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A rapid and accurate estimate of earthquake damage is a key component in a successful earthquake early warning (EEW) system. The cumulative absolute velocity (CAV) is an important and widely used parameter to measure ground motion intensity, but it cannot be correctly estimated via the traditional approach with the limited information available in typical EEW systems. Therefore, current EEW systems cannot effectively use CAV to predict earthquake damage. Herein, a CAV prediction model (DLcav) based on convolutional neural networks was proposed for EEW systems. DLcav is an end‐to‐end solution to continuously predict CAV using arriving seismic waves of increasing length and supplemented with additional auxiliary information. The effectiveness of DLcav to predict CAV was tested based on Japanese ground motion records, and the generalization ability of DLcav was assessed using the ground motion records from Chile. The results demonstrate that DLcav can rapidly predict CAV with good accuracy, which will help better estimate earthquake damage in EEW systems. [ABSTRACT FROM AUTHOR]

Conditional Spectrum (CS), characterized by a conditional mean and conditional standard deviation, serves as a target spectrum linking seismic hazard information to ground motion selection for seismic demand analysis. Current Ground Motion Selection and Modification (GMSM) methods aim to align with this target spectrum but face challenges due to the limited availability of recorded ground motions and potential modifications, leading to difficulties in ensuring selected ground motions accurately reflect site characteristics. Addressing this issue, the study presents an algorithm to select hazard-consistent CS-based records utilizing a stochastic ground motion model with a dual objective: (1) alleviate the need for scaling during the selection process, and (2) select records consistent with the target hazard and the contributing causal scenarios. To achieve both objectives, the study generates a database of hazard-targeted ground motions utilizing the kriging surrogate with scenarios sampled from the disaggregation matrix. Then, a postprocessing step explicitly considers causative parameters in the selection process. The algorithm's potential to select site-specific ground motions is demonstrated using sites in the Western United States, providing insights into the computational cost and accuracy. Additionally, statistical comparisons are conducted to explore circumstances where similar hazard consistency can be achieved without the postprocessing step, reducing the overall computational cost. Finally, the selected ground motions are favorably compared to those selected through traditional conditional spectrum-based approaches based on their spectral shape and ground motion intensity measures. [ABSTRACT FROM AUTHOR]

Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical, and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region have become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical, and geotectonical nature. The dataset comprises 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions. [ABSTRACT FROM AUTHOR]

The effects of evolutionary Arias intensity are thoroughly investigated based on ground motion simulation and nonlinear dynamic response. A new methodology is developed to generate a series of spectral-equivalent synthetic motions with different energy accumulation paths using wavelet packets. Systematic studies are performed on dynamic responses of hysteretic systems and liquefiable grounds using the simulated motions and actual recordings. An attempt is made to develop the relationship between liquefaction-induced deformation and shaking intensity rate which is used to quantify the rate of Arias intensity accumulation. The results indicate the need of considering evolutionary Arias intensity in nonlinear dynamic analysis. [ABSTRACT FROM AUTHOR]

The diagrid structural system has become popular in the construction of high-rise buildings in light of significant advantages over other structural systems. The present study explores the effects of the vertical near-fault earthquake component on the axial forces of diagonal elements in steel diagrid structures. Nonlinear time-history analysis was carried out using 11 near-fault earthquake records. A total of nine three-dimensional models of 12, 18, and 24 stories, each with diagonal angles of 45, 63.4, and 71.5 degrees, were designed and analyzed. Due to the three-dimensional modeling complexities of diagrid structures, a method was developed to transform three-dimensional models into two-dimensional ones. Finally, the scenarios with and without the vertical earthquake component were compared. It was found that the incorporation of the vertical earthquake component into the analysis of diagrid structures substantially influenced the axial forces of diagonal elements. This can affect the design load estimation of diagonal elements as the main components of a diagrid structure. [ABSTRACT FROM AUTHOR]

The implementation of fluid viscous dampers has been proven as a feasible method to improve the seismic performance of buildings. However, the different variables involved in the damper's design affect the structural response, especially in terms of seismic demand on non-structural elements. This paper presents a parametric study on the floor acceleration response of three case study buildings equipped with fluid viscous dampers through nonlinear time-history analysis. The results show that the different design parameters of fluid viscous dampers significantly modify the floor acceleration response, with some damper configurations yielding floor accelerations larger than those of the buildings without dampers. [ABSTRACT FROM AUTHOR]

The reliability of Vs30 and the performance of alternative time averaged shear wave velocities (Vsz) and shear wave travel times (Ttz) at various depths, z, were investigated for the estimation of site amplification and fundamental frequency (f0) characterization by considering the linear and nonlinear soil behavior. The study revealed that alternative parameters performed better than Vs30 and the best performing z parameters changed by switching from convex to concave theoretical profiles and by increasing ground motions. For a practical usage in site investigations, guidelines to estimate nonlinear soil amplification factor and fundamental frequency from the linear ones were presented. [ABSTRACT FROM AUTHOR]

