Fault System Research Articles

Late Palaeozoic high-K calc-alkaline to shoshonitic series magmatism and related W(–Mo–Cu–Au) metallogeny of the Kyrgyz Tien Shan, Central Asia

In the Kyrgyz Tien Shan, numerous high-K calc-alkaline to shoshonitic series intrusions are associated with the large fault system known as the ‘Major structural line of Tien Shan’, or ‘Nikolaev Line’. During the Carboniferous, this lineament represented a zone of intracontinental, possibly back-arc rifting associated with a north-dipping subduction, whereas in the Late Carboniferous to Permian it was part of a larger continental collision structure. These Late Paleozoic high-potassic intrusions comprise numerous intrusive phases that vary in composition from the early mafic (monzogabbro, monzodiorite) through intermediate (monzonite, syenite, quartz syenite) to late stage and more evolved (quartz monzonite, granodiorite, monzogranite, leucogranite–alaskite) members locally intersected by monzodiorite–porphyry and lamprophyre dykes. They can be related to low degrees (from ∼1–2 to 2–2.5 vol%) of partial melting of metasomatically enriched upper mantle followed by magma fractionation and emplacement at shallower crustal levels. In summary, the high-K magmas formed in continental- and post-collisional arc settings with a progressive input of crustal material. From the west to the east, the potassic intrusions contain progressively higher Nb and Y concentrations, reflecting their derivation in a post-collisional setting. The A-type granite signatures also become more distinct in this direction. This is consistent with the tectonic model implying the ‘scissor-like’ closure of the Late Paleozoic Turkestan palaeo-ocean from east to west. These high-potassic intrusions are accompanied by W–Mo–Cu–Au skarn/porphyry to Au(–W) replacement-style deposits, which are part of the extended Au (Au–W–Mo–Cu) metallogenic belt of Tien Shan. The association of skarn and porphyry-style W–Mo to Mo–Cu–Au–W mineralization defines these ‘porphyry–skarn’ systems as a distinct group containing strongly oxidized andradite-dominant skarns. An early W partitioning into magmatic–hydrothermal fluid, together with Mo and Cu, is typical of this magmatic–hydrothermal system and can be explained by an early H 2 O saturation of the parental magma. The late-stage mafic dykes including lamprophyres probably reflect the presence of another, but concealed, mafic intrusion releasing CO 2 and metals, such as Au, As, Sb, Bi and Te, into the hydrothermal mineral system.

Research on the HHO improved BP neural network fault prediction algorithm for distribution networks based on weather factors

Abstract Weather factors have a substantial impact on the operation and maintenance of the distribution network, but the current system fault prediction platform mainly focuses on the operating characteristics of the system, that is, the internal parameters, and rarely considers the external parameters. Firstly, by studying the fault data of the distribution network in a city in northern China caused by weather factors, this paper obtains the main weather factors affecting the reliability of power supply in this area. Then, the Harris Hawks optimization (HHO) improved BP neural network algorithm is used to establish the main reliability evaluation models suitable for this region, and based on this, the fault probability of this region is predicted under the target weather. Finally, the prediction results are compared with the actual fault data caused by weather factors in this area. The results show that both the PSO-BP algorithm and HHO-BP neural network algorithm achieve better prediction accuracy than the BP neural network algorithm, and the HHO-BP algorithm has better convergence speed.

Study on unified expression of event occurrence flexible logic based on superposition quantum states

To determine the multi logical relationship in the process of cause event leading to result event, a unified expression of flexible logic of event occurrence based on the superposition of multi quantum states is proposed. According to the premise that the logical relationship between any numbers of events can be simplified to the logical relationship between the two events, 20 kinds of flexible logical relationships are studied, and 16 of them are selected to establish the unified expression of flexible logic of event occurrence. By studying those 16 kinds of logical relationships, 8 kinds of logical relationships without obvious correlation are further determined, and finally the unified expression of event occurrence flexible logic of superposition of three quantum states is formed. The result shows that the expression can express 8 kinds of superposition states of logical relationships at the same time, and the different logical forms in the probability of occurrence of result events can be obtained. Finally, the characteristics of the expression and the problems that may be encountered in the process of solving are analyzed. And through the example analysis, the usage process and function of the present method were explained. It can be used to express the logical relationship between the cause event and the result event in the system fault evolution and determine the probability of fault occurrence.

