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At least 469 records · Page 26

Analytic model of the γ -surface deviation and influence on the stacking fault width between partial dislocations

The stacking fault width (R$_{eq}$) between partial dislocations within an FCC crystalline lattice characterizes the onset of numerous plastic flow mechanisms, as well as the relationship between material strength and grain size. Continuum models traditionally consider a complete unit of dislocation slip ( b ) along the $\langle{110}$$\rangle$ direction distributed between two discrete partial dislocations, each with a fixed partial Burgers vector ( b p ), which bound a stacking fault. Across the stacking fault, the vectorial slip is assumed to be constant, yielding a constant intrinsic stacking fault energy density, $\gamma$$_{isf}$ Here, we demonstrate that the vectorial displacement path taken in accomplishing a complete unit of slip (b) deviates from the expected displacement path containing the local minima, $\gamma$$_{isf}$ leading to a correction in the nominally derived stacking fault width. The magnitude of the correction depends on both the net orientation of the dislocation within the lattice, and also the degree of relaxation of each partial Burgers vector along the $\langle{\bar{1}12}$$\rangle$ direction. We derive a simple analytic model for the corrected stacking fault width, explicitly accounting for the deviation, by introducing a variable ξ (0 < ξ < 1), which governs the magnitude of each partial dislocation component along the $\langle{\bar{1}12}$$\rangle$ direction. Significantly, our model predicts a correction to R$_{eq}$ of ~$\mathscr{O}$ (|b|) for the nominally screw dislocation, and has no noticeable influence on nominally edge dislocations. We apply our model towards computing the stacking fault width of several FCC metals, and demonstrate excellent agreement both with our own numerical data as well as that obtained from ab initio and Molecular Statics (MS) methods within the literature. Lastly, the results from this study demonstrate that, upon judicious application, discrete linear elastic models are successful in reproducing elastic interactions as computed from higher fidelity models on the spatial scale of metallic dislocation cores.

36 MATERIALS SCIENCE↗

De-risking fault leakage risk and containment integrity for subsurface storage applications

The subsurface is pivotal in the energy transition, for the sequestration of CO 2 and energy storage. It is crucial to understand to what extent geological faults may form leakage pathways that threaten the containment integrity of these projects. Fault flow behavior has been studied in the context of hydrocarbon development, supported by observations from wells drilled through faults, but such observations are rare in geoenergy projects. Focusing on mechanical behavior as early indicator of potential leakage risks, a probabilistic Coulomb Failure Stress workflow is developed and demonstrated using data from the Decatur CO 2 sequestration project to rank faults based on their containment risk. The analysis emphasizes the importance of fault throw relative to reservoir thickness and pore pressure change in assessing reactivation risks. Integrating this mechanical assessment with geological and dynamic fault analyses contributes to derisking fault containment for geoenergy applications, providing valuable insights for the successful development of subsurface storage projects.

58 GEOSCIENCES↗

A new coupled multiphase flow–finite strain deformation–fault slip framework for induced seismicity

