Pseudo-spectral Acceleration Research Articles

Review Paper on Seismic Analysis of Multi-Storied Reinforced Concrete Building with Fluid Viscous Dampers

Abstract: Frequent earthquakes around the world and the large number of buildings at risk have made it essential to focus on controlling how structures respond to these events. This demand has driven the increased use of structural response control methods globally. This study investigates the seismic performance of multi-storied Reinforced Concrete (RC) Buildings, distinguishing between Regular and Irregular Plan , with a focus on the role of Fluid Viscous Dampers (FVDs). The study aims to quantify the improvements in seismic resilience provided by these damping devices in mitigating the adverse effects of seismic events. Buildings having Regular and Irregular Plans are analyzed, with and without FVD using ETABS2018. The story responses in terms of Pseudo Spectral Accelerations, Maximum Displacement, Story Drift and Story Shear have been compared. The results of the Time History Analysis represent the effectiveness of dampers in improving the structural response and the damping demand on structural systems

Uncertainty propagation from crustal geologies to rock-site ground motion with a Fourier Neural Operator

Seismic hazard analyses in the area of a nuclear installation must account for a large number of uncertainties, including limited geological knowledge. Combining the accuracy of physics-based simulations with the expressivity of deep neural networks can help to quantify the influence of crustal geological uncertainties on surface ground motion. This work uses a Factorised Fourier Neural Operator (F-FNO) to learn the relationship between 3D crustal heterogeneous geologies and time-dependent wavefields at the Earth’s surface up to a 5 Hz maximal frequency. The F-FNO is pretrained on a generic database and then, fine-tuned with only 250 samples targeted to the Le Teil region (South-Eastern France). The F-FNO correctly predicts the wave arrival times and the main wavefronts. As quantified by Goodness-Of-Fit (GOF) criteria, 83% of predictions have excellent phase GOF and 75% have very good envelope GOF. The Peak Ground Velocity and Pseudo-Spectral Acceleration are also accurate, especially for geologies with low-to-moderate heterogeneities. Thanks to the F-FNO speed, ground motion distributions can be easily computed and provide safety margins compared to 1D simulations. These results show that the F-FNO is an efficient surrogate model to quantify the range of ground motion a nuclear installation could face in the presence of geological uncertainties.

Design response spectrum based on shock-waveform decomposition method

This study applies the shock-waveform (SW) decomposition method, originally developed for mechanical shock analysis, to earthquake ground motions. It reveals a general shape similarity between the envelope of the Pseudo-Spectral Accelerations (PSAs) of SW decomposed components and the PSA of the corresponding ground motion. Based on this similarity, a novel method to determine the characteristic period Tg, the long-period transition period TD, the shape correction period Tβ, and the Design Response Spectrum (DRS) is proposed and evaluated. New methods to determine Tg, TD and Tβ from the signal decomposition perspective are integrated into the normalized DRS in Eurocode 8–2022, enabling the construction of the normalized DRS based on SW method (SWDRS). Furthermore, simple ground motion attenuation regression equations are derived to relate the parameters (Tg, TD, Tβ) and the corresponding spectral ordinates of the normalized SWDRS model with seismic magnitude and site conditions. The SWDRS model is validated by randomly selecting two sites in United States. For each site, the SWDRS is determined by using the attenuation regression equations and the DRS spectral plateau value from the official seismic hazard map. Comparisons between the SWDRS, the latest local DRS, and the severest historical PSA recorded at the specific site demonstrate that the SWDRS provides more accurate spectral values over intermediate- and long-period ranges for structural seismic design.

