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DOE OSTI2023

Quaternary slip rates and most recent surface rupture of the Bitterroot fault, western Montana

The Bitterroot fault is a ~100-km-long Quaternary active normal fault that bounds the eastern margin of the north–south-trending Bitterroot Mountains and accommodates extension near the Intermountain Seismic Belt. Here, new detailed mapping using high-resolution topographic data derived from light detection and ranging (lidar) along the southern Bitterroot Range documents multiple generations of fault scarps in Holocene–Pleistocene deposits with vertical off sets that increase in magnitude with age. Fault mapping indicates a complex fault geometry characterized by an en echelon pattern of discontinuous segments of 41–78° east-dipping normal faults that appear to cut the older Eocene detachment fault, and locally 70–88° west-dipping antithetic normal faults. 10 Be cosmogenic exposure dating provides in situ age control for 32 surface boulders (>1 m) sampled in glacial deposits. Near Como Dam, two Pinedale-age glacial moraine sequences yield peak age distributions of 15.0 ± 0.4 ka and 16.4 ± 0.6 ka as apparent exposure ages (e = 0), and 15.4 ± 0.4 ka and 16.8 ± 0.6 ka based on the maximum allowed boulder surface erosion rate (e = 2 mm/ka). Vertical separation of 3.5 ± 0.2 m across the ~16–17 ka glacial moraine off set by the Bitterroot fault scarp yields a fault slip rate of 0.2–0.3 mm/yr. Glacial Lake Missoula highstand shorelines, inset into the ~15 ka glacial moraine and vertically off set 4.6 ± 1.6 m by an antithetic strand of the Bitterroot fault, yield fault slip rates of 0.2–0.5 mm/yr that overlap with fault slip rates on the main strand near Lake Como (0.2–0.3 mm/yr). At the Ward Creek fan located ~15 km to the north of Lake Como, two glacial debris fan sequences yield peak age distributions of 16.6 ± 0.4 ka and 62.8 ± 1.7 ka (e = 0), and 17.0 ± 0.4 ka and 69.9 ± 2.2 ka (e = 2 mm/ka). Vertical separations of 2.4 ± 0.3 m and 4.5 ± 0.2 m on the ~17 ka and ~63–70 ka fan surfaces off set by the Bitterroot fault yield fault slip rates of 0.2–0.3 mm/yr and 0.1 mm/yr, respectively. Our results indicate broadly consistent fault slip rates for the main fault segments at Lake Como (0.2–0.3 mm/yr) and the Ward Creek fan (0.1–0.3 mm/yr) with an along-strike range of 0.1–0.3 mm/yr for the southern Bitterroot fault. Fault scaling relations and evidence of multiple late Quaternary fault surface ruptures suggest the Bitterroot fault could produce a Mw ~7.2 earthquake. Structural model constraints and our slip rate results indicate both high-angle or low-angle fault geometries are possible at depth. A seismogenic low-angle fault model could generate a larger earthquake of Mw >7.2. Earthquake history is unknown for the Bitterroot fault, but fault scarps in young glacial deposits demonstrate its seismogenic potential. Data from this study suggest seismic hazards from the Bitterroot fault may pose a high level of risk to the Missoula metropolitan area, the State’s second most populous region, and major infrastructures across the Missoula and Bitterroot Valleys.

58 GEOSCIENCES↗

DOE OSTI2022

Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements

An end-to-end supervised learning method is developed to classify transmission line faults in a twoyear field-recorded dataset that includes synchronized measurements of three-phase voltages recorded by 38 Phasor Measurement Units (PMU) sparsely located in in the US Western Grid interconnection. Statistical analysis is performed to extract features from this large dataset to train Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) classifiers initially. The training further leverages a simulated dataset from a synthetic grid with 12 PMUs to increase the number of faults of types infrequently seen in the field-recorded dataset. Training the classification models with the combined dataset resulted in a classification accuracy of 97.7%. This is a significant improvement over 89.7% to 92.5% accuracy obtained by relying on the field-recorded dataset alone.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

The Feasibility of Incorporating a 3D Velocity Model Into Earthquake Location Around Salt Lake City, UT Using a Physics Informed Neural Network

