Complex Fault Research Articles

Advancing Fault Detection Efficiency in Wireless Power Transmission with Light GBM for Real-Time Detection Enhancement

This study introduces WirelessGridBoost, an innovative framework designed to revolutionize real-time fault detection in wireless electrical grids by harnessing the power of the LightGBM machine learning algorithm. Traditional fault detection systems in electrical grids often face challenges such as latency and scalability due to the intricate nature of grid operations and limitations in communication infrastructure. To overcome these challenges, WirelessGridBoost integrates LightGBM, a highly efficient gradient boosting decision tree algorithm, with wireless technology to facilitate advanced fault detection capabilities. Trained on historical sensor data, the LightGBM model demonstrates exceptional proficiency in discerning complex fault patterns inherent in electrical grid operations. Deployed across strategically positioned wireless nodes within the grid, WirelessGridBoost enables prompt identification of anomalies in real-time. Extensive simulations and experiments conducted on a real-world grid testbed validate the effectiveness of WirelessGridBoost, achieving a fault detection accuracy of 96.80% and reducing latency by 38% compared to conventional methods. This research presents a promising avenue for enhancing fault detection efficiency in wireless electrical grids through the innovative WirelessGridBoost framework.

A Fault Identification Method of Hybrid HVDC System Based on Wavelet Packet Energy Spectrum and CNN

Aiming at the shortcomings of traditional fault identification methods in fault information acquisition, In the scenario of hybrid HVDC transmission system, a new fault identification method is proposed by using wavelet packet energy spectrum and convolutional neural network (CNN), which effectively solves the problem of complex fault feature extraction of hybrid HVDC transmission system. This method effectively improves the accuracy of fault identification. Firstly, tThe frequency-domain characteristics of the fault transient signal are extracted by wavelet packet transform, and the feature differences are reflected in the form of energy spectrum. Secondly, according to the extracted energy feature information, the order of fault line and fault type is identified by CNN. Finally, through example verification and algorithm comparison, it is concluded that, the mentioned model has a strong ability to identify faults, and has strong anti-noise interference and tolerance to transition resistance.

Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array.

The power transformer is one of the most crucial pieces of high-voltage equipment in the power system, and its stable operation is crucial to the reliability of power transmission. Partial discharge (PD) is a key factor leading to the degradation and failure of the insulation performance of power transformers. Therefore, online monitoring of partial discharge can not only obtain real-time information on the operating status of the equipment but also effectively predict the remaining service life of the transformer. Meanwhile, accurate localization of partial discharge sources can assist maintenance personnel in developing more precise and efficient maintenance plans, ensuring the stable operation of the power system. Dual partial discharge sources in transformer oil represent a more complex fault type, and piezoelectric transducers installed outside the transformer oil tank often fail to accurately capture such discharge waveforms. Additionally, the sensitivity of the built-in F-P sensors can decrease when installed deep within the oil tank due to the influence of oil pressure on its sensing diaphragm, resulting in an inability to accurately detect dual partial discharge sources in transformer oil. To address the impact of oil pressure on sensor sensitivity and achieve the detection of dual partial discharge sources under high-voltage conditions in transformers, this paper proposes an optical fiber ultrasonic sensor with a pressure-balancing structure. This sensor can adapt to changes in oil pressure environments inside transformers, has strong electromagnetic interference resistance, and can be installed deep within the oil tank to detect dual partial discharge sources. In this study, a dual PD detection system based on this sensor array is developed, employing a cross-positioning algorithm to achieve detection and localization of dual partial discharge sources in transformer oil. When applied to a 35 kV single-phase transformer for dual partial discharge source detection in different regions, the sensor array exhibits good sensitivity under high oil pressure conditions, enabling the detection and localization of dual partial discharge sources in oil and winding interturn without obstruction. For fault regions with obstructions, such as within the oil channel of the transformer winding, the sensor exhibits the capability to detect the discharge waveform stemming from dual partial discharge sources. Overall, the sensor demonstrates good sensitivity and directional clarity, providing effective detection of dual PD sources generated inside transformers.

