Strong Ground Motion Research Articles

Parametric study on a resilient hybrid steel-shape memory alloy yielding damper

A critical factor obstructing structural resilience is residual deformation after a damaging event. The search for a solution for removing residual deformation has led to the consideration of Shape Memory Alloys (SMAs) that can undergo large deformations and return to their original undeformed shape. This study focuses on an innovative hybrid yielding steel-SMA damper that uses monofilament wire loops. Because of numerous design parameters that affect the performance of this hybrid damper, this research aims to carry out a parametric study to optimize the damper’s performance. The study was conducted at the device level as well as a structural level. At the device level, the key design parameters, including SMA to steel ratio, max imposed strain, and the length of the elements, were evaluated. At the same time, the damper’s effect on the seismic performance of low, mid, and high-rise structures was investigated at the structural-level study. In the end, the results showed that using the damper in strong ground motions successfully reduced the maximum residual drift up to 71%, 97%, and 92% for low, mid, and high-rise structures, respectively. Therefore, it was concluded that the damper could add the self-centering ability to hysteretic dampers while maintaining satisfactory energy dissipation performance. Furthermore, some of the advantages claimed by the developers, including versatility in design and performance, adequate load resistance, and stable behavior, were also confirmed in this study.

Sensitivity Study of Seismic Amplification Effect of Large-Scale Sichuan Basin on Key Parameters During the Great Wenchuan Earthquake

The effect of soil parameters on basin amplification effect has been widely investigated, especially for the small and medium-sized basins under plane wave incidence or point source ruptures. However, the sensitivities of seismic amplification effect of large-scale basins with respect to soil parameters during great earthquakes with tremendous rupture faults have obtained relatively less attention. In this paper, based on the established three-dimensional Sichuan basin model, the effects of four material parameters of the basin sediments, including the shear wave velocity, Poisson’s ratio, and the shear quality factor of the Quaternary sediment, as well as the velocity of the rock above the basin crystalline basement (which will be referred as SVQS, PRQS, QFQS, and VCBR, respectively), on the long-period wave amplification patterns of the Sichuan basin during the great Wenchuan earthquake are investigated by using the spectral element method and parallel computing technique. The results show the following: (1) SVQS has the greatest influence on the basin horizontal component ground motions, while the vertical component is comparably insensitive to it. (2) PRQS demonstrates comparable effects on the horizontal and vertical basin ground motions. With the increase of PRQS, the amplitudes and regions of the strong shakings both become smaller. However, the influence of PRQS is less significant compared with SVQS and VCBR. (3) QFQS mainly affects the relatively high-frequency motions inside the basin, and the low-frequency motions are generally insensitive to it. With the reduction of QFQS, the amplitudes and regions of the basin strong ground motions turn a little smaller, but the distribution features are generally unchanged. (4) Effects of VCBR on the horizontal and vertical component basin ground motions are opposite. With the growth of VCBR, the amplitudes and areas of strong horizontal motions increase consequently, but they decrease for the vertical component.

Shear-wave velocity determination by combining data from passive and active source field investigations in Kumamoto city, Japan

We present the 1D subsoil structure and local site effects at KUMA strong ground motion station in Kumamoto City, Japan. We analyze data from a field campaign conducted in the framework of the Blind Prediction BP1 test of the 6th IASPEI/IAEE International Symposium: Effects of Surface Geology on Seismic Motion. In parallel with other participants of the BP1 test, we process data from passive and active source measurements aiming to determine the shear-wave velocity, Vs, structure and the site response at KUMA station. Passive measurements are associated to five microtremor arrays. In each array, seven seismometers have been deployed in a common-center triangle shape, recording microtremors simultaneously for 1 to 2 h. The vertical component of microtremors was analyzed using the spatial autocorrelation (SPAC) method. Cross-correlation coefficients were computed for all station pairs available for each array. By fitting the average SPAC’s coefficients to the first-kind zero-order Bessel function, J0, and assuming that microtremors primarily comprise fundamental mode Rayleigh waves, phase velocity dispersion curves were determined. Phase velocity values for frequencies > 15 Hz were obtained from data of a close-by active source geophone profile. We integrated the data with those of the passive measurements and obtained an experimental phase velocity dispersion curve. The resulting curve shows low velocity variation, from 150 to 200 m/s, in the surface layers, whereas significant dispersion appears in frequencies below 2.5 Hz. By inverting this curve, we achieved to determine the 1D shear-wave velocity structure at KUMA station. Site response characteristics were determined by applying the Horizontal-to-Vertical-Spectral-Ratios method. Significantly amplified peaks in the frequency range between 0.3 to 1.5 Hz dominate HVSR spectral ratios. These peaks correspond to resonant frequencies of soils and originate from different impedance contrasts within the substratum of the site.Graphical

