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At least 199 records · Page 11

Physics Coupled Machine Learning Applications for Geological Carbon Storage

Poster presented at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. In this poster, a physics-based method, CRM is coupled with the advanced artificial intelligence (AI)/machine learning (ML) models in virtual learning environment (VLE) for three-dimension details of reservoir responses and evaluations for a comprehensive understanding for CCS field operations and reservoir managements.

Liu, Guoxiang↗

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗

TEAMER – Harvesting Subsea Water Motion to Provide Clean Electrical Power (Abstract)

Power generation from vortex induced vibration (VIV) is an emerging field with new technologies that are just beginning to be field tested. In this TEAMER project, WITT Energy will be field testing the power production of its pendulum system in two different configurations to evaluate its performance. The amount of power produced by a VIV instrument depend on the frequency at which it vibrates. The vibrational frequency is controlled by the device shape and its interaction with the flow velocity. Computer models are used to predict vibration frequencies as a function of flow velocity but they may be inaccurate due to complicated bathymetry and bottom roughness that is not captures by the models. This project will test the WITT VIV device in the Sequim Bay channel over a range of tidal velocities. Two tests will be completed with different pipe lengths that are expected to vary the vibrational frequency and therefore the power produced. PNNL will use an acoustic doppler current profiler (ADCP) to monitor the flow conditions during the tests. These tests will help WITT Energy evaluate how closely field operations follow computer model predictions and how best to configure their device for electricity production.

16 TIDAL AND WAVE POWER↗

MARTA’s (Muon Array with RPC for Tagging Air showers) DAQ system

The successful development of a low-power and standalone DAQ system to be used with RPCs is presented. These will be used to measure the muonic component of cosmic-ray’s air showers. The system includes a front-end, high voltage, detector monitoring and a Central Unit to manage the different components of the system. The front-end is based on the MAROC ASIC coupled to an FPGA respecting the strict demands of field operations in cosmic-ray experiments. Prototypes were produced and deployed, performing as expected. An engineering array will be installed at the Pierre Auger Observatory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Generation of Data-Driven Expected Energy Models for Photovoltaic Systems

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.

14 SOLAR ENERGY↗

Unraveling the Mysteries of Turbulence Transport in a Wind Farm

A true physical understanding of the mysteries involved in the recovery process of the wake momentum deficit, downstream of utility-scale wind turbines in the atmosphere, has not been obtained to date. Field data are not acquired at sufficient spatial and temporal resolutions to dissect some of the mysteries of wake turbulence. It is here that the actuator line method has evolved to become the technology standard in the wind energy community. This work presents the actuator line method embedded into an Open source Field Operation and Manipulation (OpenFOAM) large-eddy simulation solver and applies it to two small wind farms, the first one consisting of an array of two National Renewable Energy Laboratory 5 Megawatt (NREL 5-MW) turbines separated by seven rotor diameters in neutral and unstable atmospheric boundary-layer flow and the second one consisting of five NREL 5-MW wind turbines in unstable atmospheric conditions arranged in two staggered arrays of two and three turbines, respectively. Detailed statistics involving power spectral density (PSD) of turbine power along with standard deviations reveal the effects of atmospheric turbulence and its space and time scales. In conclusion, high-resolution surface data extracts provide new insight into the complex recovery process of the wake momentum deficit governed by turbulence transport phenomena.

17 WIND ENERGY↗

Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview

Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020).

47 OTHER INSTRUMENTATION↗

National Wind Technology Center Dynamic 5-Megawatt Dynamometer

The National Wind Technology Center (NWTC) offers wind industry engineers a unique opportunity to conduct a wide range of tests. Its custom-designed dynamometers can test wind turbine systems from 1 kilowatt (kW) to 5 megawatts (MW). The NWTC's new dynamometer facility simulates operating field conditions to assess the reliability and performance of wind turbine prototypes and commercial machines, thereby reducing deployment time, failures, and maintenance or replacement costs. Funded by the U.S. Department of Energy with American Recovery and Reinvestment Act (ARRA) funds, the 5-MW dynamometer will provide the ability to test wind turbine drivetrains and connect those drivetrains directly to the electricity grid or through a controllable grid interface (CGI). The CGI tests the low-voltage ride-through capability of a drivetrain as well as its response to faults and other abnormal grid conditions.

