Search Results (873)

The accurate identification of seismic faults, which serve as crucial fluid migration pathways in hydrocarbon reservoirs, is of paramount importance for reservoir characterization. Traditional interpretation is inefficient. It also struggles with complex geometries, failing to meet the current exploration demands. Deep learning boosts fault identification significantly but struggles with edge accuracy and noise robustness. To overcome these limitations, this research introduces SwiftSeis-AWNet, a novel lightweight and high-precision network. The network is based on an optimized MedNeXt architecture for better fault edge detection. To address the noise from simple feature fusion, a Semantics and Detail Infusion (SDI) module is integrated. Since the Hadamard product in SDI can cause information loss, we engineer an Attention-Weighted Semantics and Detail Infusion (AWSDI) module that uses dynamic multi-scale feature fusion to preserve details. Validation on field seismic datasets from the Netherlands F3 and New Zealand Kerry blocks shows that SwiftSeis-AWNet mitigates challenges like the loss of small-scale fault features and misidentification of fault intersection zones, enhancing the accuracy and geological reliability of automated fault identification. Full article

Research on reliability control for enhancing power systems under random loads holds significant and undeniable importance in maintaining system stability, performance, and safety. The primary challenge lies in determining the reliability index while optimizing system parameters. To effectively address this challenge, we developed a novel intelligent algorithm and conducted an optimal reliability assessment for a Negative Stiffness Device (NSD) seismic isolation structure incorporating fractional-order damping. This algorithm combines the Gaussian Radial Basis Function Neural Network (GRBFNN) with the Particle Swarm Optimization (PSO) algorithm. It takes the reliability function with unknown parameters as the objective function, while using the Backward Kolmogorov (BK) equation, which governs the reliability function and is accompanied by boundary and initial conditions, as the constraint condition. During the operation of this algorithm, the neural network is employed to solve the BK equation, thereby deriving the fitness function in each iteration of the PSO algorithm. Then the PSO algorithm is utilized to obtain the optimal parameters. The unique advantage of this algorithm is its ability to simultaneously achieve the optimization of implicit objectives and the solution of time-dependent BK equations.To evaluate the performance of the proposed algorithm, this study compared it with the algorithm combines the GRBFNN with Genetic Algorithm (GA-GRBFNN)across multiple dimensions, including performance and operational efficiency. The effectiveness of the proposed algorithm has been validated through numerical comparisons and Monte Carlo simulations. The control strategy presented in this paper provides a solid theoretical foundation for improving the reliability performance of mechanical engineering systems and demonstrates significant potential for practical applications. Full article

Carbon black (CB)-filled rubber materials are extensively used in civil engineering seismic isolation. However, CB-filled rubber materials often experience mechanical property degradation because of exposure to environmental factors. To better understand the influences of thermo-oxidative, ultraviolet and ozone aging on mechanical property degradation, uniaxial tension and dynamic mechanical analysis (DMA) tests were carried out. In the uniaxial tension tests, the stress strength and elongation decreased with an increase in aging time. In the DMA tests, the effective temperature ranges decreased by 3.4–14%. And the neo-Hookean model was applied to simulate the hyperelasticity of CB-filled rubber materials. The relationship between the elastic modulus (a constant of the neo-Hookean model) and aging time was established, which provided a qualitative relationship between crosslink density and aging time. In addition, the dispersion of the CB aggregate was investigated using an atomic force microscope (AFM). The results indicated that the mechanical property degradation might be closely related to the aggregate diameter. This paper establishes a bridge between the microstructure and mechanical properties of CB-filled rubber materials, which can improve the understanding of the mechanical property degradation mechanisms of rubber materials and the fabrication of rubber components. Full article

