Longitudinal current profile reconstruction from a wakefield response in plasmas and structures
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
SEARCH · Search NASA
Results for “structure reconstruction”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Reconstruction wedges in AdS / CFT with boundary fractallike structures
Not Available
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Inference of three-dimensional hot-spot and shell morphology in inertial confinement fusion experiments using a convolutional neural network
The performance of inertial confinement fusion (ICF) implosions is sensitive to the three-dimensional (3D) morphology of the hot-spot and shell configurations. The ability to infer shell-mass uniformity and reconstruct 3D hot spots is crucial for quantifying the degradation of ignition criteria and improving symmetry in ICF implosion experiments. In this work, we present a deep-learning convolutional neural network (CNN) for reconstructing 3D hot-spot and shell structures for ICF capsules. The 3D geometry of the hot spot is reconstructed from x-ray images measured from multiple lines of sight on OMEGA. The shell configuration is inferred indirectly through machine learning using a convolutional neural network extensively trained on a dec3d simulation database. This simulation-dependent approach yields consistent agreement between reconstructed 3D shell densities and machine-learning optimized dec3d simulation results. This work demonstrates a CNN framework that successfully reconstructs 3D capsule structures from two-dimensional images in ICF implosions.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Protein identification from electron cryomicroscopy maps by automated model building and side-chain matching
Using single-particle electron cryo-microscopy (cryo-EM), it is possible to obtain multiple reconstructions showing the 3D structures of proteins imaged as a mixture. Here, it is shown that automatic map interpretation based on such reconstructions can be used to create atomic models of proteins as well as to match the proteins to the correct sequences and thereby to identify them. This procedure was tested using two proteins previously identified from a mixture at resolutions of 3.2 Å, as well as using 91 deposited maps with resolutions between 2 and 4.5 Å. The approach is found to be highly effective for maps obtained at resolutions of 3.5 Å and better, and to have some utility at resolutions as low as 4 Å.
59 BASIC BIOLOGICAL SCIENCES↗
Vortex tubes in turbulent flows: Identification, representation, reconstruction
In many cases the structure of a fluid flow is well-characterized by its vortices, especially for the purpose of visualization. In this paper we present a new algorithm for identifying vortices in complex flows. The algorithm produces a skeleton line along the center of a vortex by using a two-step predictor-corrector scheme. The vorticity vector field serves as the predictor and the pressure gradient (in the perpendicular plane) serves as the corrector. We describe an economical description of the vortex tube's cross-section: a 5-term truncated Fourier series is generally sufficient, and it compresses the representation of the flow by a factor of 4000 or more. We reconstruct the vortex tubes as generalized cylinders, providing a polygonal mesh suitable for display on a graphics workstation. We show how the reconstructed geometry of vortex tubes can be enhanced to help visualize helical motion in a static image.
Banks, David C.↗
The Role of Secondary Particle Structures in Surface Phase Transitions of Ni-Rich Cathodes
Nanometer-thick reconstruction layers on layered cathode surfaces have been widely observed on both pristine and cycled materials. However, the mechanisms of reconstruction and the role that these structures play in electrochemical performance are not fully understood. From a crystallographic perspective, such surface reconstruction layers result from cation site-mixing between Li and transition-metal ions, but it remains far from clear as to what the critical factors are that control such cation mixing for various cathode chemistries. In this paper, we report observations on surface transformations during cycling of a Ni-rich cathode-oxide that are governed by direct contact with the liquid electrolyte. Specifically, within a secondary particle, the three-dimensional hierarchical aggregate of primary particles leads to the formation of grain boundaries of different characteristics, including open grain boundaries that allow the permeation of liquid electrolyte, and closed grain boundaries that exclude liquid electrolyte penetration. Upon battery cycling, surfaces in direct contact with the liquid electrolyte showed a surface reconstruction layer while the surfaces that did not have contact with the electrolyte showed no such reconstructions. In addition, the critical role of oxygen in reconstruction of grain boundaries is demonstrated, and the unexpected oxygen depletion at twin boundaries result in severe phase transitions. The present work provides further insights into phase transitions at solid-solid and solid-liquid interfaces within secondary cathode particles and suggests strategies for mitigating surface/interfacial degradation.
