Bulletin of Earthquake Engineering最新文献

Accurate representation of site amplification is essential for seismic hazard analysis, particularly in regions with complex geological structure. This study develops a Bayesian hierarchical site amplification model that captures nonlinear, period-dependent, and regionally variable behavior using an extensive strong-motion dataset from Türkiye. The model employs a piecewise V_S30 functional form derived from nonparametric scaling and clustering, and incorporates nonlinear scaling with reference rock motion intensity (PSA_rock). Regional variability is introduced through random-slope adjustments, enabling spatial differences in amplification to be represented while maintaining statistical stability through partial pooling. Results indicate pronounced nonlinear and regional variability for soft soils and reduced regional differences for stiff sites (V_S30 > 600 m/s). A key observation is a systematic amplification peak within the 400–550 m/s velocity range, where the model exhibits consistent underprediction across periods. Because this feature persisted even for stations located on flat basin interiors, a detailed investigation of stations in this V_S30 interval was conducted and is presented in the study. Mapping and site-specific examination reveal that many of these stations are located near slope breaks, basin edges, or transitional geological settings, suggesting that 2D/3D wave-propagation or impedance-transition effects—rather than V_S30 alone—may drive the increase in the amplification. Additionally, residual underprediction persists at high-V_S30 rock sites, highlighting the need for improved empirical characterization of stiff-soil and rock conditions. Overall, the proposed Bayesian framework provides a flexible, data-driven, and uncertainty-aware approach for modeling site amplification, with direct applications in probabilistic seismic hazard analysis and performance-based earthquake engineering.

So far, various elements have been proposed for modeling concrete shear walls, which are generally classified into two categories: micro and macro elements. The number of degrees of freedom in macro elements is much lower compared with micro elements; which results in having less analysis time. In many studies, macro element called Multiple-Vertical-Line-Element-Model (MVLEM) is used to model the shear wall made of concrete. These elements simulate the overall nonlinear behavior of simple shear walls well, but cannot be used to model the shear walls with openings. In this paper, a modified MVLEM is used to simulate concrete shear walls with symmetrical and asymmetrical openings. For this purpose, two experimental concrete shear walls with symmetrical and asymmetrical openings were modeled, and then verified using the micro finite element method. Subsequently, a method was proposed by MVLEM elements to model the beam behavior based on the beam moment distribution diagram. Due to the moment distribution of the concrete wall with symmetrical opening, the coupling beam was modeled as two simple concrete shear walls, connected to one another from top parts. In the shear wall with asymmetric openings, the beam is modeled as a simple shear wall. Three different methods were proposed to connect the coupling beam to the shear wall. Then the behavior of two micro walls with symmetrical and asymmetrical openings, three macro walls with symmetrical and asymmetrical openings are investigated. The proposed models were analyzed through static, cyclic, and dynamic loading protocols. The results indicated that the models exhibited acceptable behavior.

To address the need for quantitatively optimizing the input of pulse-like ground motions (PGMs) during the design phase, this study presents a multi-parameter empirical model for the pulse amplification factor (PAF), incorporating two key components: the response spectrum amplification factor (A_f) and the velocity pulse period (T_p). The A_f model is constructed using Gaussian function branches, decoupling peak ground acceleration A_fPGA, the maximum value A_fmax at T/T_P = 0.96, A_fmin1 at T/T_P = 0.1, and A_fmin2 at T/T_P = 10.0. The A_fPGA, A_fmax, A_fmin1, and A_fmin2 are modeled as functions of source, path, and site parameters. Residual and standard deviation analysis reveal that the T_p predictions significantly influence the PAF model’s predictive performance, prompting the development of a new T_p prediction model. Correlation analysis suggests that T_p correlates strongly with magnitude and moderately with site conditions, rupture distance, and exhibits depth dependence only for shallow events (h < 3·0 km). The multi-parameter A_f model reduces the standard deviation of ln(A_f) by an average of 15%, with a maximum reduction of 38% near T/T_p≈1.0. Following adjustments, the model enhances response spectrum prediction accuracy for PGMs, achieving an average total standard deviation reduction of 0.137 (18.7%) across the spectral period range of 0.01–10·0s, with a maximum reduction of 0.233 (26.0%). This model supports the evaluation of pulse effects on critical infrastructures and can serve as a foundation for integrating directional amplification characteristics into seismic hazard analysis.

