Fault System Research Articles

Poroelastic effects on rupture propagation across fault stepovers

The role of poroelasticity in influencing the frequency of ruptures jumping through strike-slip stepovers remains unclear. To understand how poroelastic effects govern long-term rupture behavior in strike-slip fault systems with stepovers, we conduct earthquake sequence simulations incorporating undrained pore pressure responses across the full spectrum of Skempton's coefficient. Our findings reveal that Skempton's coefficient significantly affects the effective normal stress, which can either cause fault clamping or unclamping, and ultimately influences rupture propagation across fault stepovers. The likelihood of rupture jumping is predominantly determined by Skempton's coefficient and the width of the stepover, with Skempton's coefficient showing an approximately linear relationship to the critical jumpable step size. Specifically, a higher Skempton's coefficient facilitates rupture jumping across fault segments, even over larger stepover distances. Analytical solutions involving dislocation and Skempton's coefficient provide practical methods for evaluating pore pressure changes and associated seismic hazards near fault stepovers. Our statistical analysis identifies a critical jumpable width of 4.4–5.1 km due to static stress transfer, assuming a typical range of Skempton's coefficient for compressional stepovers, beyond which ruptures are unlikely to propagate. This study underscores the potential of using physics-based earthquake sequence models to reflect statistical fault rupture behaviors. Given that multi-segment earthquake ruptures present challenges in assessing maximum rupture lengths, our findings offer crucial insights into the role of poroelastic effects and the conditions that facilitate or limit rupture propagation across fault stepovers.

D-InSAR-Based Analysis of Slip Distribution and Coulomb Stress Implications from the 2024 Mw 7.01 Wushi Earthquake

On 23 January 2024, an Mw 7.01 earthquake struck the Wushi County, Xinjiang Uygur Autonomous Region, China. The occurrence of this earthquake provides an opportunity to gain a deeper understanding of the rupture behavior and tectonic activity of the fault system in the Tianshan seismic belt. The coseismic deformation field of the Wushi earthquake was derived from Sentinel-1A ascending and descending track data using Differential Interferometric Synthetic Aperture Radar (D-InSAR) technology. The findings reveal a maximum line-of-sight (LOS) displacement of 81.1 cm in the uplift direction and 16 cm in subsidence. Source parameters were determined using an elastic half-space dislocation model. The slip distribution on the fault plane for the Mw 7.01 Wushi earthquake was further refined through a coseismic slip model, and Coulomb stress changes on nearby faults were calculated to evaluate seismic hazards in surrounding areas. Results indicate that the coseismic rupture in the Mw 7.01 Wushi earthquake sequence was mainly characterized by left-lateral strike-slip motion. The peak fault slip was 3.2 m, with a strike of 228.34° and a dip of 61.80°, concentrated primarily at depths between 5 and 25 km. The focal depth is 13 km. This is consistent with findings reported by organizations like the United States Geological Survey (USGS). The fault rupture extended to the surface, consistent with field investigations by the Xinjiang Uygur Autonomous Region Earthquake Bureau. Coulomb stress results suggest that several fault zones, including the Kuokesale, Dashixia, Piqiang North, Karaitike, southeastern sections of the Wensu, northwestern sections of the Tuoergan, and the Maidan-Sayram Fault Zone, are within regions of stress loading. These areas show an increased risk of future seismic activity and warrant close monitoring.

Fault Diagnosis of Aircraft Hydraulic Pipeline Clamps Based on Improved KPCA and WOA–KELM

Due to the complexity and diversity of aviation hydraulic pipeline systems, there has been a lack of qualitative formulas or characteristic indicators to describe clamp failures within these systems. In this paper, based on the data-driven idea, an improved KPCA-based feature extraction method is proposed and combined with the optimized KELM for fault diagnosis and condition monitoring of aviation hydraulic line clamps. Firstly, the kernel parameters of KPCA are combined using polynomial and Gaussian kernels based on their proportional weights. Secondly, a GA–PSO (Genetic Algorithm–Particle Swarm Optimization) hybrid algorithm is employed to optimize the kernel parameters, selecting 13 time-domain and 4 frequency-domain feature indicators to form the initial feature dataset, which is then subjected to dimensionality reduction using the improved KPCA. Finally, diagnosis is conducted using a KELM optimized by the whale optimization algorithm. The results indicate that, across multiple diagnostic trials, the average diagnostic accuracy can reach 99.99%, providing a feasible approach for the precise diagnosis of clamp faults in aviation hydraulic pipeline systems.