Earthquake location algorithms typically require travel time calculation. Doing this calculation in 3D, despite advances in algorithm efficiency and computational power, can still be prohibitively expensive in terms of resources and storage. Implementation of high-resolution 3D models in routine earthquake location would be a significant step forward in most of the world. Machine learning algorithms have potential to act as substitutes for travel time calculation algorithms or stored travel time tables. We investigate EikoNet - a physics informed neural network machine learning model that estimates travel times very quickly and comes with negligible memory-overhead. Specifically, we apply EikoNet to the Wasatch Fault Community Velocity Model (WFCVM), a highly detailed and complex 3D velocity model of the Salt Lake City, UT region. While routine locations in the area and studies of the 2020 Magna, UT earthquake sequence used a 1D velocity model, a 3D model may help better our understanding the structure of the major fault in the region. Our primary goal was to test the speed, memory requirements, and accuracy of EikoNet compared to a reference eikonal solver. We find that while the EikoNet is exceedingly fast and requires little memory overhead, achieving acceptable accuracy in estimated travel times is difficult and requires extensive computational resources.

58 GEOSCIENCES↗

DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗

DOE OSTI2022

LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)

The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.

14 SOLAR ENERGY↗

DOE OSTI2025

Evidence for a Single Holocene Paleoseismic Event on the Pajarito Fault, Northern New Mexico

Low-slip rate fault systems tend to be less studied than their high-slip rate counterparts, and paleoseismic techniques used to study them may pose challenges in interpretation that differ from high-slip rate systems. A good example of this is the Pajarito fault system (PFS), a normal fault complex within the Rio Grande rift. Despite numerous previous paleoseismic trenching studies conducted on the PFS between 1990 and 2003, considerable uncertainty remains regarding its Holocene paleoseismic history, particularly for the primary Pajarito fault (PF). To further clarify the PF paleoseismic history, we present data from paleoseismic investigations of 6 trenches at 3 distinct locations along the PF. Though the totality of the age and structural data obtained in this study is complex and not entirely consistent with any one interpretation, a single Holocene paleoearthquake occurring younger than ∼1,600 to 2,300 kcal yr BP is the simplest interpretation. It is possible that the PF records two Holocene events, with a penultimate event 6.9–2.4 kcal yr BP event and the aforementioned most recent event (MRE) between 2.3 and 1.6 kcal yr BP. However, only a single wall of one trench, out of a total of 12 walls in our 6 trenches, provides evidence supporting that interpretation. This study finds evidence of a single late Holocene paleoseismic event on the PF and sparse evidence for 2 Holocene paleoseismic events on the PF and highlights the benefits of logging multiple trench walls to better understand the complexity that results from this low-slip rate, low-deposition-rate fault system.

58 GEOSCIENCES↗

DOE OSTI2024

Impacts of Control, Penetration, and Distribution of Embedded Storage Network in Bulk Power System

The current shift in generation mix from fossil fuel plants towards variable and intermittent renewable energy sources is poised to create a future grid with reduced physical inertia and mismatch between generation and demand. Embedded storage, which is a concept of a coordinated network of storage units sited at the interface between the transmission and distribution system, is proposed as a mechanism to provide a buffer between generation and demand. This paper proposes an automated framework to model and integrate embedded storage in large-scale power systems with industry-grade grid-following (GFL) and grid-forming (GFM) control technologies. More importantly, the developed framework is used to explore the impacts of embedded storage control, penetration, location, and capacity in providing fast frequency response to the grid under contingency events such as generator trips and faults. The framework and study are conducted using the transient-stability simulation tool PSS/E and a realistic model of the Puerto Rico grid as a chosen test system. The simulation results show that GFL and GFM embedded storage, distributed throughout the system, with sufficient penetration and capacity, can effectively improve primary frequency response of the system under the studied contingency events.