On 22 May 2012, a magnitude Mw 5.6 earthquake struck the Pernik region of western Bulgaria, causing structural damage in nearby cities, including Sofia. This study assesses the seismic response of a six-story reinforced concrete building in central Sofia, utilizing real accelerogram data recorded at the basement (SGL1) and sixth floor (SGL2) levels during the earthquake. Using the Kanai–Yoshizawa (KY) model, the study estimates inter-story motion and assesses amplification effects across the structure. Analysis of peak ground acceleration (PGA), velocity (PGV), displacement (PGD), and spectral ratios reveals significant dynamic amplification of peak ground acceleration and displacement on the sixth floor, indicating flexible and dynamic behavior, as well as potential resonance effects. The analysis combines three spectral techniques—Horizontal-to-Vertical Spectral Ratio (H/V), Floor Spectral Ratio (FSR), and the Random Decrement Method (RDM)—to determine the building’s dynamic characteristics, including natural frequency and damping ratio. The results indicate a dominant vibration frequency of approximately 2.2 Hz and damping ratios ranging from 3.6% to 6.5%, which is consistent with the typical damping ratios of mid-rise concrete buildings. The findings underscore the significance of soil–structure interaction (SSI), particularly in sedimentary basins like the Sofia Graben, where localized geological effects influence seismic amplification. By integrating accelerometric data with advanced spectral techniques, this research can enhance ongoing site-specific monitoring and seismic design practices, contributing to the refinement of earthquake engineering methodologies for mitigating seismic risk in earthquake-prone urban areas. Full article

The development of mining operations in high-altitude regions is associated with a number of geomechanical challenges caused by increased rock fracturing, adverse climatic conditions, and high seismic activity. These issues are particularly relevant for the exploitation of gold ore deposits, where the stability of open-pit slopes directly affects both safety and extraction efficiency. The aim of this study is to develop and practically substantiate a comprehensive approach to assessing and ensuring slope stability, using the Bozymchak gold ore deposit—located in a high-altitude and seismically active zone—as a case study. The research involves the laboratory testing of rock samples obtained from engineering–geological boreholes, field shear tests on rock prisms, laser scanning of pit slopes, and digital geomechanical modeling. The developed calculation schemes take into account the structural features of the rock mass, geological conditions, and the design contours of the pit. In addition, special bench excavation technologies with pre-shear slotting and automated GeoMoS monitoring are implemented for real-time slope condition tracking. The results of the study make it possible to reliably determine the strength characteristics of the rocks under natural conditions, identify critical zones of potential collapse, and develop recommendations for optimizing slope parameters and mining technologies. The implemented approach ensures the required level of safety. Full article

Concrete structures increasingly face dynamic loading conditions, such as seismic events, vehicular traffic, and environmental vibrations, necessitating enhanced energy dissipation capabilities. The damping ratio, a critical parameter quantifying a material’s ability to dissipate vibrational energy, is typically low in conventional concrete, prompting extensive research into strategies for improvement. This review comprehensively explores the impact of advanced concrete types—such as Engineered Cementitious Composites (ECCs), Ultra-High-Performance Concrete (UHPC), High-Performance Concrete (HPC), and polymer concrete—on enhancing the damping behavior. Additionally, key mix design innovations, including fiber reinforcement, rubber powder incorporation, and aggregate modification, are evaluated for their roles in increasing energy dissipation. External factors, particularly curing conditions, are also discussed for their influence on the damping performance. The findings consolidate experimental and theoretical insights into how material composition, mix design, and external treatments interact to optimize dynamic resilience. To guide future research, this paper identifies critical gaps including the need for multi-scale numerical simulation frameworks, standardized damping test protocols, and long-term performance evaluation under realistic service conditions. Advancing work in material innovation, optimized mix design, and controlled curing environments will be essential for developing next-generation concretes with superior vibration control, durability, and sustainability. These insights provide a strategic foundation for applications in seismic-prone and vibration-sensitive infrastructure. Full article

