Bulletin of Earthquake Engineering最新文献

The assessment of earthquake risk at the national scale is crucial for the design and implementation of risk reduction measures. Due to its location in the southwest of the Eurasian plate, Portugal is exposed to moderate to strong seismic events, such as the well-known 1755 Lisbon earthquake. We reviewed existing studies covering exposure, seismic hazard, vulnerability, and risk assessment for Portugal, and performed probabilistic seismic hazard and risk analyses for the country using new model components. These include a new exposure model developed for the residential building stock using the 2021 national Building Census Survey, a recent exposure model for commercial and industrial buildings, updated vulnerability functions for 116 building classes, and the recently released European Probabilistic Seismic Hazard model. The seismic risk results include average annual economic losses, fatalities, buildings with complete damage, and population left homeless. These results allowed the identification of the regions in Portugal with the highest earthquake risk, as well as which building classes contribute the most to the overall impact.

The paper presents findings from a parametric study analysing geometric (e.g., shape ratio, edge inclination) and stratigraphic factors (e.g. impedance ratio) influencing ground motion in trapezoidal valleys. The study involved 2160 visco-elastic analyses, considering 180 2D models with diverse shapes and soil properties, undergoing 12 synthetic input motions. Analyses results showed that the motion at the valley centre increases with both shape and impedance ratios, while it is independent of the edge slope; on the other hand, the maximum amplification at the edges depends on their inclination and on the impedance ratio, while it is independent of the valley shape. The position and size of the zone of maximum amplification at the edges depend on all the previous parameters. A valley amplification factor (VAF) is introduced to quantify spectral acceleration increase due to 2D effects. Closed-form equations are proposed to evaluate VAF based on valley properties. The proposed VAF is then applied to predict seismic amplification in two central Italian valleys, providing results well-comparable to those obtained from 2D numerical analyses. The described approach can be easily implemented into codes of practice as a conservative design tool to estimate 2D amplification along the surface of ‘shallow valleys’ subjected to moderate seismic actions.

The parametric seismic fragility model of elephant-foot buckling (EFB) in the tank wall of the unanchored storage tanks is introduced by utilizing the results of a parametric study of eighteen tank-soil configurations. The model can be used to rapidly assess the seismic vulnerability to EFB for a larger number of tanks. The parametric study involved a 1D cloud-based soil response analysis to relate the ground-motion intensity measure at the bedrock with that at the free surface, and a pushover analysis of the refined finite element model of the tank to assess the engineering demand parameter in terms of axial compressive stress in the tank wall and the critical value that triggers EFB. As a consequence, the parametric seismic fragility model can be applied to intensity measures at the bedrock, as it is demonstrated for the spectral acceleration at the tank’s impulsive period, S_{e,bedrock,EFB}, and the peak ground acceleration, PGA_bedrock,EFB. The input parameters of the introduced seismic fragility model are the harmonic average shear-wave velocity in the top 30 m of soil, V_s,30, the slenderness ratio of the tank, H/R, the ratio between radius and wall thickness of the tank, R/t, and the standard deviation of log values for the intensity measure causing EFB. The model reliably predicts the median intensity measure causing the onset of EFB in the investigated tank-soil configurations, especially when S_{e,bedrock,EFB} is selected for the intensity measure. However, further investigation is required to enhance the accuracy of predicted intensity measures that trigger EFB by considering the dynamic impact between the base plate and the foundation during an earthquake and accounting for the complete soil-structure interaction effects.

The emphasis of seismic design regulations on applying nonlinear dynamic analyses (NDAs) promotes using accelerograms that characterize site-specific ground motions. Commonly, amplitude levels of such accelerograms are defined by a target spectrum that could be based on a uniform hazard spectrum (UHS), which is determined by a probabilistic seismic hazard analysis (PSHA) and represents a response spectrum with ordinates having an equal probability of being exceeded within a given return period, ({T}_{r}). Conversely, the definition of ground-motion duration levels is not yet properly defined in current regulations to select accelerograms. Thus, adhering to data handling as that for amplitude ground-motion parameters, this study motivates executing PSHAs to define hazard-consistent levels for the ground-motion duration. That is, accelerograms can be selected to match both amplitude and duration ground-motion levels associated with ({T}_{r}). Further, fragility functions conditional on ({T}_{r}) that cover typical performance objectives can be developed using sets of hazard-consistent accelerograms to implement, e.g., multiple stripe analyses (MSAs). To demonstrate the importance of choosing fully hazard-consistent accelerograms to perform NDAs, this study includes the displacement- and energy-based seismic-response evaluation of a steel frame building located at different soil-profile sites in Mexico City. Sets of fully hazard-consistent accelerograms and solely amplitude-based hazard-consistent accelerograms were artificially generated per site for values of ({T}_{r}) up to 5000 years. Results indicate that the probability of failure can be underestimated if the ground-motion duration is unvaried in MSAs, e.g., structural damage caused by 50-year return-period or higher events can be more noticeable when fully hazard-consistent accelerograms take place.

