Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CT”

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.

At least 55 records · Page 3

Effect of chemical substitution and external strain on phase stability and ferroelectricity in two dimensional M 2 CT 2 MXenes

Two dimensional ferroelectric materials are gaining increasing attention for use in ultrathin electronic devices owing to the presence of a spontaneous polarization down to one or two monolayers. However, such materials are difficult to identify, especially those with out-of-plane electric polarizations. Previous work predicted that a metastable ferroelectric phase exists in the 2D MXene Sc 2 CO 2 , while further studies have predicted that this phase exists in other MXene chemistries. However, questions remain about the origin of ferroelectricity, the stability of this phase relative to other competing phases, and the effect of external stimuli in these materials. In this work, we use density functional theory calculations to investigate 12 M 2 CT 2 MXenes (M = transition metal, T = surface terminating group) and determine which have the ferroelectric phase as their ground state. We compute these materials’ polarizations, densities of states, phonon band structures, Bader charges, and Born effective charges in the ferroelectric phase to elucidate the reasons for its stabilization. We demonstrate that this ferroelectric phase can be preferentially stabilized in non-ferroelectric MXenes through full chemical substitution of Sc or O, alloying of the Sc sites, or application of epitaxial strain. Finally, we show that these materials have excellent piezoelectric properties as well. This work provides a detailed understanding of ferroelectric MXenes and show how the number of 2D ferroelectric materials can be increased through chemical substitution or application of external stimuli.

36 MATERIALS SCIENCE↗

Correlating electronic properties with M-site composition in solid solution Ti y Nb 2- y CT x MXenes

High electrical conductivity is desired in MXene films for applications such as electromagnetic interference shielding, antennas, and electrodes for electrochemical energy storage and conversion applications. Due to the acid etching-based synthesis method, it is challenging to deconvolute the relative importance that factors such as chemical composition and flake size contribute to resistivity. To understand the intrinsic and extrinsic contributions to the macroscopic electronic transport properties, a systematic study controlling compositional and structural parameters was conducted with eight solid solutions in the Ti y Nb 2-y CT x system. Here, in particular, we investigated the different roles played by metal (M)-site composition, flake size, and d-spacing on macroscopic transport. Hard x-ray photoemission spectroscopy and spectroscopic ellipsometry revealed changes to electronic structure induced by the M-site alloying. Consistent with the spectroscopic results, the low- and room-temperature conductivities and effective carrier mobility are correlated with the Ti content, while the impact of flake size and d-spacing is most prominent in low-temperature transport. The results provide guidance for designing and engineering MXenes with a wide range of conductivities.

36 MATERIALS SCIENCE↗

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)↗

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗

Micro-CT Imaging and Fluid Flow Simulations of Fractures in MSEEL Shale

micro-CT scans of a naturally fractured MSEEL shale sample as a shear fracture is generated and displaced in the center, intact region of the sample. Steady State laminar fluid flow simulations were then performed on each individual fracture during each experimental segment as effective stress and shear displacement changed. Released under LA-UR-21-24335.

Fractures,Fracturing Initiation,Marcellus Shale↗

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↗

PDF4LHC21: Update on the benchmarking of the CT, MSHT and NNPDF global PDF fits

There have been recent updates to the three global PDF fits (CT, MSHT and NNPDF), all adding large amounts of data from the LHC, and this has resulted in significant changes to the global PDFs. Given the impact that the new PDFs will have on physics comparisons at the LHC, it is crucial to perform a benchmarking among the PDFs, similar in spirit to that which was carried out for PDF4LHC15, widely used for LHC physics. In this article we detail a benchmarking comparison of three global PDF sets - CT18, MSHT20 and NNPDF3.1 - and their similarities and differences that have been observed. The end result of this study will be a new PDF4LHC21 ensemble of combined PDFs suitable for a wide range of LHC applications.

Cridge, Thomas↗

Dynamic Evaluation of the Upper Tyler Formation and Well Stimulation Fluid Interactions Using Micro-CT Imaging

Abundant concentrations of swelling clays in the oil-bearing upper Tyler Formation inhibit unconventional well stimulation techniques and associated long-term oil and gas production success. Laboratory evaluation of the geochemical interactions between the formation material and various stimulation fluids may help identify innovative approaches that provide a solution to successful well stimulation and subsequent oil production. The objective of this research was to understand the complexities of well stimulation fluid and clay mineral interactions within the Tyler Formation and identify potential fracturing fluid formulations that mitigate swelling properties of the clays in the reservoir to enhance stimulation success and promote long-term oil and gas production. Collaboration with the National Energy Technology Laboratory (NETL), utilizing their Tescan DynaTOM micro-CT analysis instrumentation, provided an innovative approach to understand real-time, dynamic interactions of the formation material and various potential stimulation fluids. Results are anticipated to identify key mechanisms occurring at the micro-scale level and provide insight into modified stimulation techniques uniquely suited for successful production applications.