Production of hydrocarbons and water from subsurface reservoirs are known to cause permanent deformation of the reservoir and seismicity along faults both of which are detrimental to sustainable development of natural resources. Most of the prior studies on understanding fluid flow-induced plasticity and seismicity have focused on one or the other phenomenon due to the numerical difficulty associated with simultaneous modeling of the two failure phenomena because stress and deformation evolve non-linearly in both plasticity and seismicity. However, in reservoirs undergoing long-term production, plastic failure can alter the stress paths of points on a fault such that the onset, location, and magnitude of actual seismic events can no longer be predicted by a poroelastic simulation due to inaccurate stress and deformation history. We present a computational framework for coupled multiphase flow, finite strain poroplastic deformation, and dynamic fault slip and use it to understand the impact of plastic deformation on the onset, location, and magnitude of induced fault slip events. We evaluate the impact of plasticity on reservoir pressure, deformation, induced stress, and fault slip by comparing infinitesimal strain elastic and finite strain poro-elastoplastic models. For real-world applications, we consider different scenarios where the reservoir is either mechanically weaker or stronger than the caprock. We analyze the stress evolution as a function of the change in reservoir pressure to understand the role of contrast in reservoir and caprock elastic moduli on geomechanical stability. The results show that the poroplastic reservoir exhibits larger vertical deformation and delayed slip than the poroelastic reservoir after the same amount of oil production. For the same amount of pressure drop, a reservoir with a smaller modulus than the caprock displays a larger vertical displacement and an earlier onset of both plastic failure and fault slip. For a reservoir with a larger modulus than the caprock, vertical displacement is larger on the reservoir top boundary and smaller on the ground surface, and a higher pressure drop is needed to induce plastic failure and fault slip.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Block Tectonics across Western Tibet and Multi-Millennial Recurrence of Great Earthquakes on the Karakax Fault

We report that fault slip rates are critical to quantify continental deformation. Those along the Karakax fault (northwestern Altyn Tagh Fault: ATF) have been debated, even though it is one of Tibet's most outstanding active faults. At Taersa, using LiDAR measurements of terrace and fan riser offsets (~6 to ~500 m) and 10 Be/ 26 Al dating of alluvial surfaces (<210 ka), we obtain a late Quaternary slip rate of ~2.5 ± 0.5 mm/yr. This doubles the ~2.6 ± 0.5 mm/yr rate time span found to the east and west. We interpret the ~150 km-long, free-faced rupture along the fault to be that of the M ~ 7.6 event felt in Hotan in 1882. Characteristic slip (~6 m) during four large earthquakes since ~10 ka implies a ~2500 ± 500 years return time. A ~3 mm/yr rate is consistent with the ~80 km offset of the Karakax river since uplift of the West Kunlun range and sediment deposition in the Tarim foreland accelerated, ~24 Ma ago. The faster slip rate (~10.5 mm/yr) on the central ATF matches the sum of those along the reactivated West Tibetan terrane boundaries (Karakax and Longmu-Gozha Co faults) at the Uzatagh triple junction (~36°N, 83°E). The abrupt termination and altitude drop of the Karakorum range where the Longmu Co and Karakorum faults meet (Angmong junction), also reflect triple junction kinematics. Such localized changes account for the rise of the Karakorum and West Kunlun ranges and support lithospheric block tectonics rather than diffusely distributed deformation.

58 GEOSCIENCES↗

Automatic speech recognition predicts contemporaneous earthquake fault displacement

Abstract Significant progress has been made in probing the state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec-2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kīlauea volcano on the island of Hawai’i. We pre-train the Wav2Vec-2.0 model using caldera seismic waveforms and augment the model architecture to predict contemporaneous surface displacement during the caldera collapse sequence, a proxy for fault displacement. We find the model displacement predictions to be excellent. The model is adapted for near-future prediction information and found hints of prediction capability, but the results are not robust. The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligence models developed for encoding audio of speech may have important applications in studying active fault zones.

58 GEOSCIENCES↗

Low-overhead transversal fault tolerance for universal quantum computation

Fast, reliable logical operations are essential for realizing useful quantum computers. By redundantly encoding logical qubits into many physical qubits and using syndrome measurements to detect and correct errors, we can achieve low logical error rates. However, for many practical quantum error correction codes such as the surface code, owing to syndrome measurement errors, standard constructions require multiple extraction rounds—of the order of the code distance d—for fault-tolerant computation, particularly considering fault-tolerant state preparation. Here we show that logical operations can be performed fault-tolerantly with only a constant number of extraction rounds for a broad class of quantum error correction codes, including the surface code with magic state inputs and feedforward, to achieve ‘transversal algorithmic fault tolerance’. Through the combination of transversal operations7 and new strategies for correlated decoding, despite only having access to partial syndrome information, we prove that the deviation from the ideal logical measurement distribution can be made exponentially small in the distance, even if the instantaneous quantum state cannot be made close to a logical codeword because of measurement errors. We supplement this proof with circuit-level simulations in a range of relevant settings, demonstrating the fault tolerance and competitive performance of our approach. Furthermore, our work sheds new light on the theory of quantum fault tolerance and has the potential to reduce the space–time cost of practical fault-tolerant quantum computation by over an order of magnitude.