Significance of Pulse-Like Ground Motions and Directivity Effects in Moderate Earthquakes: The Example of the Mw 6.1 Gölyaka-Düzce Earthquake on 23 November 2022

ABSTRACT The 1400 km long North Anatolian Fault Zone in Türkiye runs through numerous densely populated regions, including the city of Düzce that was recently hit by an Mw 6.1 earthquake on 23 November 2022. This was the first moderate event in the region after the devastating Mw 7.2 earthquake in 1999, which cost the lives of over 700 people. Despite its moderate size, the earthquake caused unexpected severe damage to a significant number of buildings, as reported by local institutions (Disaster and Emergency Management Presidency, AFAD). It is well established that ground motions in the near field can lead to increased damage due to near-field domain effects, such as ground-motion pulses and directivity effects (i.e., when the site is aligned with rupture propagation). We examine potential near-field effects using the strong ground motion database of AFAD-Turkish Accelerometric Database and Analysis Systems. To achieve this, we first analyze the behavior of the ground-motion intensities in terms of their spatial distribution and observe higher peak ground velocity than expected by ground-motion models in spatially constrained azimuthal ranges. Furthermore, we find that the majority of the near-fault recordings contain velocity pulses that are primary concentrated on the fault-parallel component. This outcome questions the widely accepted understanding from the previous studies, which mainly suggested that impulsive ground motions that are associated with directivity effects primarily occur on the fault-normal component of large-magnitude events.

Potential Seismic Hazard in Seoul, South Korea: A Comprehensive Analysis of Geology, Seismic, and Geophysical Field Observations, Historical Earthquakes, and Strong Ground Motions

ABSTRACT A series of moderate-size (Mw 4.0–6.0) earthquakes occurred in South Korea after the 2011 Mw 9.0 Tohoku–Oki megathrust earthquake, incurring public concern about possible occurrence of devastating earthquakes in Seoul—the capital city of South Korea, where historical seismic damage was reported. The seismicity is distributed in Seoul, being dominated by strike-slip earthquakes. The fault planes are oriented in north-northeast–south-southwest, which is a favorable direction to respond to the ambient stress field. Higher rates of seismicity are observed in the northwestern Seoul at depths of <10 km. Micro-to-small earthquakes occur episodically in the central Seoul along the Chugaryeong fault system that traverses Seoul in north–south. Seismic, geophysical, and geological properties illuminate the fault structures. Stochastic modeling of ground motions reproduces the seismic damages of historical earthquakes reasonably, supporting the occurrence of devastating historical earthquakes in Seoul. The seismicity distribution, focal mechanism solutions, geological features, and seismic and geophysical properties suggest the possible presence of earthquake-spawning blind faults in Seoul. The peak ground motions are assessed for moderate-size scenario earthquakes (Mw 5.4 with focal depth of 7 km) at six representative subregions in Seoul. The upper bounds of peak ground accelerations reach ∼11 m/s2. The seismic damage potentials for moderate-size earthquakes are high in most areas of Seoul, particularly around river sides covered by alluvium.

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.

Utilising Artificial Neural Networks for Assessing Seismic Demands of Buckling Restrained Braces Due to Pulse-like Motions

Buckling restrained brace frames (BRBFs) exhibit exceptional lateral stiffness, load-bearing capacity, and energy dissipation properties, rendering them a highly promising choice for regions susceptible to seismic activity. The precise and expeditious prediction of seismic demands on BRBFs is a crucial and challenging task. In this paper, the potential of artificial neural networks (ANNs) to predict the seismic demands of BRBFs is explored. The study presents the characteristics and modelling of prototype BRBFs with different numbers of stories and material properties, utilising the OpenSees software (Version 2.5.0) for numerical simulations. The seismic performance of the BRBFs is evaluated using 91 near-fault pulse-like ground motions, and the maximum inter-storey drift ratio (MIDR) and global drift ratio (GDR) are recorded as a measure of seismic demand. ANNs are then trained to predict the MIDR and GDR of the selected prototypes. The model’s performance is assessed by analysing the residuals and error metrics and then comparing the trend of the results with the real dataset. Feature selection is utilised to decrease the complexity of the problem, with spectral acceleration at the fundamental period (T) of the structure (Sa), peak ground acceleration (PGA), peak ground velocity (PGV), and T being the primary factors impacting seismic demand estimation. The findings demonstrate the effectiveness of the proposed ANN approach in accurately predicting the seismic demands of BRBFs.