In Almaty, the largest city in Kazakhstan lying on a high seismic region, many residential buildings constructed during the Soviet Union are still in service. These buildings were not properly designed against earthquakes and special seismic detailing was not well considered according to the local design code. Therefore, this paper presents an analytical seismic assessment of two typical reinforced concrete moment frame residential structures constructed in this era, representing 812 buildings with almost identical construction materials, geometries, and structural details. Two-dimensional nonlinear models were developed for these buildings in each orthogonal direction based on the structural details collected from a Kazakh government agency. Incremental dynamic analyses were then performed using 24 historical strong ground motions with fault characteristics similar to those in the Almaty region. Structural global and local seismic responses were investigated. A new approach was proposed to define structural global inter-story drift limits at different damage states based on local seismic demands considering uncertainties of earthquakes and structural nonlinear dynamic responses. Based on these inter-story drift limits, the structural fragility curves were then developed to identify the damage probability of these buildings, which were further used to roughly estimate repair costs at different earthquake intensity levels. It has been found that these buildings are vulnerable to destructive earthquakes due to poor structural details. They possess a high probability of incurring extensive damage (high repair cost) or even collapsing (irreparable) at the earthquake intensity level, with a return period of 475 years or 2475 years, respectively.

The rapid and accurate prediction of earthquake Strong-Shaking Zone (SSZ) is crucial for issuing precise early warnings to regions at high risk of strong ground shaking. Generally, the SSZ is derived from the real-time spatial distribution of observed ground motions. However, during the initial stages of large earthquakes, the SSZ is often underestimated and provide alerts without enough lead-time (the time interval between the alert declaration and the S-wave arrival to the target area). In this study, we propose an innovative approach termed Near-epicenter-based Partial Matching Crossover. Leveraging the characteristic that reliable magnitude estimates for large earthquakes are available earlier than accurate predictions of the peak ground velocity (PGV) distribution, this approach utilizes near-epicenter station data to rapidly estimate the SSZ. It achieves this by matching a segment of the fault, defined by a predetermined length, with the predicted PGV map within a 120 km radius centered at the epicenter. Application of our method to strong motion data from China, Japan and Turkey demonstrates its efficacy in quickly anticipating the post-earthquake intensity distributions for large earthquakes. Specifically, it offers a lead time of 5 s or more for 51.5% (39,354 km²), 43.3% (5772 km²), 31%(47,107 km²) and 75.3% (81,966 km²) of the I_MM = V region during the M 8 Wenchuan earthquake, the M 7.3 Kumamoto earthquake, the M 7.8 Syria earthquake and M 7.6 Turkey earthquake, respectively. The presented approach introduces a novel methodology to extend the lead time for earthquake early warnings.

Post-earthquake safety assessment of buildings and infrastructure poses significant challenges, often relying on time-consuming visual inspections. To expedite this process, safety criteria based on a demand-capacity model are utilized. However, rapid assessment frameworks require accurate estimations of intensity measures (IMs) to estimate seismic demand and assess structural health. Unfortunately, post-earthquake IM values are typically only available at monitored locations equipped with sensors or monitoring systems, limiting broader assessments. Simple spatial interpolation methods, while possible, struggle to consider crucial physical factors such as earthquake magnitude, epicentral distance, and soil type, leading to substantial estimation errors, especially in areas with insufficient or non-uniform seismic station coverage. To address these issues, a novel framework, BN-GMPE, combining a Bayesian network (BN) and a ground motion prediction equation (GMPE), is proposed. BN-GMPE enables inference and prediction under uncertainty, incorporating physical parameters in seismic wave propagation. A further novelty introduced in this work regards separating the near and far seismic fields in the updating process to attain a clearer understanding of uncertainty and more accurate IM estimation. In the proposed approach, a GMPE is employed for the estimation, and the bias and standard deviation of the prediction error are updated after any new information is entered into the network. The proposed method is benchmarked against a classic Kriging interpolator technique, considering some recent earthquake shocks in Italy. The proposed BN framework can naturally extend for estimating the probability of failure of various structures in a targeted region, which represents the ultimate aim of this research.