Probabilistic fault displacement Hazard analysis in an extensional setting: Application to a strategic Dam and methodological implications

We present a Probabilistic Fault Displacement Hazard Analysis (PFDHA) for a strategic dam located in the Upper Tiber Valley (Northern Apennines of Italy) claimed to be sited on a supposed capable fault (Montedoglio fault). We verify the seismic capability of the Montedoglio fault through detailed geological and geophysical analyses. We find no evidence for considering the Montedoglio fault as an active and capable structure, the fault being constituted by a system of discontinuous parallel faults, apparently inactive since more than 56 ± 3 ka, and likely unable to nucleate strong surface rupturing earthquakes. Since the dam lies on the hanging wall of the closest major active fault of the area (Anghiari normal fault, ∼1.5 km away), we investigate the likelihood of having distributed faulting at the dam's site in case of a strong surface-rupturing earthquake occurring on the Anghiari fault. We apply a probabilistic approach to obtain hazard curves of exceedance of vertical displacement at the dam's site for different rupture scenarios. We show that the mean hazard curve is always below an annual frequency of exceedance of 1 × 10−5, corresponding to displacement values below 1 cm over 100,000 years of return period. The study highlights several weaknesses and uncertainties in using PFDHA with state-of-the-art models, suggesting the need for improvements to enhance their applicability in earthquake engineering geology practice.

Health monitoring of automotive clutch system through feature fusion and application of tree-based classifiers

Clutch systems are crucial components of automotive systems, essential for transferring engine power to the wheels through gear shifts. A failed clutch can halt gear shifts and power transmission, rendering a vehicle immobile. Effective fault diagnosis is vital for ensuring reliability, preventing breakdowns, and addressing root causes promptly. Consequently, condition monitoring of the clutch is essential for maintaining system reliability and minimizing unwanted breakdowns. This paper presents an innovative condition-monitoring technique derived from vibration analysis to detect faults in the clutch system. The study involves extracting statistical, histogram, and autoregressive moving average features from acquired vibration signals. The J48 decision tree algorithm is utilized to select the most significant features, which are then classified using tree-based classifiers across three load conditions (no load, 5 kg, and 10 kg) and six clutch conditions. The experimental results demonstrate that the feature fusion strategy significantly enhances classification accuracy. The obtained results state that the classification accuracies for no load, 5 kg load, and 10 kg load were 98.33%, 100.00%, and 99.16%, respectively, while applying feature fusion strategies. This study highlights the effectiveness of feature fusion in improving fault diagnosis accuracy for clutch systems, presenting a robust method for real-time condition monitoring in automotive applications.

Statistical and source characterization of the 2023 Kahramanmaraş Türkiye earthquake sequence

AbstractWe studied seismic features of the 2023 Kahramanmaraş Türkiye earthquake sequence by analyzing the spatiotemporal behavior of the b- and -p values and source characteristics of the mainshocks. We complemented our study by determining the regional stress field. The b-values in the region varied from 0.45 to 1.15. We observed a slight b-value decrease (Δb≈0.2) months before the two mainshocks. Our results exhibited complex b-value patterns on the fault planes and regular aftershock productivity rates (1.14 < p < 1.25). We compare static stress drop estimates derived from effective fault dimensions to those of finite-fault dimensions. Total effective stress drops (the sum of the stress drops of all fault segments) for the earthquake doublet were almost identical (~ 2.05 MPa), while those from finite-fault dimensions are somewhat lower (0.35 and 0.96 MPa). Based on a complete stress drop case, effective seismic efficiency was 0.65 and 0.43 for both mainshocks. The amount of partial stress drop was used to discriminate between different stress drop models. No clear model is discerned for the first mainshock, but a partial or even complete stress drop, assuming finite-fault dimensions, is supported by our measurements. Stress drop estimations derived from spectral analysis (25.46 and 34.39 MPa) agreed with global studies but larger than finite and effective fault estimates. Stress inversion results indicated that in the fault segments where the mainshocks occurred, the orientation of principal axes was consistent with a strike-slip regime. Conversely, the normal-faulting regime dominates adjacent areas of the main fault system.