Inelastic response spectra for an integrated displacement and energy-based seismic design (DEBD) of structures

The severe socio-economic impact of recent earthquakes has further highlighted the crucial need for a paradigm shift in performance-based design criteria and objectives towards a low-damage design philosophy, in order to reduce losses in terms of human lives, repair/reconstruction costs, and recovery time (deaths, dollars and downtime). Currently, displacement-based parameters are typically adopted to design/assess the seismic performance of the structures, by limiting the maximum displacement or the maximum interstorey drift ratio (IDR) reached by the structure under different earthquake intensities. However and arguably, displacement-based quantities are characterized by inherent weaknesses, since, for instance, they are not cumulated parameters, thus not able to capture directly the effects of multiple cycles, deterioration and damage cumulation. Therefore, in the last decades, energy-based approaches were investigated and developed in order to establish alternative engineering demand parameters for the assessment of post-event damage through a dynamic energy balance. Towards the main goal of developing an integrated Displacement and Energy-Based Design/assessment procedure (DEBD) for actual use in practice, this research work proposes an innovative approach based on the use of inelastic spectra correlating the energy components with the corresponding maximum displacement response parameters of the structure. In practical terms, the proposal is to further integrate and develop the well-known Direct Displacement-Based Design, by directly adopting the hysteretic energy as an additional design parameter. The energy inelastic spectra are developed through an extensive parametric analysis of Single-Degree-of-Freedom (SDoF) systems, with different nonlinear hysteretic models. In such an approach, the maximum seismic energy demand imparted to a structure can be directly predicted and controlled, whilst distinguishing the various components of the energy balance, including the hysteretic one. The effects of near-field and far-field earthquakes are also investigated. Results show that in the first case the seismic demand is concentrated in the peak of a few large cycles that absorb the demand energy induced by the high component in peak ground velocity in the second case the higher equivalent number of plastic cycles tends to become critical for structures with inadequate structural details and prone to suffer by cumulative cycles and overall plastic fatigue mechanisms.

Pre-earthquake fuzzy logic-based rapid hazard assessment of reinforced concrete buildings

The main purpose of this paper is to present a rapid building assessment fuzzy logic (FL) modelling for risk assessment based on expert construction engineering verbal informatics. Before an earthquake, a set of input expert assessment variables are transformed into five types of hazard categorization as "no damage", "slight damage", "moderate damage", "severe damage", and "collapse". Main variables are reported by expert engineers based on visual inspection of structural components in addition to the building location's peak ground velocity (PGV) micro zonation numerical value, soil type and building's material information. Each input variable and output hazard class is fuzzified. A valid set of fuzzy rule base components is written based on input variables, each of which has an appropriate output hazard class. The fuzzy hazard assessment model has input and output variables in terms of fuzzy sets. Thus, the overall model output is in the form of a fuzzy set and then defuzzified to find the percentage of each hazard class for a single building. The application of this fuzzy logic model is presented for twenty existing reinforced concrete buildings, and the final hazard categories of these buildings are presented with interpretations and recommendations.

Source Scaling and Ground-Motion Variability along the East Anatolian Fault

Abstract We investigate the source scaling and ground-motion variability of 1585 earthquakes with Mw>3 occurring along the East Anatolian fault since 2010. We compile a dataset of 17,691 Fourier amplitude spectra of S waves recorded by 186 stations. A spectral decomposition is applied to isolate the source contribution from propagation and site effects. Source spectra are fit with Brune’s model to estimate seismic moment and corner frequency and to compute the stress drop Δσ. The 10th, 50th, and 90th percentiles of the Δσ distribution are 0.18, 0.51, and 1.69 MPa, respectively, and the average Δσ increases with earthquake magnitude. For the two mainshocks of the 2023 sequence, the estimated Δσ is about 13 MPa, significantly larger than the Δσ of the smaller events. At intermediate and high frequencies, the interevent residuals are correlated with Δσ. When recorded peak ground accelerations and velocities for Mw<6 are compared with the predictions from ground-motion models proposed in the literature, the negative value of the average interevent residuals is consistent with low values of Δσ. Contrariwise, the average residuals for the peak parameter of the Mw 7.8 and 7.5 mainshocks of the 2023 sequence are almost zero, but with distance dependencies.

