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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scattering Matrix Determination in Crystalline Materials from 4D Scanning Transmission Electron Microscopy at a Single Defocus Value

Recent work has revived interest in the scattering matrix formulation of electron scattering in transmission electron microscopy as a stepping stone toward atomic-resolution structure determination in the presence of multiple scattering. Here, we discuss ways of visualizing the scattering matrix that make its properties clear. Through a simulation-based case study incorporating shot noise, we shown how regularizing on this continuity enables the scattering matrix to be reconstructed from 4D scanning transmission electron microscopy (STEM) measurements from a single defocus value. Intriguingly, for crystalline samples, this process also yields the sample thickness to nanometer accuracy with no a priori knowledge about the sample structure. The reconstruction quality is gauged by using the reconstructed scattering matrix to simulate STEM images at defocus values different from that of the data from which it was reconstructed.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Ultrasonic nondestructive evaluation of graphite epoxy composite laminates

Quantitative ultrasonic techniques are summarized with applications to the measurement of frequency-dependent attenuation and backscatter and to the NDE of composite laminates. Results are listed for the ultrasonic NDE of graphite-epoxy composite laminates including impact and fatigue damage as well as porosity. The methods reviewed include transmission measurements of attenuation, reconstructive tomography based on attenuation, estimating attenuation from backscattered ultrasound, and backscatter approaches. Phase-sensitive and -insensitive detection techniques are mentioned such as phase cancellation at piezoelectric receiving transducers and acoustoelectric effects. The techniques permit the NDE of the parameters listed in inhomogeneous media and provide both images from the transmission mode and in the reflection mode.

Miller, James G.↗
DOE OSTI2025

Iterative Reconstruction for Multimodal Neutron Tomography

Here, we describe a unified framework for model-based iterative 3-D reconstruction of multimodal neutron transmission, hydrogen-scatter, and induced-fission images from low resolution data recorded using 14.1-MeV neutrons and the associated-particle imaging (API) technique. The framework, which was developed to facilitate use in challenging field-deployment scenarios, is centered around physics-based system models and a total variation (TV) constrained implementation of the simultaneous iterative reconstruction technique (SIRT). Modified to solve a statistically weighted least squares (WLS) problem, the SIRT algorithm is accelerated using ordered subsets and Nesterov’s momentum for which we derive a near-optimal value of the governing Lipschitz constant. The approach enables the reconstruction of images that are high resolution compared to the acquired data and is robust to both limited statistics and a limited number of projection angles. Moreover, the framework is fast enough to be practical. Example images are provided that demonstrate both the ability to perform fast-neutron imaging of high-atomic-number materials with low radiation dose and the benefit of multimodal neutron imaging to identify key materials.

Hydrogen scatter↗
DOE OSTI2024

Understanding the Effect of Curvature on the Magnetization Reversal of Three-Dimensional Nanohelices

Comprehending the interaction between geometry and magnetism in three-dimensional (3D) nanostructures is important to understand the fundamental physics of domain wall (DW) formation and pinning. Here, we use focused-electron-beam-induced deposition to fabricate magnetic nanohelices with increasing helical curvature with height. Using electron tomography and Lorentz transmission electron microscopy, we reconstruct the 3D structure and magnetization of the nanohelices. The surface curvature, helical curvature, and torsion of the nanohelices are then quantified from the tomographic reconstructions. Furthermore, by using the experimental 3D reconstructions as inputs for micromagnetic simulations, we can reveal the influence of surface and helical curvature on the magnetic reversal mechanism. Hence, we can directly correlate the magnetic behavior of a 3D nanohelix to its experimental structure. In conclusion, these results demonstrate how the control of geometry in nanohelices can be utilized in the stabilization of DWs and control of the response of the nanostructure to applied magnetic fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparative Study of Data-Driven Area Inertia Estimation Approaches on WECC Power Systems

