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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Clutter Distributions for Tomographic Image Standardization in Ground-Penetrating Radar

Multistatic ground-penetrating radar (GPR) signals can be imaged tomographically to produce 3-D distributions of image intensities. In the absence of objects of interest, these intensities can be considered to be estimates of clutter. These clutter intensities spatially vary over several orders of magnitude and vary across different arrays, which makes a direct comparison of these raw intensities difficult. However, by gathering statistics on these intensities and their spatial variation, a variety of metrics can be determined. In this study, the clutter distribution is found to fit better to a two-parameter Weibull distribution than Gaussian or log-normal distributions. Based on the spatial variation of the two Weibull parameters, scale and shape, more information may be gleaned from these data. How well the GPR array is illuminating various parts of the ground, in depth and cross track, may be determined from the spatial variation of the Weibull scale parameter, which may in turn be used to estimate an effective attenuation coefficient in the soil. The transition in depth from clutter- to noise-limited conditions (which is one possible definition of GPR penetration depth) can be estimated from the spatial variation of the Weibull shape parameter. Lastly, the underlying clutter distributions also provide an opportunity to standardize image intensities to determine when a statistically significant deviation from background (clutter) has occurred, which is convenient for buried threat detection algorithm development that needs to be robust across multiple different arrays.

42 ENGINEERING↗
DOE OSTI2020

Supplementary material for manuscript: Microcomputed X-ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives

This data contains the supplemental information that will be accessible to the public from the paper “Microcomputed X-ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives”. The data set contains the reconstructed slices for the 3D images of three different high explosives including: HMX-HTPB, PBX 9501 and PBX 9502. The data sets are folders of reconstructed tiffs showing the microstructure (crystals, binder, voids) and a segmented data set of each. Finally, a .gif movie is also present that plays the slices sequentially. The folders contain the voxel size information. See the manuscript for more details.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Angled slit design for computed tomographic imaging of electron beams

Computed tomographic method and apparatus includes an electron or ion beam having a beam axis, a refractory metal disk; at least one slit in the refractory metal disk that receive the beam, wherein the slit is at an angle to the beam axis; a beam entrance opening in the slit that allows the beam to enter; an effective beam exit opening in the slit that allow the beam to exit, wherein the beam effective exit opening is smaller than the beam entrance opening; and a system for moving the beam across the refractory metal disk, wherein the beam enters the slit through the beam entrance opening and exits the slit through the effective beam exit opening; and a computed tomographic device for measuring the beam that enters and exits the slit for analyzing the beam.

Elmer, John W.↗
DOE OSTI2022

Tomographic imaging of atmospheric pressure plasma on complex surfaces

Many plasma types and behaviors such as streamer, arcs, cathode spots, anode spots, ionization waves, and magnetic field interactions create non-symmetric, fully 3D plasma structures. The plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and the interfacing material properties. For example, ionization waves propagate in directions where ionization rates are highest, leading to complex configurations that are not fully understood or well characterized. Recent advances in laser diagnostics and models have been able to investigate well-controlled idealized plasmas in 2D fashion, but the complex structure in actual plasmas requires a technique than can provide a more complete 3D picture. However, 3D plasma diagnostics do not currently exist. To address this limitation, this activity will leverage available equipment to build a new tomographic optical imaging capability and advance the state-of-the-art in plasma diagnostics to investigate 3D phenomena on complex surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

X-ray and gamma-ray tomographic imaging of fuel relocation inside sodium fast reactor test assemblies during severe accidents