A Mathematical Approach for Predicting Sufficient Separation Gap between Adjacent Buildings to Avoid Earthquake-Induced Pounding

Studies on earthquake-related damage underscore that buildings are vulnerable to significant harm or even collapse during moderate to strong ground motions. Of particular concern is seismic-induced pounding, observed in numerous past and recent earthquakes, often resulting from inadequate separation gaps between neighboring structures. This study conducted an experimental and numerical investigation to develop a mathematical equation to calculate a sufficient separation gap in order to avoid the collision between adjacent mid-rise steel-frame buildings during seismic excitation. In this study, the coupled configuration of 15-storey & 10-storey, 15-storey & 5-storey, and 10-storey & 5-storey steel frame structures was considered in the investigation. The investigation concluded with a large number of data outputs. The outputs were used to predict structural behavior during earthquakes. The obtained data were categorized into three main categories according to the earthquake's Peak Ground Acceleration (PGA) levels. Also, the derived equations were divided into three different equations to estimate the required seismic gap between neighboring buildings accordingly. The derived equations are distilled to empower engineers to rigorously evaluate non-irregular mid-rise steel frame buildings. Doi: 10.28991/CEJ-2023-09-10-02 Full Text: PDF

Analysis of Peak Ground Acceleration and Seismogenic Fault Characteristics of the Mw7.8 Earthquake in Turkey

A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using Matlab, SeismoSignal, and Surfer software: Matlab (Version R2016a), SeismoSignal (Version 5.1.0), and Surfer (Version 23.0.15), and obtained the peak ground acceleration (PGA) contour map. We analyzed the near-fault effect, the fault locking segment effect, and the trampoline effect of the earthquake based on the spatial distribution of PGA, the fault geometry, and slip distribution. We found that the earthquake generated a very strong ground motion concentration effect in the near-fault area, with the maximum PGA exceeding 2000 cm/s2. However, the presence of fault locking segments influenced the spatial distribution of ground motion, resulting in four significant PGA high-value concentration areas at a local dislocation, a turning point, and the end of the East Anatolian Fault. We also revealed for the first time the typical manifestation of the trampoline effect in this earthquake, which was characterized by a large vertical acceleration with a positive direction significantly larger than the negative direction. This paper provides an important reference for understanding the seismogenic mechanism, damage mode, characteristics, and strong earthquake law of the Turkey earthquake.

Kinematic deformation and intensity assessment of the 2021 Maduo MS7.4 earthquake in Qinghai revealed by high-frequency GNSS

Rapid acquisition of the kinematic deformation field and seismic intensity distribution of large earthquakes is crucial for postseismic emergency rescue, disaster assessment, and future seismic risk research. The advancement of GNSS observation and data processing makes it play an important role in this field, especially the high-frequency GNSS. We used the differential positioning method to calculate the 1 HZ GNSS data from 98 sites within 1000 km of the MS7.4 Maduo earthquake epicenter. The kinematic deformation field and the distribution of the seismic intensity by using the peak ground velocity derived from displacement waveforms were obtained. The results show that: 1) Horizontal coseismic response deformation levels ranging from 25 mm to 301 mm can be observed within a 1000 km radius from the epicenter. Coseismic response deformation on the east and west sides shows bilateral asymmetry, which markedly differs from the symmetry presented by surface rupture. 2) The seismic intensity obtained through high-frequency GNSS and field investigations exhibits good consistency of the scope and orientation in the high seismic intensity area, although the former is generally slightly smaller than the latter. 3) There may exist obstacles on the eastern side of the seismogenic fault. The Maduo earthquake induced a certain tectonic stress loading effect on the western Kunlun Pass-Jiangcuo fault (KPJF) and Maqin-Maqu segment, resulting in higher seismic risk in the future.

