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At least 253 records · Page 14

Subspace-based Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

A subspace-based form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique is based on an eigenvalue decomposition of the background noise cross-spectral matrix. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels, and when background data do not match between measurements. Experimental results show limited success in recovering signal behavior for data in which conventional background subtraction fails. The results also demonstrate the subspace subtraction technique's ability to maintain a physical coherence relationship in the modified cross-spectral matrix. Deconvolution results from microphone phased array data indicate that array integration methods are largely insensitive to subtraction type, and that background subtraction with appropriate background data is an effective alternative to diagonal removal.

deconvolution↗

A Compact Dual-Band Bowtie Antenna for RF and ISM bands Operation

Traditionally, bowtie antennas have been known to exhibit wide impedance characteristics, omnidirectional radiation patterns, and linear polarization. There is a broad range of applications from medical imaging, archaeological survey, and Ground Penetrating Radar (GPR) to trackers and sensor networks where wideband bowtie antenna designs are required for their operations. Broadening the bandwidth of bowtie antenna requires widening the flare angle of the bowtie arms, which consequently results in a large surface area that may not be suitable for space-constrained applications. Moreover, drawback attributes of the wideband bowtie designs feature inconsistent radiation pattern across the bandwidth and low signal-to-noise (SNR) ratios. As it is known, the SNR would be improved in dual- or multi-band antennas due to their reduced bandwidth. To this end, dual-band/multi-band antennas are preferred over wideband antennas in applications where more than a single frequency of interest is present. Previously, a two-port double-dipole elements was reported, whose arms were orthogonally interleaved to facilitate operation in both the standard WLAN frequency bands (J. M. Steyn and et. al, Progress in Electromagnetic Research, Vol. – 10 pp. 151-161). Even though the antenna is not very compact it does exhibit good cross-polarization, moderate gain in both frequency bands. Another dual-band bowtie antenna which excites two bands using a single transmission line was reported (Wen Chao Zheng and et. al, IEEE Trans. Antennas propag., 2014). The design was compact and did not need multi-port feeding network. In this paper, a dual-band compact bowtie antenna operating at 900 MHz (RF band) and 2.45 GHz (ISM band) using a single excitation port is introduced. It is printed on a 1.54mm thick dielectric substrate (εr = 3.38). The antenna consists of two sets of bowtie arms, a microstrip transmission line to feed the bowtie arms, and a ground plane acting as a reflector to partially reduce the back radiation. One of the bowtie arms of each frequency is printed on the top layer and the other arm, which is mirror imaged, is printed on the bottom layer of the substrate. The length of the bowtie controls the resonance frequency of the antenna and the flare angle controls the bandwidth of the antenna. The microstrip transmission line, connected to a 50 Ω SMA probe, feeds the bowtie antenna. The compact antenna can be used for both RF and ISM band applications. The bowtie arms at the lower frequency band are miniaturized by elongating their electrical lengths. The influence of miniaturizing the bowtie arms and the supporting partial ground plane is observed in the reduced peak gain and degraded front-to-back ratio. These are partly neutralized using four quarter-wave choke-slots in the ground plane with two on each side of the feeding transmission line. The proposed antenna is numerically investigated and finalized by the finite-element based full-wave EM solver, ANSYS HFSS. The miniaturization has reduced the ground plane size by ~45% and the arms size by ~41%. In addition to the size reduction benefits, the antenna shows reasonable peak gain and front-to-back ratio in both the bands. The corresponding results will be presented and discussed at the conference.

Saininad Naik↗

Online Photometric Calibration of Automatic Gain Thermal Infrared Cameras

Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.