The present work reports on x-ray and gamma-ray high-spatial resolution computerized tomography measurements of the Pin Bundle Metallic Fuel Relocation (PBR) assemblies tested in the Metallic Uranium Safety Experiment (MUSE) facility at Argonne National Lab (ANL). The aim of the study was to characterize fuel relocation structures that develop during severe core accidents pertaining to SFR assemblies; these include but are not limited to advanced core disruption recreated in the PBR-1 assembly, and cladding breach recreated in the PBR-2 assembly. We report the x-ray tomography measurements were able to resolve small quantities of relocation fuel; with increased presence of relocation fuel, the x-ray 1measurements spatially mapped the material but could not resolve the inner regions of these. The gamma-tomography measurements showed improved results, resolving the relocation structures in great detail. The upper plenum of the PBR-1 assembly where the molten uranium was initially inserted presented high structural damage, reflected by the partial and complete disintegration of the central rods. Relocation fuel filled the subchannels, adhering to surviving cladding walls and the assembly casing. In the lower portion of the measured section, the tomogram degrades due to photon starvation effects hinting at the increased amount of relocation fuel potentially plugging the assembly; flow blockage in this section was difficult to determine due to the tomogram’s degradation from photon starvation. Small fragments were observed further down the assembly, dislodged from the initial insertion of the molten material. This section was used as an unperturbed assembly reference, with a calculated blockage of less than 1% from the present fragments. The PBR-2 assembly was characterized by columnar relocation structures propagating through the subchannels. Three of the relocation structures were captured in the measured section, with evidence of cross migration on to adjacent subchannels. The measured section in this assembly captures the leading edge of two structures. The calculated flow blockage was 16% in the planes where the three relocation structures are present, but this quickly decreases to approximately 5% past the leading edge of two of the structures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Multi-modal tomographic imaging system for poolside characterization of nuclear test fuels: Design considerations and studies

Testing and qualification of advanced nuclear fuels involves an iterative process of prototyping, in-pile irradiation testing, and in-situ or ex-situ examination. Fuel restructuring and fission product migration during burnup are among the most important aspects of fuel evolution that affect several important performance characteristics such as heat removal, accident tolerance, and fission product retention. Pool-side non-destructive characterization techniques provide fuel developers with tools to understand fuel evolution at different points of burnup. A design for a compact, submersible, and multi-modal gamma-ray tomography system for imaging irradiated nuclear fuel is presented here. Detector selection, collimator geometry and fabrication, mechanical design, imaging protocol and acquisition speed are discussed. Modeling calculations show that sub-millimeter resolution can be achieved in both transmission computed tomography images as well as in emission computed tomography images in a matter of hours. Several design compromises and fabrication challenges are discussed which should be taken into consideration for future submersible gamma-ray tomography instruments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives

Microstructural characterization of composite high explosives (HEs) has become increasingly important over the last several decades in association with the development of high fidelity mesoscale modeling and an improved understanding of ignition and detonation processes. HE microstructure influences not only typical material properties (e.g., thermal, mechanical) but also reactive behavior (e.g., shock sensitivity, detonation wave shape). A detailed nondestructive 3D examination of the microstructure has generally been limited to custom-engineered samples or surrogates due to poor contrast between the composite constituents. Highly loaded (>90 wt%) HE composites such as plastic-bonded explosives (PBX) are especially difficult. Here, we present efforts to improve measurement quality by using single and dual-energy microcomputed X-ray tomography and state-of-the-art image processing techniques to study a broad set of HE materials. Some materials, such as PBX 9502, exhibit suitable contrast and resolution for an automatic segmentation of the HE from the polymer binder and the voids. Other composite HEs had varying levels of success in segmentation. Post-processing techniques that used commercially available algorithms to improve the segmentation quality of PBX 9501 as well as zero-density defects such as cracks and voids could be easily segmented for all samples. Aspects of the materials that lend themselves well to this type of measurement are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Method and apparatus to obtain limited angle tomographic images from stationary gamma cameras

A nuclear imaging system and method for performing three-dimensional imaging of anatomical structures. The system and method includes two or more gamma ray detectors each used in combination with a variable-slant hole collimator. The detectors are positioned in close proximity to, or in contact with, the structure being imaged. The detectors remain in a stationary position during the data collection process. An imaging or reconstruction method is then used to reconstruct a three-dimensional image from the data derived from the detectors.