Zhou, Hengyun [QuEra Computing, Boston, MA (United↗

Earthquake disaster mitigation of Lembang Fault West Java with electromagnetic method

The Lembang fault is located around eight kilometers from Bandung City, West Java, Indonesia. The existence of this fault runs through densely populated settlement and tourism area. It is an active fault structure with increasing seismic activity where the 28 August 2011 earthquake occurred. The seismic response at the site is strongly influenced by local geological conditions. The ambient noise measurements from the western part of this fault give strong implication for a complex 3-D tectonic setting. Hence, near surface Electromagnetic (EM) measurements are carried out to understand the location of the local active fault of the research area. Hence, near surface EM measurements are carried out to understand the location of the local active fault and the top of the basement structure of the research area. The Transientelectromagnetic (TEM) measurements are carried out along three profiles, which include 35 TEM soundings. The results indicate that TEM data give detailed conductivity distribution of fault structure in the study area.

58 GEOSCIENCES↗

Phase response curves for models of earthquake fault dynamics

We systematically study effects of external perturbations on models describing earthquake fault dynamics. The latter are based on the framework of the Burridge-Knopoff spring-block system, including the cases of a simple mono-block fault, as well as the paradigmatic complex faults made up of two identical or distinct blocks. The blocks exhibit relaxation oscillations, which are representative for the stick-slip behavior typical for earthquake dynamics. Our analysis is carried out by determining the phase response curves of first and second order. For a mono-block fault, we consider the impact of a single and two successive pulse perturbations, further demonstrating how the profile of phase response curves depends on the fault parameters. For a homogeneous two-block fault, our focus is on the scenario where each of the blocks is influenced by a single pulse, whereas for heterogeneous faults, we analyze how the response of the system depends on whether the stimulus is applied to the block having a shorter or a longer oscillation period.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Internal structure of the San Jacinto fault zone at the Ramona Reservation, north of Anza, California, from dense array seismic data

SUMMARY We image the internal structure of the San Jacinto fault zone (SJFZ) near Anza, California, with seismic data recorded by two dense arrays (RA and RR) from ∼42 000 local and ∼180 teleseismic events occurring between 2012 and 2017. The RA linear array has short aperture (∼470 m long with 12 strong motion sensors) and recorded for the entire analysed time window, whereas the RR is a large three-component nodal array (97 geophones across a ∼2.4 km × 1.4 km area) that operated for about a month in September–October 2016. The SJFZ at the site contains three near-parallel surface traces F1, F2 and F3 from SW to NE that have accommodated several Mw > 6 earthquakes in the past 15 000 yr. Waveform changes in the fault normal direction indicate structural discontinuities that are consistent with the three fault surface traces. Relative slowness from local events and delay time analysis of teleseismic arrivals in the fault normal direction suggest a slower SW side than the NE with a core damage zone between F1 and F2. This core damage zone causes ∼0.05 s delay at stations RR26–31 in the teleseismic P arrivals compared with the SW-most station, and generates both P- and S-type fault zone trapped waves. Inversion of S trapped waves indicates the core damaged structure is ∼100 m wide, ∼4 km deep with a Q value of ∼20 and 40 per cent S-wave velocity reduction compared with bounding rocks. Fault zone head waves observed at stations SW of F3 indicate a local bimaterial interface that separates the locally faster NE block from the broad damage zone in the SW at shallow depth and merges with a deep interface that separates the regionally faster NE block from rocks to the SW with slower velocities at greater depth. The multiscale structural components observed at the site are related to the geological and earthquake rupture history at the site, and provide important information on the preferred NW propagation of earthquake ruptures on the San Jacinto fault.