17 WIND ENERGY↗

Field Emission and Consequences as Observed and Simulated for CEBAF Upgrade Cryomodules

High gamma and neutron radiation levels were monitored at the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory (JLab) after installation of new cavity cryomodules and initial test runs in the frame of the ongoing 12 GeV upgrade program. The dose rates scaled exponentially with cavity accelerating fields, but were independent of the presence of an electron beam in the accelerator. Hence, field emission (FE) is the source of origin. This has led to concerns regarding the high field operation (100 MV per cryomodule) in the future 12 GeV era. Utilizing supercomputing, novel FE studies have been performed with electrons tracked through a complete cryomodule. It provides a principal understanding of experimental observations as well as ways to mitigate FE as best as practicable by identification of problematic cavities.

Marhauser, Frank↗

Magnetic and Structural Design of a 15 T $Nb_3Sn$ Accelerator Depole Model

Hadron Colliders (HC) are the most powerful discovery tools in modern high energy physics. A 100 TeV scale HC with a nominal operation field of at least 15 T is being considered for the post-LHC era. The choice of a 15 T nominal field requires using the Nb3Sn technology. Practical demonstration of this field level in an accelerator-quality magnet and substantial reduction of the magnet costs are the key conditions for realization of such a machine. FNAL has started the development of a 15 T $Nb_{3}Sn$ dipole demonstrator for a 100 TeV scale HC. The magnet design is based on 4-layer shell type coils, graded between the inner and outer layers to maximize the performance. The experience gained during the 11-T dipole R&D campaign is applied to different aspects of the magnet design. This paper describes the magnetic and structural designs and parameters of the 15 T $Nb_3Sn$ dipole and the steps towards the demonstration model.

43 PARTICLE ACCELERATORS↗

Understanding How Biomass Burning Impacts Climate Change

Biomass burning in Africa is creating a plume that spreads across the Atlantic Ocean all the way to Brazil. Allison Aiken, a research scientist at Los Alamos National Laboratory, collects data about the black carbon aerosols within this plume and their impact on the environment to help improve global climate modeling. A leader in energy science, Los Alamos develops climate models in support of the Laboratory’s mission to strengthen the nation’s energy security. Allison’s work is part of FIDO, a field operations team funded by the Energy Department’s Office of Science’s ARM Climate Research Facility.

54 ENVIRONMENTAL SCIENCES↗

PERSISTENT CURRENT EFFECT IN 15-16 T NB3SN ACCELERATOR DIPOLES AND ITS CORRECTION

Nb3Sn magnets with operating fields of 15-16 T are considered for the LHC Energy Doubler and a future Very High Energy pp Collider. Due to large coil volume, high critical current density and large superconducting (SC) filament size the persistent current effect is very large in Nb3Sn dipoles al low fields. This paper presents the results of analysis of the persistent current effect in the 15 T Nb3Sn dipole demonstrator being developed at FNAL, and describes different possibilities of its correction including passive SC wires, iron shims and coil geometry.

43 PARTICLE ACCELERATORS↗

An Overview of Broadband Laser Ranging (BLR) Architecture and Measurement Considerations

Broadband Laser Ranging (BLR) is a developmental diagnostic intended to measure the position of rapidly moving surfaces in combination with optical velocimetry. Design and employment of a BLR diagnostic on dynamic experiments requires consideration for both the inherent measurement system tradeoffs as well as architectural choices appropriate to the nature of investigation. The diagnostic uses spectral interferometry to measure distance by mapping femtosecond laser pulses to the time domain via chromatic dispersion within the fiber-optic architecture. The system parameters and governing equations that describe measurement range, resolution, and Doppler sensitivity will be discussed. We will also briefly review the impact of diagnostic architectural choices including: nature of interferometer, Interferometric dispersion matching, optical amplification, integration of optical velocimetry, BLR calibration, and field operability. To summarize we will present the architectural and operational approach currently being pursued by NSTec within an on-going collaboration between NSTec, Lawrence Livermore and Los Alamos National Labs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advantage and Challenges of $Nb_3Sn$ Superconducting Undulators

Utilization of Nb3Sn superconducting wires offers the possibility to increase undulators’ nominal operation field and temperature margin, but requires overcoming chal-lenges that are described in this paper. The achievable field levels for a Nb3Sn version of superconducting undulators being developed at APS-ANL and the conductor choice are also presented and discussed.