Kross, Brian J.↗
DOE OSTI2022

Tomographic Muon Imaging of the Great Pyramid of Giza

The pyramids of the Giza plateau have fascinated visitors since ancient times and are the last of the Seven Wonders of the ancient world still standing. It has been half a century since Luiz Alvarez and his team used cosmic-ray muon imaging to look for hidden chambers in Khafre’s Pyramid. Advances in instrumentation for High-Energy Physics (HEP) allowed a new survey, ScanPyramids, to make important new discoveries at the Great Pyramid (Khufu) utilizing the same basic technique that the Alvarez team used, but now with modern instrumentation. Exploring the Great Pyramid Mission plans to field a very large muon telescope system that will be transformational with respect to the field of cosmic-ray muon imaging. We plan to field a telescope system that has upwards of 100 times the sensitivity of the equipment that has recently been used at the Great Pyramid, will image muons from nearly all angles, and will, for the first time, produce a true tomographic image of such a large structure.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Artificial neural network approach for multiphase segmentation of battery electrode nano-CT images

The segmentation of tomographic images of the battery electrode is a crucial processing step, which will have an additional impact on the results of material characterization and electrochemical simulation. However, manually labeling X-ray CT images (XCT) is time-consuming, and these XCT images are generally difficult to segment with histographical methods. We propose a deep learning approach with an asymmetrical depth encode-decoder convolutional neural network (CNN) for real-world battery material datasets. This network achieves high accuracy while requiring small amounts of labeled data and predicts a volume of billions voxel within few minutes. While applying supervised machine learning for segmenting real-world data, the ground truth is often absent. The results of segmentation are usually qualitatively justified by visual judgement. We try to unravel this fuzzy definition of segmentation quality by identifying the uncertainty due to the human bias diluted in the training data. Further CNN trainings using synthetic data show quantitative impact of such uncertainty on the determination of material’s properties. Nano-XCT datasets of various battery materials have been successfully segmented by training this neural network from scratch. We will also show that applying the transfer learning, which consists of reusing a well-trained network, can improve the accuracy of a similar dataset.

25 ENERGY STORAGE↗
DOE OSTI2022

Accelerating error correction in tomographic reconstruction

Abstract Spurred by recent advances in detector technology and X-ray optics, upgrades to scanning-probe-based tomographic imaging have led to an exponential growth in the amount and complexity of experimental data and have created a clear opportunity for tomographic imaging to approach single-atom sensitivity. The improved spatial resolution, however, is highly susceptible to systematic and random experimental errors, such as center of rotation drifts, which may lead to imaging artifacts and prevent reliable data extraction. Here, we present a model-based approach that simultaneously optimizes the reconstructed specimen and sinogram alignment as a single optimization problem for tomographic reconstruction with center of rotation error correction. Our algorithm utilizes an adaptive regularizer that is dynamically adjusted at each alternating iteration step. Furthermore, we describe its implementation in a software package targeting high-throughput workflows for execution on distributed-memory clusters. We demonstrate the performance of our solver on large-scale synthetic problems and show that it is robust to a wide range of noise and experimental drifts with near-ideal throughput.

Ali, Sajid (ORCID:0000000321864636)↗
DOE OSTI2024

Tomographic FLEET with a wedge array for multi-point three-component velocimetry

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is an important diagnostic technique for seedless velocimetry measurements particularly in supersonic and hypersonic flows. Typical FLEET measurements feature a single laser line and camera system to achieve one-component velocimetry along a line, although some multiple-spot and multiple-component configurations have been demonstrated. In this work, tomographic imaging is used to track the three-dimensional location of many FLEET spots. A quadscope is used to combine four unique views onto a single high-speed image intensifier and camera. Tomographic reconstructions of the FLEET emission are analyzed for three-component velocimetry from multiple FLEET spots. Glass wedges are used to create many (nine) closely spaced FLEET spots with less than 10% transmission losses. These developments lead to a significant improvement in the dimensionality and spatial coverage of a FLEET instrument with some increases in experimental complexity and data processing. Multiple-point three-component FLEET velocimetry is demonstrated in an underexpanded jet.

47 OTHER INSTRUMENTATION↗