36 MATERIALS SCIENCE↗
In situ TEM observation of calcium silicate hydrate nanostructure at high temperatures
Fire poses a substantial threat to concrete structures because calcium silicate hydrate (C-S-H) is not thermally stable at high temperatures. Herein, in situ TEM at temperatures from 20 to 800 °C was conducted to study the thermal-induced structural changes in C-S-H. We captured C-S-H shrinks at an average rate of 0.02 μm{sup 2}/{sup o}C upon heating with three stages observed, including induction, constant, and rapid periods. Our observation revealed that an 800 nm pore could be healed during pore structure evolution owing to the reconstruction and deformation among C-S-H blocks. The Ca/Si ratio was dropped at higher temperatures because of the leakage of calcium ions from the C-S-H structure to form CaO precipitates. The temperature-driven phase transformation and degradation were also detected using electron diffraction that C-S-H was transformed into metastable calcium silicate minerals above 800 °C. This work provides insights into the nanoscale transformation of C-S-H at high temperatures.
36 MATERIALS SCIENCE↗
Size Effect of Local Current-Voltage Characteristics of MX 2 Nanoflakes: Local Density of States Reconstruction from Scanning Tunneling Microscopy Experiments
Local current-voltage characteristics for low-dimensional transition-metal dichalcogenides (LDTMD), as well as the reconstruction of their local density of states (LDOS) from scanning tunneling microscopy (STM) experiments, are of fundamental interest and can be useful for advanced applications. Most of the existing models either have limited applicability for complex-shaped LDTMDs (e.g., those based on the Simmons approach) or require solving of an ill-defined integral equation to deconvolute the unknown LDOS (e.g., those based on the Tersoff approach). Using a serial expansion of the Tersoff formulas, we propose a flexible method to reconstruct the LDOS from local current-voltage characteristics measured in STM experiments. We establish a set of key physical parameters, which characterize the tunneling current of a STM-probe–sample contact and the sample LDOS expanded in Gaussian functions. Using a direct variational method coupled with probabilistic analysis, we determine these parameters from the STM experiments for MoS2 nanoflakes with different numbers of layers. The main result is the reconstruction of the LDOS in a relatively wide energy range around the Fermi level, which allows us to gain insight into the local band structure of LDTMDs. The reconstructed LDOS reveal pronounced size effects for the single-layer, two-layer, and three-layer MoS 2 nanoflakes, which we relate to the low dimensionality and strong bending or corrugation of the nanoflakes. We hope that the proposed elaboration of the Tersoff approach, allowing LDOS reconstruction, will be of critical interest for the quantitative description of STM experiments and also of use to better understand the microscopic physical aspects of the surface, strain, and bending contributions to the LDTMDs’ electronic properties.
42 ENGINEERING↗
Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)
Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
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↗
Far-infrared emission, gas, and ultraluminous HII regions in M101
We have made deconvolved maps of M101 in each of the 4 IRAS bands using a new maximum-entropy based model for reconstructing distributions with correlated structure on multiple scales. This new deconvolution procedure, developed by Weir (1992, J.Opt.Soc.Am., submitted), is superior to other maximum entropy-based techniques for several reasons. For our purposes, an important advantage is that it has less artifacts and greatly reduced systematic biases compared with the 'HiRes' maps of M101 produced by Aumann, Fowler, and Melnyk (1990, AJ, 99, 1674), thus it is accurate enough to perform aperture photometry. The deconvolved maps have a maximum resolution of approximately 30 sec, sufficient to resolve the brightest HII complexes and much of the spiral structure. The new maps and our comparison of the far-infrared, gas, and optical distributions are being written up in Kenney, Weir & Scoville (1992, in preparation). The quality of the reconstructed far-infrared maps is good enough for us to carry out most of the analyses outlined in the original proposal. From a ratio of the 60 micron and 100 micron maps, we have found that the ultraluminous HII complexes in the outer galaxy have the hottest dust temperatures with T approximately 50-60 K, which is twice as hot as most of the disk. Their extraordinary luminosity in the far-infrared is due to a relatively small amount of dust being heated to high temperatures, rather than a large concentration of dust and gas. A map of the dust opacity at 60 microns shows good overall agreement with a map of cold gas (HI+H2), indicating that throughout most of the galaxy only approximately 20 percent of the dust is warm enough to be detected by IRAS. The ultraluminous HII complexes have a high luminosity-to-gas mass ratio, independent of whether the far-infrared or the H-alpha emission line is used to measure the luminosity, which implies that gas is being converted into high mass stars more rapidly in these complexes compared to other locations in the disk.
Kenney, J. D. P.↗
Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction
X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.