Non-linear elasticity, earthquake triggering and seasonal hydrological forcing along the Irpinia fault, Southern Italy

Pump-probe experiments investigate the strain sensitivity of crustal elastic properties, showing nonlinear variations during the strain cycle. In the laboratory, pre-seismic reductions in seismic velocity indicate that asperity contacts within the fault zone begin to fail before the macroscopic frictional sliding. The recognition of such effects in natural seismic-cycles has been challenging. Here we exploit seasonal hydrological strains, performing a natural analogue to a quasi-static laboratory pump-probe experiment to investigate the nonlinear strain sensitivity of crustal rocks and its role in seismic failure along the tectonically-active Irpinia Fault System (Southern Italy). By comparing 14-years-long series of spring discharge, strain, seismic velocity variations and earthquakes rate, we find that seismicity peaks during maximum hydrological forcing and minimum seismic velocity. Seasonal strains of ~10−6 are required for both earthquake triggering and significant nonlinearity effects arising from modulus reduction. We suggest that, for faults in a critical state, cyclical softening may lead to failure and seasonal seismicity.

Self-organizing nervous systems for robot swarms.

We present the self-organizing nervous system (SoNS), a robot swarm architecture based on self-organized hierarchy. The SoNS approach enables robots to autonomously establish, maintain, and reconfigure dynamic multilevel system architectures. For example, a robot swarm consisting of n independent robots could transform into a single n-robot SoNS and then into several independent smaller SoNSs, where each SoNS uses a temporary and dynamic hierarchy. Leveraging the SoNS approach, we showed that sensing, actuation, and decision-making can be coordinated in a locally centralized way without sacrificing the benefits of scalability, flexibility, and fault tolerance, for which swarm robotics is usually studied. In several proof-of-concept robot missions-including binary decision-making and search and rescue-we demonstrated that the capabilities of the SoNS approach greatly advance the state of the art in swarm robotics. The missions were conducted with a real heterogeneous aerial-ground robot swarm, using a custom-developed quadrotor platform. We also demonstrated the scalability of the SoNS approach in swarms of up to 250 robots in a physics-based simulator and demonstrated several types of system fault tolerance in simulation and reality.

Consideration of the Transient Resistance at the Contact System Fault Location Based on the Emergency Mode Parameters

Consideration of the Transient Resistance at the Contact System Fault Location Based on the Emergency Mode Parameters

Investigation aspects of the geogenic radon potential on Bulgarian territory

Radon (222Rn) is a radioactive gas formed as a result of the radioactive decay of radium (226Ra). Radon is identified as one of the dominant sources of population exposure that could lead to lung cancer, accounting for between 3% and 14% of all lung cancers. Rocks in the Earth’s crust are a primary source of radon in the atmosphere. In this context, the geogenic radon potential (GRP) of a terrain refers to the probability of high radon concentrations being present in a building. The radon index is a concept used to characterize the geogenic potential of the terrain, providing the likelihood of radon concentration in a building, which is directly related to the influence of the Earth's surface. One approach to quantifying the radon index is based on multivariate cross-tabulation, involving two parameters: radon concentration in soil gas and the gas permeability of the earth layer, both measured at 80 cm below the surface. In Bulgaria, focused investigations on the connection between radon gas and geology, resp. on GRP have begun in the last five. As a result of the accumulated experience from field studies conducted so far related to the characterization of GRP, two important aspects have been identified that impact field measurements and the determination of radon gas in the soil, thus the methodology for calculating the radon index. The first aspect is connected with the theoretical and model-based investigations about possible state of soil saturation. The second aspect is about the GRP and fault systems in Sofia. This article makes an attempt to summarize all the studies concerning these two aspects and to suggest some further steps in the geogenic radon potential studies.