Zlobin, A. V.↗

Materials Characterization and Interrogation using Terahertz Radiation

Terahertz (THz) radiation is a powerful tool for characterizing materials and interrogating complex systems. The low-energy, non-ionizing nature of THz photons make it ideal for use as a non-destructive, non-contacting probe. Identification of materials by their unique THz response is possible through various absorption mechanisms, including vibrational (phonon) and rotational spectra. The Drude-like response of materials allows for non-contact electrical conductivity measurements as well. In the additive and advanced manufacturing realm, high sampling rates (kHz) and ability to extract electrical conductivity and composition makes in-situ THz imaging and spectroscopy a prime candidate for monitoring melt-pool dynamics in metal 3D printers. The fiberization of pulsed lasers systems enables the use of THz radiation to monitor oxide layer growth and characterize microstructure in challenging environments, whether ex-situ (e.g. post irradiation hot-cells) or in-situ (e.g. Transient Test Reactor, TREAT), through time of flight measurements and unique vibrational spectra of materials, providing crucial data on previously out of reach processes. While security imaging using THz radiation is already employed in airport body scanners, further miniaturization and ruggedization of THz systems enables materials characterization during field operations, adding a necessary and complementary tool to the arsenal of spectroscopic technologies available to the military and first responders. Cybersecurity is also a major focus for the coming decades; the use of THz interrogation methods to monitor integrated circuit operations provides a non-contacting, undetectable probe for system verification.

36 MATERIALS SCIENCE↗

MCNP Estimate of ZLS Lens Sensitivity in an X-Ray Field

The telecentric zoom lens system (ZLS) has proven to be invaluable in flash x-ray field operations and recent successful experiments pertaining to stockpile stewardship. The ZLS contains 11 custom-manufactured lenses, a turning mirror (pellicle), and an x-ray-to-visible-light converting scintillator. Images are recorded on a fully characterized CCD. All hardware is supported by computerized, programmable, electro-mechanical mounts and alignment apparatus. Seven different glass material types varying in chemical stoichiometry comprise the 11 ZLS lenses. All lenses within the ZLS are out of the path of direct x-ray radiation during normal operation. However, any unshielded scattered x-ray radiation can result in energy deposition into the lenses, which may generate some scintillating light that can couple into the CCD. This extra light may contribute to a decrease in signal-to-noise ratio (SNR) and lower the overall fidelity of the radiograph images. An estimate of the scintillation generation and sensitivities for each of the seven types of glass used as lenses in the ZLS is presented. This report also includes estimates of the total observed background decoupling that each of the lens material types contribute.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MCNP Estimate of ZLS Lens Sensitivity in an X-Ray Field

The telecentric zoom lens system (ZLS) has proven to be invaluable in flash x-ray field operations and recent successful experiments pertaining to stockpile stewardship. The ZLS contains 11 custom-manufactured lenses, a turning mirror (pellicle), and an x-ray-to-visible-light converting scintillator. Images are recorded on a fully characterized CCD. All hardware is supported by computerized, programmable, electro-mechanical mounts and alignment apparatus. Seven different glass material types varying in chemical stoichiometry comprise the 11 ZLS lenses. All lenses within the ZLS are out of the path of direct x-ray radiation during normal operation. However, any unshielded scattered x-ray radiation can result in energy deposition into the lenses, which may generate some scintillating light that can couple into the CCD. This extra light may contribute to a decrease in signal-to-noise ratio (SNR) and lower the overall fidelity of the radiograph images.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs: Preprint

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.

40 EE - Geothermal Technologies Office (EE-4G)↗