Modeling mainshock–aftershock ground motions is essential for seismic risk assessment, especially in regions experiencing frequent earthquakes. Recent studies have often employed Copula-based joint distributions or machine learning techniques to simulate the statistical dependency between mainshock and aftershock parameters. While effective at capturing nonlinear correlations, these methods are typically black box in nature, data-dependent, and difficult to generalize across tectonic settings. More importantly, they tend to focus solely on marginal or joint parameter correlations, which implicitly treat mainshocks and aftershocks as independent stochastic processes, thereby overlooking their inherent spectral interaction. To address these limitations, this study proposes an explicit and parameterized modeling framework based on the evolutionary power spectral density (EPSD) of random ground motions. Using the magnitude difference between a mainshock and an aftershock as the control variable, we derive attenuation relationships for the amplitude, frequency content, and duration. A coherence function model is further developed from real seismic records, treating the mainshock–aftershock pair as a vector-valued stochastic process and thus enabling a more accurate representation of their spectral dependence. Coherence analysis shows that the function remains relatively stable between 0.3 and 0.6 across the 0–30 Rad/s frequency range. Validation results indicate that the simulated response spectra align closely with recorded spectra, achieving R² values exceeding 0.90 and 0.91. To demonstrate the model’s applicability, a case study is conducted on a representative frame structure to evaluate seismic vulnerability and economic loss. As the mainshock PGA increases from 0.2 g to 1.2 g, the structure progresses from slight damage to complete collapse, with loss rates saturating near 1.0 g. These findings underscore the engineering importance of incorporating mainshock–aftershock spectral interaction in seismic damage and risk modeling, offering a transparent and transferable tool for future seismic resilience assessments. Full article

Physics-informed neural networks (PINNs) have emerged as a transformative methodology integrating deep learning with scientific computing. This review establishes a three-dimensional analytical framework to systematically decode PINNs’ development through methodological innovation, theoretical breakthroughs, and cross-disciplinary convergence. The contributions include threefold: First, identifying the co-evolutionary path of algorithmic architectures from adaptive optimization (neural tangent kernel-guided weighting achieving 230% convergence acceleration in Navier-Stokes solutions) to hybrid numerical-deep learning integration (5× speedup via domain decomposition) and second, constructing bidirectional theory-application mappings where convergence analysis (operator approximation theory) and generalization guarantees (Bayesian-physical hybrid frameworks) directly inform engineering implementations, as validated by $72\%$ cost reduction compared to FEM in high-dimensional spaces ($p<0.01,n=15$ benchmarks). Third, pioneering cross-domain knowledge transfer through application-specific architectures: TFE-PINN for turbulent flows ($5.12\pm 0.87\%$ error in NASA hypersonic tests), ReconPINN for medical imaging ($▵\mathrm{SSIM}=+0.18\pm 0.04$ on multi-institutional MRI), and SeisPINN for seismic systems ($0.52\pm 0.18$ km localization accuracy). We further present a technological roadmap highlighting three critical directions for PINN 2.0: neuro-symbolic, federated physics learning, and quantum-accelerated optimization. This work provides methodological guidelines and theoretical foundations for next-generation scientific machine learning systems. Full article

This paper comprehensively reviews structural vibration control systems for earthquake mitigation in civil engineering structures. Structural vibration control is vital for enhancing the resilience and safety of infrastructure subjected to seismic activity. This study examines various control strategies, including passive, active, and hybrid methods, with a focus on the advantages of semi-active systems, which offer a balance of energy efficiency and adaptive capabilities. Semi-active devices, such as magnetorheological dampers, are highlighted for their ability to offer adaptive control without the high energy demands of fully active systems. The review discusses challenges like time delays, sensor placement, and model uncertainties that can impact the practical implementation of these systems. Experimental studies and real-world applications demonstrate the effectiveness of semi-active systems in reducing seismic responses. This paper emphasizes the need for further research into optimizing control algorithms and addressing practical challenges to enhance the reliability and robustness of these systems. It concludes that semi-active control systems are a promising solution for enhancing structural resilience in earthquake-prone areas, offering a practical alternative that strikes a balance between performance and energy requirements. Full article