This study presents a high-resolution, site-specific probabilistic framework for assessing soil liquefaction hazard by explicitly modeling subsurface spatial variability and seismic hazard. Gaussian Random Field (GRF) modeling and Monte Carlo simulation were used to generate 1,000 realizations of cone tip resistance (qc) and sleeve friction (fs), calibrated from 39 Cone Penetration Tests (CPTs). Liquefaction triggering was evaluated using the CSR–CRR procedure, and the depth-integrated Liquefaction Potential Index (LPI) was computed for each realization. Monte Carlo simulations were performed under a fixed seismic demand (PGA = 0.174 g) to isolate the effects of soil spatial variability, while seismic hazard uncertainty was subsequently incorporated by convolving site-specific fragility functions with PGA-based hazard curves TBDY ( Turkish Building Earthquake Code, 2018). Logistic regression produced site-calibrated fragility relationships between LPI and the probability of liquefaction (P[Liq]), enabling multi-threshold evaluations for LPI > 15, 25, and 45. The risk density peaked near PGA ≈ 0.18 g, indicating that moderate ground motions dominate liquefaction risk. The annual probability of exceeding LPI > 15 was approximately 1.92 × 10⁻³ (≈ 0.192%/yr; ~1 in 521 years), indicating a non-negligible annual liquefaction hazard. This framework enhances realism in liquefaction risk estimation and provides actionable guidance for performance-based geotechnical design, seismic mitigation, and hazard-informed infrastructure planning in regions susceptible to soil liquefaction.

Precast concrete structures are composed of columns that exhibit significant flexural behavior, high aspect ratios, and substantial deformation and drift capacities. The existing experimental and analytical expressions found in the literature regarding the deformation and displacement capacities of columns are generally inadequate and not directly applicable to precast columns. Therefore, a comprehensive investigation into the damage capacities of precast columns is necessary. In this study, simplified expressions were developed to estimate drift ratios corresponding to various damage states of square precast columns. The effects of several design parameters, including square section depth, aspect ratio, axial load ratio, reinforcement ratios, material strengths, and embedment depth, on the damage behavior of socket columns were evaluated. Initially, based on existing experimental studies on socket foundations, a simplified equation was proposed to estimate the rotational stiffness of the socket column-foundation connection. Then, a parametric study was conducted, and to generate sufficient data, different column models were created using information obtained from previous studies on precast structures, and pushover analyses were performed. The primary damage states considered in these analyses included reinforcement yielding, concrete cover spalling, longitudinal bar buckling, and concrete crushing. Based on the analysis results, polynomial regression analyses were used to develop simplified expressions to estimate drift ratios. These expressions were found to predict experimentally measured drift values with satisfactory accuracy. Among the evaluated design parameters, the aspect ratio was found to significantly affect drift demands. Additionally, fragility analyses indicated that as the aspect ratio increases, socket columns require larger embedment depths to mitigate damage states related to longitudinal reinforcement yielding and cover concrete spalling.

To enhance the seismic resilience of liquid storage tanks (LSTs) under multi-dimensional earthquake actions, this work analyzes the performance of three-dimensional (3D) isolation device for such tanks subjected to horizontal-rocking coupled seismic excitations. Seven near-field and far-field seismic waves are selected, and the rocking component is obtained based on the frequency domain theory. A numerical model for 3D-isolated LSTs is established, accounting for liquid-solid coupling effect. The results show that the rocking component has a significant impact on the non-isolated LST, and the 3D-isolation system effectively suppresses the amplification effect of the rocking component on dynamic responses, substantially diminishing the effective stress, hoop stress, axial stress, and liquid pressure on the tank wall, with a seismic reduction rate of around 40%, hence mitigating the risk of local instability. Compared with rubber isolation, 3D-isolation is less affected by the rocking component, and its seismic isolation performance is significantly improved. Beyond the sloshing wave height, the parameter study reveals that an increase in liquid storage height and height-diameter ratio exacerbates the dynamic responses of non-isolated LST and amplifies the rocking component influence, largely due to heightened liquid inertia and structural slenderness. The 3D-isolation system demonstrates excellent adaptability across various conditions, particularly in mitigating stress concentration and liquid sloshing for tanks with high liquid level and large height-diameter ratio. The research offers a novel methodology for the seismic design of LST subjected to intricate seismic circumstances.

