1 mA cm −2 ) at which the kinetics of both factors are not naturally separated. Herein, an interface engineering approach is introduced to deconvolute the impacts of Li-morphology and SEI composition on battery performance. By using interfacial nanofilms with differing resistivity (resistive HfO 2 versus conductive ZnO), the morphology of Li is varied, and by virtue of similar acidic character of the nanofilms, the formation of anion-rich SEIs is maintained. It is established that although the surface acidity of the thin films enables preformation of a more anion-rich SEI, it is not preserved after Li plating. It is further shown that resistance-controlled, low-surface-area Li-morphology exhibits up to threefold increase in stable cycle life when tested in multiple electrolytes. Overall, these findings explain why Li-morphological control is more advantageous for performance improvement than preformed SEI modulation due to the inherent challenges in SEI preservation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrogen charging and desorption from microstructural viewpoint: A method for deconvoluting hydrogen desorption spectra and unveiling the hydrogen-microstructure interaction

Understanding the interaction of hydrogen with microstructural features in metallic materials is crucial for designing hydrogen-resistant alloys. Although thermal desorption spectroscopy (TDS) is widely used for investigating the hydrogen binding behavior of various microstructural features, its application to face-centered cubic (fcc) metals and alloys that exhibit low hydrogen diffusivity is limited due to the lumped TDS desorption signals. This paper shows that, by coupling a Sofronis–McMeeking type hydrogen transport model with a microstructure-informed finite-element model, TDS data can be deconvoluted to reveal the underlying adsorption–diffusion–desorption processes, hydrogen diffusivity, and trap-binding energies. In conclusion, the austenitic steel SS316L in solution-annealed condition is used as a demonstration material, and we focused on investigating the interaction of deuterium (hydrogen isotope) with grain boundaries, which is difficult to investigate from experiments alone but critical for design of alloys for hydrogen infrastructure.

Finite element simulation, Polycrystalline Microst↗
DOE OSTI2024

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Deconvolution of X-ray natural and magnetic circular dichroism in chiral Dy-ferroborate

Structural chirality and magnetism, when intertwined, can have profound implications on materials properties. Using X-ray imaging and spectroscopic measurements that leverage the natural and magnetic circular dichroic effects present in magnetized chiral crystal structures, we probe the interplay between chirality and magnetism across the field-induced spin-flop transition of Dy ferroborate, DyFe 3 (BO 3 ) 4 . Deconvolution of natural and magnetic circular dichroic signals at the Fe K and Dy L 2,3 absorption edges of the non-centrosymmetric structure was enabled by use of tunable temperature and magnetic field, providing access to element-specific magnetic information across the spin-flop transition. The magnetic response of Fe and Dy sublattices was found to be independent of domain chirality. The chiral domains were robust against both the (chirality preserving) R32 to P3 1 21/P3 2 21 structural phase transition at 280 K, and application of magnetic field up to 4 Tesla. A third flavor of X-ray dichroism, magneto-chiral dichroism, was not detected within the accuracy of our measurements. The absence of significant Fe magnetization along the screw, c-axis for the magnetic field strength used in this study, together with non-linear coupling of magnetic field to electric polarization across the spin-flop transition, may hinder observation of magneto-chiral dichroic effects in this system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Deconvoluting sources of variability in aerosol jet printing using light scattering measurements

Aerosol jet printing (AJP) is a digital additive manufacturing technique for hybrid and conformal electronics, where its contactless deposition readily enables patterning over 3D surface topography. However, the complexity of aerosol transport physics makes deposition rate sensitive to process variability, hindering widespread industry adoption. Light scattering measurements have recently been demonstrated as a capable tool for measuring deposition rate in real time, enabling closed-loop control and in-situ qualification frameworks. These inline optical measurements present further opportunity as a diagnostic tool to understand the effects of secondary process parameters affecting vapor–liquid equilibrium and heat and mass transport during deposition. Downstream of the optical measurement cell, changing the sheath gas flow rate, increasing temperature via an inline heater, and adding solvent vapor via a sheath gas bubbler were observed to alter drying physics during sheath-collimation, and thereby impaction efficiency. Further upstream, the introduction of solvent vapor via a carrier gas bubbler and liquid build-up in the printhead were seen to affect the quantitative relationship between the light scattering data and the true deposition rate. Using this information, tightened controls of meaningful secondary parameters were implemented to improve the batch-to-batch consistency for printing a dielectric ink. In addition to advancing AJP process reliability for production, this work demonstrates the capability of inline optical measurements to provide insight into process physics and deconvolute competing mechanisms that underly variability.

additive manufacturing↗
DOE OSTI2024

Point spread function deconvolution using a convolutional autoencoder

A major issue in optical astronomical image analysis is the combined effect of the instrument’s point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation dependent. In this work we present a very simple neural network based approach to nonblind image deconvolution that relies on feeding a convolutional autoencoder (CAE) input images that have been preprocessed by convolution with the corresponding PSF and its regularized inverse, a method which is both conceptually simple and computationally less intensive. We also present here, a new approach for dealing with limited input dynamic range of neural networks compared to the dynamic range present in astronomical images.

79 ASTRONOMY AND ASTROPHYSICS↗