New constraints from in-situ U-Pb ages and fluid inclusions of calcite cement and structural analysis on multiple stages of strike-slip fault activities in the northern Tarim Basin, NW China

Dating the activity of complex faults and fracture systems is crucial for creating reliable geological models for various tectonics and subsurface engineering applications. This study presents a comprehensive study integrating U–Pb fracture cement dating, trace elements, and fluid inclusion temperature analysis with seismic analysis of faults, fault diagenesis, and burial history studies to better constrain faulting and fracture activities in an intra-cratonic strike-slip fault system in the northern Tarim Basin. Seismic profiles indicate at least three distinct phases of fault activity corresponding to the Middle Ordovician, Permian, and Paleogene periods. Fracture cementation and crosscutting relationships corroborate the identification of three fracturing stages. U–Pb dating of fractured cement has widely detected Middle Ordovician and Early Permian age intervals. Fluid inclusion homogenization temperatures from the fractured cements, ranging across < 50 °C, 70–130 °C, and 150–180 °C, correspond to three episodes of rapid subsidence during the Ordovician, Permian, and Neogene, respectively. These results suggest three phases of fault/fracture reactivation in the Middle Ordovician (prior to 470 Ma), Early Permian (prior to 295 Ma), and Cenozoic. The fault/fracture reactivation in the Ordovician is closely related to the regional tectonic transition from extension to compression, while fault and fracture reactivation in the Early Permian may be related to hydrothermal activity associated with large-scale igneous province and oil emplacement. Fault/fracture activity in the Cenozoic may be related to a reduction in subsidence, gradual reduction of geothermal gradients, and massive oil emplacement. This research underscores the significance of integrating geochemical and subsurface datasets for accurately determining the timing of faulting and fracturing in sedimentary basins.

Tectono‐sedimentary evolution of high‐displacement crustal‐scale normal faults and basement highs on rifted margins: Klakk Fault Complex and Frøya High, Mid‐Norwegian Margin

AbstractCrustal‐scale high‐displacement (&gt;10 km) normal faults are not captured in existing tectono‐sedimentary models of rift basins. We used 2D and 3D seismic reflection and well data to perform a structural and source‐to‐sink analysis of the southern part of the Klakk Fault Complex and the western part of the Vingleia Fault Complex, Mid‐Norwegian rifted margin. The north–south trending Klakk Fault Complex has a zig‐zag to sinuous plan‐view geometry, forming a series of structural recesses and salients along strike. In cross‐section, the fault complex has a listric to convex‐up or low‐angle planar geometry with displacements above 20 km. This fault complex exhumed basement highs, the Frøya High and Sklinna Ridge, in its footwall and created a series of supradetachment basins, for example, the Rås Basin, in its hanging wall. In contrast, the northeast‐southwest trending Vingleia Fault Complex has a zig‐zag geometry in plan view and planar to listric geometry in cross‐section and displacement of up to 5 km. This fault has the Frøya High in its footwall and the southern Halten Terrace in its hanging wall. Restoration of selected structural cross‐sections shows a prominent fault‐parallel ridge, up to 15 km east of the Klakk Fault Complex interpreted as a palaeodrainage divide. This divide separates steep drainages developed along the west‐dipping footwall scarp to the Klakk Fault Complex, from broader, gentler east‐dipping drainages up to ca. 10 km long developed on a back‐tilted dip slopes along the eastern side of the Frøya High and Sklinna Ridge. Progressive headward erosion of active flank catchments was enhanced around topographically elevated structural salients to the point of capturing previous dip‐slope‐directed drainages during the earliest Cretaceous. A network of submarine canyons develop down‐dip of the drainage catchments along the Klakk Fault Complex scarp, whose geometries and length are controlled by their location with respect to the structural salients or recesses, and the presence of fault terraces. The middle Jurassic‐earliest Cretaceous synrift deposits form two seismic sequences that are filled with five distinctive seismic facies that record the evolution from a linked normal fault during rift climax to a high‐displacement stage. During the high displacement stage, exhumed local continental core complexes formed structural salients, separated along strike by structural recesses at the heads of supradetachment basins. Key elements of the high‐displacement fault stage include (i) the development of structural salients at sites of rift climax displacement maxima, (ii) development of supradetachment basins in rift climax displacement minima and (iii) migration of major depocentres away from the centre of rift climax fault segments. We synthesise these observations into a generic tectono‐sedimentary model for high‐displacement faults.