The most common strong motion parameters such as peak ground acceleration, velocity and displacement overlook the influence of the frequency content of ground motion and the duration of the shaking. Many researchers have shown that the energy input, also called high-order, parameters and duration of ground shaking are basic characteristics controlling the seismic response of structures. Many of them have been correlated with structural damage or important aspects of foundation and geotechnical engineering. In the past, a great number of Ground Motion Predictive Equations (GMPEs) have been proposed to predict the magnitude of those parameters, with a variety from simple to very complex functional forms capturing various seismic and site effects, such as magnitude scale, geometrical and anelastic attenuation, soil nonlinearity, types and geometry of faults, and the random effects associated to inter- and intra-event variability. Those GMPEs were mostly developed through calibration of regression coefficients to empirical data. On the other hand, Machine learning models, and more specifically the ANN-based models, are increasingly used in many fields of science such as earthquake engineering, geotechnical earthquake engineering and engineering seismology as evidenced by recently published extensive literature reviews. This work aims to propose new GMPEs for five high-order intensity parameters (I_A, CAV, ASI, I_H, I_c), as well as, for three definitions of strong motion duration (SD_5–95, SD_5–75, SD_20–80) for shallow earthquakes in Greece. Two classes of GMPEs are developed. The first is developed through training ANN models to strong motion data recorded in Greece. The second is based on calibrating the coefficients of a fixed functional form through the more classical forward nonlinear regression. The parallel implementation of more advanced Machine Learning Algorithms (MLA) and the more classical nonlinear regression for model calibration to empirical data and the subsequent comparison between the resulting models highlights their advantages and disadvantages in ground motion estimation.

Wooden columns often experience premature brittle failure due to insufficient ductility when subjected to combined axial and lateral loading. To overcome these limitations, this study developed a performance-based design framework for a hybrid reinforcement system integrating carbon fiber-reinforced polymer (CFRP) and embedded steel reinforcement. Multiscale experimental investigations demonstrate that compared to unreinforced specimens, this composite system achieves a 48.3% increase in axial load-carrying capacity and a 43.5% enhancement in lateral resistance. The improved deformation capacity stems from the synergistic interaction between continuous CFRP reinforcement and near-surface steel reinforcement. The study identified anchorage and bonding parameter thresholds that balance safety and efficiency: 120 mm anchorage length and 4 mm bonding layer thickness. Based on these findings, a quantitative design recommendation framework was established, linking bonding performance,axial load-carrying capacity, and cyclic degradation behavior. This framework provides rational guidance for the engineering design and retrofitting of composite timber columns.

A nonlinear seismic assessment of the 18th‑century Ayvat masonry weir was performed by integrating three‑dimensional finite‑element (FE) modeling with Ground‑Penetrating Radar (GPR) surveys. A detailed ABAQUS model of approximately 70000 continuum elements was developed and calibrated using laboratory‑measured stone–mortar properties and GPR‑derived foundation profiles. Nonlinear time‑history analyses were carried out under Turkish Earthquake Code (TEC‑2018) hazard levels DD1 (2%/50 yr) and DD2 (10%/50 yr) for both principal‑axis and 45°‑rotated records. Under the 45°‑rotated DD1 record (EQ1R), crest‑to‑base displacements reached up to 0.30 m, and the isolated local maximum damage parameter (PEMAX*) reached 0.47. In contrast, under the 45°‑rotated DD2 record (EQ2R), maximum displacements remained below 0.01 m and PEMAX* did not exceed 0.14, thereby preserving global stability while inducing residual strains at the abutments. Stress concentrations were consistently detected at material discontinuities and joint zones. Based on these results, targeted retrofitting measures, including joint reinforcement and localized strengthening, are recommended to ensure the structural safety and preserve the heritage integrity of historic masonry weirs.