Fault Site Research Articles

Damage propagation and failure mechanism of single dome historical Masonry Mosque after February 6, 2023, Kahramanmaraş earthquake doublets (Mw = 7.7 and Mw = 7.6)

Many historical masonry mosques and minarets, including Milky Minaret Mosque and Ulu Mosque, which are very close to Ak Minaret Mosque in Malatya, suffered severe damage and collapsed after the Kahramanmaraş earthquake on February 6, 2023. Despite the settled loose soil properties and the presence of a small stream flow near the mosque, Ak Minaret Mosque, a historical masonry mosque with a single dome and square, remains operational even after the aforementioned earthquakes. Additionally, DEMA's strong ground motion station was out of service during both earthquakes. This situation raises questions about the mosque's ability to withstand the seismic load. The basic purpose of this paper is to investigate in detail the seismic performance, damage limits, the reason for unexpectedly less damage due to the earthquakes, the potential failure mode, and possible resisted earthquake loads of the historical Ak Minaret Mosque in Malatya, Türkiye. To achieve this goal, first, dynamic identification was performed on the mosque one year prior to the aforementioned earthquakes. Next, the material properties were determined using both non-destructive and destructive testing methods. Following the dynamic identification, a numerical model was generated by 3-D solid elements, and this 3-D model was calibrated using the dynamic identification tests. The mosque underwent both nonlinear static and nonlinear dynamic analyses. Nine seismic records were selected for the nonlinear dynamic analysis. Five of them were national, including even Kahramanmaraş earthquake records, and three of them were selected from an international database on the basis of fault characteristics and site classification. The analysis results indicate that Ak Minaret Mosque incurred less damage than expected during the Kahramanmaraş earthquakes. This could be due to soil improvement prior to the construction of Ak Minaret Mosque in 1573. Moreover, the effective restoration increased stiffness and maintained the mosque’s stability. Finally, the possible resisted PGA by the mosque was around 0.22 g.

Influence of crossing fault position and site soil on the mechanical properties of bellows joint connected buried pipelines under direct shear

Buried pipeline systems are vulnerable to joint damage in earthquakes. Previous studies have shown that bellows joints are effective in increasing deformation capacity and reducing the axial force of the main pipeline. However, the effectiveness of bellows joints in enhancing the deformation capacity of the pipelines is affected by the location of the crossing fault and the soil at the site. This paper constructs and validates a finite element model of a buried steel pipeline connected by a bellows joint using ABAQUS to investigate this issue. The effects of fault location, soil properties, and internal pressure on the bellows joint connected pipelines were analyzed using a finite element model. The results indicate that the bellows joints exhibit the best energy dissipation and deformation enhancement when the fault passes directly through the joints. Bellows joints in soft soil are better at dissipating energy, reducing pipe deformation, and mitigating pipe damage compared to those in hard soils. The internal pressure is helpful to increase the mechanical properties of the pipelines. The findings can provide some guidance for pipeline design and mitigation strategies for ensuring the reliability and safety of buried pipeline systems in earthquake-prone areas.

Seismic performance of underground subway station structure near the strike-slip fault by the developed hybrid IBE-FEM method

To investigate the influence of strike-slip faults on the seismic responses of underground structures, based on the single-layer potential theory of the boundary element concept and the fault-site-underground structure coupling mechanisms, we proposed a hybrid indirect boundary element-finite element numerical method (IBE-FEM) to simulate efficiently the seismic response of the entire process from the near seismogenic-fault to the underground structure. Initially, based on the kinematic finite-fault model, the seismic wavefield of an overlying soft-soil sedimentary-layer site subjected to strike-slip faults with source parameters, such as rupture velocity, dip-angle, and upper-boundary burial depth, was solved using the indirect boundary element method (IBE). Subsequently, the accuracy of the IBE-FEM in predicting the site seismic wavefield was verified. On this basis, the influence laws of the source parameters and the fault-site coupling effects on the seismic performance of the structure were preliminarily investigated by establishing a numerical model of the nonlinear dynamic interaction system of a soil-underground structure. The results showed that the seismic responses of the underground structure located in the footwall far-fault region were more strongly affected by variations in the rupture velocity. The lateral deformation of the structure under the rupture velocity condition of bedrock shear-wave velocity (vs) was dramatically increased compared to sub-vs, and the lowest amplification is 59 %. Furthermore, the hanging wall and seismic damage concentration effects significantly impacted the structure located in a strike-slip fault site with a shallow-burial. This study provides a reliable and efficient analytical method for the seismic design of underground structures in complex near-fault regions.