From nappe stacking to strike-slip deformation: Alpine structural overprints refined by cave and karst geology in the Danubian thin-skinned units (Southern Carpathians, Romania)

Caves are ideal environments for preserving quantifiable deformational indicators in orogenic areas, as they are conditioned by regional tectonics. The caves and karst of Isverna, developed in the Barremian-Aptian limestones of the Danubian sedimentary nappes (Southern Carpathians, SW Romania), expose formerly undetected evidence of compressional tectonics, overlapping older structures related to décollement and deformation of the underlying Turonian-Senonian tectonic mélange. The Danubian domain (the distal part of the Moesian Platform) was incorporated into the Carpathian Orogen during the Late Cretaceous subduction of the Ceahlău–Severin Ocean and collision with the continental Dacia mega-unit. Subsequent Eocene–Oligocene orogen–parallel extension led to the development of a metamorphic core complex and detachment faults, constructing a complicated arcuate fault system around the Moesian Platform during the Late Miocene strike-slip deformation. The integrated analysis of structural, kinematic, and geomorphological data indicates a connection between the strike-slip deformation and the subsequent shortening, exhumation and surface exposure of Cerna Nappe within the Isverna shear zone. Four main evolutionary stages of the Danubian thin-skinned units in the central Mehedinți Mountains were distinguished from cave and karst geology, and illustrated in a detailed 3D model: i) Initial décollement and mélange deformation during the Alpine nappe stacking; ii) Extensional décollement toward SE; iii) Dextral shearing and WNW-ESE contraction; iv) Karstification and cave development. Most structural and kinematic markers recorded within the limestones of the Cerna Nappe date from stage (iii), whereas older structures were better preserved in the tectonic mélange of the Lainici Nappe. The resulting model could be further integrated into the polyphase tectonic evolution of the Southern Carpathians and their relation with the Moesian Platform. This study demonstrates the utility of caves and karst for constraining the chronology of tectonic deformations in complex structural systems and for reconstructing more refined conceptual 3D models.

Seismicity in the Weiyuan-Rongxian area, Sichuan basin, SW China

The Weiyuan-Rongxian shale gas field in the Sichuan basin, China, has experienced numerous earthquakes in recent years, causing significant casualties and property loss. To investigate the spatial–temporal evolution of seismicity and seismic fault structures, in this study, we first utilize a deep-learning-based picking algorithm –(PhaseNet) to identify seismic phases from raw seismic data between March 2019 and October 2020, and then employ a Rapid Earthquake Association and Location technique (REAL) to associate these seismic picks. Finally, the VELEST and GrowClust methods are performed to build a high-precision earthquake catalog containing 18,912 earthquakes. Our results reveal that the spatial–temporal distribution of earthquake swarms indicates a complex fault system. In the northern part of Weidong block (R1), the earthquakes illuminate a shovel-shaped structure that the dip angle of the fault plane gradually decreases with depth. In the south of Weidong block (R2), the natural fractures with dip angles of about 80° control the distribution pattern of earthquakes. In the Weixi block (R3), the Molin fault and basement fault form a typical structural wedge that bounds a triangular or wedge-shaped fault block. The majority of earthquakes located below the buried depth of the shale gas and spatio-temporal correlations between seismicity and industry operations both suggest that they are probably induced by hydraulic fracturing. The migration front of the earthquakes can be modeled by fluid diffusion with the diffusivity D between 0.2 m2/s and 3.5 m2/s. The Ms 5.2 earthquake occurring on 18 December 2019 is located in a positive ∼10 kpa Coulomb failure stress area generated by the 8 September 2019, Ms 5.4 earthquake, reaching the typical static triggering threshold. Therefore, in addition to fluid diffusion, the stress perturbation caused by previous seismic ruptures may be considered as another factor of earthquakes occurring in the Weiyuan-Rongxian. Our study provides evidences for better understanding the seismicity characteristics, seismogenic mechanism, and fault structure in Weiyuan-Rongxian shale gas field.