Battery Energy Storage, embedded storage, grid-for↗

DOE OSTI2025

Exploring Data Set Bias and Decision Support with Predictive Uncertainty Through Bayesian Approximations and Convolutional Neural Networks

Individual seismic catalogs can contain multiscale observations from fault level to global scales and associated waveforms from discrete events reflect crustal structure across many different scales and locations. Seismic network aperture, geographic location, and observation distance may not provide informative guidance or intuition on how different catalogs will behave across models trained under different conditions. We rely on uncertainty to provide guardrails for when to trust model decisions, but understanding when our uncertainty is trustworthy is an open challenge. Here, in this work, we explore Bayesian approximation methods for assigning predictive uncertainty in seismic event classification problems. We find that computationally expensive Bayesian approximations do not outperform simple ensemble methods. We also find that when exploiting multiple seismic event catalogs, joint training with data from all the catalogs combined with Bayesian approximations and supervised training for classification can obscure bias and result in less robust uncertainty while also not providing substantial performance benefits compared to training individual models for each catalog.

58 GEOSCIENCES↗

DOE OSTI2023

Enhanced Microseismicity During Production Pumping Cessation at the San Emidio Geothermal Field (Nevada, USA) in December 2016

Abstract Tectonic activity, geothermal fluids, and microseismic events (MSEs) tend to occur in similar locations as a result of spatiotemporal changes in the subsurface stress state. To quantify this association, we analyze data from a dense seismic array deployed at the San Emidio geothermal field, Nevada for 1 week in December 2016 to coincide with a 19.45‐hr shutdown of all injection and production pumping operations. 123 MSEs were detected, of which 101 occurred during the shutdown. The spatial association of the MSEs with the production wells suggests a causal relationship between the production cessation and the MSEs. Here we performed a detailed analysis to investigate reservoir material properties, distribution of seismically activated faults, and local stress state. We determined the hypocenters, magnitudes, and focal mechanisms for the MSEs, P‐wave tomographic velocity model, and local stress tensor. The results show that most MSEs occurred near the production wells. Magnitudes fall between −2.2 and 0.0 with larger events located closer to the production wells. Most MSEs occurred within a westward‐dipping normal fault zone in the reservoir associated with anomalously low P‐wave velocity values. The focal mechanism and stress inversion results show predominantly normal faulting with the maximum horizontal stress oriented north‐south. We suggest that the MSEs during shutdown were triggered on pre‐existing, small‐scale, critically stressed fault patches in the reservoir as the pore pressure increased around the production wells when the production pumping ceased. We interpret the larger MSE magnitudes closer to the production wells as a result of higher pore pressure increase.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Report on High Energy Arcing Fault Experiments: Experimental Results from Open Box Enclosures

This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena. The experiments focus on providing data to better characterize the arc to improve the prediction of arc energy emitted during a HEAF event. An open box experiment allow for direct observation of the arc, which allows diagnostic instrumentation to record the phenomenological data needed for better characterization of the arc energy source term. The data collected supports characterization of the arc and arc jet, enclosure breach, material loss, and electrical properties. These results will be used to better characterizing the hazard for improvements in fire probabilistic risk assessment (PRA) realism. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA Labs. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 22, 2020 and September 18, 2020 on near-identical 51 cm (20 in) cube metal boxes suspended from a Unistrut support structure. The three-phase arcing fault was initiated at the ends of the conductors oriented vertically and located at the center of the box. Either aluminum or copper conductors were used for the conductors. The low-voltage experiments used 1 000 volts AC, while the medium-voltage experiments used 6 900 volts AC consistent with other recently completed experiments. Durations of the experiment ranged from 1 s to 5 s with fault currents ranging from 1 kA to 30 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. The experiments were documented with normal and high-speed videography, infrared imaging and photography.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Validation of Play Fairway Analysis of the geothermal potential of Camas Prairie, south-central Idaho, by an exploration well