Correlation between seismic intensity measures and engineering demand parameters of reinforced concrete frame buildings through nonlinear time history analysis

In this paper, the correlation between different seismic intensity measures (IM) and engineering demand parameters (EDP) of reinforced concrete (RC) buildings was evaluated by means of nonlinear dynamic analyses (NLDA). The Costa Rican ground motion database and four RC buildings (4-, 6-, 8- and 10-stories) were considered in this research. Estimations of conventional IMs were derived directly from the ground motion records as well as from the response of a single degree of freedom (SDOF) linear oscillator, with a period equal to that of the fundamental period of the buildings. NLDAs were performed using unscaled and scaled records to account for different intensity levels, and the performance of the buildings was characterized in terms of three EDPs: the average inter-story drift ratio, the maximum inter-story drift ratio, and the Park & Ang damage index. Results demonstrate a significant improvement in the correlation between IMs and EDPs when the dynamic characteristics of the structure are accounted for through the response of the SDOF oscillator. On the other hand, the peak ground velocity turned out to be an effective IM, independent of the dynamic characteristics of the buildings. This is very useful when assessing potential seismic damage both for immediate decision-making and for the characterization of the seismic hazard of a region.

Geotechnical and Structural Investigations in Malatya Province after Kahramanmaraş Earthquake on February 6, 2023

Two earthquakes with moment magnitudes of 7.7 and 7.6 occured on February 6, 2023, at 04:17 a.m. (with local time, GMT+3) in Kahramanmaraş-Ekinözü Pazarcık and at 13:24 p.m. (with local time, GMT+3) in Kahramanmaraş-Elbistan, respectively, in Turkey. The earthquake was felt in a wide area within Turkey and caused structural destructions and heavy damage of buildings, especially in eleven cities including Adana, Adıyaman, Diyarbakır, Gaziantep, Hatay, Kahramanmaraş, Kilis, Malatya, Osmaniye, Şanlıurfa and Elazığ. The aim of this study was to present the detailed field investigation in Malatya province which was one of the most affected city in the region. The strong ground motion records have been analyzed and PGA distribution maps were presented. Structural defects in damaged and collapsed buildings were examined, and design and manufacturing defects were examined. The performance of soil structures was examined, and the defects demonstrated were evaluated in the context of the geological environment. The study is essential in terms of evaluating the damage and possible causes of the building stock in Malatya city center and its districts after the earthquake. In this sense, a holistic evaluation has been carried out, which can be a useful resource for Anatolian cities with typical building characteristics.

Estimating the Quality of the Most Popular Machine Learning Algorithms for Landslide Susceptibility Mapping in 2018 Mw 7.5 Palu Earthquake

The Mw 7.5 Palu earthquake that occurred on 28 September 2018 (UTC 10:02) on Sulawesi Island, Indonesia, triggered approximately 15,600 landslides, causing about 4000 fatalities and widespread destruction. The primary objective of this study is to perform landslide susceptibility mapping (LSM) associated with this event and assess the performance of the most widely used machine learning algorithms of logistic regression (LR) and random forest (RF). Eight controlling factors were considered, including elevation, hillslope gradient, aspect, relief, distance to rivers, peak ground velocity (PGV), peak ground acceleration (PGA), and lithology. To evaluate model uncertainty, training samples were randomly selected and used to establish the models 20 times, resulting in 20 susceptibility maps for different models. The quality of the landslide susceptibility maps was evaluated using several metrics, including the mean landslide susceptibility index (LSI), modelling uncertainty, and predictive accuracy. The results demonstrate that both models effectively capture the actual distribution of landslides, with areas exhibiting high LSI predominantly concentrated on both sides of the seismogenic fault. The RF model exhibits less sensitivity to changes in training samples, whereas the LR model displays significant variation in LSI with sample changes. Overall, both models demonstrate satisfactory performance; however, the RF model exhibits superior predictive capability compared to the LR model.

Modeling of Strong Ground Motion Within the Baikal Rift Zone: The Irkutsk Case

The Baikal Rift Zone is seismically active and each well recorded strong earthquake (for example, as the Kultukskoe earthquake (South of Baikal), on August 27, 2008, with Mw = 6.3) is the reason to refine existing models for seismic hazard estimates. There are several approaches to study strong ground motion, and one of them is to model synthetic accelerograms to reconstruct the rupture process. In this paper we are mostly interested in calculating accelerograms for the city of Irkutsk, considering source spectra with two corner frequencies, primarily, to reconstruct impact from the Kultukskoe earthquake.