Advanced testbed to assess disturbances in electrical grids with DERs using relays/meters with varying sampling frequencies

Distributed energy resources (DERs) are vital to achieve clean energy goals, but in some cases, their rapid deployment has led to negative effects on their reliability because of possible voltages and/or current disturbances that need to be analyzed in detail. This study created an advanced testbed with a real-time simulator and synchronized time and trigger event systems was created to compare event disturbances from intelligent electronic devices (IEDs) with different sampling frequencies and locations in an electrical grid containing DERs. This testbed is capable of capturing the recorded events of multiple IEDs and the real-time simulator to assess the effect of the disturbances and IEDs’ behaviors, including phase voltages, phase current waveforms, and total harmonic distortion (THD) analysis. In this study, a three-line-to-ground electrical fault was simulated, the disturbance event was detected, and recorded events (from 4 to 133 samples per cycle) were collected from meters and relays located at different sites. A harmonic peak algorithm, which was based on measuring the phase voltage and phase current THD peaks at the first one-cycle of the disturbance events, was created to assess and detect the fault states and locations. Several important findings resulted from performing this study, such as selecting IEDs with high sampling frequencies, installing all IEDs with similar sampling frequencies, assessing the software limitations for computing THD, studying the effect of the IEDs’ locations (downstream or upstream) with respect to the electrical fault site and the distance from the disturbance event point, evaluating the percentage errors of the phase voltage THD peaks at the first one-cycle of disturbance events, and installing synchronized time source and trigger event signal systems for recording the IEDs’ events.

Research and Application of Methods for Estimating Setback Distance of Buildings on Active Fault Sites

Research and Application of Methods for Estimating Setback Distance of Buildings on Active Fault Sites

Signal-based fault location method using time and frequency domain

This research introduces an innovative approach to fault detection in high-voltage alternating current (HVAC) systems by integrating temporal and frequency domain characteristics of signals. It utilizes Traveling Wave (TW) detection and analysis, focusing on a precise window of just 100 microseconds surrounding the TW's arrival at the measurement point. Mathematical Morphology is applied to identify time-domain properties, while the Stationary Wavelet Transform is employed to extract frequency-domain features. Additionally, the integration of a Dynamic Mode Decomposition-based technique enhances TW detection accuracy. The efficacy of this approach is extensively assessed for fault site classification and regression tasks, demonstrating superior performance compared to utilizing time or frequency-domain features separately. The study also examines the method's resilience to noisy measurements and the sufficiency of training data. Comparative analysis against existing signal-based approaches within the IEEE 34 node system underscores its heightened accuracy. Furthermore, the proposed technique showcases minimal fault location estimate errors along the feeder length and competes favorably with slower phasor-based fault detection methods in performance. Regarding the distance of the fault, its proximity to the generator, transmission line, or load significantly influences the parameters of positive, negative, and zero sequence components. When a fault occurs, these parameters undergo distinct changes, serving as indicators of the fault's severity and location. If the fault occurs near the generator or substation, there may be alterations in the voltage and current magnitudes, affecting the sequence components accordingly. In the case of a fault in the transmission line, impedance changes can lead to variations in sequence parameters. Similarly, a fault near the load can cause disturbances in the voltage and current profiles, impacting the sequence components. Analyzing these changes in positive, negative, and zero sequence parameters during a fault provides valuable insights into the fault's severity and location, aiding in effective fault detection and mitigation strategies. Key Words – fault detection, high-voltage alternating current (HVAC) systems, Traveling Wave (TW), temporal domain, frequency domain, Mathematical Morphology, Stationary Wavelet Transform, Dynamic Mode Decomposition, fault site classification,