Daftry, Shreyansh↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100$\%$ fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 $\mu$m width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. The experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Million Worker Study

Radiation health issues have been an important aspect of DOE's Worker Safety and Health programs. The goal is to ensure that workers are adequately protected from the various radiological hazards associated with DOE sites and operations. Since the early 1940’s DOE has supported the conduct of epidemiologic studies of practically every DOE (AEC) facility and collected these data, now managed by the Oak Ridge Associated Universities (ORAU), in remarkable detail. In the early 2000s, the Office of Health, Safety and Security authorized access to specific DOE worker datasets. Shortly thereafter, the DOE Office of Science provided funds for a pilot study that confirmed the feasibility of the Million Worker Study (MWS), and then additional resources were provided (with other agencies) to extend the follow-up of many populations, not just DOE workers, but also atomic veterans, industrial radiographers, nuclear power plant workers and medical radiation workers (the Million Persons Study (MPS)). This proposal was a continuation of support provided by DOE, specifically to extend the follow-up of the worker populations at the Mallinckrodt Chemical Works (MCW) and Los Alamos National Laboratory (LANL). The work addresses DOE’s interest in clarifying the health risks of their workers as well as contributing knowledge on radiation risks that is relevant today with regard to compensation schemes. The findings are also important for the US public in light of the increased population exposure to medical imaging, environmental circumstances such as hydraulic fracturing, increased exposures during high altitude flights, and with regard to nuclear accidents such as Fukushima and possible terrorist events. Furthermore, it is important to consider reducing the uncertainty in current risk estimates by developing risk coefficients based on healthy American workers who are more representative of U.S. workers and the general public than 1945 Japanese survivors of the atomic bombs living in a war-torn country which experienced deprivation, malnourishment, and increased rates of infections and other diseases. But more importantly, it is important to learn whether radiation exposures received gradually over time (e.g., years) are more or less effective in causing health effects, cancer in particular, than if the radiation dose is received all at once in a fraction of a second as experienced by the Japanese atomic bomb survivors. Finally, the ability to evaluate and combine large populations with intakes of radionuclides such as uranium, radium, plutonium, americium and polonium will provide new quantitative knowledge on human health effects that hitherto has not been possible. This cost-efficient study has built on the investments made and foundations laid by investigators and government agencies, including DOE, over the past 30-40 years, which have established early worker cohorts that can now provide answers to questions on the lifetime human health risks associated with low-level radiation exposures. Collaborating institutions included: International Epidemiology Institute, Oak Ridge Associated Universities, Oak Ridge National Laboratory, Los Alamos National Laboratory, Landauer, Inc., and Vanderbilt University. Follow-up of these two populations and the integration of them with the many other cohorts (now a total of 31) in the MPS continues under a separate DOE grant (DE-AU0000046).

61 RADIATION PROTECTION AND DOSIMETRY↗

Peptoid-based chelating ligands for selective metal chelation

The present disclosure provides peptoid-based chelating ligands, corresponding cyclic peptoids, and methods of making thereof. Functional groups may be tailored for high metal binding affinity and selectivity. The side chains of a cyclic peptoid according to the present disclosure may be selected based on, for example, high affinity for actinide or other metal ions, selectivity for actinide or other metal ions, the ability to recover a metal once it is bound to the peptoid, and whether the overall peptoid should be hydrophobic or hydrophilic. Unlike siderophores, peptoid-based chelating ligands of the present disclosure are not readily hydrolyzed under physiological conditions. Therefore, peptoid-based chelating ligands may be, for example, used to treat actinide (e.g., iron and lead) poisoning in vivo. Moreover, peptoid-based chelating ligands of the present disclosure may be used for medical imaging, chelation therapy, drug delivery, and separation technologies, for example.

Williams, Robert F.↗

Peptoid-based chelating ligands for selective metal chelation

The present disclosure provides peptoid-based chelating ligands, corresponding cyclic peptoids, and methods of making thereof. Functional groups may be tailored for high metal binding affinity and selectivity. The side chains of a cyclic peptoid according to the present disclosure may be selected based on, for example, high affinity for actinide or other metal ions, selectivity for actinide or other metal ions, the ability to recover a metal once it is bound to the peptoid, and whether the overall peptoid should be hydrophobic or hydrophilic. Unlike siderophores, peptoid-based chelating ligands of the present disclosure are not readily hydrolyzed under physiological conditions. Therefore, peptoid-based chelating ligands may be, for example, used to treat actinide (e.g., iron and lead) poisoning in vivo. Moreover, peptoid-based chelating ligands of the present disclosure may be used for medical imaging, chelation therapy, drug delivery, and separation technologies, for example.