Abstract Play Fairway Analysis (PFA) methodology was adapted for geothermal exploration at Camas Prairie, Idaho. Geophysical data, structural and geologic mapping, volcanic rock ages and vent locations, and the distribution of thermal springs and wells all indicated a relatively high geothermal potential along the southern margin of the Prairie. An exploration well (USU Camas-1) was drilled to a depth of 618.3 m to validate the PFA. A permeable zone was encountered at ~ 357.5 m with a maximum measured temperature of ~ 80 °C, which was suppressed following the injection of cold water. A moderate transmissivity of ~ 0.25–1 cm 2 /s estimated from an injection test as well a seasonal artesian flow at ~ 0.7 L/s corroborate the presence of a permeable zone. The existence of a lacustrine clay seal was confirmed near the bottom of the basin-fill sediment occupying the upper 314 m of the well. Geothermometers suggest the USU Camas-1 well water equilibrated at a reservoir temperature of ~ 120 °C. Based on the locations of both thermal and cold wells, geothermal fluids appear to be flowing upward along one or both of two fault systems. The presence of young basalts and elevated helium isotope ratios suggest that the heat source of Camas Prairie is magmatic. However, the faults may be acting as a conduit for geothermal fluids to rise from great depth without a shallow magmatic source being present. Camas Prairie is a promising area for geothermal development, but the relatively low reservoir temperatures indicate this resource may not be suitable for electric generation. Perhaps the best use would be for heating.

Lachmar, Thomas E. (ORCID:0000000249640119)↗

DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Toward improved urban earthquake monitoring through deep-learning-based noise suppression

Earthquake monitoring in urban settings is essential but challenging, due to the strong anthropogenic noise inherent to urban seismic recordings. Here, we develop a deep-learning-based denoising algorithm, UrbanDenoiser, to filter out urban seismological noise. UrbanDenoiser strongly suppresses noise relative to the signals, because it was trained using waveform datasets containing rich noise sources from the urban Long Beach dense array and high signal-to-noise ratio (SNR) earthquake signals from the rural San Jacinto dense array. Application to the dense array data and an earthquake sequence in an urban area shows that UrbanDenoiser can increase signal quality and recover signals at an SNR level down to ~0 dB. Earthquake location using our denoised Long Beach data does not support the presence of mantle seismicity beneath Los Angeles but suggests a fault model featuring shallow creep, intermediate locking, and localized stress concentration at the base of the seismogenic zone.

58 GEOSCIENCES↗

DOE OSTI2021

Conditioned Simulation of Ground-Motion Time Series at Uninstrumented Sites Using Gaussian Process Regression

Ground-motion time series are essential input data in seismic analysis and performance assessment of the built environment. Because instruments to record free-field ground motions are generally sparse, methods are needed to estimate motions at locations with no available ground-motion recording instrumentation. In this study, given a set of observed motions, ground-motion time series at target sites are constructed using a Gaussian process regression (GPR) approach, which treats the real and imaginary parts of the Fourier spectrum as random Gaussian variables. Model training, verification, and applicability studies are carried out using the physics-based simulated ground motions of the 1906 Mw 7.9 San Francisco earthquake and Mw 7.0 Hayward fault scenario earthquake in northern California. Additionally, the method’s performance is further evaluated using the 2019 Mw 7.1 Ridgecrest earthquake ground motions recorded by the Community Seismic Network stations located in southern California. These evaluations indicate that the trained GPR model is able to adequately estimate the ground-motion time series for frequency ranges that are pertinent for most earthquake engineering applications. The trained GPR model exhibits proper performance in predicting the long-period content of the ground motions as well as directivity pulses.

58 GEOSCIENCES↗

DOE OSTI2023

Northward propagation of the Gulf of Elat-Aqaba constrained by cosmogenic burial ages and magnetostratigraphy of onshore sediments

The Gulf of Elat-Aqaba (GEA), located in the southern part of the Dead Sea Transform (DST), is one of the most active segments of the Dead Sea fault system. Yet, some fundamental details concerning its evolution in space and time are still not fully understood. To better constrain the tectonic history of this region, we study a succession of alluvial, lacustrine, and fluvial deposits in the north-western edge of the GEA, which belong to the Quaternary Eilot and Garof Fms. The Eilot Fm. represents low-energy shallow freshwater bodies and sabkhas, which predate the development of the deep part of the basin. Later, in response to the subsidence of the basin, the Garof Fm. was deposited in alluvial fans that built up following the increase in the depositional energy. Cosmogenic burial ages combined with magnetostratigraphy show that these Fms. were deposited as early as 3.03 Ma and as late as 1.65 Ma, depending on the applied age model. Considering the present depth of the northern GEA, this age indicates a maximum subsidence rate of the head of the GEA of ~1.98mm/yr. We suggest that faults along the onshore margin of the deep basin were active during the deposition of the Garof Fm. and subsequently became inactive, while the faulting activity migrated toward the center of the basin. In conclusion, closed Holocene basins north of the present seashore, such as the Elat and Evrona playas, which may represent a modern analogue to the Plio-Pleistocene morphology, raise the possibility that the GEA head is still propagating northward.