The 17 January 1994 Northridge, California, Earthquake: A Retrospective Analysis

Abstract The 17 January 1994 Northridge, California, earthquake was a watershed event with far-reaching societal and scientific impacts. The earthquake, which occurred in the early days of both broadband seismic networks and the Internet, spurred advances in seismic monitoring, real-time systems, and development of data products. Motivated by the 30th anniversary of the earthquake, we present a brief retrospective of the earthquake and its impact, and reconsider both ground motions and the aftershock distribution using modern tools and the best-available data. With improvements in instrumentation and analysis methodology, recent earthquakes continue to reveal the increasing complexity of ground motions, fault systems, and earthquake ruptures. Even in the absence of data from state-of-the-art instrumentation, a retrospective consideration of ground-motion data from the Northridge earthquake reveals complexities beyond what could be characterized (and modeled) 30 yr ago. Aftershock relocations for both the 1971 Sylmar and 1994 Northridge earthquakes also reveal an updated view of fault complexity. Our study does provide a cautionary tale regarding legacy data sets and research results that are not easily accessible, which can result in discrepancies between catalog data and products from the best available science. We also briefly describe outreach products produced as a part of the anniversary commemoration.

Strong controlling effect of stress evolution on the 2022 Ms5.0 Honghe earthquake sequence

Understanding stress evolution patterns as a response to earthquake ruptures at geologically complex tectonic faults is vital because of the role of fault geometry as a source for the stress evolutionary constraints. Here, we analyze the 2022 Ms5.0 Honghe earthquake sequence and calculate the tectonic stress distribution of the two Ms. ≥ 3.5 earthquakes in this sequence. Results indicate that the focal mechanism type of the sequence obtained corresponds to strike-slip motion with an ESE-oriented strike and a steeply dipping NE-oriented nodal plane. The focal region is subjected to NNW-oriented horizontal compression and ENE-oriented horizontal tension. We find that the adjacent Ailaoshan fault constituted the major seismogenic fault of the mainshock and the regional stress field exerted a strong controlling effect on the associated postseismic events. Our results suggest that the stabilization of tectonic faults may help to enhance the effects of stress accumulation on the occurrence of medium-to-strong earthquakes.

Complex fault geometry and slip distribution of 2022 Mw 6.6 Menyuan, China, earthquake from joint inversion of GNSS and InSAR observations

Complex fault geometry and slip distribution of 2022 Mw 6.6 Menyuan, China, earthquake from joint inversion of GNSS and InSAR observations

Complex Segment Linkage Along the Sevier Normal Fault, Southwestern Utah

Abstract Major normal fault systems are composed of segments that link as displacement accumulates, with linkage zone characteristics that reveal fault zone evolution. The steeply west-dipping Sevier fault zone in southwestern Utah, displays a complex fault network that developed between two long (&amp;gt;10 km), en echelon segments near the town of Orderville. Geologic map data and cross-sections of the transfer zone between the Mt. Carmel segment in the south and the Spencer Bench segment in the north reveal more than ten normal faults and four relay ramps displaying a range of geometries, including two relay ramps that display ramp-parallel folds. We suggest that transfer zone deformation was initially dominated by faults subparallel to the primary segments with later cross-faults that hard-linked these faults across most of the transfer zone. When the transfer zone was a soft-linked system, a displacement deficit likely existed relative to fault segments to the north and south. This early fault configuration would have reduced the efficiency of slip propagation associated with major earthquakes (&amp;gt;M7.0). In contrast, the present-day transfer zone, with a complex but hard-linked fault network, shows displacements that transition smoothly from the higher displacement (~800 m) southern segment to the lower displacement (~400 m) northern segment. That transition, combined with extensional strain within the zone, suggests that the Orderville fault network would be unlikely to impede propagation associated with future major earthquakes. The kinematic model of fault evolution presented here has implications for those investigating geothermal energy potential, groundwater flow, natural gas and oil reservoirs, mineral deposit formation, or seismic hazards.