Williams, Robert F.↗

Gamma Ray Detection In Liquid Argon Time Projection Chambers

Gamma rays are photons in excess of 100 keV of energy and can be produced by a variety of mechanisms like radioactive decay and inelastic neutrino-argon interactions. A reconstruc- tion of Compton scattering gamma rays was developed for use in liquid argon time projection chambers. This reconstruction was tested with detectors developed to demonstrate the ca- pabilities of Deep Underground Neutrino Experiment (DUNE) Near Detector Liquid Argon target (ND LAr). In October 2024, a radioactive fluorine-18 source was placed next to the Full Scale Demonstrator. The data obtained was used to test this reconstruction algorithm. It was able to determine the direction of the photons with an error of less than 10 percent. In addition to this work, there has been significant work on designing a liquid argon based Positron Emission Tomography (PET) scanner. PET scanners detect gamma rays emitted by a tracer chemical to help screen for diseases like cancer. In addition to the applications to medical imaging, this thesis briefly explores the applications of this reconstruction to de-excitation photons produced in interactions between neutrinos and argon nuclei. These applications could improve studies focusing on neutrinos originating from accelerators and supernovae.

Murphy, Thomas [Syracuse U.]↗

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

60 APPLIED LIFE SCIENCES↗

Physical interpretation and development of ultrasonic nondestructive evaluation techniques applied to the quantitative characterization of textile composite materials

In this Progress Report, we describe our continuing research activities concerning the development and implementation of advanced ultrasonic nondestructive evaluation methods applied to the inspection and characterization of complex composite structures. We explore the feasibility of implementing medical linear array imaging technology as a viable ultrasonic-based nondestructive evaluation method to inspect and characterize complex materials. As an initial step toward the application of linear array imaging technology to the interrogation of a wide range of complex composite structures, we present images obtained using an unmodified medical ultrasonic imaging system of two epoxy-bonded aluminum plate specimens, each with intentionally disbonded regions. These images are compared with corresponding conventional ultrasonic contact transducer measurements in order to assess whether these images can detect disbonded regions and provide information regarding the nature of the disbonded region. We present a description of a standoff/delay fixture which has been designed, constructed, and implemented on a Hewlett-Packard SONOS 1500 medical imaging system. This standoff/delay fixture, when attached to a 7.5 MHz linear array probe, greatly enhances our ability to interrogate flat plate specimens. The final section of this Progress Report describes a woven composite plate specimen that has been specially machined to include intentional flaws. This woven composite specimen will allow us to assess the feasibility of applying linear array imaging technology to the inspection and characterization of complex textile composite materials. We anticipate the results of this on-going investigation may provide a step toward the development of a rapid, real-time, and portable method of ultrasonic inspection and characterization based on linear array technology.

Miller, James G.↗

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired. To improve the imaging quality as a result of this limitation, convolutional neural networks (CNNs) have recently been shown to be capable of producing 3D models from visible light images or medical x-ray images rendered by volumetric computed tomography. Here, we propose a CNN to reconstruct 3D ICF spherical shells from single radiographs. We also examine the sensitivity of the 3D reconstruction to different illumination models using preprocessing techniques such as pseudo-flatfielding. To resolve the issue of the lack of 3D supervision, we show that training the CNN utilizing synthetic radiographs produced by known simulation methods allows for reconstruction of experimental data as long as the experimental data are similar to the synthetic data. We also show that the CNN allows for 3D reconstruction of shells that possess low mode asymmetries. Further comparisons of the 3D reconstructions with direct multiple LOS measurements are justified.