Intelligent fault diagnosis for unbalanced battery data using adversarial domain expansion and enhanced stochastic configuration networks

An accurate and efficient fault diagnosis method for battery systems is crucial to ensuring the safety of battery packs. Addressing the issue of insufficient actual fault data in battery operations, this paper proposes an intelligent fault diagnosis method based on feature-enhanced stochastic configuration networks and adversarial domain expansion of imbalanced battery fault data (AFDEM-FESCN). Firstly, we designed an adversarial fault domain data expansion method (AFDEM). By learning the distribution of fault data through adversarial training, the distribution of sample domains is balanced, thereby reducing model bias. Subsequently, we adjusted the distribution of SCN iterative parameters and added a linear feature layer. This enhances the feature extraction capability of the network through distribution overlay, enabling fault diagnosis. Finally, the effectiveness and feasibility of the proposed method were validated through a practical battery system fault diagnosis case, achieving a diagnostic accuracy of 92.1%. Experimental results demonstrate that the AFDEM-FESCN method exhibits good accuracy in battery system fault diagnosis, providing an effective solution to the challenge of imbalanced data in intelligent fault diagnosis.

Modelling and Diagnosis of Hybrid Dynamic Systems by a Multi-Model Approach

Fault diagnosis is an essential task in ensuring the smooth operation of complex dynamic systems. The consequences of faults can be serious, leading to loss of life, harmful emissions to the environment, high repair costs and economic losses caused by unplanned production line stoppages. The work developed in this paper concerns the modeling and diagnosis of faults (sensor faults, system faults, actuator faults) in hybrid dynamic systems using our multi-model approach (which combines two sub-models, one continuous and the other discrete). The aim is to integrate three well-known tools in the literature: the Bond Graph, the Observer and the Timed Automata, to design a global diagnostic model. The hybrid dynamic system is modeled by connecting the tools for the continuous part, i.e. the bond graph and the observer, to the timed automata for the discrete part. The resulting model is used for fault diagnosis in two stages: The first is fault detection by analyzing the residuals generated by the system output and that of the observer. The second step involves fault localization, which results from analysis of the signature matrix and temporal identification of the system. The proposed method combines the advantages of these tools to obtain the best performance, particularly in the fault location phase. The simulation results prove the effectiveness of the proposed model for the hybrid dynamic system. Moreover, these results also evaluate the performance of the proposed diagnostic approach while reducing non-detections, detection delays and false alarms.

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

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

Distributed observer for fault estimation in Load-Frequency Control of multi-area power systems with communication delays

This paper proposes an innovative approach to designing a distributed observer for fault and state estimations in Load Frequency Control (LFC) of time-delayed multi-area interconnected power systems. To reach this goal, the paper first provides exhaustive information and analysis on the structure, disturbances, and faults in multi-area power systems. Then, an L1 observer with the capability to simultaneously estimate the system’s states, process/actuator faults, and sensor faults is proposed. This observer exhibits robustness against various types of disturbances as well as time delays present within both the system and the communication network. The sufficient conditions for designing the proposed observer, guaranteeing the system stability, and minimizing the L1 performance index, are expressed as optimization problems employing Linear Matrix Inequality (LMI) techniques. Additionally, the effectiveness and credibility of the proposed distributed observer in estimating all states and faults in all areas are validated through simulation results.

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

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

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

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

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

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

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

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

A rapid analysis of aftershock processes after a moderate magnitude earthquake with ML methods

SUMMARY Moderate magnitude earthquakes and seismic sequences frequently develop on fault systems, but whether they are linked to future major ruptures is always ambiguous. In this study, we investigated a seismic sequence that has developed within a portion of the stretching region of the Apennines in Italy where moderate to large earthquakes are likely to occur. We captured a total of 2039 aftershocks of the 2023 September 18, Mw 4.9 earthquake occurred during the first week, by using machine-learning (ML) based algorithms. Aftershocks align on two 5–7 km long parallel faults, from a length that exceeds what is expected from the main shock magnitude. The segments are ramping at about 6 km depth on closely spaced N100 striking 70 N dipping planes, at a distance of some kilometres from the main shock hypocentre. Our results indicate that even moderate magnitude events trigger seismicity on a spread set of fault segments around the main shock hypocentre, revealing processes of interaction within the crustal layer. The possibility that larger earthquakes develop during seismicity spread is favoured by pore pressure diffusion, in relation with the closeness to criticality of fault segments. Based on the very rapid activation of seismicity on the entire system and a back-front signal from the hypocentre of the main event, we infer that fluid pressure, initially high within the crustal layer, rapidly dropped after the main shock. Our study reinforces the importance of timely extracting information on fault geometry and seismicity distribution on faults. ML-based methods represent a viable tool for semi-real-time application, yielding constraints on short-time forecasts.