Impact of Multiple Faults on the Maximum Credible Ground-Motion Parameters of Large Earthquakes at a Near-Field Site

The ground-motion simulation of regional-specific earthquake scenarios is crucial for the seismic design of key facilities. Herein, we considered parameter uncertainty in ground-motion simulations and the impact of multiple faults when determining the maximum credible ground-motion parameters of large earthquakes at a near-field dam. The source models of the Daju–Lijiang, Xiaozhongdian–Daju, and Longpan–Qiaohou faults were established based on geological and geophysical data. Although the method for identifying asperity is not yet mature and still faces many difficulties, it provides an opportunity to identify the non-uniform slip distribution on the rupture plane by earthquake scenarios. A multi-scheme stochastic finite-fault simulation method was then used to estimate the minimum; mean; maximum; and 50th-, 84th-, and 95th-percentile values of the peak ground acceleration and pseudo-spectral acceleration response spectra. The results showed that the Longpan–Qiaohou fault can generate the largest ground-motion parameters compared with the other two faults. Moreover, this result was supported by the statistical analysis of the results of twelve thousand simulations of these three faults. Thus, it can be concluded that the maximum credible ground-motion parameters are represented by the 84th-percentile pseudo-spectral acceleration response spectrum of the Longpan–Qiaohou fault. This finding will benefit the seismic safety design of the target dam. More importantly, this multi-scheme method can be applied to other key facilities to obtain reasonable ground-motion parameters.

Use of spatial autocorrelation of microtremor using L- and triangle- arrays for estimations of S-wave velocity model and soil response at ITS Surabaya

Abstract Institut Teknologi Sepuluh Nopember (ITS) Surabaya is geologically vulnerable to earthquake hazards. Therefore, preparedness is necessary to address emergencies and risks caused by earthquake at ITS Surabaya. In this study, dispersion curve were obtained through the analysis of microtremor data using the Spatial Autocorrelation (SPAC) method. Microtremor data acquisition was performed at the PLN ITS Futsal Field using L- and triangle-arrays. We successfully got dispersion curves from both arrays. The shear wave velocity (Vs) profile and the best model of Vs profile for each array were obtained by inverting the dispersion curves. By using a two-layer model, the first layer produces identical velocities with a depth of 5.44 meters for an L-array and 5.02 meters for a triangle array. In the second layer, the resulting velocities for each array have quite a difference. The best model of Vs profile for both arrays were used to analyse 1D soil response with a linear approach in the frequency domain. Parameters including Peak Ground Acceleration (PGA), 5% damped Pseudo Spectral Acceleration (PSA), and Fourier Amplitude Ratio (FAR) were obtained from the linear approach analysis that could describe the ground’s response to seismic waves. Vs influences the soil response, the higher the difference in Vs values of a layer with the layer below it (half-space), the higher the increase in PGA, PSA, and FAR.

Vertical Ground Motion Prediction Equations for Interplate and Intermediate-Depth Intraslab Earthquakes at Mexico City’s Hill Zone

ABSTRACT We present ground motion prediction models for spectral pseudo acceleration (5% damping), peak ground velocity, and peak ground acceleration values from interplate and intermediate-depth intraslab earthquakes at the so-called hill zone of Mexico City for the vertical component and the vertical-to-horizontal ratio case. There are no previous models for the vertical component from these events in Mexico City. The prediction equations were developed as a function of magnitude and also as a function of distance to the fault surface of earthquakes by using 30 and 26 seismic recordings from interplate (1965–2022) and intermediate-depth intraslab (1964–2017) earthquakes at the hill zone of the city by using Bayesian regression analyses. The attenuation models are developed for interplate events for distances ranging from 280 km to over 500 km and Mw from 6 to 8.1, and for intraslab events for distances to the fault surface ranging from 100 km up to about 600 km, focal depths from 40 km to over 120 km and Mw from 5 to 8.2. Nevertheless, since at large distances ground motions are generally weak, we recommend the applicability of the proposed models to be restricted to up to 400 km. The models are adequate to estimating the seismic hazard at the hill zone of Mexico City, as proved by contrasting analytical versus empirical seismic exceedance rates for the vertical component.

