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Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32

Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, formerly FS-C, and FS02, formerly FS1-2) in human-readable comma-separated value text files. There are two header lines in each file describing the data contained in that column along with their units, respectively. Data have been decimated from 2 to 1 Hz to match the Pason data found in the linked GDR dataset below (16A78-32 Stimulation Pason Data). These files contain the time series spanning the same time interval as the Pason data as well as ambient data for 5 hours before the stimulation and 5 hours following shut in. The station locations were chosen based on their proximity to the borehole seismometers owned and operated by the University of Utah. See README.txt for more information.

15 GEOTHERMAL ENERGY↗

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 1

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore fuel product. The long-term EnCore ® fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 2

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore ® fuel product. The long-term EnCore fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15 N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pion-Production Target for Mu2e-II: Design and Prototype

The higher beam intensity available for Mu2e-II will require a substantially different target design. This paper discusses our recent advances in conceptual R&D for a Mu2e-II target station. The design is based on energy deposition and radiation damage simulations as well as thermal and mechanical analyses to estimate the survivability of the system. We considered rotated targets, fixed granular targets and a novel conveyor target with tungsten or carbon spherical elements that are circulated through the beam path. The motion of the spheres can be generated either mechanically or both mechanically and by a He-gas flow. The simulations identified the conveyor target as the preferred approach, and that approach has been developed into a prototype. We describe this first prototype for the Mu2e-II target and report on its mechanical tests performed at Fermilab that indicate the feasibility of the design, discuss its challenges as well as suggest directions for further improvement.

Neuffer, David↗

A Machine Learning Approach for Hourly Traffic Prediction Used in EV-Charging Sites

Reliable forecasting of hourly traffic volumes on highways is critical for planning and operating electric-vehicle charging infrastructure without overloading the grid. In this work, we develop and evaluate a station-specific machine-learning approach based on NeuralProphet, enhanced with conditional seasonality to better distinguish weekday, weekend, and holiday patterns. For each station, the model automatically retrieves the same calendar day from the prior years as an AR-Net initialization, fits trend and Fourier-based seasonality components, and then applies short-term auto-regressive corrections. We train and test on 2021 and 2022 TMAS data, respectively, and validate performance over the whole year. We chose to demonstrate how the model performs on a typical weekday (3/15/2022), weekend (3/27/2022), and a special holiday (12/25/2022). Our results yield MAPE of 7.4%, 23.6%, and 32.0%, respectively. Over the entire year 2022, the overall MAPE was 17%. This demonstrates that station-specific models with conditional seasonality can achieve accurate, scalable hourly forecasts for EV-charging load planning.

99 - GENERAL AND MISCELLANEOUS↗

System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents

Following the Fukushima Daiichi nuclear accident in 2011, researches on Accident-tolerant fuels (ATFs) are currently of high interest in not only the nuclear industry but also governmental and international organizations. In this work, a quantitative evaluation of the performance of monolithic FeCrAl cladding and Cr-coated Zircaloy cladding has been performed for Pressurized Water Reactor (PWR) Station Blackout (SBO) accidents. A generic PWR model has been built in system thermal-hydraulics code TRACE based on the Surry Nuclear Power Station with counter-current natural circulation modelling capability for hotleg and steam generator U-tube components during the accidents. The base model results are then compared to MELCOR and RELAP simulations to verify the system component implementation in TRACE. Two PWR SBO scenarios were investigated, including: short-term SBO and long-term SBO with early reactor coolant pump (RCP) seal failure. These scenarios are defined to be very similar to the accidents studied in the State-of-the-Art Reactor Consequence Analysis (SOARCA) project. TRACE code is modified to reflect the oxidation kinetics of FeCrAl and Cr-coating. Larson-Miller creep rupture model is also implemented in TARCE using its built-in control systems to simulate the creep rupture of hotlegs. Additionally, the comparison between the TRACE models with and without the counter-current flow modeling resulted in significant difference when comparing ATF cladding to Zircaloy for short term SBO, while it marginal impacted the performance during long term SBO with RCP seal failure. For short term SBO, both ATF cladding underwent hot leg creep rupture ~20 min after Zircaloy cladding. While Zircaloy and Cr-coated cladding had generated significant amount of hydrogen gas (>10 kg) before the creep rupture event, FeCrAl cladding had only generated <0.5 kg of hydrogen gas. For long term SBO with RCP seal failure, significant hydrogen generation and fuel melting was predicted before hot leg creep rupture for the ATF cladding while providing only 10–20 min additional coping time compared to Zircaloy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Pooling Data Improves Multimodel IDF Estimates over Median-Based IDF Estimates: Analysis over the Susquehanna and Florida