A Novel Method for Rolling Bearing Fault Diagnosis Based on Gramian Angular Field and CNN-ViT.

Fault diagnosis is one of the important applications of edge computing in the Industrial Internet of Things (IIoT). To address the issue that traditional fault diagnosis methods often struggle to effectively extract fault features, this paper proposes a novel rolling bearing fault diagnosis method that integrates Gramian Angular Field (GAF), Convolutional Neural Network (CNN), and Vision Transformer (ViT). First, GAF is used to convert one-dimensional vibration signals from sensors into two-dimensional images, effectively retaining the fault features of the vibration signal. Then, the CNN branch is used to extract the local features of the image, which are combined with the global features extracted by the ViT branch to diagnose the bearing fault. The effectiveness of this method is validated with two datasets. Experimental results show that the proposed method achieves average accuracies of 99.79% and 99.63% on the CWRU and XJTU-SY rolling bearing fault datasets, respectively. Compared with several widely used fault diagnosis methods, the proposed method achieves higher accuracy for different fault classifications, providing reliable technical support for performing complex fault diagnosis on edge devices.

Lithological control of the active Mejillones fault from Triassic to Quaternary, northern Chile

Understanding the lithological control of crustal faults near cities is important for assessing the seismic hazard and characterising complex fault systems. We studied the Mejillones Fault (MF), located near one of the strategic ports in northern Chile. The MF is an active geological fault that extends 40 km in the N-S direction and is part of an extensive complex system of structures known as the Atacama Fault System (AFS). We built an S-wave tomography model using seismic ambient noise data that was recorded continuously in a dense network of stations from 2013 to 2015. The tomographic maps exhibited velocity anomalies that correlate with surface geology. We found lower velocities in the western part of the MF than in the eastern zone, with a shear wave velocity (Vs) of about 2.4 km/s, associated to fractured metamorphic rocks (Triassic) and marine sediments (Neogene-Quaternary). Higher velocities (Vs > 3.0 km/s) in the eastern part of the fault are related to igneous rocks from the Upper Jurassic. The difference in velocities between the western and eastern zones of the MF remained persistent in depth. The potential depth of the MF could be >5 km and delimits the boundary between 2 different geological zones. Intermediate Vs (∼2.8 km/s) at −23.25°, observed up to 4 km depth, can be associated with andesitic rocks deposited in an intra-arc basin (Upper Triassic) and accommodated by the MF over the last ∼200 Myr, evidencing the activity of this fault from Triassic to Quaternary.

High‐Frequency Ground Motions of Earthquakes Correlate With Fault Network Complexity

AbstractUnderstanding the generation of damaging, high‐frequency ground motions during earthquakes is essential both for fundamental science and for effective hazard preparation. Various theories exist regarding the origin of high‐frequency ground motions, including the standard paradigm linked to slip heterogeneity on the rupture plane, and alternative perspectives associated with fault complexity. To assess these competing hypotheses, we measure ground motion amplitudes in different frequency bands for 3 ≤ M ≤ 5.8 earthquakes in Southern California and compare them to empirical ground motion models. We utilize a Bayesian inference technique called the Integrated Nested Laplace Approximation (INLA) to identify earthquake source regions that produce higher or lower ground motions than expected. Our analysis reveals a strong correlation between fault complexity measurements and the high‐frequency ground motion event terms identified by INLA. These findings suggest that earthquakes on complex faults (or fault networks) lead to stronger‐than‐expected ground motions at high frequencies.

