Fault System Research Articles

Experimental study on the rupture behaviors of orthogonal faults: effects of stress state and rupture initiation location

Summary Fault rupture dynamics is expected to be significantly affected by the geometry of fault system, especially for orthogonal faults. However, the rupture behaviors of orthogonal faults especially the coseismic interactions are far from fully understood. Here, we present experimental results from a series of laboratory earthquakes to elucidate the effect of the stress state and initiation location on the rupture behaviors of orthogonal faults. Our results reveal a phase diagram of rupture behaviors of orthogonal faults, which is collectively controlled by stress state and rupture initiation location. For events initiating from the main fault, the rupture cannot jump to the branch, which may be due to the clamping effect or the inhibited shear stress accumulation on the branch. On the contrary, events initiating from the branch can persistently trigger ruptures of the main fault. This difference highlights the directional effect associated with the rupture of orthogonal faults. Further, the rupture length of triggered ruptures on the main fault is controlled by the stress state of the fault system. With the increase of the ratio between the shear stress and normal stress, the rupture length of the main fault increases. Our results reproduce the rupture behaviors of orthogonal faults, which may provide insights into the rupture characteristics of natural earthquakes.

Investigation of Condition Monitoring System for Grid Connected Photovoltaic (GCPV) System with Power Electronics Converters Using Machine Learning Techniques

Power systems protection has become more vital in recent years to ensure stability, reliability, security, and power quality due to the exponential growth of grid-connected photovoltaic (GCPV) systems. As a result, several nations have set new grid codes for the grid connection of PV plant installations to overcome these concerns. Investigating Fault Ride Through (FRT) capacity is one of the primary criteria for grid codes. For three-phase GCPV systems, fault detection and classification approaches are proposed in this study. Firstly, different faults that occurred in the GCPV system are categorized and compared, with the critical and analytical evaluation of grid codes, particularly FRT requirements such as Low Voltage Ride Through (LVRT) and High Voltage Ride Through (HVRT) for different nations. Further, a detailed classification and a comparison of the existing FRT techniques are presented for better control methods based on system complexity, detection accuracy, and other evolutionary criteria. To ensure smooth grid operation, accurate fault detection and condition monitoring of the systems are required. This paper discusses a machine learning (ML) based technique for detecting faults in 3-phase GCPV systems. Multi-peak phenomena caused by FRT capabilities and anti-islanding detection are the main problems experienced while integrating a PV system into the local grid. The fault classification technique is developed using weighted K-nearest neighbor (WKNN) and fine gaussian support vector machine (FGSVM) based ML approaches utilizing Wavelet Transform. The proposed ML-based findings show that the fault detection algorithm-based classification accuracy has significantly improved.

A scaling relationship for the width of secondary deformation around strike-slip faults

Simple mechanical arguments suggest that slip along interlocked, rough faults, damages surrounding rocks. The same arguments require that the scale of secondary damage is proportional to the size of geometric irregularities along the main fault. This relationship could apply at all scales, but has, so far, been difficult to observe at the 10s to 100 s of km scales of large, natural faults, often because large-scale deformation is distributed across wide, complex plate-boundary fault systems, like the San Andreas Fault. The geometry and geology of another large-scale plate-boundary strike slip fault—the Queen Charlotte Fault (QCF)—is, in contrast, especially simple. Here, we show that observations of secondary deformation are well-aligned with predictions of stress variations caused by geometric irregularities along the QCF, suggesting a geometric relationship between primary fault geometry and secondary deformation. The analytic stress solution reveals that the highest stresses and highest likelihood of failure are confined to a zone of influence (ZOI) with a width quantified by ZOI=λ/2π, where λ is the wavelength of geometric variations along the main fault. This simple model is consistent with ~100-km-scale observations along the QCF and can theoretically be used to predict the width of secondary deformation at all scales.