With the increasing integration of inverter-based resources into the power grid, there has been a notable reduction in system inertia, potentially compromising frequency stability. To assess the suitability of existing area inertia estimation techniques for real-world power systems, this paper presents a rigorous comparative analysis of system identification, measurement reconstruction, and electromechanical oscillation-based area inertia estimation methodologies, specifically applied to the large-scale and multi-area WECC 240-bus power system. Comprehensive results show that the system identification-based approach exhibits superior robustness and accuracy relative to its counterparts.

area inertia estimation↗
DOE OSTI2021

Deep-learning-based image registration for nano-resolution tomographic reconstruction

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. We report the method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

deep learning↗
NASA NTRS1992

Real-time demonstration hardware for enhanced DPCM video compression algorithm

The lack of available wideband digital links as well as the complexity of implementation of bandwidth efficient digital video CODECs (encoder/decoder) has worked to keep the cost of digital television transmission too high to compete with analog methods. Terrestrial and satellite video service providers, however, are now recognizing the potential gains that digital video compression offers and are proposing to incorporate compression systems to increase the number of available program channels. NASA is similarly recognizing the benefits of and trend toward digital video compression techniques for transmission of high quality video from space and therefore, has developed a digital television bandwidth compression algorithm to process standard National Television Systems Committee (NTSC) composite color television signals. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a non-adaptive predictor, non-uniform quantizer and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The non-adaptive predictor and multilevel Huffman coder combine to set this technique apart from other DPCM encoding algorithms. All processing is done on a intra-field basis to prevent motion degradation and minimize hardware complexity. Computer simulations have shown the algorithm will produce broadcast quality reconstructed video at an average transmission rate of 1.8 bits/pixel. Hardware implementation of the DPCM circuit, non-adaptive predictor and non-uniform quantizer has been completed, providing realtime demonstration of the image quality at full video rates. Video sampling/reconstruction circuits have also been constructed to accomplish the analog video processing necessary for the real-time demonstration. Performance results for the completed hardware compare favorably with simulation results. Hardware implementation of the multilevel Huffman encoder/decoder is currently under development along with implementation of a buffer control algorithm to accommodate the variable data rate output of the multilevel Huffman encoder. A video CODEC of this type could be used to compress NTSC color television signals where high quality reconstruction is desirable (e.g., Space Station video transmission, transmission direct-to-the-home via direct broadcast satellite systems or cable television distribution to system headends and direct-to-the-home).

Bizon, Thomas P.↗
DOE OSTI2022

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Resolution of Virtual Depth Sectioning from Four-Dimensional Scanning Transmission Electron Microscopy

Abstract One approach to three-dimensional structure determination using the wealth of scattering data in four-dimensional (4D) scanning transmission electron microscopy (STEM) is the parallax method proposed by Ophus et al. (2019. Advanced phase reconstruction methods enabled by 4D scanning transmission electron microscopy, Microsc Microanal25, 10–11), which determines the scattering matrix and uses it to synthesize a virtual depth-sectioning reconstruction of the sample structure. Drawing on an equivalence with a hypothetical confocal imaging mode, we derive contrast transfer and point spread functions for this parallax method applied to weakly scattering objects, showing them identical to earlier depth-sectioning STEM modes when only bright field signal is used, but that improved depth resolution is possible if dark field signal can be used. Through a simulation-based study of doped Si, we show that this depth resolution is preserved for thicker samples, explore the impact of shot noise on the parallax reconstructions, discuss challenges to making use of dark field signal, and identify cases where the interpretation of the parallax reconstruction breaks down.

3D imaging↗
NASA NTRS1996

3-D Imaging In Virtual Environment: A Scientific Clinical and Teaching Tool

The advent of powerful graphics workstations and computers has led to the advancement of scientific knowledge through three-dimensional (3-D) reconstruction and imaging of biological cells and tissues. The Biocomputation Center at NASA Ames Research Center pioneered the effort to produce an entirely computerized method for reconstruction of objects from serial sections studied in a transmission electron microscope (TEM). The software developed, ROSS (Reconstruction of Serial Sections), is now being distributed to users across the United States through Space Act Agreements. The software is in widely disparate fields such as geology, botany, biology and medicine. In the Biocomputation Center, ROSS serves as the basis for development of virtual environment technologies for scientific and medical use. This report will describe the Virtual Surgery Workstation Project that is ongoing with clinicians at Stanford University Medical Center, and the role of the Visible Human data in the project.

