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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
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 OSTI2020

CarbonSafe TR McMillen-2

Computed tomography and core logger data described in Technical Report "Computed Tomography Scanning and Geophysical Measurements of the T.R. McMillen #2 Core" by R. Schmitt et al, 2020.

CarbonSAFE↗
DOE OSTI2023

ISGS Seal wells

Computed tomography and core logger data described in Technical Report "Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin" by Paronish et al., 2023

carbon storage↗
DOE OSTI2024

WARE 1-9 Well

Computed tomography and core logger data described in Technical Report "Computed Tomography Scanning and Geophysical Measurements of the J. F. WARE Gas Unit 1-9 Well in Smith County, Texas" by Brinza et al. , 2024.

CoreCM↗
DOE OSTI2020

4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique

The temporally and spatially resolved tracking of lithium intercalation and electrode degradation processes are crucial for detecting and understanding performance losses during the operation of lithium-batteries. Here, high-throughput X-ray computed tomography has enabled the identification of mechanical degradation processes in a commercial Li/MnO 2 primary battery and the indirect tracking of lithium diffusion; furthermore, complementary neutron computed tomography has identified the direct lithium diffusion process and the electrode wetting by the electrolyte. Virtual electrode unrolling techniques provide a deeper view inside the electrode layers and are used to detect minor fluctuations which are difficult to observe using conventional three dimensional rendering tools. Moreover, the 'unrolling' provides a platform for correlating multi-modal image data which is expected to find wider application in battery science and engineering to study diverse effects e.g. electrode degradation or lithium diffusion blocking during battery cycling.

25 ENERGY STORAGE↗
DOE OSTI2026

3D analysis of abnormal grain growth in calcia doped alumina in the presence of large pores

Abnormal grain growth has been previously found to increase with the inclusion of large pores (∼60 µm in diameter) in 80 ppm calcium doped alumina. However, the two-dimensional analysis could not accurately describe the proximity of the abnormal grains and pores to establish a correlation. This study uses laboratory-based diffraction contrast tomography and x-ray computed tomography to spatially map the pores and abnormal grains in 3D. A preference towards the formation of abnormal grains near large pores is found when compared to all potential sites. This finding supports that the pores may be a nucleation site for complexion transitions that promote abnormal grain growth. The growth of the abnormal grains in a subsequent heat treatment at 1600°C for 16 hrs was also studied. The elongation along the principal axes is similar for both small and large grains, again supporting that abnormal grain growth was facilitated by a complexion transition.

Abnormal grain growth↗
DOE OSTI2020

Water content of carbon dioxide at hydrate forming conditions

There is an interest to ensure sub-saturated water content in lines containing carbon dioxide in applications such as enhanced oil recovery and carbon sequestration, to reduce risks of hydrate blockage and corrosion. The water content of carbon dioxide at various temperatures and pressures has been measured in the past, but there is no consistent set of measurements that could be used for carbon dioxide storage and transportation design work. The solubility of water in a carbon dioxide rich gas phase at hydrate forming conditions was measured in this work. Pressures ranged from 12.06 to 29.30 bar along two isotherms, 1 °C and -7 °C, all within the gaseous carbon dioxide and hydrate stability zone. For the first time in these types of measurements, the solid phase was also characterized and confirmed to be carbon dioxide hydrate via X-ray computed tomography, simultaneous with water content measurements of the gas phase. Once carbon dioxide hydrate conversion had reached a maximum value (65% estimated by X-ray computed tomography), the equilibrium water content was measured. Prior to reaching this maximum carbon dioxide hydrate conversion, the water content in carbon dioxide was observed to decrease as liquid water converted to carbon dioxide hydrate. Furthermore, this slow conversion to hydrate, metastability of the hydrate phase, or unexpected phases may be responsible for the large discrepancy between prior data sets for similar carbon dioxide water content measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

J&L #1 Well-Pennsylvania Oriskany Characterization

Dataset for this database page represents data from technical report "Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County PA " Sharma, M; Paronish, T.; Mitchell, N.; Crandall, D.; Neubaum, J. Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County PA; DOE.NETL-2023.3889; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2023; p 37.

Appalachian Basin↗
DOE OSTI2025

High spatial resolution neutron imaging of lithium-ion batteries: Correlating microstructure and lithium transport

Thick electrodes for lithium-ion batteries can increase the overall energy density, but increasing the electrode thickness introduces charge transport limitations. These limitations may be mitigated through proper electrode structuring. Here, high spatial resolution neutron imaging was used to understand the correlation between microstructure and lithium transport in lithium-ion anodes. Batteries with distinct graphite anode microstructures were produced and studied with high spatial resolution in operando neutron radiography to observe the effects of structure on transport. High spatial resolution neutron computed tomography was performed following in operando neutron radiography. X-ray computed tomography and scanning electron microscopy were used to observe the finer scale anode structure to complement neutron imaging. Solvent-free anodes containing a tightly-packed layered structure confined lithium movement close to the separator. This structure limited capacity, but supported better rate capability. Conversely, a more open pore structure in the wet cast anodes yielded higher capacity with reduced rate capability. Together, these results show that lithium distributions can be controlled by the macroscopic structure of the electrodes, the microstructural pore network, and the microscale active areas that support electrochemical reactions. Furthermore, multimodal imaging applying the complementary strengths of neutron and X-ray methods is shown as a tool for advancing battery design.