Research on Data-Driven Fault Scenario Simulation Model of Distributed Network

Distribution lines are critical components of today's power system, and can directly impact on power supply security and stability. An effective power system protection system should detect any faults as soon as they occur. There are two steps in fault diagnosis. One is defect classification, which has already achieved excellent accuracy rates. As a result, this study concentrates on the opposite objective, which is fault location. This research introduces a War Strategy Water Wave Optimization (WSWWO) based Deep Q Network for radial distribution networks using synchronous generators for Distributed Generation (DG). The algorithm estimates the fault site by analyzing voltage and current samples at the main feeder head, and scheduled active and reactive power injections by network synchronous generators. A full-order synchronous machine model was utilized to analyze the dynamic behavior of DG plants during fault transients. Here, the Deep Q Network is trained by WSWWO, and hybridized by two optimization algorithms, War Strategy Optimization (WSO) and Water Wave Optimization (WWO). Furthermore, the experimental results revealed that the WSWWO-Deep Q Network outperformed state-of-the-art models in terms of Accuracy and Error, with values of 0.997 and 0.141, respectively.

Analysis of the characteristics and causes of city gas explosion accidents based on DT-AR algorithm

In order to effectively prevent and control accidents, it is essential to trace back the causes of gas explosions in cities. The DT-AR(decision tree-association rule) algorithm is proposed as a quantitative analysis of gas accident features and causality. First, 210 gas explosion accident investigation reports were taken as samples. The gas accident causation system is divided into three aspects, including environmental factors, management factors and physical factors. Management factors were sorted into organizational-level and individual-level factors from the investigation reports. Second, the CART decision tree model was used to compare location features, organizational causality features, and individual causality features of the piped and bottled gas accidents, and a decision tree model with the gas system fault site as the root node was built to filter the key feature variables. In order to reveal factor correlations and deep-level causation, the Apriori algorithm is used to mine accident association rules. The combinations on the branches of the decision tree are used as constraints to filter the critical causality rule, which improves the efficiency of association rule screening and enhances prediction accuracy. The results demonstrate that the DT-AR algorithm can evaluate the importance of variables, quickly locate effective combinations of factors, and mine the complete causal chain. The association rule is screened based on the constraint of the key element combination of the decision tree, which compensates for the low efficiency of the Apriori algorithm for association rule mining. In addition, the accident-caused excavation results provide an effective path for gas companies, outsourced service companies and administrative departments to implement gas safety chain supervision, which can address the problem of gas accident safety management failures and provide decision support for accident prevention.

Shaking table tests on deformation pattern and failure mechanism of fault-crossing tunnels in non-rupture scenario

Tunnels, as critical underground infrastructures, often intersect with faults. Field investigations have underscored the susceptibility of fault-crossing tunnels to extensive damages during earthquakes. Hence, large-scale shaking table tests are conducted to investigate the deformation pattern and failure mechanism of fault-crossing tunnels under transverse excitation, particularly in non-rupture scenarios. The dynamic behavior of the tunnel, as expected, is dominated by the surrounding strata. Acceleration responses vary notably across different regions of the fault site. The disparity increases with the increments of seismic intensity and input frequency. The tunnel section at the interface between the fault and the hanging wall manifest the strongest acceleration, where the largest strains of the tunnel and most of the lining cracks also occur, highlighting its vulnerability to seismic vibrations. The damage-induced non-linearity of the tunnel is then identified by the decreasing dominant frequency thereof. The fault-crossing tunnel exhibits unique three-dimensional shearing-torsional deformations, elucidated through the test data and an analytical model. This deformation pattern provides a better understanding of the seismic responses of fault-crossing tunnels under seismic vibrations.