Numerous rural residential buildings exhibit inadequate seismic performance when subjected to blast-induced vibrations, which poses potential threats to their overall stability and structural integrity when in proximity to blasting project sites. The investigation conducted in conjunction with the Qianshi Mountain blasting operations along the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway integrates household field surveys and empirical measurements to perform modal analysis of rural residential buildings through finite element simulation. Adhering to the principle of stratified arrangement and composite measurement point configuration, an effective and reasonable experimental observation framework was established. In this investigation, the seven-story rural residential building in adjacent villages was selected as the research object. Strong-motion seismographs were strategically positioned adjacent to frame columns on critical stories (ground, fourth, seventh, and top floors) within the observational system to acquire test data. Methodical signal processing techniques, including effective signal extraction, baseline correction, and schedule conversion, were employed to derive temporal dynamic characteristics for each story. Combined with the Fourier transform, the frequency–domain distribution patterns of different floors are subsequently obtained. Leveraging the structural dynamic theory, time–domain records were mathematically converted to establish the structure’s maximum response spectra under blast-induced loading conditions. Through the analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, the dynamic response patterns of rural residential buildings subjected to blast-induced vibrations have been elucidated. Following the normalization of peak acceleration and velocity parameters, the mechanisms underlying differential floor-specific dynamic responses were examined, and the layout principles of measurement points were subsequently formulated and summarized. These findings offer valuable insights for enhancing the seismic resilience and structural safety of rural residential buildings exposed to blast-induced vibrations, with implications for both theoretical advancements and practical engineering applications. Full article

This study investigates two novel prefabricated frame joints: prestressed steel sleeve-connected prefabricated reinforced concrete joints (PSFRC) and non-prestressed steel sleeve-connected prefabricated reinforced concrete joints (SSFRC). A total of three PSFRC specimens, four SSFRC specimens, and one cast-in-place joint were designed and fabricated. Seismic performance tests were conducted using different end-plate thicknesses, grout strengths, stiffener configurations, and prestressing tendon configurations. The experimental results showed that all specimens experienced beam end failures, and three failure modes occurred: (1) failure of the end plate of the beam sleeve, (2) failure of the variable cross-section of the prefabricated beam, and (3) failure of prefabricated beams at the connection with the steel sleeves. The load-bearing capacity and initial stiffness of the structure are increased by 35.41% and 32.64%, respectively, by increasing the thickness of the end plate. Specimens utilizing C80 grout exhibited a 39.05% higher load capacity than those with lower-grade materials. Adding stiffening ribs improved the initial stiffness substantially. Specimen XF2 had 219.08% higher initial stiffness than XF1, confirming the efficacy of stiffeners in enhancing joint rigidity. The configuration of the prestressed tendons significantly influenced the load-bearing capacity. Specimen YL2 with symmetrical double tendon bundles demonstrated a 27.27% higher ultimate load capacity than specimen YL1 with single centrally placed tendon bundles. An analytical model to calculate the moment–rotation relationship was established following the evaluation criteria specified in Eurocode 3. The results demonstrated a good agreement, providing empirical references for practical engineering applications. Full article

Historic masonry towers represent a significant part of the cultural heritage, which is often subject to retrofitting for preservation purposes. Due to the poor quality of the mortar, if present at all, the connection of existing towers to the foundation is generally such that it cannot ensure their monolithic behaviour under seismic action. When choosing a retrofitting technique, engineers often find themselves in a dilemma, whether to strengthen the connection between the tower and the foundation in order to enable the transfer of bending moments from the tower to the foundation due to seismic action, or to leave the towers freely rested on the foundation in order to enable the rocking motion mechanism. The aim of this paper was to investigate how the connection between the tower and the foundation affects the seismic resistance of masonry towers. For this purpose, a series of numerical analyses were performed on 2D numerical models that were created based on the geometry of five towers from the Italian region. In these numerical analyses, each of the towers is subjected to an incremental dynamic analysis in time for the case that it is freely supported on the base and for the case that it is freely rested base. The numerical analyses showed that: (i) unretrofitted towers have relatively low seismic resistance and rocking mechanisms cannot be realised to a significant extent; (ii) retrofitted masonry towers resting freely on the base have a significantly higher seismic resistance compared to the same towers connected to the base due to the rocking motion mechanism. The conclusions drawn on the basis of the conducted studies can serve engineers when choosing a technique for strengthening masonry towers. Full article