The research on fault and structural trap of the Weixinan Sag, Beibuwan Basin, South China Sea

The Weixinan Sag in Beibuwan Basin is a pilot area of the offshore exploration and development integrated technology. The main oil bearing layers, first member of Liushagang formation and third member of Weizhou formation, develop many fault systems and structural traps. The key factors of the offshore exploration and development integrated technology are”the fault research”and “the effectiveness of structural trap”. Fault research includes the study of the geometry, dynamics, kinematics characteristics of fault, and the division of fault system. The effectiveness of structural trap include analogical studies on the structural characteristics of traps, quantitative studies on fault lateral sealability, fault vertical sealability, and prediction technology of oil column height. Synthesizing the relationship of the law of oil and gas distribution,the differential fault system in the internal of the No. 2 fault zone, and the effectiveness research of traps, the fault-controlled reservoir laws and the dominant fault-controlled reservoir mode are obtained. The research on fault and trap of offshore integrated exploration and development has been successfully applied in the Weixinan Sag. The 37 of 45 development evaluation wells have been drilled successfully and the drilling success rate is 82%. It has promoted the ODP(original drilling project) implementation of 5 oilfields, the adjustment implementation of 8 oilfields and made important contribution to the increase of reserves and production in the Weixinan Sag.

Hard Sample Mining-Enabled Supervised Contrastive Feature Learning for Wind Turbine Pitch System Fault Diagnosis

Abstract The presence of multiple failure severities in the wind turbine pitch system due to the long-term wear and tear poses challenges in accurately classifying the system's health condition, thus increasing maintenance costs or damage risks. This paper proposes a novel method based on hard sample mining-enabled supervised contrastive learning (HSMSCL) to address this problem. The proposed method leverages the powerful feature extraction capabilities of supervised contrastive learning to extract discriminative features from highly imbalanced data. Additionally, the method incorporates a cosine similarity-based hard sample mining framework that constructs hard sample pairs within mini-batches during both the representation learning and classifier training phases, thereby improving the diagnostic performance of the model for hard samples. The proposed method achieves macro G-mean of 0.9991 and 0.9971 on two real datasets containing data on wind turbine pitch system cog belt fractures. These results indicate significantly superior fault diagnosis performance compared to existing methods, highlighting its potential for enhancing the reliability and efficiency of fault diagnosis in wind turbine pitch systems.

3D Structure of Low‐Angle Normal Faults and Tectono‐Sedimentary Processes of Nascent Continental Core‐Complexes in the SE South China Sea

AbstractThis contribution explores the formation and evolution of hyper‐extended basins, associated with the early stage of core complex formation, controlled by low‐angle normal faults active at <30°. Based on a high‐resolution industrial 3D seismic reflection survey along the southern margin of the South China Sea (SCS) (Dangerous Grounds), we mapped and analyzed the 3D geometry of low‐angle normal fault systems and the related stratigraphy. Two main hyper‐extended basins were documented, filled by up to 6 km of sediments including pre‐ to post‐rift sequences. The observed normal faults on depth migrated seismic sections show an average dip angle of <30° and appear planar, characterized by continuous reflections with no clear steepening at depth and sole‐out on distinct decollement levels. Detailed fault surface mapping reveals the occurrence of km‐scale corrugations together with large wavelength undulation. The formation of these hyper‐extended basins is associated with polyphased syn‐rift infill during the development of the low‐angle normal faults. The first syn‐rift sequence appears as chaotic and discontinuous packages that has been dismembered and fragmented during the activity of low‐angle normal faults. The second syn‐rift package shows unexpected sedimentary wedges developing successively toward the footwall and the hangingwall. This geometry results from the interplay between the main low‐angle normal fault and antithetic faults defining a so‐called extensional fishtail. The deep structure of these basins shows nascent domes with limited evidence of magmatism. Eventually, these basins likely capture the earliest stage of core complex development in the proximal margin of the southern SCS.

Interseismic deformation in the northwestern Sichuan-Yunnan block constrained by Sentinel-1 InSAR and GNSS

The northwestern Sichuan-Yunnan block (NW SYB), located in the southeastern Tibetan Plateau, is characterized by complex fault systems. Its detailed crustal deformation is crucial to comprehending the kinematics of the Tibetan expansion. In this study, we integrate the Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) data to obtain the high-resolution present-day deformation of the NW SYB, which provides insights into the strain partitioning, fault kinematics, and block motion characteristics in this region. Our results show that the elastic strain is not only built up around faults but also widely distributed in the off-fault areas. The Ganzi segment of the Ganzi-Yushu fault and the Luhuo segment of the Xianshuihe fault in the study area accommodate 5.31 mm/yr and 8.41 mm/yr left-lateral strike-slip motion, respectively. The small-scale faults show certain deformation, among which the left-lateral and right-lateral slip rates of the Litang and Zhongdian faults are 2.53 mm/yr and 1.97 mm/yr, respectively. The spatial patterns of the strain partitioning and block motion show that the active strike-slip faults accommodate displacements from Cenozoic block extrusion and rotation, which partially coordinate the kinematic discrepancy of the Tibetan expansion. Our geodetic measurements and existing structural observations indicate that the southeastward expansion of the Tibetan Plateau is absorbed mainly by E-W shortening and N-S extension in the NW SYB, may accommodated by continental strike-slip faults in the upper crust and distributed shear in the lower crust.