Local Site Effect of Fault Site and Its Impact on Seismic Response of Fault-Crossing Tunnel

ABSTRACT The areas where tunnels crossing faults are especially susceptible to seismic damage. Local site effects associated with fault site notably contribute to the unfavourable impact on the seismic behaviour of tunnels. In this study, large-scale shaking table tests were conducted to investigate the fault site effect and its impact on the seismic response of tunnels. Real earthquake records, synthetic seismic wave, and sinusoidal waves were selected as input motions, excited in both transverse and longitudinal directions of the tunnel. The local site effect of the fault site was evaluated by time-frequency analysis. The test results indicate that the acceleration response within the fault is significantly greater than those on both sides, regardless of excitation direction. Dynamic characteristics of different regions of the fault site exhibit distinct variations under different excitation directions, with the dynamic behaviour of the strata within the fault playing a crucial role. Marked waveform distortion and trapped waves can be observed within the fault, attributed to harmonic distortion, waveform conversion at fault interfaces, and varying seismic wave propagation pathways. The region of maximum seismic response of the fault-crossing tunnel predominantly occurs near the interface between the fault and the hanging wall. The seismic response of the tunnel located in the hanging wall exceeds that in the footwall. The dynamic characteristics of the fault-crossing tunnel are significantly affected by the dynamic characteristics of the strata around the tunnel, highlighting the necessity of comprehending strata dynamics in the seismic design of such tunnels. The aforementioned findings could offer valuable insights for the seismic design of mountain tunnels crossing fault zones.

First reports on the genetic diversity and phylogenetic relationships of bathynellids (Malacostraca: Bathynellidae) from Lake Baikal

Within the fauna of Lake Baikal, two species of bathynellids are known: Bathynella baicalensis Bazikalova, 1954 and Baicalobathynella magna (Bazikalova, 1954), both originally described from the southern basin of the lake. The authors’ findings indicate that bathynellids are prevalent across all three basins of the lake, occuring on habitats such as methane seeps, mud volcanoes and hydrothermal vents. A comprehensive analysis of the COI (mtDNA) and 18S rRNA (nuclear DNA) gene fragments from bathynellids collected at tectonic fault sites in the northern basin of the lake revealed the absence of any representatives of the genus Bathynella Vejdovsky, 1882 among them. Instead, individuals identified as Baicalobathynella cf. magna comprise two genetic lineages at the species level, which diverged from a common ancestor approximately 7 Ma. The genus Altainella Camacho, 2020, whose representatives inhabit the interstitial hyporheic zone of the Onon river in Mongolia and Aktru mountain river of Altai, is designated as the closest relative of the Baikal bathynellids studied.

A survey of scan-capture power reduction techniques

With the advent of sub-nanometer geometries, integrated circuits (ICs) are required to be checked for newer defects. While scan-based architectures help detect these defects using newer fault models, test data inflation happens, increasing test time and test cost. An automatic test pattern generator (ATPG) exercise’s multiple fault sites simultaneously to reduce test data which causes elevated switching activity during the capture cycle. The switching activity results in an IR drop exceeding the devices under test (DUT) specification. An increase in IR-drop leads to failure of the patterns and may cause good DUTs to fail the test. The problem is severe during at-speed scan testing, which uses a functional rated clock with a high frequency for the capture operation. Researchers have proposed several techniques to reduce capture power. They used various methods, including the reduction of switching activity. This paper reviews the recently proposed techniques. The principle, algorithm, and architecture used in them are discussed, along with key advantages and limitations. In addition, it provides a classification of the techniques based on the method used and its application. The goal is to present a survey of the techniques and prepare a platform for future development in capture power reduction during scan testing.

A Survey on Fault Identification System in OTN using Neural Network

The diversity of information and services that are sent via optical networks is growing day by day, hence the survivability of optical networks has emerged as a significant research issue in recent years. The location of the fault in an optical transmission network (OTN) is very important when investigating the survivability of optical networks. The first step is to create network model with three channel, after which it is necessary to analyze common alarm data, as well as fault monitoring points and common fault sites. The fault location field of OTN incorporates the artificial neural network (ANN), which is used to identify whether or not a probable fault site is present. In this paper, we had done a review of earlier research work in this field and identified the research gap in the introduction of neural networks into the area of fault identification in optical transport networks.