The ultimate goal of research on seismic mitigation technologies is engineering application. However, current studies primarily focus on the application of dampers in planar structures, while actual engineering structures are three-dimensional (3D) in nature. A type of damper, making up tuned mass dampers (TMDs) and inerters, has excellent vibration mitigation performance and needs brackets to connect to structures. In this work, a coupled dynamic model of an energy dissipation system (EDS) comprising a TMD, an inerter, a bracket, and a 3D building structure is presented, along with analytical solutions for stochastic seismic responses. The main work is as follows. Firstly, based on D’Alembert’s dynamics principle, the seismic dynamic equations of an EDS considering a realistic damper and a 3D structure are formulated. The general dynamic equations governing the bidirectional horizontal motion of the EDS are further derived using the dynamic finite element technique. Secondly, analytical expressions for spectral moments and variances of seismic responses are obtained. Finally, four numerical examples are presented to investigate the following: (1) verification of the proposed response solutions, showing that the calculation time of the proposed method is approximately 1/500 of that of the traditional method; (2) examination of spatial effects in 3D structures under unidirectional excitation, revealing that structural seismic responses in the direction along the earthquake ground motion is approximately 10⁴ times that in the direction perpendicular to the ground motion; (3) investigation of the spatial dynamic characteristics of a 3D structure subjected to unidirectional seismic excitation, showing that the bracket parameters significantly affect the damping effects on an EDS; and (4) application of the optimization method for the damper’s parameters that considers system dynamic reliability and different weights of the damper’s parameters as constraints, indicating that the most economical damping parameters can achieve a reduction in displacement spectral moments by 30–50%. The proposed response solutions and parameter optimization technique provide an effective approach for evaluating stochastic seismic responses and optimizing damper parameters in large-scale and complex structures. Full article

As a key transportation infrastructure, it is of great significance to ensure the seismic safety of the high-speed railway hub station. Taking Changde high-speed railway hub station as background, a comprehensive 3D numerical model of the high-speed railway station structure is proposed to consider the engineering geological characteristics of the site, soil nonlinearity, and pile-soil interactions. The results show that the hub station structural system, considering pile-soil interaction, presents the ‘soft-upper-rigid-down’ characteristics as a whole, and the natural vibration is lower than that of the station structure with a rigid foundation assumption. Under the action of three strong seismic motions, the nonlinear site seismic effect is significant, the surface acceleration is significantly enlarged, and decreases with the buried depth. The interaction between pile and soil is related to the nonlinear seismic effect of the site, which deforms together to resist the foundation deformation caused by the strong earthquake motions, and the depth range affected by the interaction between the two increases with the increase of the intensity of earthquake motion. Among the three kinds of input earthquake motions, the predominant frequency of the Kobe earthquake is the closest to the natural vibration of the station structure system, followed by the El Centro earthquake. Moreover, the structures above the foundation of the high-speed railway hub station structural system are more sensitive to the spectral characteristics of Taft waves and El Centro waves compared to the site soil. This is also the main innovation point of this study. The existence of the roof leads to the gradual amplification of the seismic response of the station frame structure with height, and the seismic response amplification at the connection between the roof and the frame structure is the largest. The maximum story drift angle at the top floor of the station structure is also greater than that at the bottom floor. Full article

Accurate seismic performance assessment of flexure-shear critical reinforced concrete (RC) columns necessitates precise hysteresis modeling that captures their distinct cyclic characteristics—particularly pronounced strength degradation, stiffness deterioration, and pinching effects. However, existing hysteresis models for such circular RC columns fail to comprehensively characterize these coupled cyclic degradation mechanisms under repeated loading. This study develops a novel hysteresis model explicitly incorporating three key mechanisms: (1) directionally asymmetric strength degradation weighted by hysteretic energy, (2) cycle-dependent pinching governed by damage accumulation paths, and (3) amplitude-driven stiffness degradation decoupled from cycle count, calibrated and validated using 14 column tests from the Pacific Earthquake Engineering Research Center (PEER) structural performance database. Key findings reveal that significant strength degradation primarily manifests during initial loading cycles but subsequently stabilizes. Unloading stiffness degradation demonstrates negligible dependency on cycle number. Pinching effects progressively intensify with cyclic advancement. The model provides a physically rigorous framework for simulating seismic deterioration, significantly improving flexure-shear failure prediction accuracy, while parametric analysis confirms its potential adaptability beyond tested scenarios. However, applicability remains confined to specific parameter ranges with reliability decreasing near boundaries due to sparse data. Deliberate database expansion for edge cases is essential for broader generalization. Full article