enhanced oil recovery↗

Automatic threat recognition system and method using material disambiguation informed by physics in x-ray CT images of baggage

An automatic threat recognition (ATR) system is disclosed for scanning an article to recognize contraband items or items of interest contained within the article. The ATR system uses a CAT scanner to obtain a CT image scan of objects within the article, representing a plurality of 2D image slices of the article and its contents. Each 2D image slice includes information forming a plurality of voxels. The ATR system includes a computer and determines which voxels have a likelihood of representing materials of interest. It then aggregates those voxels to produce detected objects. The detected objects are further classified as items of interest vs. not of interest. The ATR system is based on learned parameters for a novel interaction of global and object context mechanisms. ATR system performance may be optimized by using jointly optimal global and object context parameters learned during training. The global context parameters may apply to the article as a whole and facilitate object detection. The object context parameters may apply to the individual object detections.

Paglieroni, David W.↗

DETERMINATION OF STRUT QUALITY FACTORS IN ADDITIVELY MANUFACTURED LATTICES USING IN-SITU COMPRESSION TESTING µ-CT

In response to the need for an automated, commercial method to qualify additively manufactured (AM) lattice components, an experiment was conducted to evaluate the effects of defective lattice struts on the structural compression strength. Lattice samples with known defective or missing struts were compressed using a Deben CT5000RT and imaged using xray µ-CT. The compressive force and x-ray computed tomography results were compared to defect free standards to evaluate the impact of each defect type on the overall structure’s compressive strength. This analysis will allow for simplifications to Finite Element Analysis (FEA) on AM parts without sacrificing model fidelity. Understanding the contribution of each defect type and severity will also better inform non-destructive evaluation (NDE) personnel of the inspection parameters necessary to detect the smallest feature of importance.

Dinova, Vincent A.↗

District Geothermal Heating + Cooling Deployment in a CT Environmental Justice Community

The report marks the team’s completion of all required tasks and milestones. Work completed for Task 1 (Technical and Economic Feasibility Assessment & Procurement Drafting) included development of analysis and design model; completion of technical, economic, and environmental assessments; and technical outreach and coalition design. Components for Task 2 (Outreach & Community Engagement) involved broad outreach and community-engagement efforts (including stakeholder meetings and a webinar as well as development of a formal engagement plan) and development of a web page and a case study. For Task 3 (Workforce Transition, Development, & Training Plan), the team undertook a formal statewide geothermal workforce needs assessment, developed corresponding recommendations for both the state as a whole and the Wallingford project, and held several workshops. For Task 4 (Project Management & Data Sharing), the team drafted a data-sharing plan.

15 GEOTHERMAL ENERGY↗

Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components

X-ray computed tomography (XCT) is essential for nondestructive evaluation and quality control of large-scale metal components. XCT imaging, however, faces significant challenges from metal artifacts, particularly those caused by Compton scattering, which degrade image quality and obscure critical details. Hardware-based solutions (e.g. scatterControl) offer advancements by intercepting scattered photons and reducing artifacts, but they can be time-consuming and require additional processing. Here, we propose modifying and leveraging a novel deep learning (DL) framework, Simurgh, to enhance and accelerate scatter correction in XCT. By combining scatterControl with DL-based artifact removal, we demonstrate significant reduction in scan time while producing high-quality reconstructions. Through extensive evaluation on industrial XCT data, we show that our methods reduce scan time by up to more than 10 x while preserving flaw detectability. Quantitative analysis across multiple segmentation techniques confirms that Simurgh-based reconstructions consistently outperform traditional Feldkamp-Davis-Kress, model-based iterative reconstruction, and commercial DL models in both pixel-level and task-specific evaluations, enabling scalable, high-throughput XCT workflows for characterization of large scale components in applications such as casting and metal additive manufacturing.

Complex metal parts↗

Mt. Simon Sandstone - High Resolution CT

High resolution micro-computed tomography images of sandstone from the Mt. Simon formation at different depths. These images provide an insight into the pore structure of the Mt. Simon sandstone (e.g. for potential CO2 storage). This data set can be used to further study the formation as a whole..

CCS,CO2 Sequestration,Carbon Sequestration,Compute↗