58 GEOSCIENCES↗

DOE OSTI2022

Metamorphism-facilitated faulting in deforming orthopyroxene: Implications for global intermediate-depth seismicity

Significance The exothermic metamorphic reaction in orthopyroxene (Opx), a major component of oceanic lithospheric mantle, is shown to trigger brittle failure in laboratory deformation experiments under conditions where garnet exsolution takes place. The reaction product is an extremely fine-grained material, forming narrow reaction zones that are mechanically weak, thereby facilitating macroscopic faulting. Oceanic subduction zones are characterized by two separate bands of seismicity, known as the double seismic zone. The upper band of seismicity, located in the oceanic crust, is well explained by dehydration-induced mechanical instability. Our newly discovered metamorphism-induced mechanical instability provides an alternative physical mechanism for earthquakes in the lower band of seismicity (located in the oceanic lithospheric mantle), with no requirement of hydration/dehydration processes.

58 GEOSCIENCES↗

DOE OSTI2022

Ultra High-Temperature Magnetic Bearing System for s-CO 2 Turbines/Expanders. Phase II Final Report

The goal of this project is to design and construct of a prototype of ultra-high temperature permanent magnet (UHT–PM), which provides the force to pull the spinning shaft towards the target position in the magnetic bearing (MB) clearance circle. This project will develop a PM biased MB system, that is actively cooled to the 550°C maximum operating temperature limit of PMs. The MB test environment will include 700°C, 40krpm and 4,000 psi requirements to advance the supercritical carbon dioxide (sCO 2 ) and other types of Brayton power cycle systems. The proposed novel MBs combine PMs for supplying the bias field and electromagnets for supplying the control field, both in UHT conditions. The choice of material is the UHT Sm-Co PMs (US patent 6,451,132) due to their significantly better thermal stability. The 6-pole homopolar design permits uninterrupted force delivery via a redundant control capability (US patent 7,429,811) even if 3 poles were to fail. The Phase I efforts was to focus on development and demonstration of component technologies and detailed design of full scale components and a demonstrator test rig for use in Phase II. UHT–PMs were produced and used in the MB actuator. The operating environment of the EEC-T550 Sm-Co magnet material could be extended by implementing active cooling. Electromagnetic coils imbedded in the MB provide forces to stabilize the shaft position at the target via sensing and control stages. Shaft position sensors enable to identify the present position of the spinning shaft relative to its desired target position in the MB clearance circle (air gap). Auxiliary bearings will be installed to provide a backup support system in the event that power to the MB fails or there is a fault in a device providing current to the MB coils. For control, reliability and safety reasons the sensors and auxiliary bearings are typically located as close as possible to the MBs, which exposes them to the same environmental conditions. Development of only the actuator for the UHT environment is an inadequate approach to complete integration of the MB system in the turbine/expander. Therefore the UHT sensor and auxiliary bearing were designed and developed along with the actively cooled, UHT-PM actuator development. Although shaft position sensors are commercially available (Kaman) they may cost up to $10k per channel, and a full 5 axis magnetic suspension is best implemented with up to 20 sensors. Once successfully completed, this project will significantly extend the operating environment capability for turbomachinery applications such as nuclear power, concentrated solar thermal, fossil fuel, geothermal, and shipboard propulsion. The further advancement of UHT-PM-MB will also strengthen the US position in PM technology, which is presently heavily dominated by China. The UHT Sm-Co magnet material that will be utilized in the proposed work has been developed exclusively by the project proposer. Many actuators, motors, generators and other MB applications will greatly benefit from the proposed work.

24 POWER TRANSMISSION AND DISTRIBUTION↗