Bulletin of Earthquake Engineering最新文献

During seismic sequences, macroseismic damage effects cannot always be distinguished and assigned with certainty to individual shocks. In particular, the intensity that quantifies the effects of the earthquakes is a classification of the cumulative effect of all the shocks that occurred. This affects the estimation of the macroseismic parameters that can be obtained (location, magnitude), which cannot have the same reliability as single mainshocks, with implications for seismotectonics or hazard assessment. To try to solve this problem, a methodology was recently proposed using the case study of the event of 2016, October 30th (Mw = 6.6), based on the deletion of intensities above an established threshold for common localities hit by previous earthquakes during a sequence. In this paper, we analyse the variation of earthquake parameters of some Italian sequences by systematically applying this methodology and varying the cut threshold of intensity. The results provide a more complete evaluation of the proposed method and its reliability and suggest an alternative approach based on all available MDPs to compute earthquake parameters of aftershocks.

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. We select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

This paper aims to propose reliable factors that accurately capture the effect of target ductility of non-structural components (NSCs) on floor acceleration, velocity, and displacement demands at both the ground level and the upper building floors. A linear time history analysis (THA) was performed on four moment-resisting archetype buildings using historical and synthetic ground motions matched to the Montreal Site Class C uniform hazard spectrum (UHS) through frequency domain matching. The NSCs’ seismic demands and ductility-based modification factors were determined using uncoupled analysis, in which the equations of motion were solved using the Iterative Newmark Integration approach implemented in MATLAB. The seismic floor acceleration, displacement, and velocity demand amplitudes were reduced with increased NSC ductility, especially inside the resonance period range. The effect of ductility on the seismic acceleration demands was found to be significant near the resonance condition for the first three primary periods of the supporting structure. Conversely, the displacement and velocity demand were predominantly affected by the first primary mode. Specifically, for NSCs with moderate to high ductility levels, a 40%-60% decrease in demand was observed compared to NSCs exhibiting elastic behavior in the resonance condition. In contrast, the effect of ductility was minimal for out-of-resonance conditions and on ground-level seismic demands. Moreover, the sensitivity analysis on damping variations showed minimal impact on the proposed factors, further supporting their robustness. In conclusion, while ductility minimizes resonance effects on NSCs, a trade-off between the benefits of ductility and an acceptable damage level must be considered.

The geotechnical engineering community widely uses the one-dimensional (1D) Equivalent Linear Site Response Analysis (EQLSRA). However, the literature review reveals that surface ground motion characteristics predicted employing EQLSRA are often overdamped, especially at high frequencies. Recent studies have pointed out that the algorithm used within EQLSRA for obtaining the Equivalent Shear Strain (ESS) is one of the primary reasons for its unsatisfactory performance. Usually, for a given strain time history, the corresponding ESS is taken as Strain Ratio (STR) times the absolute peak strain. Conventionally, a constant value (usually ranging from 0.40 to 0.75 and typically 0.65) is manually set as STR. Though ESS plays a pivotal role in EQLSRA, not much attention has been given to the estimation of STR. This work aims to resolve such issues. Here, a new notion for the computation of STR is proposed, which can be easily integrated within EQLSRA. The coined idea takes into account the frequency content and intensity in the induced seismic strain waveform for the determination of STR. The suitability of the modified EQLSRA (mod-EQLSRA) incorporating the proposed technique of STR calculation is tested with the help of 15 Kiban Kyoshin Network (KiK-net) stations and 110 ground motions. It is found that the average absolute error in the surface Peak Horizontal Acceleration (PHA) predicted employing the mod-EQLSRA reduces by approximately 54% when compared to that estimated via the traditional EQLSRA.

Structural systems in buildings are designed to manage seismic impacts through ductile inelastic responses, allowing significant cyclic deformations without substantial loss of load-bearing capacity. Reinforced concrete wall structures dissipate energy mainly through the cyclic yielding of steel reinforcement bars. However, repeated inelastic cycles accumulate damage, increasing the risk of reinforcing bar fracture due to low-cycle fatigue. This study introduces a novel modeling methodology that simulates the fracture of reinforcement in such scenarios, which traditional models often neglect or simplify by imposing maximum strain capacities on reinforcing steel. Our approach integrates a model that accounts for cumulative damage and fracture due to low-cycle fatigue using the newly implemented reinforcement ductile fracture model (RDFM) in OpenSees software. This allows for a detailed representation of cumulative damage and bar fractures, enhancing the predictive accuracy of the cyclic behavior and subsequent strength and stiffness degradation of reinforced concrete walls. Validated against 23 selected reinforced concrete wall cyclic tests, the methodology effectively captures the impact of low-cycle fatigue on concrete walls, contributing to more accurate post-earthquake building assessments. Furthermore, the study proposes a novel calibration for the Equivalent Slenderness Factor ((Psi )) tailored to wall conditions. This research advances our understanding of structural behavior under seismic loads, offering a robust tool for enhancing seismic performance assessments and influencing future design protocols.