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

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

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

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

Geochemistry of Cenozoic mafic potassic and sodic volcanic rocks in southwestern Madagascar: Long-lived lithospheric mantle heterogeneities in an extensional tectonic setting

Cenozoic (≥ 43 Ma) silica undersaturated (potassic) trachybasalts and trachyandesites in southwestern Madagascar (Tsianihy-Manja, southern Morondava Basin) form a small monogenetic volcanic field emplaced above Paleogene detritic sedimentary rocks, along a NE-SW-trending fault system. These olivine-chromite±clinopyroxene-phyric primitive lavas (Mg# = 69; MgO = 10–11 wt%; Cr = 450 ppm, Ni = 200 ppm; K2O = 3–4 wt%) have highly peculiar trace element and isotopic composition (e.g., Ba/Nb = 18.4; 87Sr/86Sri = 0.70529–0.70555, 143Nd/144Ndi = 0.51262–0.51263, 206Pb/204Pbm = 18.415–18.424, 207Pb/204Pbm = 15.576–15.579, 208Pb/204Pbm = 38.799–38.813). A hitherto undescribed plug of primitive (sodic) basanite of the 11–12 Ma-old Ankililoaka district south of Tsianihy-Manja (hosting spinel lherzolite mantle xenoliths) has noticeable different geochemistry (Ba/Nb = 8–9.2; 87Sr/86Sri = 0.70346–0.7036, 143Nd/144Ndi = 0.51281–0.51282, 206Pb/204Pbm = 19.079–19.374, 207Pb/204Pbm = 15.621–15.645, 208Pb/204Pbm = 39.115–39.424).The relatively low CaO, Sc, V, Fe2O3t, MnO at high MgO, Cr and Ni, and the potassic affinity of the Tsianihy-Manja trachybasalts, all indicate that the mantle source is relatively clinopyroxene-poor (i.e., depleted by previous melt extractions), in the same way as the source of lamproitic (or boninitic) magmas, but the primitive nature, the concentration of high field strength elements, the incompatible element patterns and their isotopic ratios indicate their unequivocal within-plate setting and indicate a derivation by low-degree partial melting of an incompatible element-enriched mantle and insignificant role for crustal contamination. In terms of incompatible element concentrations, and thus also Sr-Nd-Pb-isotopic composition, we find no evidence in favour of a mid-ocean ridge basalt (MORB)-mantle component, or for a MORB-mantle strongly enriched by ocean island basalt-like components, to form the mantle source regions of the Tsianihy-Manja and Ankililoaka mafic alkaline rocks. The significant isotopic change from the northernmost Cenozoic volcanic rocks of Madagascar and those in the central and southern part of the island (which range in composition from sodic to potassic, and from tholeiitic basalt to olivine melilitite) implicates a distinct source heterogeneity, and ultimately assess the role of the old continental lithospheric mantle as source region.

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

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

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

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

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

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

Empirical study on fine-tuning pre-trained large language models for fault diagnosis of complex systems

With increasing complexity and interconnectivity of the modern industrial systems, effectively diagnosing faults is a core step to Prognostic and Health Management (PHM). Language models, particularly Large Language Models (LLMs) that pre-trained on massive corpora, have demonstrated remarkable capabilities in Natural Language Processing (NLP) and its related downstream tasks. However, how to leverage these models for facilitating system fault diagnosis and verify its effectiveness is rarely explored. This paper incorporates the potential comprehension ability of pre-trained LLMs, and investigates the efficacy of fine-tuning LLMs for realizing efficient system fault diagnosis. The experiments conducted in this study involve both open-source and closed-source models, and utilize a simulation and a real fault diagnosis dataset. We find that these models consistently achieve high performance across various metrics compared to the baselines. Additionally, qualitative and quantitative analysis is performed to investigate several aspects of the approach, such as the impact of dataset size, data normalization, missing values and explainability of the diagnosis, further showcasing the potential as well as limitations of the approach.

Molecular dynamics simulation of arc ablation for CuCr contact materials and improvement method of ablation resistance

Renewable energy generation is a development trend worldwide due to sustainability and environmental protection. High-voltage direct current (HVDC) transmission is indispensable in the renewable energy system due to its efficient power transmission capability and adaptability to complex grid structures. The DC vacuum circuit breaker (VCB) is essential for system control and fault protection. However, with the development of DC systems towards high voltage and large current, the ablation resistance of CuCr contact materials in VCBs has become the leading technical bottleneck. In order to enhance the ablation resistance of CuCr contact materials, this paper investigates a new molecular dynamics (MD) simulation model for arc ablation of CuCr contacts; therefore, it proposes a design method for contact materials measured by characteristic parameters of ablation resistance. Results are as follows: Firstly, the Cu particles cause a severe ablation on CuCr contacts with the effect of arcs. Subsequently, the model’s accuracy is verified by the influence of Cr content on ablation resistance. Furthermore, Mo and W metal elements were used to dope and strengthen the CuCr10 contact material, and CuCr8Mo2 and CuCr7Mo3 have an apparent improvement in resistance to arc ablation, which are alternatives for reinforced CuCr10 contact materials.