Results for “Automated Testing” — Page 70

DOE OSTI2025

Fermilab Automation of Coil Winding System

The automated coil winder project creates a repeatable, scalable method for producing superconducting magnet coils with increased accuracy and efficiency. The design uses an ortho cyclic winding method to achieve high fill factors by combining computer numerical control (CNC), microcontroller-based controls, and sophisticated optimization techniques. The method optimizes coil turns, core geometry, and current consumption by utilizing analytical models based on magnetic moment, Ohm’s law, and power constraints. For particle accelerator applications, prototype testing using a 3D-printed coil winder has shown enhanced winding repeatability, thermal management, and manufacturability.

Dzida, Rafal [Northern Illinois U.]↗

DOE OSTI2018

A computational fluid dynamics simulation framework for ventricular catheter design optimization

OBJECTIVE Cerebrospinal fluid (CSF) shunts are the primary treatment for patients suffering from hydrocephalus. While proven effective in symptom relief, these shunt systems are plagued by high failure rates and often require repeated revision surgeries to replace malfunctioning components. One of the leading causes of CSF shunt failure is obstruction of the ventricular catheter by aggregations of cells, proteins, blood clots, or fronds of choroid plexus that occlude the catheter’s small inlet holes or even the full internal catheter lumen. Such obstructions can disrupt CSF diversion out of the ventricular system or impede it entirely. Previous studies have suggested that altering the catheter’s fluid dynamics may help to reduce the likelihood of complete ventricular catheter failure caused by obstruction. However, systematic correlation between a ventricular catheter’s design parameters and its performance, specifically its likelihood to become occluded, still remains unknown. Therefore, an automated, open-source computational fluid dynamics (CFD) simulation framework was developed for use in the medical community to determine optimized ventricular catheter designs and to rapidly explore parameter influence for a given flow objective. METHODS The computational framework was developed by coupling a 3D CFD solver and an iterative optimization algorithm and was implemented in a high-performance computing environment. The capabilities of the framework were demonstrated by computing an optimized ventricular catheter design that provides uniform flow rates through the catheter’s inlet holes, a common design objective in the literature. The baseline computational model was validated using 3D nuclear imaging to provide flow velocities at the inlet holes and through the catheter. RESULTS The optimized catheter design achieved through use of the automated simulation framework improved significantly on previous attempts to reach a uniform inlet flow rate distribution using the standard catheter hole configuration as a baseline. While the standard ventricular catheter design featuring uniform inlet hole diameters and hole spacing has a standard deviation of 14.27% for the inlet flow rates, the optimized design has a standard deviation of 0.30%. CONCLUSIONS This customizable framework, paired with high-performance computing, provides a rapid method of design testing to solve complex flow problems. While a relatively simplified ventricular catheter model was used to demonstrate the framework, the computational approach is applicable to any baseline catheter model, and it is easily adapted to optimize catheters for the unique needs of different patients as well as for other fluid-based medical devices.

Neurosciences & Neurology↗

DOE OSTI2016

ASPCAP: THE APOGEE STELLAR PARAMETER AND CHEMICAL ABUNDANCES PIPELINE

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) has built the largest moderately high-resolution ( R ≈ 22,500) spectroscopic map of the stars across the Milky Way, and including dust-obscured areas. The APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) is the software developed for the automated analysis of these spectra. ASPCAP determines atmospheric parameters and chemical abundances from observed spectra by comparing observed spectra to libraries of theoretical spectra, using χ {sup 2} minimization in a multidimensional parameter space. The package consists of a fortran90 code that does the actual minimization and a wrapper IDL code for book-keeping and data handling. This paper explains in detail the ASPCAP components and functionality, and presents results from a number of tests designed to check its performance. ASPCAP provides stellar effective temperatures, surface gravities, and metallicities precise to 2%, 0.1 dex, and 0.05 dex, respectively, for most APOGEE stars, which are predominantly giants. It also provides abundances for up to 15 chemical elements with various levels of precision, typically under 0.1 dex. The final data release (DR12) of the Sloan Digital Sky Survey III contains an APOGEE database of more than 150,000 stars. ASPCAP development continues in the SDSS-IV APOGEE-2 survey.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

On-Track Measurement of Road Load Changes in Two Close-Following Vehicles: Methods and Results

As emerging automated vehicle technology is making advances in safety and reliability, engineers are also exploring improvements in energy efficiency with this new paradigm. Powertrain efficiency receives due attention, but also impactful is finding ways to reduce driving losses in coordinated-driving scenarios. Efforts focused on simulation to quantify road load improvements require a sufficient amount of background validation work to support them. This study uses a practical approach to directly quantify road load changes by testing the coordinated driving of two vehicles on a test track at various speeds (64, 88, 113 km/h) and vehicle time gaps (0.3 to 1.3 s). Axle torque sensors were used to directly measure the load required to maintain steady-state speeds while following a lead vehicle at various gap distances. Through trial and error, test methods were developed that appear to provide satisfactory results, considering the challenges of track testing under real-world conditions (wind, weather, temperature changes, etc.). We found that total road load was reduced by about 10-12% at an optimum gap time of 0.25 to 0.4 s. Challenges that were encountered included less repeatability of load measurements at short gap distances and powertrain mode switching (from a hybrid vehicle) that rendered the 88-km/h results less useful. This study will provide the framework for further investigations on coordinated-driving road load using track testing methods.