Adaptive Generalized Extended State Observer for a Single Phase PV Grid-connected System Operating Under the Sudanese-Sahelian Climate of Cameroon

Knowing the health of a system allows to guarante its efficiency and sustainability. The state observer is one of several techniques used by authors to estimate system state. This paper focuses on the problem of simultaneous states estimation of DC (Direct Current) and AC (Alternating Current) sides of a single-phase Photovoltaic (PV) grid-connected operating under the Sudanese-Sahelian climate of Cameroon. A generalized extended state observer (GESO) has been designed to simultaneously estimate the three states and the three disturbances of the system. A good estimation of the state and disturbances is achieved by the appropriate choice of the observer gain and the disturbance compensation gain resulting from the correct pole placement. The GESO robustness has been tested by varying the PV voltage and grid voltage. When there are no input fluctuations, the estimation errors of nominal states and disturbances converge to zero. The fluctuation in PV voltage resulting from partial shading has a significant impact on the boost converter current. The boost converter current varies proportionally with the drop in voltage due to partial shading from 55% to 59%. Under the grid voltage fluctuation, the boost converter current remains stable while the DC bus voltage and inverter current are significantly affected. The proposed GESO prove its robustness to perturbations from the PV array and grid side into the Single-Phase PV Grid-connected System. This paper contributes to the study of observers applied to the PV system and points the way to future work on diagnosing faults in PV systems operating in Cameroon's Sudanese-Sahelian climate.

Geology of the Golobar and Rumaceo faults, Basque-Cantabrian Pyrenees

ABSTRACT The lateral transition between different styles of deformation is crucial for understanding local-scale structures since it influences orogenic reconstructions at the crustal scale. This is especially important at the westernmost Basque-Cantabrian Pyrenees, where the transition from the thin-skinned Basque-Cantabrian Pyrenees to the thick-skinned Cantabrian Mountains remains a subject of debate. To address this, detailed geological mapping and proper fault characterisation are critical. This research focused on the surface characterisation of the Golobar Fault System, one of the faults located at the transition between the two styles of deformation. The results of this study include not only a detailed geological map of the Golobar Fault System but also its integration with neighbouring seismic sections and well data. This approach enhances the understanding of the deeper portions and lateral thickness variations, thereby providing a more comprehensive understanding of the Golobar area within the regional framework.

Operation status monitoring for 500 kV DC circuit breaker with internal failures and relative backup fault isolation schemes

As the primary protection and control device in direct current (DC) power systems, DC circuit breakers (DCBs) have complex structures and numerous components, making it prone to diversified internal failures. This paper explores an operation status monitoring method for DCBs, and relative backup fault isolation schemes and system recovery schemes are proposed to handle cases of DCBs with different internal failures. Contributions of this paper are: (1) An operation status monitoring method is proposed to reflect the failure degrees of DCB, categorizing the statuses of DCB into status-1 (normal), status-2 (minor failure) and status-3 (major failure). (2) According to the failure degrees of DCB, relative backup fault isolation and system recovery schemes are proposed to ensure the fault isolation scope is as small as possible and the system could recovery as fast as possible. Simulations are conducted in PSCAD/EMTDC for validation.

The certainty matrix for fault data and interpretations

This paper introduces an approach for expressing certainty in the analysis and interpretation of faults, using a modification of the risk matrix commonly used in risk assessment. The certainty matrix uses qualitative or semi-quantitative analyses of both the data used and an interpreted characteristic of individual faults or fault systems. These characteristics may include the existence of faults, the certainty of trace lengths, the age of faults, or the influence of faults on sub-surface fluid flow. This approach improves the ability to make justifiable interpretations and decisions about faults and fault-affected areas, including about issues relevant to geothermal energy exploration or the underground storage of radioactive waste. The use of this approach is illustrated using three faults from Somerset, UK.