Geochemistry & Geophysics↗

En echelon faults reactivated by wastewater disposal near Musreau Lake, Alberta

We use machine-learning and cross-correlation techniques to enhance earthquake detectability by two magnitude units for the earthquake sequence near Musreau Lake, Alberta, which is induced by wastewater disposal. This deep catalogue reveals a series of en echelon ~N–S oriented strike-slip faults that are favourably oriented for reactivation. These faults require only ~0.6 MPa overpressure for triggering to occur. Earthquake activity occurs in bursts, or episodes; episodes restricted to the largest fault tend to have earthquakes starting near the southern end (distant from injectors) and progressing northwards (towards the injectors). While most events are concentrated along these ~N–S oriented faults, we also delineate smaller faults. Together, these findings suggest pore pressure as the triggering mechanism, where a time-dependent increase in pore pressure likely caused these faults to progressively reawaken. Analysis of the ‘next record-breaking event’, a statistical model that forecasts the sequencing of earthquake magnitudes, suggests that the next largest event would be M L ~4.3. The seismically illuminated length of the largest fault indicates potential magnitudes as large as M w 5.3.

58 GEOSCIENCES↗

Fault-Tolerant Operation of Bosonic Qubits with Discrete-Variable Ancillae

Fault-tolerant quantum computation with bosonic qubits often necessitates the use of noisy discrete-variable ancillae. In this work, we establish a comprehensive and practical fault-tolerance framework for such a hybrid system and synthesize it with fault-tolerant protocols by combining bosonic quantum error correction (QEC) and advanced quantum control techniques. We introduce essential building blocks of error-corrected gadgets by leveraging ancilla-assisted bosonic operations using a generalized variant of path-independent quantum control. Using these building blocks, we construct a universal set of error-corrected gadgets that tolerate a single-photon loss and an arbitrary ancilla fault for four-legged cat qubits. Notably, our construction requires only dispersive coupling between bosonic modes and ancillae, as well as beam-splitter coupling between bosonic modes, both of which have been experimentally demonstrated with strong strengths and high accuracy. Moreover, each error-corrected bosonic qubit is comprised of only a single bosonic mode and a three-level ancilla, featuring the hardware efficiency of bosonic QEC in the full fault-tolerant setting. We numerically demonstrate the feasibility of our schemes using current experimental parameters in the circuit-QED platform. Finally, we present a hardware-efficient architecture for fault-tolerant quantum computing by concatenating the four-legged cat qubits with an outer qubit code utilizing only beam-splitter couplings. Our estimates suggest that the overall noise threshold can be reached using existing hardware. These developed fault-tolerant schemes extend beyond their applicability to four-legged cat qubits and can be adapted for other rotation-symmetrical codes, offering a promising avenue toward scalable and robust quantum computation with bosonic qubits. Published by the American Physical Society 2024

Physics↗

A Typology of Quantum-Classical Faults

This paper introduces an extended taxonomy of faults specific to hybrid quantum-classical systems, addressing the unique challenges that arise from integrating quantum accelerators into high-performance computing (HPC) infrastructures. Building on the foundational fault classification by Avizienis et al., we incorporate fault types unique to quantum computing-such as qubit decoherence, spontaneous gate errors, and photon loss-alongside traditional and human-induced faults including development errors, operational mistakes, and malicious attacks. Our taxonomy classifies faults by their origin (natural vs. human-made), intent (accidental, deliberate non-malicious, or malicious), system boundaries (internal vs. external), and persistence (transient to permanent). We also explore how different architectural integration patterns-ranging from tight coupling to loose on-premise and cloud-based configurations-shape the manifestation and propagation of faults. These scenarios are analyzed in terms of timing mismatches, interface inconsistencies, and security threats such as data tampering and denial-of-service attacks. Through this fault-centric lens, we aim to support the co-design of dependable quantum-classical systems and highlight the critical role that integration strategies play in ensuring reproducibility, resilience, and security across hybrid computing platforms.