Silver-induced γ→ε martensitic transformation in FeMn alloys: An experimental and computational study

Porous FeMn alloys with additions of 0, 1, 3 and 5 wt% of Ag were fabricated using powder metallurgy and sintering. The microstructure of the fabricated alloys was characterized using X-ray diffraction, transmission electron microscopy and selected area electron diffraction. While equiatomic FeMn and FeMn-1Ag alloys possess a fully austenitic structure, a change in the crystallographic structure is observed upon addition of 3 and 5 wt% of Ag, where a mixture of γ austenite and ε martensite phases is observed. Compression tests reveal that such structural transition causes an increase of the yield stress. The evolution of microstructure with the Ag content can be understood from theoretical calculations which show that Ag atoms prefer the intrinsic stacking fault (ISF) sites, revealing lower energy for the ε atomic plane sequence. This causes local depletion of the electronic charge, therefore weakening the interatomic bonds at the ISF plane and facilitating the phase transition. In addition, the total energy difference between the γ and ε phases decreases upon Ag addition. This enables the coexistence of both phases in the sample with 5 wt% Ag. Both experimental and theoretical data agree that the magnetization value gradually increases upon Ag addition. This is due to the local stress that is introduced by Ag atoms, which expand the Ag-Fe and Ag-Mn first neighbour interatomic bonds compared to FeMn. This stress results in electronic charge transfer that locally alters the Fe and Mn atomic magnetic moments. These results are appealing for the design of FeMn-based alloys with tuneable phase composition and physical properties for several technological applications.

Investigation of urban active faults using the short-offset transient electromagnetic method: an example from Shunping, Hebei Province, China

Abstract The presence of an urban active fault carries a geological hazard risk that threatens urban construction. Therefore, detecting such faults is crucial for mitigating potential risks and ensuring safe urban development. The grounded-wire source short-offset transient electromagnetic method (SOTEM) offers an opportunity to identify faults with high-conductivity. The results of a SOTEM survey conducted in Shunping, Hebei Province, were presented to detect buried faults and locate the industrial park. Data were analysed using the one-dimensional inversion method with SOTEMsoft software, which was denoised using the short-time sliding window adaptive singular value decomposition algorithm based on the wavelet threshold. Despite the challenges posed by urban features, particularly traffic, the survey results located the fault and hold significant potential to reveal its extent and depth. The study highlights the importance of avoiding fault sites during urban construction, even though the area is currently tectonically stable. This paper reveals an unusual opportunity to study the effectiveness of electromagnetic methods for detecting buried faults in cities and reveal geological structures covered by Quaternary formations.

Исследование влияния переходного сопротивления на дистанционное определение места повреждения на основе одностороннего метода

Fault location on 110–220 kV overhead power lines is one of the main functions of modern relay protection devices. Currently, the actual errors of fault location based on emergency mode (EM) parameters in most cases are about 5 %. However, there are cases when they exceed 10–20 %. One-sided fault location based on EM parameters and improvement of its accuracy are important issues to study since there isn’t a communication channel on power lines for the transmission of emergency information everywhere. The main parameter that has a significant impact on the accuracy of fault location method is the transient resistance. The aim of the research is to study the effect of transient resistance on the one-sided fault location method based on EM parameters proposed by A.E. Arzhannikov. In the course of the study, the following tasks are set: assessment of the effect of transient resistance on the accuracy of the specified fault location method; determination of the polarizing value for fault location, which ensures greater accuracy of the method, including the presence of transient resistance at the place of a short circuit; defining a criterion to recognize the type of short circuit that does not depend on the transient resistance; development of a method to determine the value of the transient resistance at the fault location. To study and evaluate the errors of distance fault location based on EM parameters, a series of calculations of short circuit currents has been made for various transient resistances at the fault location and at various distances of the fault. The calculation of currents and data processing has been carried out in the ARM SRZA software package. A single overhead line with a voltage of 110 kV with a two-sided supply and a length of 70 km is chosen as the object under study. To perform the research, the primary converters are taken as ideal. The authors have obtained the estimation of the errors of the one-sided fault location method. It is proposed to use the zero-sequence current as a polarizing quantity in the indicated fault location method, which provides greater accuracy than the use of the negative sequence current. To ensure the stable operation of one-sided fault location based on EM parameters, especially in case of short circuit with significant transient resistances, the use of methods that are insensitive to transient resistances is justified. A parameter to identify the type of short circuit is proposed, the coefficient of the image Kobr. Its values are determined for each type of short circuit, a small dependence on transient resistances is found. A calculation substantiation is given for the value of the identification coefficient of two-phase faults (Phase-to-Phase and Phases-to-Earth) according to the ratio of negative and zero sequence currents. The authors have estimated the transient resistance at the fault site by the ratio of symmetrical components for the simulated power transmission line. The results of the study can be used to improve the existing methods of fault location based on EM parameters, namely: to improve their accuracy considering the transient resistance at the fault site; to improve their accuracy using a suitable polarizing value; to determine the type of short circuit more accurately by using the proposed identification parameter.