A New Spatial Variation Model for Ground-Motion Intensities Combined with Correlation and Coherency

Abstract Regional seismic risk or loss assessments generally require simulation of spatially distributed ground motions using multiple intensity measures. Hence, in this study, ground-motion model estimation is performed with a spatial correlation. Previously, many researchers have analyzed spatial correlations and developed empirical models using ground-motion recordings. In this study, ground motions occurring in California between 2019 and 2023 were used to analyze spatial correlations using semivariograms for the peak ground acceleration and pseudospectral acceleration in various spectral periods. Based on the analysis results, two aspects need to be revised in the conventional correlation model: (1) the empirical exponential model cannot reasonably reflect the target spatial correlation at a separation distance <10 km, and (2) the variation in the spatial correlation ground-motion intensity cannot be described at a small separation distance <1 km. Owing to these limitations, we revised the fitting model of the semivariogram to better characterize the spatial correlation. In the model, another function called coherency, replaced the spatial correlation to characterize the variation in the Fourier phase rather than the intensity within a separation distance <1 km. This research shows that the spatial variation in any region can be analyzed by combining the coherence and correlation functions for practical seismic-risk or loss assessment problems.

Hybrid Empirical Ground-Motion Models for the Island of Hawaii Based on an Updated Strong Ground-Motion Database

ABSTRACT In this study, we develop ground-motion models (GMMs) for the Island of Hawaii. This area has been the site of several significant earthquake events with a growing database of strong ground-motion observations. Ground-motion modeling on the Island of Hawaii is challenging due to different anelastic attenuation characteristics, the volcanic origin of some of the events, and event depth distribution. Only a few GMMs have been developed for the Island of Hawaii. In this study, we apply a hybrid empirical method (HEM) to develop two separate GMMs for shallow (hypocentral depth ≤ 20 km) and deep (hypocentral depth > 20 km) earthquakes on the Island of Hawaii. We utilize the ratio of the stochastic point-source model in the target and host regions as an appropriate adjustment factor. We apply these adjustment factors to convert the GMMs from the host (western North America) to the target (Island of Hawaii) region. We considered five GMMs proposed in the Next Generation Attenuation Phase 2 project by the Pacific Earthquake Engineering Research Center to model ground motions in the host region. We developed GMMs to predict peak ground acceleration and 5%-damped pseudospectral acceleration at periods T = 0.01–10 s, for moment magnitudes (M) in the range of 3–7.5, and for Joyner–Boore distances in the RJB≤200 km range. The applicability of HEM to develop GMMs for the Island of Hawaii and the growing strong ground-motion data result in further improvements in the capability of GMMs.

Broadband Ground-Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation

ABSTRACT We present a data-driven framework for ground-motion synthesis that generates three-component acceleration time histories conditioned on moment magnitude (M), rupture distance (Rrup), time-average shear-wave velocity at the top 30 m (VS30), and style of faulting. We use a Generative Adversarial Neural Operator (GANO)—a resolution invariant architecture that guarantees model training independent of the data sampling frequency. We first present the conditional ground-motion synthesis algorithm (cGM-GANO) and discuss its advantages compared to the previous work. We next train cGM-GANO on simulated ground motions generated by the Southern California Earthquake Center Broadband Platform (BBP) and on recorded the Kiban–Kyoshin network (KiK-net) data, and show that the model can learn the overall magnitude, distance, and VS30 scaling of effective amplitude spectra (EAS) ordinates and pseudospectral accelerations (PSA). Results specifically show that cGM-GANO produces consistent median scaling with the training data for the corresponding tectonic environments over a wide range of frequencies for scenarios with sufficient data coverage. For the BBP dataset, cGM-GANO cannot learn the ground-motion scaling of the stochastic frequency components (f > 1 Hz); for the KiK-net dataset, the largest misfit is observed at short distances (Rrup<50 km) and for soft-soil conditions (VS30<200 m/s) due to the scarcity of such data. Except for these conditions, the aleatory variability of EAS and PSA are captured reasonably well. Finally, cGM-GANO produces similar median scaling to traditional ground-motion models (GMMs) for frequencies greater than 1 Hz for both PSA and EAS but underestimates the aleatory variability of EAS. Discrepancies in the comparisons between the synthetic ground motions and GMMs are attributed to inconsistencies between the training dataset and the datasets used in GMM development. Our pilot study demonstrates GANO’s potential for efficient synthesis of broadband ground motions.