Giusto, Edorado [University of Naples Federico II,↗

Adaptive Hierarchical Voltage Control of a DFIG-Based Wind Power Plant for a Grid Fault

This paper proposes an adaptive hierarchical voltage control scheme of a doubly-fed induction generator (DFIG)-based wind power plant (WPP) that can secure more reserve of reactive power (Q) in the WPP against a grid fault. To achieve this, each DFIG controller employs an adaptive reactive power to voltage (Q-V) characteristic. The proposed adaptive Q-V characteristic is temporally modified depending on the available Q capability of a DFIG; it is dependent on the distance from a DFIG to the point of common coupling (PCC). The proposed characteristic secures more Q reserve in the WPP than the fixed one. Furthermore, it allows DFIGs to promptly inject up to the Q limit, thereby improving the PCC voltage support. To avert an overvoltage after the fault clearance, washout filters are implemented in the WPP and DFIG controllers; they can prevent a surplus Q injection after the fault clearance by eliminating the accumulated values in the proportional-integral controllers of both controllers during the fault. Test results demonstrate that the scheme can improve the voltage support capability during the fault and suppress transient overvoltage after the fault clearance under scenarios of various system and fault conditions; therefore, it helps ensure grid resilience by supporting the voltage stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AN APPROACH TO BRINGING AUTOMATED FAULT DETECTION AND DIAGNOSIS (AFDD) TOOLS FOR HVAC&R INTO THE MAINSTREAM

Heating, ventilation and air-conditioning (HVAC) systems can consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. in commercial buildings. Additionally, commercial refrigeration (R) systems add about 2 quads to commercial buildings energy consumption. Most HVAC systems have one or more faults (low/high refrigerant charge, valve leakage, condenser/evaporator fouling, filter/dryer restriction, economizer faults, controls faults) that result in increased energy consumption. Automated fault detection and diagnosis (AFDD) tools have been developed to address this national issue and many tools are commercially available. AFDD tools have the potential to save considerable energy for existing commercial RTUs, chillers and refrigeration systems. These devices can be used for both retro commissioning, and, when faults are addressed, continuous commissioning as well. However, there appears to be multiple market barriers for this technology. A key market barrier for this technology is the lack of awareness of AFDD products among potential customers. Most HVAC contractors are not familiar with the latest AFDD technologies and HVAC technicians lack skills regarding these technologies. Quantifying potential benefits to building owners is difficult since there are several FDD tools with varying capabilities. For instance, there are several FDD products ranging from handling just economizer faults to those that also handle full-blown refrigerant-side and air-side faults. Methods/algorithms used in FDD vary significantly. Even though there are efforts to develop standards, currently there are no standards/methods to define functions, capabilities, accuracy, and reliability of FDD tools. Moreover, most of the commercial AFDD tools have not been verified in the field independently. This paper presents a comprehensive approach to bringing HVAC AFDD tools into the mainstream. The approach involves demonstrating ten commercially available tools at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying market barriers, and assisting utility companies in developing incentive programs. This paper presents selection of AFDD tools, ite identification, and field testing and evaluation method.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SRF Cavity Fault Classification Using Machine Learning At CEBAF