A multi-node self-powered fault detection system by triboelectric-electromagnetic nanosensors for smart transportation

The harnessing of vibrational energy is becoming increasingly pivotal in the development of intelligent rail transit systems. The integration of emerging technologies such as triboelectric nanogenerators (TENGs), electromagnetic generators (EMGs), or hybrid generators has become crucial for fault detection and energy harvesting in rail transit. This paper introduces a self-powered fault detection system (SPFDS). SPFDS combines multiple compact rotating Triboelectric-Electromagnetic Nanosensor (TENS) nodes with a deep learning-based diagnostic module to transform vibrational energy generated during train operations into electrical power and accurately identifies five distinct train bogie fault conditions. Simulations and experiments have shown that the TENS nodes, with a root mean square power of 0.21 W and a power density of 1595.7 W/m³, can efficiently detect various bogie faults. Additionally, their power output is adequate to support commercial sensors and Bluetooth modules. Through hyperparameter optimization, the diagnostic module utilizing multi-TENS nodes achieves an average diagnostic accuracy of 99.38 % for the five fault modes of freight train bogies. Implementing multiple TENS nodes in SPFDS enhances fault detection accuracy by an average of 32 % compared to a single TENS node, with a peak increase of 128 %. The multi-node TENS configuration and SPFDS's self-powered detection capabilities represent an innovative approach to complex fault detection, significantly contributing to the advancement of vibration energy harvesting and the development of distributed self-powered sensor network technologies for smart transportation.

A computational topology-based method for extracting fault surfaces

Fault surface extraction is a crucial step in seismic interpretation, which can help structural interpretation and structural modeling. A key focus of fault surface extraction research is to extract fault surfaces in their entirety as much as possible, rather than just in fault segments, which is more challenging in some complex fault situations. To address this challenge, we develop a fault surface extraction method based on computational topology to extract fault surfaces in their entirety as much as possible from a fault attribute and effectively handle some complex fault situations, such as intersecting faults. From a given seed point on the target fault, we use the idea of regional growth to search for high-confidence points on the target fault, called fault control points, under the constraints of the fault attribute and the calculated fault orientations. Through these fault control points, we extract the fault boundary and process the fault attribute so that only the target fault is included. Furthermore, we use an operation in computational topology called collapse to extract the target fault from the processed fault attribute using the fault boundary as a constraint. By incorporating fault orientation information and using a relatively large search distance during the control point search, our method enables the integration of segmented faults and facilitates the handling of complex fault situations such as intersecting faults. The collapse operation ensures that the extracted fault surfaces align with the fault attribute, correspond to the actual fault locations in seismic data, and enhance fault continuity. In addition, we develop an automatic method for picking seed points to realize the extraction of all the faults in the research data. We test our method on several field data sets and the experimental results demonstrate its effectiveness. In some complex fault situations, such as intersecting faults, our method performs well and indicates a significant improvement over the compared method.

A Multiplex Rupture Sequence Under Complex Fault Network Due To Preceding Earthquake Swarms During the 2024 Mw 7.5 Noto Peninsula, Japan, Earthquake

AbstractA devastating earthquake with moment magnitude 7.5 occurred in the Noto Peninsula in central Japan on 1 January 2024. We estimate the rupture evolution of this earthquake from teleseismic P‐wave data using the potency‐density tensor inversion method, which provides information on the spatiotemporal slip distribution including fault orientations. The results show a long and quiet initial rupture phase that overlaps with regions of preceding earthquake swarms and associated aseismic deformation. The following three major rupture episodes evolve on segmented, differently oriented faults bounded by the initial rupture region. The irregular initial rupture process followed by the multi‐scale rupture growth is considered to be controlled by the preceding seismic and aseismic processes and the geometric complexity of the fault system. Such a discrete rupture scenario, including the triggering of an isolated fault rupture, adds critical inputs on the assessment of strong ground motion and associated damages for future earthquakes.