X-ray tomography↗
Fluid Physics of Foam Evolution and Flow
The grant supported theoretical, numerical and experimental work focused on the elucidation of the fluid physics of foam structure, evolution and flow. The experimental work concentrated on these subject areas: (a) Measurements of the speed of reconnections within a foam; (b) statistics of bubble rearrangements; and (c) three-dimensional reconstruction of the foam structure. On the numerical simulation and theory side our efforts concentrated on the subjects: (a) simulation techniques for 2D and 3D foams; (b) phase transition in a compressible foam; and (c) TCP structures.
Aref, H.↗
A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques
Assessing the fingerprint of a material’s microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation.
36 MATERIALS SCIENCE↗
Ultrasparse View X-ray Computed Tomography for 4D Imaging
X-ray computed tomography (CT) is a noninvasive, nondestructive approach to imaging materials, material systems, and engineered components in two and three dimensions. Acquisition of three-dimensional (3D) images requires the collection of hundreds or thousands of through-thickness X-ray radiographic images from different angles. Such 3D data acquisition strategies commonly involve suboptimal temporal sampling for in situ and operando studies (4D imaging). Herein, we introduce a sparse-view imaging approach, Tomo-NeRF, which is capable of reconstructing high-fidelity 3D images from <10 twodimensional radiographic images. Experimental 2D and 3D X-ray images were used to test the reconstruction capability in two-view, four-view, and six-view scenarios. Tomo-NeRF is capable of reconstructing 3D images with a structural similarity of 0.9971–0.9975 and a voxel-wise accuracy of 81.83–89.59% from 2D experimentally obtained images. Furthermore, the reconstruction accuracy for the experimentally obtained images is less than the synthetic structures. Experimentally obtained images demonstrate a similarity of 0.9973–0.9984 and a voxelwise accuracy of 84.31–95.77%.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Transport anomalies in the layered compound BaPt 4 Se 6
We report a layered ternary selenide BaPt 4 Se 6 featuring sesqui-selenide Pt 2 Se 3 layers sandwiched by Ba atoms. The Pt 2 Se 3 layers in this compound can be derived from the Dirac-semimetal PtSe 2 phase with Se vacancies that form a honeycomb structure. This structure results in a Pt (VI) and Pt (II) mixed-valence compound with both PtSe 6 octahedra and PtSe 4 square net coordination configurations. Temperature-dependent electrical transport measurements suggest two distinct anomalies: a resistivity crossover, mimic to the metal-insulator (M-I) transition at ~150 K, and a resistivity plateau at temperatures below 10 K. The resistivity crossover is not associated with any structural, magnetic, or charge order modulated phase transitions. Magnetoresistivity, Hall, and heat capacity measurements concurrently suggest an existing hidden state below 5 K in this system. Angle-resolved photoemission spectroscopy measurements reveal a metallic state and no dramatic reconstruction of the electronic structure up to 200 K.
36 MATERIALS SCIENCE↗
Efficient high-resolution rotor wake calculations using flow field reconstruction
Recent computational studies of helicopter flowfields for acoustic applications has led to the development of exceptionally efficient analysis methods for carrying out Lagrangian simulations of the vortex wake. The capabilities of these methods are demonstrated here through calculations involving a variety of wake/rotor interactions associated with both main rotor and tail rotor flowfields. These methods incorporate a flowfield reconstruction approach efficiently to compute vortex wake interactions within arbitrary regions located near the main rotor. This paper summarizes the development of the reconstruction approach and outlines some of its potential uses, while focusing primarily on its application to rotor noise calculations. The development of the nearfield velocity corrections used in the analysis of close vortex interactions is described, and the overall structure of the current reconstruction approach is discussed.
Quackenbush, Todd R.↗
Identification of a low-energy metastable 1 T -type phase for monolayer VSe 2
Elucidating the polymorphism of transition metal dichalcogenide layers and the interplay between structure and properties is a key challenge for the application of these materials. We identify a low-energy metastable phase of monolayer VSe 2 and elucidate its magnetic and electronic properties. This structure is distinct from the previously identified charge density wave (CDW) phase. However, while having rather distinct properties it is very close in energy to the CDW phase and is likely to be realized in experiments. Importantly, local bonding instabilities, as characterized by reconstruction of the electronic structure over a wide energy range, are important for this distortion, which includes both V off-centering in the octahedral coordination cages and a partial disproportionation into two distinct types of V. The phase does not have a ferromagnetic ground state. Furthermore, the results show that the physics of 1T–VSe 2 are richer than previously known with an interplay of Fermi surface instabilities and local bonding effects.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