Machine learning‐based peak ground acceleration models for structural risk assessment using spatial data analysis

AbstractPredicting peak time‐domain ground‐motion parameters, such as peak ground acceleration (PGA), peak ground velocity, and peak ground displacement at a specific location, is challenging because of the limited number of recorded ground motions and the complexity of ground‐motion prediction equations. This study presents a novel approach that integrates a geographic information system with a spatial data analysis‐based machine learning PGA prediction model to overcome these challenges and predict PGA classes as a function of the PGA of the respective seismic stations, interstation distance of the seismic stations, and time‐average shear‐wave velocity in the upper 30 m of the target station. The proposed spatial data analysis‐based machine learning approach demonstrated the ability to generate satisfactory results in a short period. To account for the spatial dependencies of the variables, a feature selection method for spatial data using mutual information‐based feature selection was proposed, which provides a well‐prepared spatial matrix for machine learning algorithms. This study evaluates the performance of the model using various machine learning algorithms, including Random Forest, Naïve Bayes, K‐Nearest Neighbors, Decision Tree, AdaptiveBoost, Random Undersampling Boost, Extreme Gradient Boost (XGBoost), and Categorical Boost (CatBoost). Among these, XGBoost and CatBoost performed better than the other methods and yielded fairly accurate results. The models were validated using K‐Fold cross‐validation, and the Wilcoxon signed‐rank test was used for comparison. The spatial data analysis‐based machine learning models, particularly XGBoost and CatBoost, achieved high‐accuracy rates in classifying the PGA levels of 99.1% and 98.9%, respectively. Hyperparameters for the XGBoost model were tuned through GridSearchCV. Tree‐based models outperformed parametric models, indicating complex non‐linear spatial relationships, and by combining spatial feature selection with machine learning models demonstrated improved performance. Additionally, real‐time applications of spatial data analysis‐based machine learning PGA prediction models were used to estimate the seismic vulnerability of postulated concrete box‐girder bridges in San Fernando, thus providing insights into damage probabilities based on predicted PGA values.

Nonlinear Dynamic Analysis of Pilotis Structures Supported by Drift-Hardening Concrete Columns.

Pilotis structures consisting of upper concrete bearing-walls and a soft first story have been well used in residential and office buildings in urban areas to primarily accommodate parking lots. In this research, drift-hardening concrete (DHC) columns developed by the authors are proposed to form the pilotis story with the aims of reducing its excessive residual drift caused by stronger earthquakes than anticipated in current seismic codes, mitigating damage degree, and enhancing resilience of the pilotis story. Nonlinear dynamic analysis was conducted to investigate the dynamic response characteristics of the wall structures supported by DHC columns. To this end, two sample six-story one-bay pilotis structures were designed following the current Japanese seismic design codes and analyzed. One sample structure is supported by ductile concrete (DC) columns, while the other is supported by DHC columns, which have the same dimensions, steel amount, and concrete strength as DC columns. Three representative ground motions were adopted for the nonlinear dynamic analysis. The analytical parameter was the amplitude of peak ground acceleration (PGA), scaled by the peak ground velocity (PGV) ranging between 12.5 cm/s and 100 cm/s with an interval of 12.5 cm/s. The analytical results have revealed that the residual drift of the pilotis story composed of DHC columns could be reduced to nearly zero under selected earthquakes scaled up to PGV = 100 cm/s, owing to not only the inherent self-centering ability of DHC columns but also the shake-down effect, which implies that the use of DHC columns can greatly enhance resilience of pilotis structures under strong earthquake inputs and promote its application in the buildings located in strong earthquake-prone regions. The maximum inter-story shear forces (MISFs) along the building height of the two models are also compared.

Coseismic slip and deformation mode of the 2022 Mw 6.5 Luding earthquake determined by GPS observation

The Luding Mw 6.5 earthquake on September 5, 2022 occurred in the southeast section of the Xianshuihe Fault, filling a seismic gap previously identified by the earthquakes (M > 6.5) since 1700. The horizontal coseismic displacements are obtained using remeasurement data from global positioning system (GPS) campaign stations over a range of ∼80 km from the epicenter. The overall pattern of displacements is consistent with left-lateral strike-slip. The largest displacement (∼ 227 mm in the north-north-east direction) is observed at station ZD17, located ∼10 km east of the epicenter. Coseismic slip distribution primarily propagates to the south-southeast of the epicenter, corresponding to the interseismic locking area. The lower stress accumulation of the north-northwest direction of the epicenter may arrest the rupture propagation. Slip located at shallower depths (1–3 km) is systematically smaller than that at deeper depths (4–8 km), suggesting a moderate shallow coseismic slip deficit. The distributed inelastic deformation caused by strong ground motion might be the main reason for the shallow slip deficit. The Daofu–Kangding section of the Xianshuihe and the Shimian–Mianning section of the Anninghe faults received a significant Coulomb stress increase caused by the Luding earthquake, and remained unbroken and hazardous.