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is the first large high power CW recirculating electron accelerator to make use of SRF accelerating structures. The structures are configured in two anti-parallel linacs connected by arcs. Each linac consists of twenty C20/C50 cryomodules each containing eight 5-cell cavities and five C100 upgrade cryomodules each containing eight 7-cell cavities. Accurately classifying the source of cavity faults is critical for improving accelerator performance. A cavity fault triggers a waveform acquisition process where 17 waveform records sampled at 5 kHz are recorded for each of the 8 cavities in the affected cryomodule. The waveform record length is sufficiently long for transient microphonic effects to be observable. This data combined with archived signals sampled at 10 Hz are used to classify faults. Significant time is required for a subject matter expert to analyze and identify the intra-cavity signatures of imminent faults. This paper describes a path forward that utilizes machine learning for automatic fault classification. Post-training identification of the physical origins of faults are discussed, as are potential machine-trained model-free implementations of trip avoidance procedures. These methods should provide new insights into cavity fault mechanisms and facilitate intelligent optimization of cryomodule performance

Solopova, A.↗

Superconducting Radio-frequency Cavity Fault Classification Using Machine Learning at Jefferson Laboratory

We report on the development of machine learning models for classifying C100 superconducting radiofrequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Of the 418 SRF cavities in CEBAF, 96 are designed with a digital low-level RF system configured such that a cavity fault triggers recordings of RF signals for each of eight cavities in the cryomodule. Subject matter experts analyze the collected time-series data and identify which of the eight cavities faulted first and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time - rather than postmortem - identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the machine learning models during a recent physics run. We also discuss efforts for further insights into fault types through unsupervised learning techniques and present preliminary work on cavity and fault prediction using data collected prior to a failure event.

Tennant, C. D.↗

SRF CAVITY FAULT PREDICTION USING DEEP LEARNING AT JEFFERSON LAB

In this study, we present a deep learning-based pipeline for predicting superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelera-tor Facility (CEBAF) at Jefferson Lab. We leverage pre-fault RF signals from C100-type cavities and employ deep learning to predict faults in advance of their onset. We train a binary classifier model to distinguish between stable and impending fault signals. Test results show accuracies exceeding 99% for distinguishing between normal signals and pre-fault signals from a class of more slowly developing fault types, such as microphonics. We describe results from a proof-of-principle demonstration on a realistic, imbalanced data set and report performance metrics. Encouraging results suggest that future SRF systems could leverage this framework and implement measures to mitigate the onset in more slowly developing fault types.

Rahman, M.↗

Fault-related CO 2 degassing, geothermics, and fluid flow in southern California basins---Physiochemical evidence and modeling

Our studies have had an important impact on societal issues. Experimental and field observations show that CO 2 degassing, such as might occur from stored CO 2 reservoir gas, can result in significant stable isotopic disequilibrium. In the offshore South Ellwood field of the Santa Barbara channel, we show how oil production has reduced natural seep rates in the area, thereby reducing greenhouse gases. Permeability is calculated to be ~20-30 millidarcys for km-scale fault-focused fluid flow, using changes in natural gas seepage rates from well production, and poroelastic changes in formation pore-water pressure. In the Los Angeles (LA) basin, our characterization of formation water chemistry, including stable isotopic studies, allows the distinction between deep and shallow formations waters. Our multiphase computational-based modeling of petroleum migration demonstrates the important role of major faults on geological-scale fluid migration in the LA basin, and show how petroleum was dammed up against the Newport-Inglewood fault zone in a “geologically fast” interval of time (less than 0.5 million years). Furthermore, these fluid studies also will allow evaluation of potential cross-formational mixing of formation fluids. Lastly, our new study of helium isotopes in the LA basin shows a significant leakage of mantle helium along the Newport Inglewood fault zone (NIFZ), at flow rates up to 2 cm/yr. Crustal-scale fault permeability (~60 microdarcys) and advective versus conductive heat transport rates have been estimated using the observed helium isotopic data. The NIFZ is an important deep-seated fault that may crosscut a proposed basin decollement fault in this heavily populated area, and appears to allow seepage of helium from the mantle sources about 30 km beneath Los Angeles. The helium study has been widely cited in recent weeks by the news media, both in radio and on numerous web sites.

54 ENVIRONMENTAL SCIENCES↗