Study of conveyor belt deviation detection based on improved YOLOv8 algorithm

Conveyor belt deviation is a commmon and severe type of fault in belt conveyor systems, often resulting in significant economic losses and potential environment pollution. Traditional detection methods have obvious limitations in fault localization precision and analysis accuracy, unable to meet the demands of efficient and real-time fault detection in complex industrial scenarios. To address these issues, this paper proposes an improved detection algorithm based on YOLOv8, aiming to achieve efficient and accurate detection during the operation of the belt. Firstly, an Enhanced Squeeze-and-Excitation (ESE) module is incorporated into C2f to boost feature extraction for rollers and belts. Secondly, the construction of the BiFPN_DoubleAttention module in the neck network enhances bidirectional feature fusion and attention mechanism, thereby improving multi-scale object localization accuracy under complex environments. Then, a Multi-Head Self-Attention (MHSA) mechanism is introduced in the head network, better capturing positional features of small roller targets and belt areas in various environments, thus enhancing detection performance. Finally, extensive experiments are conducted on a self-built dataset, achieving an accuracy of 98.1%, mAP0.5 of 99.0%, and a detection speed of 46 frames per second (FPS). This method effectively handles variations and disturbances in the conveyor belt transportation environment, meeting real-time diagnostic needs for belt misalignment in the industry.

Characteristics of the Albian Westgate Formation polygonal fault system

Borehole logs and 3-D seismic data are used to determine the characteristics of a polygonal fault system (PFS) in the Albian Westgate Formation in western Saskatchewan and eastern Alberta. The basal Upper Cretaceous formation is a siliceous siltstone to mudstone deposited in the Western Interior Seaway beneath the Great Plains of North America. The faulted zone is layerbound within the ~80 m thick Westgate Formation at Swift Current, Saskatchewan. Most faulting occurs along grabens approximately 125 m wide and 10 m deep. The grabens are interconnected, have random strike directions, and lengths up to 800 m. The continuous depositional environment of the Westgate Formation enables timing and compacted sediment thickness estimates for the PFS initiation. The faults appear to have started in ~15 m or more of compacted sediment within the first 270,000 years of the 1.5 Myr Westgate Formation interval. Interpreting the seismic dataset and accompanying wellbore data has resulted in a simple model that enables PFS identification using only wellbore data. Wellbore data interpretations from Alberta and Saskatchewan show the PFS identified at Swift Current may range across a large area. The implications for an extensive PFS identification in the Lower Cretaceous Westgate Formation and homotaxially equivalent Mowry Shale across central North America are discussed.

Multidisciplinary high resolution Geophysical Imaging of Pantano Ripa Rossa Segment of the Irpinia Fault (Southern Italy)

The Irpinia Fault, also known as the Monte Marzano Fault System, located in the Southern Apennines (Italy), is one of the most seismically active structures in the Mediterranean. It is the source of the 1980, Ms 6.9, multi-segment rupture earthquake that caused significant damage and nearly 3,000 casualties. Paleoseismological surveys indicate that this structure has generated at least four Mw ~ 7 surface-rupturing earthquakes in the past 2 ka. This paper presents a comprehensive, high-resolution geophysical investigation focused on the southernmost fault segment of the Monte Marzano Fault System, i.e., the Pantano-Ripa Rossa Fault, outcropping within the Pantano di San Gregorio Magno intramontane basin. The project, named TEst Site IRpinia fAult (TESIRA), was supported by the University of Napoli Federico II to study the near-surface structure of this intra-basin fault splay that repeatedly ruptured co-seismically in the past thousands of years. Our imaging approach included 2D and 3D electrical and seismic surveys, gravimetry, 3D FullWaver electrical tomography, drone-borne GPR and magnetic surveys, and CO2 soil flux assessment across the surface rupture. This multidisciplinary investigation improved our understanding of the basin shallow structure, providing an image of a rather complex subsurface fault and basin geometry. Seismic data suggest that fault activity at the Pantano segment of MMFS is characterized by a near-surface cumulative displacement greater than previous estimations, calling into question earlier assumptions about the timing of its activation. Despite some challenges with our drone-mounted survey equipment, the integrated dataset provides a comprehensive and reliable image of the subsurface structure. This work demonstrates the utility of developing an integrated approach at high-resolution geophysical imaging and interpretation of fault zones with weak morphological expressions.