Physics-informed machine learning for fault-leakage reduced-order modeling

Geologic carbon storage (GCS) is a promising technology for mitigating CO2 emissions. The overall success of GCS depends on safe operations that are informed by risk assessment and have proper mitigation plans in place. Performing quantitative probabilistic risk assessment for a GCS site using traditional reservoir simulators can be challenging due to the high computational costs. To overcome this challenge, the US Department of Energy’s National Risk Assessment Partnership (NRAP) project has developed an integrated assessment modeling approach that utilizes computationally efficient reduced-order models (ROM) for simulating various parts of a GCS storage site to quantify uncertainty. In this study, we develop a reduced-order model for fault leakage risk assessment. We use a deep learning approach to build the reduced-order model. We perform a sensitivity analysis and find that the deep learning model yields high accuracy with a much smaller computational cost than full-physics simulation. We also evaluate the performance of the model in scenarios where simulations are not possible to run, providing analysis not previously performed in fault-leakage ROM analyses. Based on a sensitivity analysis of the model, we suggest a simplified conceptual model for fault leakage and site monitoring.

Built-In Self-Test of High-Density and Realistic ILV Layouts in Monolithic 3-D ICs

Nanoscale interlayer vias (ILVs) in monolithic 3-D (M3D) ICs have enabled high-density vertical integration of logic and memory tiers. However, the sequential assembly of M3D tiers via wafer bonding is prone to variability in the immature fabrication process and manufacturing defects. The yield degradation due to ILV faults can be mitigated via dedicated test and diagnosis of ILVs using built-in self-test (BIST). Prior work has carried out fault localization for a regular 1-D placement of ILVs in the M3D layout where shorts are assumed to arise only between unidirectional ILVs. However, to minimize wirelength in M3D routing, ILVs may be irregularly placed by a place-and-route tool, and shorts can also occur between an up-going ILV and a down-going ILV. To test and localize faults in realistic ILV layouts, we present a new BIST framework that is optimized for test time and PPA overhead. We also present a graph-theoretic approach for representing potential fault sites in the ILVs and carry out inductive fault analysis to drop noncritical sites. We describe a procedure for optimally assigning ILVs to the BIST pins and determining the BIST configuration for test-cost minimization. Evaluation results for M3D benchmarks demonstrate the effectiveness of the proposed framework.

An analytical model to ascertain the fragmentation of cementite lamella at lamellar fault sites

ABSTRACT An analytical model is conceptualised and implemented for the first time to study the kinetics of cementite lamella fragmentation at the lamellar fault site occurring at an early stage of austenitisation in eutectoid steel. The model is conceived on the basis of two prime diffusion phenomena; namely, the curvature-dependent diffusion within cementite lamella and the diffusion-assisted dissolution in austenite. Both these diffusion phenomena are observed to have adequate significance in view of respective kinetic factors ascertained therein. The model is validated with necessary experimental work pertaining to the progress of lamellar fragmentation during isothermal holding at an austenitisation temperature of 775°C. The experimental result is closely followed by the developed model. A lamellar fragmentation time of 260 s is predicted accordingly for the incomplete austenitisation-based heat treatment of eutectoid steel.

Remote Fault Identification and Analysis in Electrical Distribution Network Using Artificial Intelligence

This research describes a method for wavelet decomposition and machine learning-based fault site classification in a radial power distribution network. The first statistical observation is produced using wavelet decomposition and wavelet-based detailed coefficients in terms of Kurtosis and Skewness parameters. For this objective, six distinct machine learning methods are deployed. They are evaluated and compared using unknown data sets with varying degrees of unpredictability. One approach has been shown to be the most accurate in locating the location of the problem bus.