The impact of blast vibration on the site response

In civil engineering, one of the main problems is the stability of structures. Blast vibrations can be one of several elements influencing the stability of these structures. In order to prevent any effects on the structures, the maximum suggested values of the peak particle velocity and frequency from the blast are generally determined using the existing appropriate government rules and industry standards as reference. In this paper, the effect of these vibration on the site response has been investigated. Parameters such as peak ground acceleration, Pseudo spectral acceleration and maximum stress and strain has been compared for two different soil models. The results indicate that the soft soil has a significant impact and amplifies the input parameters considerably.

An equivalent point-source stochastic model of the NGA-East ground-motion models

The main objective of this study is to estimate seismological parameters in Central and Eastern North America (CENA), including the geometrical spreading, anelastic attenuation, stress parameter, and site attenuation parameters. In this study, we use particle swarm optimization (PSO) to invert a weighted average of the median 5%-damped pseudo-spectral acceleration (PSA) predicted from the Next Generation Attenuation-East (NGA-East) ground-motion models (GMMs) to develop a point-source stochastic GMM with a well-constrained set of ground-motion parameters. Magnitude-specific inversions are performed for moment magnitude ranges M = 4.0–8.0, rupture distances Rrup = 1–1000 km, and periods T = 0.01–10 s, and National Earthquake Hazard Reduction Program site class A conditions. The result of this study yields a single stochastic GMM that yields PSA values similar to the median NGA-East GMMs. The parameters derived from this study can be used for the hybrid empirical method (HEM) applications. This study is the first to perform a formal inversion using the GMMs developed for the NGA-East project. The approach has been validated using simulated small-to-moderate magnitude and large-magnitude data derived from the NGA-West2 GMMs.

The 2023 US 50-State National Seismic Hazard Model: Overview and implications

The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard (both increases and decreases compared to previous NSHMs) are substantial because the new model considers more data and updated earthquake rupture forecasts and ground-motion components. In developing the 2023 model, we tried to apply best available or applicable science based on advice of co-authors, more than 50 reviewers, and hundreds of hazard scientists and end-users, who attended public workshops and provided technical inputs. The hazard assessment incorporates new catalogs, declustering algorithms, gridded seismicity models, magnitude-scaling equations, fault-based structural and deformation models, multi-fault earthquake rupture forecast models, semi-empirical and simulation-based ground-motion models, and site amplification models conditioned on shear-wave velocities of the upper 30 m of soil and deeper sedimentary basin structures. Seismic hazard calculations yield hazard curves at hundreds of thousands of sites, ground-motion maps, uniform-hazard response spectra, and disaggregations developed for pseudo-spectral accelerations at 21 oscillator periods and two peak parameters, Modified Mercalli Intensity, and 8 site classes required by building codes and other public policy applications. Tests show the new model is consistent with past ShakeMap intensity observations. Sensitivity and uncertainty assessments ensure resulting ground motions are compatible with known hazard information and highlight the range and causes of variability in ground motions. We produce several impact products including building seismic design criteria, intensity maps, planning scenarios, and engineering risk assessments showing the potential physical and social impacts. These applications provide a basis for assessing, planning, and mitigating the effects of future earthquakes.