Fault detection research on novel transfer learning-based method for cross-condition, cross-system and cross-operation in public building HVAC sensors

Transfer learning (TL) has the inspiring potential for artificial intelligence in heating, ventilation and air conditioning (HVAC) system with insufficient data labels. However, traditional TL-based methods are limited when applied across different conditions, systems, and operations.Unfortunately, public building HVAC systems encounter challenges related to data acquisition and richness, making it difficult to obtain data from similar HVAC systems conditions, scenarios and operations. It proposes a novel TL-based method that combines energy and mass balance constraint equation (EBCe) to diagnose the sensor faults in HVAC systems across different systems, conditions and operations.Firstly, it utilizes laboratory data as the source domain data and constructes EBCe based on the common physical laws of HVAC system to reduce the data differences between laboratory and public buildings. Then, an laplacian kernel domain-adaptive neural network (LkDaNN) is proposed to generalize more efficiently feature differences between the source domain data and target domain data. Finally, experiment analyzes the non-fault and four control-sensors fault under both cross-operation and non-cross operation conditions. The experimental results demonstrate that the EBCe-LkDaNN method achieves satisfactory fault detection and diagnosis (FDD) performance.The overall FDD accuracy of porposed method can reach 90.72 % and 88.64 % under different cross-operation, respectively. Practical application of the EBCe-LkDaNN strategy for HVAC sensor FDD are discussed at last.

Feature-weighted Random Forest with Boruta for Fault Diagnosis of Satellite Attitude Control Systems

The performance of random forest (RF) based satellite attitude control system (ACS) fault diagnosis methods is limited by uninformative features in high-dimensional data. To solve this problem, we proposed a feature-weighted random forest with Boruta (FWRFB) based fault diagnosis method is proposed for fault diagnosis of ACSs. Firstly, a Boruta feature selection algorithm is used to obtain a feature set and determine significant feature weights. Subsequently, a novel feature-weighted random forest (FWRF) algorithm is designed, which utilizes feature-weighted random sampling instead of simple random sampling to generate feature subsets in the RF. The FWRFB effectively utilizes the feature information while mitigating noise interference. Finally, a FWRFB-based diagnostic module is developed for online fault diagnosis of ACSs. The effectiveness of the proposed method is verified by the ACS data from a semi-physical simulation platform.

SIMULATION OF GEOELECTRIC STRUCTURE OF NORTHERN VIETNAM BY 3D INVERSION OF MAGNETOVARIATIONAL TIPPERS

This paper presents the results of constructing a model of the geoelectric structure of Northern Vietnam obtained by 3D inversion of magnetovariational tippers calculated for 13 values of variation periods in a range of 40–10047 s at 12 points where geomagnetic variations are recorded. Inversion is performed using the ModEM software, which makes it possible to construct a model in a 400 × 400 × 200-km spatial region with the center at the Hanoi Observatory (PHU). The resulting model of the geoelectric structure contains two regional blocks separated by the Red River fault region. A conductive block is located in the southwest of the fault region, and a high-resistivity block is located in the northeast. The boundary of the blocks, inclined to the northeast at an angle of about 45°, is visible to a depth of 150 km. The conductive block occupies the region between the Red River and Song Ma faults. Its western boundary could not be localized due to insufficient data in this region. Highly conductive local blocks stand out against the background of the regional conductive block. They usually gravitate toward the faults and are located in a depth range of 10–20 km with a slight inclination to the west on latitudinal profiles and to the south on meridional ones. In a depth range of 12–14 km, they merge into one highly conductive band extending in the northwest and marking the Red River fault system connected to the Gulf of Tonkin waters. Also, there are more massive highly conductive blocks in depth intervals of 20–50 km, which are often associated with upper crustal ones. There is a highly conductive block observed on the latitudinal profile, passing through the central region of the Hanoi Basin, and steeply dipping to the east (75°) to depths of more than 100 km. The deep geoelectric features of the Red River fault system are compared with the geoelectric section under their continuation in Southern Tibet in the adjacent territory in China.