Efficient detection and analysis of shunt faults in electric power distribution systems (EPDS) using DCFC and EFDC algorithm: a modeling and simulation approach

ABSTRACT The electrical power distribution system (EPDS) is an essential component of the power system. Electricity and its services have risen enormously in the recent period, and the primary task of EPDS is to distribute uninterrupted electricity to the consumer. The EPDS comprises numerous intricate, unpredictable, and interlinked components that are frequently susceptible to disruption or malfunction. Faults on EPDS are intended to be appropriately recognized and categorized before being eliminated as quickly as feasible. An efficient fault recognition mechanism makes relaying operations realistic, fast, safe, and dependable. In this article, we introduce a MATLAB simulation model based on the Electrical Fault Detection and Classification (EFDC) algorithm for shunt fault analysis in the EPDS and distinguish among heterogeneous types of shunt fault based on current and voltage waveform throughout the fault. The recommended fault scrutiny and isolation framework might aid in segregating malfunctioning sections from healthy EPDS. Numerous electrical shunt faults are modeled and simulated to detect such deficient behaviors. The suggested EFDC algorithm’s efficacy, including Digital Comparative Fault Classifier (DCFC), is examined by simulating different kinds of shunt faults throughout ring-main EPDS’s source and load regions to evaluate the proposed technique’s adaptability, as well as the outcomes are promising.

Experimental and Modeling Study of Arc Fault Induced Thermal Runaway in Prismatic Lithium-Ion Batteries

With the widespread application of electrochemical energy storage technology, the safety issues of lithium-ion batteries have garnered significant attention. The issue of arc faults resulting from electrical failures is especially critical, as it can lead to catastrophic battery disasters. Therefore, this paper first established an arc testing platform and conducted experiments on top cover and body of prismatic lithium-ion batteries to analyze the thermoelectric characteristics between arc and battery. Under experimental conditions of 300 V and 15 A, it was found that arcs can induce thermal runaway in batteries. Subsequently, based on the experimental conditions, a mathematical model was established to induce thermal runaway in batteries through an equivalent method of arc heat source. By comparing the temperature curves of model and experiment, the RMSE of temperature at the center point of large surface was 5.09 °C (with a maximum temperature of 212 °C), indicating the accuracy of the model. This paper’s research on arc faults in battery systems revealed the evolution pattern and realized that arcs can trigger thermal runaway in batteries. The model for arc-triggered thermal runaway in batteries is highly accurate, capable of reducing the number of experiments, accelerating experimental progress, and is of significant importance for guiding the design of arc experiments about batteries.

Enhanced power system fault detection using quantum‐AI and herd immunity quantum‐AI fault detection with herd immunity optimisation in power systems

Enhanced power system fault detection using quantum‐AI and herd immunity quantum‐AI fault detection with herd immunity optimisation in power systems

Large-Depth Ground-Penetrating Radar for Investigating Active Faults: The Case of the 2017 Casamicciola Fault System, Ischia Island (Italy)

We conducted large-depth Ground-Penetrating Radar investigations of the seismogenic Casamicciola fault system at the volcanic island of Ischia, with the aim of constraining the source characteristics of this active and capable fault system. On 21 August 2017, a shallow (hypocentral depth of 1.2 km), moderate (Md = 4.0) earthquake hit the island, causing severe damage and two fatalities. This was the first damaging earthquake recorded on the volcanic island of Ischia from the beginning of the instrumental era. Our survey was performed using the Loza low-frequency (15–25 MHz) GPR system calibrated by TDEM results. The data highlighted variations in the electromagnetic signal due to the presence of contacts, i.e., faults down to a depth larger than 100 m below the surface. These signal variations match with the position of the synthetic and antithetic active fault system bordering the Casamicciola Holocene graben. Our study highlights the importance of employing large-depth Ground-Penetrating Radar geophysical techniques for investigating active fault systems not only in their shallower parts, but also down to a few hundred meters’ depth, providing a contribution to the knowledge of seismic hazard studies on the island of Ischia and elsewhere.