Duoba, Michael↗

DOE OSTI2020

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Automated extraction of interfacial dislocations and disconnections from atomistic data

Here we introduce Interfacial Line Defect Analysis (ILDA), a method for identifying and extracting interfacial dislocations and disconnections with little-to-no input from the user on the nature of the interface. By simply providing the orientations and coherency strains for the crystals in a coherent reference state of the interface, ILDA provides exact Burgers vectors. Alternatively, these orientations and strains can be estimated using local atomic deformation gradients, making ILDA fully automated and providing estimated Burgers vectors. ILDA also determines the step height associated with each defect line segment, in case the associated defect is a disconnection. The heart of the method is the identification of atoms residing at co-incidence sites between the two crystals and the construction of a surface mesh connecting these sites that is used to compose Burgers circuits and insert defect line segments. We demonstrate the performance of ILDA in two test cases: a twist grain boundary and a phase boundary.

36 MATERIALS SCIENCE↗

DOE OSTI2021

deeplenstronomy: A dataset simulation package for strong gravitational lensing

Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more example systems to train the algorithms than have presently been discovered, which creates a need for simulated images as training dataset supplements. This work introduces and summarizes deeplenstronomy, an open-source Python package that enables efficient, large-scale, and reproducible simulation of images of astronomical systems. A full suite of unit tests, documentation, and example notebooks are available at https://deepskies.github.io/deeplenstronomy/ .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Identification of Leakage Spectra from Neutron Activation in Glass/Cherenkov Detectors - Paper 96

Oak Ridge National Laboratory has developed a new detector system concept that can be deployed in major US cities to identify the leakage spectrum of a nuclear weapon detonation. The detector is based on a small piece of glass that has been doped with an element that has a high activation cross section and creates a radioactive activation product with a reasonable length half-life. The decay of the activation product(s) after exposure creates Cherenkov light which can propagate to a photomultiplier and can be turned into a count-rate signal. The signal from each glass in each detector in a city can be individually analyzed to determine the amount of activation products produced in the initial exposure. Several activation products can be determined in a single glass if the half-lives are not the same. With a known source location and a detailed 3D model of a city, neutron transport simulations can be made by using a library of known sources to predict the activation amounts each source would have made in the glass detectors. A simple comparison of the measured activation amounts and the predicted activation amounts can identify the source spectrum contained in the library that is the best match. Choosing dopants with a large range in the threshold energy for the activation reactions can help to differentiate the spectra in the library. The method of matching the measured activation amounts to the predicted activation amounts to identify the source spectrum is similar to the analysis used for the passive Activation Foil Integrated Detector System (AFIDS), also developed at Oak Ridge National Laboratory. In AFIDS, wires or foils of known mass and isotopic composition are deployed before and then collected after exposure. Counting gammas in a nearby laboratory determines the activation amounts. The glass/Cherenkov system is active - it uses a battery-powered detector to count flashes of Cherenkov light and to communicate its count rates to a remote location for further analysis. Work has been performed in several areas, including glass making, automated detection and communication systems and software tools for analysis of the signal and source spectrum identification. Bell and Boatner have developed phosphate glasses that incorporate elements with high capture cross sections, and Hayward has simulated the response with Geant4 and measured the response with isotopic gamma sources. This paper will focus on the software tools for determining the activation amounts from the Cherenkov count-rate signal and finding the best matching source spectrum. A test problem in an urban environment is used to demonstrate the potential of a spectrum identification system using neutron activation. The analysis methods developed to identify the neutron leakage spectra from Cherenkov light given off by neutron activation in doped glasses work well. The calculation used to unfold the count-rate information into the number of actual activation products uses robust algorithms that can also compute associated uncertainties. These uncertainties and the known uncertainties of the glass tube material compositions are incorporated into the matching analysis to determine which of the source spectra in the library best matches the measured activation data. Any measurement method used to identify a neutron source spectrum relies at some point on a comparison against known sources; no identification method is definitive. Detection systems measure some physical aspect of the source, not its serial number. Many systems measure the physical aspect to determine that the source has some property, and then leave it to experts to determine which potential sources share that property. The analysis system presented here incorporates the comparison into the analysis itself. The statistical tests show which of the known library sources match the measured data the best and whether that match is a good match. If the best match still does not fit the measured data well (a very high χ{sup 2} value), that indicates the true source is not one of the sources in the library. This is still valuable information for decision makers. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗

DOE OSTI2014

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Modeling CO 2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 m i2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi 2 of existing 3D seismic data for use in modeling CO 2 - EOR oil recovery and CO 2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO 2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO 2 -EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO 2 -EOR in Kansas. 4. Built a regional well database covering 30,000 mi 2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project’s interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO 2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO 2 , and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO 2 -EOR needs to move to the next generation to increase effectiveness of CO 2 and efficiency and safety of the injection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Evaluating Automated Face Identity-Masking Methods with Human Perception and a Deep Convolutional Neural Network

Face de-identification (or “masking”) algorithms have been developed in response to the prevalent use of video recordings in public places. Here, we evaluated the success of face identity masking for human perceivers and a deep convolutional neural network (DCNN). Eight de-identification algorithms were applied to videos of drivers’ faces, while they actively operated a motor vehicle. These masks were pre-selected to be applicable to low-quality video and to maintain coarse information about facial actions. Humans studied high-resolution images to learn driver identities and were tested on their recognition of active drivers in low-resolution videos. Faces in the videos were either unmasked or were masked by one of the eight algorithms. When participants were tested immediately after learning (Experiment 1), all masks reduced identification, with six of eight masks reducing identification to extremely poor performance. In a second experiment, two of the most effective masks were tested after a delay of 7 or 28 days. The delay did not further reduce identification of the masked faces. In all masked conditions, participants maintained stringent decision criteria, with low confidence in recognition, further indicating the effectiveness of the masks. Next, the DCNN performed an identity-matching task between high-resolution images and masked videos—a task analogous to that done by humans. The pattern of accuracy for the DCNN mirrored some, but not all, aspects of human performance, highlighting the need to test the effectiveness of identity masking for both humans and machines. The DCNN was also tested on its ability to match identity between masked and unmasked versions of the same video, based only on the face. DCNN performance for the eight masks offers insight into the nature of the information in faces that is coded in these networks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Precision Control of a Slender High Payload 22 DoF Nuclear Robot System: TARM Re-ascending - 18346

The DEMO Remote Maintenance System (RMS) functional requirements represent a truly extreme environment. In the current design of the in-vessel RMS, blanket segment maintenance represents one of the most challenging tasks overall. As part of the JET (Joint European Torus) project, an ambitious 22 DoF transporter was created, the TARM (Telescopic Articulated Remote MAST). The TARM has been identified as a suitable test bed for the early development and verification of the control system and structural simulators. This paper outlines the development of the TARM into a multi-purpose test-rig for Precision Control of a Slender High Payload large DoF Nuclear Robot System. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Analyzing Xyloglucan Endotransglycosylases by Incorporating Synthetic Oligosaccharides into Plant Cell Walls

Not provided.

Biochemistry & Molecular Biology↗

DOE OSTI2021

Preliminary Thermoluminescent Dosimeter Glow Curve Analysis with Automated Glow Peak Identification for LiF Mg,Ti

When appropriately analyzed, thermoluminescent dosimeter glow curve analysis allows for improved quantification of thermoluminescent material behavior while flagging abnormalities. The mathematical separation of a glow curve into contributions from energetically unique trap states, or glow curve analysis, may be used to remove undesired effects of signal fading for complex materials. A generalized glow curve analysis software for the separation of glow curves is presented in this paper. Written in C ++ , the software uses the first-order kinetics model with automatic peak identification. The automatic identification of peaks is achieved through a unique peak-finding algorithm. Here, the program was performance tested using experimental glow curve data from LiF:Mg,Ti, and comparative results are presented.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

ADVANTG—An Automated Variance Reduction Parameter Generator (Rev. 1)

The primary objective of ADVANTG is to reduce both the user effort and the computational time required to obtain accurate and precise tally estimates across a broad range of challenging transport applications. ADVANTG has been applied to simulations of real-world radiation shielding, detection, and neutron activation problems. Examples of shielding applications include material damage and dose rate analyses of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source and High Flux Isotope Reactor (Risner and Blakeman 2013) and the ITER Tokamak (Ibrahim et al. 2011). ADVANTG has been applied to a suite of radiation detection, safeguards, and special nuclear material movement detection test problems (Shaver et al. 2011). ADVANTG has also been used in the prediction of activation rates within light water reactor facilities (Pantelias and Mosher 2013). In these projects, ADVANTG was demonstrated to significantly increase the tally figure of merit (FOM) relative to an analog MCNP simulation. The ADVANTG-generated parameters were also shown to be more effective than manually generated geometry splitting parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