Traditional multimodel methods for estimating future changes in precipitation intensity, duration, and frequency (IDF) curves rely on mean or median of models’ IDF estimates. Such multimodel estimates are impaired by large estimation uncertainty, shadowing their efficacy in planning efforts. Here, assuming that each climate model is one representation of the underlying data generating process, i.e., the Earth system, we propose a novel extension of current methods through pooling model data: (i) evaluate performance of climate models in simulating the spatial and temporal variability of the observed annual maximum precipitation (AMP), (ii) bias-correct and pool historical and future AMP data of reasonably performing models, and (iii) compute IDF estimates in a nonstationary framework from pooled historical and future model data. Pooling enhances fitting of the extreme value distribution to the data and assumes that data from reasonably performing models represent samples from the “true” underlying data generating distribution. Through Monte Carlo simulations with synthetic data, we show that return periods derived from pooled data have smaller biases and lesser uncertainty than those derived from ensembles of individual model data. We apply this method to NA-CORDEX models to estimate changes in 24-h precipitation intensity–frequency (PIF) estimates over the Susquehanna watershed and Florida peninsula. Our approach identifies significant future changes at more stations compared to median-based PIF estimates. The analysis suggests that almost all stations over the Susquehanna and at least two-thirds of the stations over the Florida peninsula will observe significant increases in 24-h precipitation for 2–100-yr return periods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A mechanistic model of a PWR-based nuclear power plant in response to external hazard-induced station blackout accidents

Natural hazard-induced nuclear accidents, such as the Fukushima Daiichi Accident that occurred in Japan in 2011, have significantly increased reactor safety studies in understanding nuclear power plant (NPP) responses to external hazard events such as earthquakes and floods. Natural hazards could cause the loss of offsite power in nuclear power plants, potentially leading to a Station Blackout (SBO) accident that significantly contributes to the overall risk of nuclear power plant accidents. Despite the fact that extensive research has been conducted on the station blackout accident for nuclear power plant, further understanding of these events is needed, particularly in the context of the dynamic nature of external hazards such as external flooding. This paper estimates the progression of station blackout events for a generic pressurized water reactor (PWR) in response to external flooding events. The original RELAP5-3D model of the Westinghouse four-loop design pressurized water reactor was adopted and modified to simulate the external flood-induced station blackout accident, including the short-term and long-term station blackout scenarios. A sensitivity analysis of long-term station blackout, examining reactor operation times and analyzing key parameters over time, was also conducted in this work. The results of the analyses, especially the critical timing parameters of key event sequences, provide useful insights about the time during the external flooding event, which is important for plant operators to make timely decisions to prevent potential core damage. This paper represents significant progress toward developing an integrated risk assessment framework for further identifying and assessing the effects of the critical sources of uncertainties of nuclear power plant under external hazard-induced events.

Liu, Tao↗

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗

Powering the Blue Economy: A Survey of Station-Keeping Methods for Mooringless Platforms

The term “ocean platform” is used to reference everything from stationary, typically moored, buoys to mobile water vehicles, whether they operate on the ocean’s surface or underwater. For certain applications for which relatively stationary station-keeping conditions are desired, the use of mooring systems is not always a viable alternative either for economic, environmental, regulatory, or otherwise practical reasons, or a combination thereof, (e.g., short deployments, sensitive ecosystems, very deep project sites). Maintaining a platform at a single waypoint or reference location without being moored would require additional control systems and a power source to counteract the drift forces that would naturally displace it. Mobile platforms, which are usually untethered except for remotely operated vehicles, typically require energy input to power their station-keeping capabilities so that they hold or control their location in the ocean. Currently, most of these platforms use combustion engines or batteries for this purpose, which, depending on the specific systems, may be costly, pollute the environment, or create limitations on the length of the deployment. However, powering this kind of platforms with surrounding renewable resources (waves, currents, winds, or sun) has been identified as a promising solution to expand their application. The intent of this report is to investigate station-keeping methods for various ocean platforms that are not moored or otherwise anchored to the ocean floor, or another platform or vessel, paying particular interest to technologies that use marine renewable resources to power their operation, because that is of particular interest to the U.S. Department of Energy’s Powering the Blue Economy (PBE) initiative. As a first step, 72 articles and technical reports related to mooringless station-keeping methods were collected for review. The preliminary literature review provided a broad overview of common themes across the literature from which a descriptive methodology for analyzing various platforms was developed. That is, station-keeping methods were categorized based on their predominant energy source and consumption (renewable, nonrenewable, or hybrid if the platform uses renewable and nonrenewable resources equally), and their localization strategy (drift reduction, “path-planning or “waypoint-holding”). In addition, platform types were segregated into the following groups: buoys, surface drifters, and unoccupied surface vehicles (USVs); offshore renewable energy systems; and unoccupied underwater vehicles (UUVs). The main types of station-keeping methods encountered in this report achieve their intended localization strategy by means of drift mitigation, steering, and/or propulsion. Drift mitigation is commonly accomplished via drogues and sea anchors. Stand-along steering subsystems use control surfaces (e.g., ship rudder, wing sail, etc.) that react to ocean currents, waves, or winds to provide varying-degrees of course adjustments. Combined steering and propulsion subsystems include differential thrusters, directional thrusters separate from a primary thruster that cause the platform to pitch up/down or yaw clockwise/counterclockwise, or vectored thrusters that direct the propulsion in a range of directions relative to the platform’s local coordinate system. Propulsion is often achieved by running a motor and applying active control strategies but can also involve buoyancy shifts and using sails to generate lifting forces that propel a platform in a desired direction. Future research is primarily expected to take place in the form of a technoeconomic analysis that would aim to determine the technological viability, cost, and added value of mooringless station-keeping use cases identified through this research, including docking for UUV recharging or for georeferencing drifter buoys, deep-sea floating wind farms, U.S. Navy sonar arrays, and a Pacific Ocean wave buoy network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Formal methods approach to the charging facility location problem for battery electric vehicles

Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Geothermal Play-Fairway Analysis of Washington State Prospects: Final Report

The Washington State Geothermal Play-Fairway Analysis overcomes the exploration challenges posed by dense vegetation, glacial deposits, and extreme precipitation. The geothermal play-fairways we target are locations where heat, permeability, and saturated porosity are present in sufficient volume to provide adequate heat exchange at depths accessible by modern drilling technology. The three study areas lie along the Cascade Range magmatic arc and are near Mount Baker, Mount St. Helens, and the Wind River Valley. The seven-year project is divided into three phases. In Phase 1 we build on a previous statewide assessment of geothermal resources and develop an initial modeling approach. The results are a series of favorability, uncertainty, and risk maps for three targeted study areas. Based on these initial results, we collect new geologic and geophysical data to further refine our modeling and reduce exploration uncertainty in Phase 2. We improve the modeling method to handle the new data and update the favorability, uncertainty, and risk maps. We also update the conceptual geothermal resource models. In Phase 3 we validate our modeling approach by drilling two temperature-gradient holes and collecting and analyzing core, image logs, and new geochemistry. Our modeling approach improves on an earlier statewide method through a more-rigorous and detailed assessment of heat and permeability. Permeability potential is assessed through geomechanical modeling of the deformation that can generate and maintain reservoir porosity and permeability. Metrics to inform heat potential include temperature-gradient wells, which are sparse in Washington; proximity of Quaternary volcanic vents and young intrusive rock; spring temperature; and reservoir temperature inferred from geothermometry. We weight the individual components using an expert-guided approach known as the Analytical Hierarchy Process. During Phase 2 we also develop a fluid-filled fracture model, and an infrastructure model that helps to delineate areas which are more favorable for geothermal development based on proximity to transmission lines, elevation, land ownership and use restrictions, and availability of process water. New geologic and geophysical data is collected during Phase 2 in each of our three main study areas. At Mount Baker and north of Mount St. Helens we conduct 1:24,000-scale geologic mapping and lidar analysis to better constrain the location and character of surface faults; detailed mapping in the Wind River Valley was completed just prior to the start of this project. Ages of intrusive rocks are determined with 40 Ar/ 39 Ar geochronology, though all of our samples are Miocene or older. We collect ground based gravity observations (a total of 1,580 new stations) in all of our study areas and ground-based magnetic lines (a total of 93 km) at Mount Baker. These data are combined with existing gravity and aeromagnetic data and used to constrain fault locations and geometry. Two to three cross sections are constructed at each study area using the mapped surface geology and forward-modeling of the gravity and magnetic data; these cross sections form the basis for our updated conceptual models. We collect magnetotelluric surveys at Mount Baker and Mount St. Helens and these data are inverted to form a resistivity model from the surface to about 10 km depth; each model shows conductive zones that can be interpreted as upwelling geothermal fluids. At Mount St. Helens we deploy a passive seismic array and use the newly detected events to refine the location of the Saint Helens seismic zone. We also employ ambient-noise tomography to develop a detailed seismic-velocity model for the study area and use this model to help constrain our cross sections and conceptual model. Based on the new data collected during Phase 2—and our updated models—we develop a campaign of temperature-gradient holes and core analysis to validate our modeling in Phase 3. Drill hole MB76-31 is located near Little Park Creek, 11 km west-southwest of the summit of Mount Baker, and is 1,471 ft deep. About 410 ft of core from the lower portion of the hole—and image logs from ~175 ft below ground surface to the bottom—are collected and analyzed. Water samples are collected and processed for geothermometry. Drill hole MSH17-24 is located along upper Schultz Creek, 16 km north-northeast of Mount St. Helens and has core from 470 ft to the bottom at 1,053 ft. We did not collect image logs due to borehole stability concerns, but water samples are collected and analyzed for geothermometry. Repeat temperature-gradient measurements are made at both sites and thermal conductivity is measured from core samples. At MB76-31, the equilibrated temperature gradient of 64°C/km and calculated heat flow of 141–159 mW/m 2 is more than twice the regional average. Detailed mapping and analysis of the core, coupled with correlation to the image logs, indicates a history of permeability generation consistent with our predictions of high permeability. Because the site has high favorability in the Phase 2 model, we consider the results a positive validation of the modeling. At site MSH17-24, the equilibrated temperature gradient of ~15°C/km and calculated heat flow of 41–43 mW/m 2 are similar to regional. Geochemical analysis of the water samples indicates a meteoric source without any geothermal component. Detailed outcrop-based mapping of fault exposures near the drill site and analysis of image logs from nearby boreholes indicates a history of permeability generation consistent with our predictions. Because the site has low favorability in the Phase 2 model, we consider the results a positive validation of the modeling. Together, the two sites provide a reasonably positive validation of the Phase 2 modeling and should encourage future use of this modeling approach.