A simple and flexible bootstrap-based framework to quantify epistemic uncertainty of ground motion models by light gradient boosting machine

Ground motion models (GMM) incorporating proper epistemic uncertainty quantification are fundamental for seismic hazard analysis, structural seismic design, and earthquake risk management. However, this critical uncertainty has not been systematically addressed in recently prevalent machine learning (ML)-based GMMs. To rectify this gap, a straightforward and flexible framework based on bootstrapping is proposed for generic ML algorithms. Specifically, a group of datasets are generated through bootstrap resampling, each employed to develop an individual GMM. In the inference phase, the epistemic uncertainty is represented by the prediction samples from this ensemble of models. In case study, the Light Gradient Boosting Machine (LGBM), is applied to establish a GMM on the NGA-West2 database. Overfitting is mitigated by early-stopping, and its implications on uncertainty components and random-effect variability are thoroughly examined. Compared to artificial neural network (ANN) in literature, our work demonstrates a decrease in the standard deviation of inter- and intra-event variability by an average of 0.051 and 0.140, respectively. Moreover, our model adeptly captures the heteroscedasticity of epistemic uncertainty, particularly over different regions and within the range of the metadata with limited data. The significance of epistemic uncertainty is highlighted by its potential to diminish the statistical significance of seismic scaling effects at short-period pseudo spectral acceleration (PSA) for great events and at rock sites.

Ensemble Region-Specific GMMs for Subduction Earthquakes

Abstract This study develops data-driven global and region-specific ground-motion models (GMMs) for subduction earthquakes using a weighted average ensemble model to combine four different nonparametric supervised machine-learning (ML) algorithms, including an artificial neural network, a kernel ridge regressor, a random forest regressor, and a support vector regressor. To achieve this goal, we train individual models using a subset of the Next Generation Attenuation-Subduction (NGA-Sub) data set, including 9559 recordings out of 153 interface and intraslab earthquakes recorded at 3202 different stations. A grid search is used to find each model’s best hyperparameters. Then, we use an equally weighted average ensemble approach to combine these four models. Ensemble modeling is a technique that combines the strengths of multiple ML algorithms to mitigate their weaknesses. The ensemble model considers moment magnitude (M), rupture distance (Rrup), time-averaged shear-wave velocity in the upper 30 m (VS30), and depth to the top of the rupture plane (Ztor), as well as tectonic and region as input parameters, and predicts various median orientation-independent horizontal component ground-motion intensity measures such as peak ground displacement, peak ground velocity, peak ground acceleration, and 5%-damped pseudospectral acceleration values at spectral periods of 0.01–10 s in log scale. Although no functional form is defined, the response spectra and the distance and magnitude scaling trends of the weighted average ensemble model are consistent and comparable with the NGA-Sub GMMs, with slightly lower standard deviations. A mixed effects regression analysis is used to partition the total aleatory variability into between-event, between-station, and event-site-corrected components. The derived global GMMs are applicable to interface earthquakes with M 4.9–9.12, 14≤Rrup≤1000 km, and Ztor≤47 km for sites having VS30values between 95 and 2230 m/s. For intraslab events, the derived global GMMs are applicable to M 4.0–8.0, 28≤Rrup≤1000 km, and 30≤Ztor≤200 km for sites having VS30 values between 95 and 2100 m/s.

Response of Geologic Units to The Ground Parameters of Tarutung Earthquake 2022 Mw 5.8 : A Preliminary Study