Ross, Muriel D.↗
DOE OSTI2020

PtychoShelves , a versatile high-level framework for high-performance analysis of ptychographic data

Over the past decade, ptychography has been proven to be a robust tool for non-destructive high-resolution quantitative electron, X-ray and optical microscopy. It allows for quantitative reconstruction of the specimen's transmissivity, as well as recovery of the illuminating wavefront. Additionally, various algorithms have been developed to account for systematic errors and improved convergence. With fast ptychographic microscopes and more advanced algorithms, both the complexity of the reconstruction task and the data volume increase significantly. PtychoShelves is a software package which combines high-level modularity for easy and fast changes to the data-processing pipeline, and high-performance computing on CPUs and GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluating Cryo–TEM Reconstruction Accuracy of Self–Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo–TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA–reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo–TEM 3D reconstructions of self–assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. In conclusion, these findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

36 MATERIALS SCIENCE↗
NASA NTRS2023

Neural Radiance Fields for Shadow Removal and Relighting of Satellite Imagery

Multi-view stereo photogrammetric techniques have been conventionally utilized to generate Global Digital Elevation Models (GDEM) of planetary and lunar surfaces. However, these methods, relying on conventional feature detectors, are often subject to inaccuracies caused by changes in lighting conditions, including diffuse reflection and harsh shading. This has limited the ability of these methods to accurately reconstruct shadowed regions in orbital imagery, such as highly shaded urban areas and the permanently shadowed regions (PSRs) located in the lunar surface, which are critical targets for NASA's Artemis program. Neural Radiance Fields (NeRFs) offer a novel solution to these limitations by breaking away from traditional photogrammetric assumptions of ridged, opaque surfaces. NeRFs are capable of reconstructing 3D objects with variably transmissive properties, such as fluids, PSRs, and reflective surfaces. In this work, we demonstrate the robustness of NeRFs in generating high-fidelity 3D models of terrain from highly shaded orbital imagery acquired from small satellites in low earth orbit (LEO). Our results showcase the ability of NeRF to overcome the limitations of traditional photogrammetric methods and provide a promising solution for reconstructing complex scenes in challenging lighting conditions.

Caleb Ashmore Adams↗
NASA NTRS2013

Sleuthing the MSL EDL Performance from an X Band Carrier Perspective

During the Entry, Descent, and Landing (EDL) of NASA's Mars Science Laboratory (MSL), or Curiosity, rover to Gale Crater on Mars on August 6, 2012 UTC, the rover transmitted an X-band signal composed of carrier and tone frequencies and a UHF signal modulated with an 8kbps data stream. During EDL, the spacecraft's orientation is determined by its guidance and mechanical subsystems to ensure that the vehicle land safely at its destination. Although orientation to maximize telecom performance is not possible, antennas are especially designed and mounted to provide the best possible line of sight to Earth and to the Mars orbiters supporting MSL's landing. The tones and data transmitted over these links are selected carefully to reflect the most essential parameters of the vehicle's state and the performance of the EDL subsystems for post-EDL reconstruction should no further data transmission from the vehicle be possible. This paper addresses the configuration of the X band receive system used at NASA / JPL's Deep Space Network (DSN) to capture the signal spectrum of MSL's X band carrier and tone signal, examines the MSL vehicle state information obtained from the X band carrier signal only and contrasts the Doppler-derived information against the post-EDL known vehicle state. The paper begins with a description of the MSL EDL sequence of events and discusses the impact of the EDL maneuvers such as guided entry, parachute deploy, and powered descent on the frequency observables expected at the DSN. The range of Doppler dynamics possible is derived from extensive 6 Degrees-Of-Freedom (6 DOF) vehicle state calculations performed by MSL's EDL simulation team. The configuration of the DSN's receive system, using the Radio Science Receivers (RSR) to perform open-loop recording for both for nominal and off-nominal EDL scenarios, is detailed. Expected signal carrier power-to-noise levels during EDL are shown and their impact on signal detection is considered. Particular attention is given to the selection of the appropriate RSR processing bandwidths and to its configuration for real-time signal detection. The X-band carrier frequency obtained through post-processing of the open-loop recorded spectrum is given. Detection of spacecraft status and completion of key vehicle events through their Doppler signature is discussed and illustrated. This Doppler-derived information is compared against the very accurate vehicle data obtained post-EDL via MSL's UHF radio subsystem. The paper concludes with a discussion on the advantages and disadvantages of transmitting the X-band carrier and tone signal in the general context of EDL communications and lessons learned for future missions with EDL sequences are given