AC fault ride-through control strategy of MMC-UHVDC system with hierarchical connection mode

The ultra-high voltage direct current (UHVDC) transmission composed of modular multilevel converters (MMC) is an important technology for large-scale centralized transmission of renewable energy. In UHVDC system, temporary faults in the AC power grid system are a high probability fault, and the fault control strategy affects the safety and reliability of system operation. This paper studies on the condition of AC power grid faults occurring at the receiving converter station. Firstly, study the system characteristics after the occurrence of AC faults, and use theoretical analysis to derive the trend of DC voltage changes of each converter valve. Then, an AC fault ride-through control strategy with high power transmission capability is proposed with hierarchical connection structure, the strategy controls the system to synchronously reduce DC voltage and AC active power after a fault, maximizing the retention of the system’s transmission capacity during the occurrence of faults, thereby reduce power shock in the system. Finally, a simulation model of the dual ended system has built based on the PSCAD simulation platform. The simulation results show that when a single-phase ground fault and a three-phase ground fault occur in the high valve group at the receiving station, the system can retain about 83% and 50% of the transmission capacity during the fault period, respectively. Meanwhile, there is no serious overvoltage or overcurrent phenomenon in the system. The simulation results verified the effectiveness of the proposed control strategy.

Rupture segmentation on the East Anatolian fault (Turkey) controlled by along-strike variations in long-term slip rates in a structurally complex fault system

The East Anatolian fault in Turkey exhibits along-strike rupture segmentation, typically resulting in earthquakes with moment magnitude (Mw) up to 7.5 that are confined to individual segments. However, on 6 February 2023, a catastrophic Mw 7.8 earthquake struck near Kahramanmaraş (southeastern Turkey), defying previous expectations by rupturing multiple segments spanning over 300 km and overcoming multiple geometric complexities. We explore the mechanics of successive single- and multi-segment ruptures using numerical models of the seismic cycle calibrated to historical earthquake records and geodetic observations of the 2023 doublet. Our model successfully reproduces the observed historical rupture segmentation and the rare occurrence of multi-segment earthquakes. The segmentation pattern is influenced by variations in long-term slip rate along strike across the kinematically complex fault network between the Arabian and Anatolian plates. Our physics-based seismic cycle simulations shed light on the long-term variability of earthquake size that shapes seismic hazards.

Harmonic Sequence Component Model-Based Small-Signal Stability Analysis in Synchronous Machines during Asymmetrical Faults

Power systems are complex and often subject to faults, requiring accurate mathematical models for a thorough analysis. Traditional time-domain models are employed to evaluate the dynamic response of power system elements during transmission system faults. However, only the positive sequence components are considered for unbalanced faults, so the small-signal stability analysis is no longer accurate when assuming balanced conditions for asymmetrical faults. The dynamic phasor approach extends traditional models by representing synchronous machines with harmonic sequence components, making it suitable for an unbalanced condition analysis and revealing dynamic couplings not evident in conventional methods. By modeling electrical and mechanical equations with harmonic sequence components, the study implements an eigenvalue sensitivity analysis and participation factor analysis to identify the variable with significant participation in the critical modes and consequently in the dynamic response of synchronous machines during asymmetric faults, thereby control strategies can be proposed to improve system stability. The article validates the dynamic phasor model through simulations of a single-phase short circuit, demonstrating its accuracy and effectiveness in representing the transient and dynamic behavior of synchronous machines, and correctly identifies the harmonic sequence component with significant participation in the critical modes identified by the eigenvalue sensitivity to the rotor angular velocity and rotor angle.

Power system fault diagnosis with quantum computing and efficient gate decomposition

Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers. However, most classical methods suffer from significant time-consuming, memory overhead, and computational complexity issues as the scale of the power system concerned increases. With rapid development of quantum computing technology, the combinatorial optimization method based on quantum computing has shown certain advantages in computational time over existing methods. Given this background, this paper proposes a quantum computing based power system fault diagnosis method with the quantum approximate optimization algorithm. The proposed method reformulates the fault diagnosis problem as a Hamiltonian by using Ising model, which completely preserves the coupling relationship between faulty components and various operations of protective relays and circuit breakers. Additionally, to enhance problem-solving efficiency under current equipment limitations, the symmetric equivalent decomposition method of multi-z-rotation gate is utilized. Furthermore, the small probability characteristics of power system events is utilized to reduce the number of qubits. Simulation results based on the test system show that the proposed methods can achieve the same optimal results with a faster speed compared with the classical higher-order solver provided by D-Wave.