On 1st October 2022, a moderate crustal earthquake with Mw 5.8 occurred in the northen part of Tarutung region and was strongly felt by the local peoples and followed by massive damages. The occurrence of the Tarutung earthquake was firstly assumed in the southern part of the Renun fault then updated to the pull-apart system of Toru fault. Here, we concern about the ground paramaters that generated a massive shaking and connect with the recent geologic units beneath the Tarutung region. The peak ground acceleration (PGA) and peak ground velocity (PGV) clearly show an amplification case may arise in the basin formation that consists of Alluvium Formation whereas the attenuation to the west and east part with Martimbang and Sipoholon Caldera Formation. The PGV was ranging at 0 – 10 cm/s and the PGA was ranging at 0% – 16% gal which are suitable with the intensity range at 3 – 6 MMI. The PGV, PGA and intensity relationship show a possibility of the building damage percentage is up to 80% and 50% of the surrounding area may potentially experience a complete damage. The pseudo-spectral acceleration (PSV) at 0.3s, 1.0s, and 3.0s also show a potential damage that can be found at low-moderate building structure with 8% - 16% gal. The ground parameters show an empirical relationship that can be used to assess the possible of geologic units in the Tarutung region. Furthermore, our result benefits can be applied to support the mitigation program and environmental planning in Tarutung region in the near future.

Ground motion models for Fourier amplitude spectra and response spectra using Machine learning techniques

AbstractOne of the main objectives in engineering seismology or in seismic hazard studies is to estimate the possible ground motion for a given earthquake scenario. In the sparse data regions mostly the ground motion models (GMM) are developed using either seismological models or hybrid empirical approaches. However, if these GMMs do not accommodate the regional seismological attributes, a large uncertainty in ground motion estimates is possible. To overcome this concern, scaling 5% damped Pseudo Spectral Acceleration (PSA) from Fourier amplitude spectra (FAS) proves to be physically consistent as it can capture both spatial and temporal characteristics of the ground motion. Hence, the present study aims to develop a GMM for PSA using FAS and significant duration as the predictor variables. However, since there are few GMMs available for FAS, the current study also aims to develop a GMM for FAS using the earthquake parameters as the predictor variables for intraplate regions. This article employs an Artificial Neural Network (ANN) to develop both GMMs using the Next Generation Attenuation (NGA)‐East database for both horizontal (Effective Amplitude spectra for FAS and RotD50 component for PSA) and vertical components. To verify the performance of the developed models, the residuals analysis and parametric studies have been performed. The parametric study shows that the GMMs can capture the magnitude and distance scaling consistent with the observations. Further, the PSA GMM compared with the global GMMs and it is observed that the predictions lie well within the median of all the available models, proving the models’ effectiveness in estimating the ground motion predictions for future data. The developed model can be used only within the considered ranges of the predicted variables such as rupture distances between [19.05–1000] km, the Mw ranges from [3.12–5.74] with Vs30 in the range of [209–2000] m/s.

Regional spectral characteristics, quality factor and site responses in western-central Sichuan, China (II): Application to stochastic ground motion simulation

The stochastic finite-fault approach was used to model the 2022 Luding earthquake with a magnitude of Mw 6.6 in China at 16 selected near-field stations. To investigate the impact of the site effect on the synthetic results, two models were taken into account: One model was obtained from the generalized inversion technique, and the other model was obtained from the horizontal-to-vertical spectral ratio method. The high-frequency attenuation parameter was estimated to be 0.040 s and the value of 4.0 MPa for the stress parameter was adopted. Comparisons of the recorded and simulated Fourier amplitude spectrum, pseudospectral acceleration, peak ground acceleration, and peak ground velocity were performed to investigate the capability of the selected input parameters. In addition, the model bias, simulated peak ground acceleration and peak ground velocity were calculated by the local site amplification estimated by the two methods. The results show that the site effects estimated by the generalized inversion technique can well simulate the high-frequency response spectra and Fourier amplitude spectrum and can provide peak ground acceleration and peak ground velocity values consistent with the recorded values, while the local site amplification roughly calculated by the horizontal-to-vertical ratio method underestimates the main ground motion characteristics. Furthermore, strong-motion records with the same magnitude but different hypocentral distance ranges in the generalized inversion technique are used to estimate near-surface site effects, which shows that the distance range has a small impact on the estimation of local site amplification. Model parameters that performed well in this study provide confidence in understanding and quantifying seismic hazards in the Luding area from earthquake scenarios with different magnitudes.