25 ENERGY STORAGE↗
DOE OSTI2023

Ultrasound and X-ray Cross-Characterization of a Graded Impedance Impactor used for Shock-Ramp Compression Experiments

Abstract In this work we perform ultrasound measurements on an impedance graded impactor made by tape casting magnesium, copper, and tungsten. We also destructively extract small representative samples from the part for complementary characterization with x-ray computed tomography. Combining the two data sets enables direct assignment of some of the measured ultrasound features to specific material characteristics identified by x-ray tomography. Our results demonstrate how ultrasound inspection, informed by x-ray computed tomography, can be used to identify sub-millimeter material amalgamations and spatial heterogeneities in this graded material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

CT and Scanning Data of the KGS Wellington 1-32 CarbonSAFE Core

Data described in the NETL Technical Report Series "Computed Tomography Scanning and Geophysical Measurements of the Wellington 1-32 Core", including processed and raw CT and measurements from NETL's multi-sensor core logger. Paronish, T.; Schmitt, R.; Mitchell, N; Brown, S; Crandall, D.; Moore, J.; Hasiuk, F.; Potter, N.; Holubnyak, Y.E. Computed Tomography Scanning and Geophysical Measurements of the Wellington 1-32 Core; DOE.NETL-2021.2882; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2022; p 108. DOI: https://doi.org/10.2172/1894355 https://edx.netl.doe.gov/dataset/computed-tomography-scanning-and-geophysical-measurements-of-the-wellington-1-32-core

CarbonSafe↗
DOE OSTI2023

ISGS CarbonSAFE Lively Grove Core

Computed tomography and core logging data from the Lively Grove #1 Well core drilled by the Illinois State Geological Survey in 2021 under DE-FE0031892. Data description can be found in: Crandall, D.; Paronish, T.; Mitchell, N.; Jarvis, K.; Brown, S.; Moore, J.; Gill, M.; Blakley, C.; Okwen, R.; Korose, C.; Carman, C. Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core; DOE/NETL-2023/3877; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2023; p 61.

CarbonSafe↗
DOE OSTI2021

Impact of electrode porosity architecture on electrochemical performances of 1 mm-thick LiFePO4 binder-free Li-ion electrodes fabricated by Spark Plasma Sintering

Thick electrodes with high active material loadings have been intensively studied over the last couple of decades in pursuit of achieving high energy density systems. To optimize and enhance the electrochemical performance of such electrodes, one has to control the pore morphology by, for example, varying the pore size and shape, and the level of porosity. In the present work, the fabrication of thick binder-free LiFePO4 (LFP) electrodes with two different pore sizes (12 and 20 mu m) and porosities (21 vol% and 44 vol%) using Spark Plasma Sintering (SPS) and templating approach is reported. The well-controlled porous architecture inside the thick electrodes is realized by fine-tuning experimental parameters. The impact of porosity architecture on electrochemical performance is quantified and correlated with the 3D tortuosity values determined from both micro-computed tomography and electrochemical impedance-based experimental methods. Based on the micro-computed tomography data analysis, estimated tortuosity values along X, Y, and Z axes reveal an anisotropic effect perpendicularly to the SPS compression axis (Z-direction). This is particularly profoundly observed in the samples with larger pores (20 mu m). The correlation between morphological properties and the rate capability performance is established indicating that the capacity loss happens mainly due to the Li-ion diffusion limitations.

Cathode material↗
NASA NTRS1993

Neural networks for calibration tomography

Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.

Decker, Arthur↗
NASA NTRS1991

Determinants of the mechanical properties of bones

The mechanical properties of bones are governed by the same principles as those of man-made load-bearing structures, but the organism is able to adapt its bone structure to changes in skeletal loading. In this overview of the determinants of the strength and stiffness of bone, a continuum approach has been taken, in which the behavior of a macroscopic structure depends on its shape and size, and on the mechanical properties of the material within. The latter are assumed to depend on the composition (porosity and mineralization) and organization (trabecular or cortical bone architecture, collagen fiber orientation, fatigue damage) of the bone. The effects of each of these factors are reviewed. Also, the possible means of non-invasively estimating the strength or other mechanical properties of a bone are reviewed, including quantitative computed tomography, photon absorptiometry, and ultrasonic measurements. The best estimates of strength have been obtained with photon absorptiometry and computed tomography, which at best are capable of accounting for 90% of the strength variability in a simple in vitro test, but results from different laboratories have been highly variable.

Non-NASA Center↗
DOE OSTI2025

Enhancing synchrotron radiation micro-CT images using deep learning: an application of Noise2Inverse on bone imaging

In bone-imaging research, in situ synchrotron radiation micro-computed tomography (SRµCT) mechanical tests are used to investigate the mechanical properties of bone in relation to its microstructure. Low-dose computed tomography (CT) is used to preserve bone's mechanical properties from radiation damage, though it increases noise. To reduce this noise, the self-supervised deep learning method Noise2Inverse was used on low-dose SRµCT images where segmentation using traditional thresholding techniques was not possible. Simulated-dose datasets were created by sampling projection data at full, one-half, one-third, one-fourth and one-sixth frequencies of an in situ SRµCT mechanical test. After convolutional neural networks were trained, Noise2Inverse performance on all dose simulations was assessed visually and by analyzing bone microstructural features. Visually, high image quality was recovered for each simulated dose. Lacunae volume, lacunae aspect ratio and mineralization distributions shifted slightly in full, one-half and one-third dose network results, but were distorted in one-fourth and one-sixth dose network results. Following this, new models were trained using a larger dataset to determine differences between full dose and one-third dose simulations. Significant changes were found for all parameters of bone microstructure, indicating that a separate validation scan may be necessary to apply this technique for microstructure quantification. Noise present during data acquisition from the testing setup was determined to be the primary source of concern for Noise2Inverse viability. While these limitations exist, incorporating dose calculations and optimal imaging parameters enables self-supervised deep learning methods such as Noise2Inverse to be integrated into existing experiments to decrease radiation dose.

Obata, Yoshihiro (ORCID:0000000303659129)↗