There is an increasing demand for precast reinforced concrete (RC) structures due to their undeniable advantages, such as rapid assembly, material standardization, and labor quality. The structural performance of precast RC structures depends not only on the quality of the precast members but also on joints and connections. In recent years, significant attention has been given to replaceable energy-dissipative devices for beam-to-column connections in precast RC structures. This paper proposes a novel moment-resisting energy-dissipative beam end connection in precast RC systems. The proposal is based on the results of intensive experimental and numerical studies conducted in the research project. The beam longitudinal reinforcements are connected to the joint using the developed fuse-type mechanical couplers (FTMCs) that have energy dissipation capability. While the bending moment in the connection is transformed into an axial force couple and transferred by FTMCs, the shear force is transmitted through the steel hinge at the center of the beam. The cyclic behavior of the proposed connection was experimentally investigated, resulting in a robust numerical model for the connection. The experiments demonstrated that the proper configuration of FTMCs in the connection enables reaching a 4% drift ratio without causing major damage to the RC beams. Macro models adopting pivot and kinematic hysteresis approaches for FTMCs were built in the numerical part. The pivot model reasonably and consistently predicted the experimental force–displacement relations of the proposed connections. The ability of the pivot model to estimate the energy dissipation capacities varies almost 6 ~ 16%.

Soil liquefaction significantly contributes to inducing catastrophic damage to the infrastructures. Different ground improvement methods were used widely to improve the seismic resistance of liquefiable deposits to mitigate liquefaction. Use of granular column technique is a popular and well-recognized improvement technique due to its drainage, shear reinforcement, and densification characteristics. However, studies relating to seismic resistance of stone column-reinforced ground against multiple shaking events were limited. Recent seismic events also have shown the possibility of liquefaction and reliquefaction due to multiple seismic events. Considering this, the performance assessment of the granular column technique in liquefiable soil under repeated shaking events is addressed in this study. The possibility of re-using construction and demolition waste concrete aggregates as an alternative to natural aggregates is also attempted to propose sustainability in ground improvement. For experimental testing, a saturated ground having 40% density was prepared and subjected to sequential incremental acceleration loading conditions, i.e., 0.1 g, 0.2 g, 0.3 g, and 0.4 g at 5 Hz loading frequency for 40 s shaking duration using a 1 g Uni-axial shake table. The efficiency of selected ground improvement was evaluated and compared with untreated ground. The experimental results showed that ground reinforced with granular columns performs better up to 0.2 g shaking events in minimizing pore water pressure and settlement. Possibility of column clogging, and inadequate area replacement ratio (5%) affects the performance of column during repeated shaking. Also, irrespective of improvement in in-situ ground density; continuous generation of pore water pressure due to absence of drainage posing reliquefaction potential in untreated ground under repeated shaking events.

This paper presents a comprehensive and integrated databank of the Iranian strong ground motions that occurred from 1973 to 2018. The databank consists of 7196 three-component acceleration records from 3180 earthquakes and 1157 stations in Iran. In this paper, the characteristics of this databank are presented in terms of event, station, and recording distributions. The events are characterized by magnitude in the range 2.4–7.7. Shear wave velocity has been measured and reported at 603 strong motion stations of the databank. In this study, three different empirical techniques are applied to classify the stations. A new method is proposed for site classification based on the correlation coefficient between the horizontal-to-vertical (H/V) response spectral ratios of the ground motion records recorded by each station. All the acceleration time histories in the databank have been uniformly processed using filtering and wavelet de-noising methods to remove high- and low-frequency noise. Moreover, by comparison between the Fourier Amplitude Spectrum (FAS) of the noises detected in all acceleration time series by the filtering and the wavelet de-noising methods, it was determined that the mean FAS of the noises detected by the wavelet de-noising method in most of the frequencies is higher than mean and mode of FAS of the noises detected by the filtering method.

Within the European TURNkey project, a knowledge-based exposure-modelling framework was developed, enabling the consideration of different levels of investigation and data availability. In particular, the proposed framework recognizes various levels and origins of uncertainties, as well as the completeness of a building stock catalogue. Despite substantial efforts, the main question still needs to be answered: How reliable can the developed tools and instruments be if they are not tested and validated by actual events? The L’Aquila 2009 earthquake has been the subject of several analytical strategies to enrich earthquake engineering knowledge. In this study, the information provided by the Italian Observed Damage Database is analyzed, explicitly focusing on the seismic sequence of the L’Aquila 2009 earthquake within the delimited area of the city’s historical center. A second dataset, where the European Macroseismic Scale (EMS-98) was used as a reference, is integrated into the study, and the results are compared. A methodology is implemented for a systematically evaluating the database based on the EMS-98. From the data analysis, a proposal is made to define a comparable EMS-98 building typology and to assign vulnerability classes considering optimistic, pessimistic and most likely criteria. The reliability of the sample is then explored using the knowledge-based exposure modelling framework established by the TURNkey Project. Accuracy is then evaluated through an empirical inspection of frontal (lateral) views available in Google Street View (2022). Images before and after the event are collected and compared with the available data. Intrinsic problems encountered during the process are then listed and discussed, particularly regarding the use of the database, the joint between the studied datasets, and the post-processing required to use the data for damage prognosis. This paper intends to demonstrate how reliable datasets for the building stock, including structural types and corresponding vulnerability classes, can be elaborated. Not least, exposure modelling has to transform the available data into a descriptive form that can be linked directly with the Fragility or Vulnerability Functions, expecting that these assignments are the best suited or representative ones. The data layers provided by the study enable the testing and training of exposure modelling techniques for the selected event and target region.