A site amplification model for Switzerland based on site-condition indicators and incorporating local response as measured at seismic stations

AbstractThe spatial estimation of the soil response is one of the key ingredients for the modelling of earthquake risk. We present a ground motion amplification model for Switzerland, developed as part of a national-scale earthquake risk model. The amplification model is based on local estimates of soil response derived for about 240 instrumented sites in Switzerland using regional seismicity data by means of empirical spectral modelling techniques. These local measures are then correlated to continuous layers of topographic and geological soil condition indicators (multi-scale topographic slopes, a lithological classification of the soil, a national geological model of bedrock depth) and finally mapped at the national scale resorting to regression kriging as geostatistical interpolation technique. The obtained model includes amplification maps for PGV (peak ground velocity), PSA (pseudo-spectral acceleration) at periods of 1.0, 0.6 and 0.3 s; the modelled amplification represents the linear soil response, relative to a reference rock profile with VS30 (time-averaged shear-wave velocity in the uppermost 30 m of soil column) = 1105 m/s. Each of these amplification maps is accompanied by two layers quantifying its site-to-site and single-site, within event variabilities, respectively (epistemic and aleatory uncertainties). The PGV, PSA(1.0 s) and PSA(0.3 s) maps are additionally translated to macroseismic intensity aggravation layers. The national-scale amplification model is validated by comparing it with empirical measurements of soil response at stations not included in the calibration dataset, with existing city-scale amplification models and with macroseismic intensity observations from historical earthquakes. The model is also included in the Swiss ShakeMap workflow.

Improving the Seismic Performance of Steel Frames under Mainshock–Aftershock Using Post-Tensioned Connections

In this study, the seismic responses of moment-resisting steel frames (MRSFs) with welded and post-tensioned connections under 28 artificial seismic sequences (mainshock–aftershock) are compared. For this aim, the mainshock are scaled at different ground motion intensity levels as a function of the spectral pseudo-acceleration corresponding to the fundamental period of vibration of the structure Sa(T1), whereas different intensity levels of the aftershocks are used for a percentage of the peak maximum acceleration of the mainshock. The seismic performance comparison of both structural systems is computed for the maximum, residual inter-story drift and hysteretic energy demands. The results show that post-tensioned frames significantly reduce the structural demands, especially in the case of residual inter-story drifts and hysteretic energy in comparison with moment-resisting steel frames with welded connections. The reductions in the structural response tend to be larger as the intensity of the aftershock tends to increase. Therefore, it is concluded that the use of post-tensioned connections is a great alternative to mitigate the seismic response of buildings subjected to seismic sequences.

A relocated earthquake catalog and ground motion database for the southern East African rift system

The southern East African rift system (EARS) is geologically rare considering its early-stage continental rift setting combined with a deep seismogenic zone. Several seismically vulnerable communities are located within this tectonically active region, resulting in a significant seismic risk. However, the ground motion and seismic hazard analyzes necessary to increase the earthquake preparedness in the region have been limited due to the relatively short instrumentation history and scarce ground motion data available. Here, we present a newly compiled ground motion database for the southern EARS which is critically lacking and preventing local ground motion studies. This database includes a regional catalog of 882 earthquakes spanning 1994–2022 (magnitudes 3–6.5) with available waveform records within epicentral distances of 300 km. Three different velocity models were used to relocate 256, 255, and 252 events, respectively, to quantify depth sensitivity, relocating events down to depths of 35–40 km. The final database contains 10,725 time-series records from 353 stations along with P- and S-wave phase arrivals for each record. The ground motion database contains peak ground acceleration and velocity and 5% damped pseudo-spectral acceleration for 291 frequencies from 1.0 to 30 Hz for the horizontal components. In addition, a Fourier amplitude spectrum table for 212 frequencies from 0.1 to 30 Hz is included. The database is accessible through the ISC repository ( https://doi.org/10.31905/4GGVBFBE ).