Mars Science Laboratory (MSL)↗
DOE OSTI2022

Progress on Associated-Particle Imaging Algorithms, 2022

The present work describes progress on developing imaging algorithms that use fast neutron signatures acquired using the associated-particle imaging (API) method. The present work complements ongoing work to develop neutron source and detector hardware to enable field inspection by investigating algorithms that are capable of discriminating among critical materials or extracting three-dimensional (3D) geometrical information from single-sided or transmission measurements. The present work is divided into three approaches: 1.Iterative reconstruction of inelastic gamma-ray emissions to perform 3D time-of-flight (TOF) imaging in a single view in either transmission or backscatter configurations. Iterative reconstruction enables image resolution better than the inherent TOF resolution. 2.Decomposition of registered neutron and x-ray radiographs into an assumed material list for each pixel in the image. 3.Material identification using full spectral analysis that includes the emergent neutron and gamma ray energies, times, and angles. Progress for each approach is summarized for fiscal year (FY) 2022.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

New Computer Simulations of Macular Neural Functioning

We use high performance graphics workstations and supercomputers to study the functional significance of the three-dimensional (3-D) organization of gravity sensors. These sensors have a prototypic architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scaled-up, 3-D versions run on a Cray Y-MP supercomputer. A semi-automated method of reconstruction of neural tissue from serial sections studied in a transmission electron microscope has been developed to eliminate tedious conventional photography. The reconstructions use a mesh as a step in generating a neural surface for visualization. Two meshes are required to model calyx surfaces. The meshes are connected and the resulting prisms represent the cytoplasm and the bounding membranes. A finite volume analysis method is employed to simulate voltage changes along the calyx in response to synapse activation on the calyx or on calyceal processes. The finite volume method insures that charge is conserved at the calyx-process junction. These and other models indicate that efferent processes act as voltage followers, and that the morphology of some afferent processes affects their functioning. In a final application, morphological information is symbolically represented in three dimensions in a computer. The possible functioning of the connectivities is tested using mathematical interpretations of physiological parameters taken from the literature. Symbolic, 3-D simulations are in progress to probe the functional significance of the connectivities. This research is expected to advance computer-based studies of macular functioning and of synaptic plasticity.

Ross, Muriel D.↗
DOE OSTI2020

Progress on Associate-Particle Imaging Algorithms, 2020

The present work describes progress on the development of imaging algorithms that use fast neutron signatures acquired using the associated-particle imaging (API) method. The present work complements ongoing work to develop neutron source and detector hardware to enable field inspection by investigating algorithms that are capable of discriminating between critical materials or extracting three-dimensional geometrical information from single-sided or transmission measurements. The present work is divided into three approaches:(1)Iterative reconstruction of inelastic gamma-ray emissions to perform three-dimensional time-of-flight imaging in a single view in either transmission or backscatter configurations. Iterative reconstruction enables image resolution better than the inherent TOF resolution.(2)Decomposition of registered neutron and x ray radiographs into an assumed material list for each pixel in the image.(3)Material identification using full spectral analysis that includes the emergent neutron and gamma ray energies, times, and angles.Progress for each approach is summarized for fiscal year 2020.

97 MATHEMATICS AND COMPUTING↗