15 GEOTHERMAL ENERGY↗

Ambient Noise Attenuation Tomography Reveals an Asymmetric Damage Zone Across San Jacinto Fault Near Anza, California

Here, we perform seismic attenuation tomography of the shallow structure for the San Jacinto Fault in the Ramona Reservation of southern California. The study uses ambient seismic noise recorded by a linear array of 65 3-C sensors across the fault. We extract amplitude decay information, with uncertainty, from noise interferometry functions. To account for strong heterogeneities in the complex shallow fault zone structure, we apply a frequency-dependent amplitude correction for focusing/defocusing effects using inverted phase velocity maps obtained by solving the transport equation. We then estimate the attenuation structure based on the linear station-triplet method for both Love and Rayleigh waves. The attenuation tomography indicates strong attenuation correlated with known San Jacinto Fault surface traces. The Love wave attenuation tomography reveals an asymmetric damage zone that exists primarily on the fault side with faster seismic velocity, consistent with earthquake ruptures on a fault bimaterial interface with preferred propagation direction to the northwest.

58 GEOSCIENCES↗

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗

DC Fast Charging Infrastructure for Electrified Road Trips

To assess DC fast charging station network required for electrified road trips by 2030 in California, a new charging infrastructure simulation tool/model, EVI-Pro (Electric Vehicle Infrastructure Projection) RoadTrip, has been developed. In contrast to the existing EVI-Pro model that is primarily for short-distance travels, EVI-Pro RoadTrip is exclusively focused on road trips (long-distance travels, 100 or miles per day per vehicle). Also, the charging paradigm or strategy is different. EVI-Pro RoadTrip is built upon waypoint charging, in which vehicles are forced to stop to charge or replenish the on-board batteries, along the routes between origins and destinations. On the other hand, EVI-Pro is based on destination charging, in which charging is conducted when vehicles are parked in destinations (e.g., work, home). EVI-Pro RoadTrip takes coordinate-level origin and destination data for road trips (intra-state as well as domestic or international out-of-state) and estimates energy consumption and charging needs along the routes between origins and destinations on a minute-by-minute resolution. Based on charging demands for electrified road trips across the state, the optimal locations of charging stations are determined accounting for preferred land use types (e.g., commercial areas) and station service area (e.g., 5 or less miles). Based on station-by-station charging load profiles, the required number of plugs/connectors is estimated for each station and entire state. By comparing hosting capacity of the electric grid (circuit-level) and the charging load output from EVI-Pro RoadTrip, capacity deficit is also evaluated.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

Weather and Random Forest-based Load Profiling Approximation Models and its Transferability across Climate Zones

This study is to provide predictive understanding of the associations of various weather attributes with residential and commercial load profiles, for a variety of climate zones and seasons. In this work, machine learning (ML) approaches were used to identify and quantify the impacts of various weather attributes on residential and commercial electricity demand and its components across the western United States. Performance and transferability of the developed ML models were then evaluated across different temperate zones (e.g., southern, middle, and northern US) and across coastal, mid-continent, and wet zones, with inputs of weather condition data from the National Oceanic and Atmospheric Administration (NOAA) at representative weather stations. The predictive models were developed based on the ranked/screened factors using the regression tree (RT) and random forest (RF) approaches, for five different scenarios (seasons).

load composite, Random Forest, regression tree, lo↗