Neuro-Fuzzy Framework for Fault Prediction in Electrical Machines via Vibration Analysis

The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolutionizing industrial processes. However, despite the push towards predictive maintenance, there still is a significant gap in fault prediction algorithms for electrical machines. This paper proposes a signal spectrum-based machine learning approach for fault prediction, specifically focusing on bearing faults. This study compares the effectiveness of traditional neural network algorithms with a novel approach integrating fuzzy logic. Through extensive experimentation and analysis of vibration spectra from various mechanical faults in bearings, it is demonstrated that the fuzzy-neuro network model outperforms traditional neural networks, achieving a validation accuracy of 99.40% compared to 94.34%. Incorporating fuzzy logic within the neural network framework offers advantages in handling complex fault combinations, showing promise for applications requiring higher accuracy in fault detection. While initial results are encouraging, further validation with more complex fault scenarios and additional fuzzy layers is recommended to fully explore the potential of fuzzy-neuro networks in fault prediction for electrical machines.

The 2022 Har Lake earthquake sequence highlights a complex fault system in the western Qilian Shan, northeastern Tibetan Plateau

SUMMARY The 2022 Har Lake earthquake sequence, which began in 2022 January and lasted for ∼70 d, jolted the Har Lake area, which is located in the western Qilian Shan, northeastern Tibetan Plateau. Two Mw &amp;gt; 5.5 earthquakes occurred during the earthquake sequence, among which the March 25 Mw 5.8 event is considered the largest event recorded in the area. However, determining the seismogenic faults of the earthquake sequence, as well as the detailed rupture features, is difficult due to the lack of geological data and near-field seismological observations. In this study, we use Sentinel-1 synthetic aperture radar (SAR) data to obtain the coseismic deformation field, identify possible ruptured faults and associated fault geometries, and further estimate detailed coseismic slip models of the two Mw &amp;gt; 5.5 earthquakes. The results show that the January 23 Mw 5.6 earthquake (Earthquake A) occurred on a N15° W-trending dextral-slip fault with a dip angle of ∼61°. For the March 25 Mw 5.8 earthquake (Earthquake B), the interferometric synthetic aperture radar (InSAR) data can be described by either an ∼N–S-trending dextral-slip fault or an ∼E–W-trending sinistral-slip fault. The ∼N–S-trending fault better describes the aftershock distribution, while the ∼E–W-trending model is more consistent with the regional geological setting. We suggest that the complex coseismic ruptures in the multiple-fault system are driven by widespread NE–SW-trending compression in the western Qilian Shan. This study demonstrates the importance of integrating geodetic and seismological observations to capture the full complexity of moderate earthquakes and further suggests potential seismic hazards in the Har Lake area.

Synthesis of Current Seismicity and Tectonics Along the 1857 Mw7.9 Fort Tejon Earthquake Rupture and the Southernmost San Andreas Fault, California, USA

AbstractWe evaluate seismicity and tectonics along the San Andreas Fault (SAF) in southern California to elucidate ongoing near‐field crustal deformation processes. The principal slip surfaces (PSSs) or the fault core that accommodate major earthquakes, form the boundary between the tectonic plates. We analyze seismicity catalogs extending back to 1857, 1932, and 1981 with progressively improved magnitude of completeness and spatial resolution. The 1857 to present statewide catalog that is complete at M5.5+ documents minimal aftershock activity for the Mw7.9 1857 and 1906 Mw7.8 San Francisco earthquakes. The higher quality 1932 and 1981 catalogs show that the PSSs (the rupture zone) of the 1857 Mw7.9 Fort Tejon earthquake exhibits remarkable seismic quiescence both in the core and in the adjacent extended‐damage zone. Further south, the fault core is still aseismic but the shape of the SAF is more complex, and the rate of adjacent seismicity is much higher. This fault complexity and the seismicity rate are larger the more the strike of the SAF deviates from the Pacific plate velocity‐vector direction. The focal mechanisms of the SAF adjacent earthquakes are also heterogeneous and rarely have strikes and dips that are consistent with slip on the nearby PSSs. We infer that the southern SAF is locked, and a lack of seismicity at the core of the fault may be a standard feature of faults that almost exclusively accommodate high‐slip rates by producing major earthquakes. Correspondingly future aftershock sequences of major earthquakes on the southern SAF will likely have below average aftershock productivity.