An exploration of potentially reversible controls on millennial-scale variations in the slip rate of seismogenic faults: Linking structural observations with variable earthquake recurrence patterns

Paleoseismic studies show that faults within a fault system may trade off slip over time, with mechanically complementary faults displaying alternating fast- and slow periods. Each of these periods spans multiple seismic cycles, and typically involves ~20-25m of slip. This suggests that the relative strength (or tendency to slip) of individual faults varies, over time and displacement scales larger than those of individual seismic cycles. The mechanisms responsible for these strength variations must: affect rocks in the strongest portion of the fault (the brittle-ductile transition) as this likely controls the overall slip rate of the fault; be reversible (or able to be counteracted) on a cyclical basis; provide a negative feedback that operates to change the fault from its current state; and have a measurable effect on fault strength over a time or length scale that corresponds to the observed fast and slow periods of fault slip. In this paper, we systematically explore 19 potentially weakening and 11 potential strengthening mechanisms and evaluate them in light of these criteria. This analysis reveals a relatively small subset of mechanisms that could account for the observed behavior, leading us to suggest a possible model for fault strength evolution.

Satellite land surface temperature for mapping the structurally controlled geothermal anomalies in the Cretaceous rift, South Egypt

ABSTRACT Exploration of new geothermal systems often requires regional-scale investigation. Satellite Land Surface Temperature (LST) products are essential in geothermal anomaly identification and mapping. In this study, seven thermal anomalies covering Egypt were observed using the Sentinel-3 LST images acquired in 2019 and confirmed using the 2020 LST images. In addition, the LST analysis reveals three new anomalies covering the southern part of Egypt (Kalabsha, Natash, and Wadi Allaqi), which are structurally controlled. Nuqra-Kharit-Natash is a good site for geothermal energy owing to the following reasons: 1) the high geothermal gradient beneath the Wadi Natash region (heat flow ~100 mW/m2); 2) the presence of many geothermal anomalies retrieved from the analyses of the Landsat-8 acquired in August 2018; 3) existence of surface geothermal manifestation at the western boundary of the basin includes warm springs and the tufa deposits. Intricate structural patterns, including NW-oriented normal faults, ENE-to-WNW-oriented right-lateral faults, and NNE-oriented sinistral strike-slip faults, characterise Wadi Natash. Wadi Natash LST anomaly shows a solid relation to fault trends. High values of LST are arranged along NW and NNE faults and recorded the peak at the intersection of two fault trends. Recent seismic activity along the NNE fault system enhances the permeability along this trend and its intersection with the NW-oriented fault.

Identification of combined sensor faults in structural health monitoring systems

Fault diagnosis (FD), comprising fault detection, isolation, identification and accommodation, enables structural health monitoring (SHM) systems to operate reliably by allowing timely rectification of sensor faults that may cause data corruption or loss. Although sensor fault identification is scarce in FD of SHM systems, recent FD methods have included fault identification assuming one sensor fault at a time. However, real-world SHM systems may include combined faults that simultaneously affect individual sensors. This paper presents a methodology for identifying combined sensor faults occurring simultaneously in individual sensors. To improve the quality of FD and comprehend the causes leading to sensor faults, the identification of combined sensor faults (ICSF) methodology is based on a formal classification of the types of combined sensor faults. Specifically, the ICSF methodology builds upon long short-term memory (LSTM) networks, i.e. a type of recurrent neural networks, used for classifying ‘sequences’, such as sets of acceleration measurements. The ICSF methodology is validated using real-world acceleration measurements from an SHM system installed on a bridge, demonstrating the capability of the LSTM networks in identifying combined sensor faults, thus improving the quality of FD in SHM systems. Future research aims to decentralize the ICSF methodology and to reformulate the classification models in a mathematical form with an explanation interface, using explainable artificial intelligence, for increased transparency.

Correction To: Photovoltaic system fault detection techniques: a review

Correction To: Photovoltaic system fault detection techniques: a review

Slip Rate for the Rose Canyon Fault through San Diego, California, Based on Analysis of GPS Data: Evidence for a Potential Rose Canyon–San Miguel-Vallecitos Fault Connection?

ABSTRACT The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half-space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5 mm/yr. Although limited in terms of near-fault benchmarks, we find an improved model fit using an asymmetrical elastic half-space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.