3D Reconstruction↗

Terahertz time-domain spectroscopy imaging of pancreatic ductal adenocarcinoma tissues

Pancreatic ductal adenocarcinoma (PDAC) ranks among the malignancies with the highest fatality and morbidity rates. This is predominantly attributable to an absence of understanding the intricate and diverse microenvironment of the tumor. We use terahertz time-domain spectroscopy (THz-TDS) imaging in transmission geometry to probe ex-vivo the heterogenous microenvironment of the genetically modified murine PDAC tissue that closely resembles the PDAC heterogeneity in human malignancy. We introduced a maximum a-posteriori probability estimation algorithm to objectively the tumor’s heterogenous microenvironment using the average values of refractive index and absorption coefficient within the useable terahertz bandwidth as imaging markers. Furthermore, direct comparison of stained histopathologic images and the refractive index and the absorption coefficient high-resolution, two dimensional maps of the same PDAC samples confirms the high potential of the THz-TDS method for tumor tissue characterization.

absorption↗

Computed Tomography Scanning and Geophysical Measurements of the Wabash No.1 Core

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize Mt. Simon core from the Wabash CarbonSAFE project, Wabash No. 1 well. The primary impetus of the work in this report is a collaboration between NETL Research and Innovation Center and the Illinois State Geological Survey at the Prairie Research Institute, University of Illinois Urbana-Champaign in Champaign, Illinois. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/wabash-no-1-well. The Wabash No. 1 well was drilled as part of a U.S. Department of Energy (DOE) funded Carbon Storage Assurance Facility Enterprise field project to assess the feasibility of developing a commercial-scale geological storage complex at the Wabash Valley Resources Integrated Gasification Combined Cycle plant near Terre Haute, Indiana. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the pore space in fine-grained structures; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy-related examinations traditionally performed at NETL.

54 ENVIRONMENTAL SCIENCES↗

Core Characterization of Bakken Shale from the Bedwell 33-52-1-1H Well, Sheridan County, Montana

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core of the Bedwell 33-52-1-1H well (API 25-091-21920), a wildcat field in Sheridan County, Montana. The primary impetus of this work is to provide a unique dataset to researchers at universities, national laboratories, geological surveys, and other locations for additional analyses. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/bedwell-33-52-1-1h-well. The equipment and techniques used to characterize the full core were non-destructive, enabling future examinations and analyses to be performed on these cores. However, none of the equipment used was suitable for direct visualization of the pore space in fine-grained structures such as those found in shales; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. A selection of samples (Table 1) were cored, sliced, and powdered for additional characterization analyses. These analyses did involve destructive subsampling of the full core at discrete sections, and the results are presented here in the context of the larger core description. Selected sections of the core were removed from the full core for detailed analyses using the following destructive techniques: bulk inductively coupled plasma-optical emission spectroscopy (ICP-OES), isolation of carbon and sulfur, Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and higher resolution CT scan with NETL’s micro-CT scanning systems. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

04 OIL SHALES AND TAR SANDS↗

Computed Tomography Scanning and Geophysical Measurements of UW Enterprises LP 1-250512-129 Well in Southwestern Indiana

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize Illinois Basin core of the Upper Devonian-Early Mississippian New Albany Shale Formation from Posey County, Indiana. The primary impetus of this work is a collaboration between Indiana Geological and Water Survey at Indiana University Bloomington, NETL, and Woolsey Operating Company LLC to characterize and make publicly available core information from the New Albany Shale of the Illinois Basin. Core characterization of this unconventional oil/gas well will aid in understanding the lithology changes and the fracture complexity of the New Albany Shale. There is a potential for this formation to be developed in the future for critical mineral and rare earth element (CM/REE) extraction. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/uw-enterprises. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on this core. None of the equipment used was suitable for direct visualization of the pore space in the fine-grained structures studied; however, fractures, discontinuities, and millimeter-scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Targeted higher resolution CT scanning of select sections was performed with NETL’s industrial and micro-CT scanner. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

58 GEOSCIENCES↗