Liquefaction has been known as a phenomenon in which the shear strength and stiffness of saturated soil are reduced by the generation of pore water pressure under earthquake loading. Consequently, liquefaction-induced settlement can result in severe damage including building cracks or slope failure, which pose a threat to human lives and properties. In the current Vietnamese standard TCVN 9386:2012, liquefaction potential hazard is often evaluated using the simplified method, which solely identifies the areas with a high risk of liquefaction. Prediction of Safety Factor (FS), Settlement (S), Liquefaction Potential Index (LPI), and Liquefaction Severity Number (LSN) has not received sufficient attention to a completeness standard. This study assesses the liquefaction of the site at Ho Chi Minh City, Vietnam by using four conventional methods: the simplified procedure, linear equivalent analysis, loosely-coupled effective stress analysis, and fully-coupled effective stress analysis based on standard penetration test (SPT) data in Ho Chi Minh Metropolitan City. A class of seismic events that are compatible with the design response spectrum in the Vietnamese standard TCVN 9386:2012 is used as input ground motion at the bedrock. According to the results of different methods, maps of ground settlement, LPI, and LSN are proposed as useful references for construction works on such soils, which may have a high potential for liquefaction and subsidence. [ABSTRACT FROM AUTHOR]

Landslide research has benefited greatly from advances in remote sensing techniques. However, the recent increase in available data on land surface movement provided by InSAR techniques can lead to identifying only those areas that were active during data acquisition as hazardous, overlooking other potentially unsafe areas or neglecting landslide-specific geological settings in hazard assessments. Here, we present a case study that serves as a reminder for landslide researchers to carefully consider the geology and geomorphology of study areas where complex active movements are detected using InSAR technology. In an area extensively studied using InSAR and UAV-related techniques, we provide new insights by applying classical approaches. The area is the coastal stretch of La Herradura, and its importance lies in the fact that it has served as an illustrative example in the Product User Manual of the European Ground Motion Service, a platform that provides ground motion data on a European scale. Our approach is to revisit the area and carry out qualitative geological and geomorphological assessments supported by UAV surveys and GIS spatial analysis on a broader scale than previously published investigations. Our classical approach has yielded the following new observations, crucial for risk assessment and land management: active landslides identified by InSAR techniques since 2015 are bodies nested within large mass movements that affect entire slopes. A variety of processes contribute to slope dynamics, such as large slumps, marble rock spreading and block sliding, and surface rock falls and topples. The revised delineation of the landslide bodies reveals an area almost five times larger than previously mapped. These new findings in a well-known area highlight (1) the importance of updating and downscaling previous maps and (2) the ongoing importance of classical fieldwork and desk studies as basic complements to modern InSAR analyses. [ABSTRACT FROM AUTHOR]

Near-fault ground motions (NFGM) may have a significant component of the long period velocity pulse (LPVP) due to the directivity effect. The structures subjected to such ground motions are prone to experience large displacements. In this paper, the damage potential of such motions is compared with NFGM (without LPVP) and far-field motions in terms of seismic demand (inter-storey drift and inelastic displacement). Due to the lack of site-specific recorded NFGM, the synthetic ground motions are generated and used in this study. For this purpose, first the bedrock motions are obtained through stochastic simulation approach in which the Specific Barrier Model (SBM) is used as source spectrum and then these motions are transferred to the ground surface using one-dimensional ground response analysis. In order to obtain the NFGM with pulse, the bedrock motions are superimposed with the LPVPs and then transferred to the ground surface. To illustrate, the case of a ten-storey reinforced concrete (RC) building is considered in Delhi region (India) which falls under the seismic zone-IV. The main finding of this study is the observation that the NFGM with LPVP impose almost double seismic demand compared to the NFGM without LPVP, specially for the structures lying in the velocity-region of the response spectrum. In this study, the effect of depth of bedrock on seismic demand is highlighted and recommended to be included in the design seismic demand of NFGM. [ABSTRACT FROM AUTHOR]

The discrete-like crack model (DLCM), a crack-analysis scheme incorporated with the nonlinear finite element method, is redeveloped for parallelism. The algorithm of the new DLCM based on the theory of bond redistribution is implemented through the OpenMP interface and enables analyses of a 50-story building with more than four million degrees of freedom. The analysis considers the drying shrinkage and creep during the construction and service periods, static pushover loading, and a time history of a near-fault strong ground motion. The amount of cracks is quantified as the total length that occurs on the concrete surfaces. The structural damage due to compression softening exhibits a strong correlation with the length of cracks with opening widths larger than 2 mm. The analyzed building becomes unrepairable when the total length of the >2 mm wide cracks exceeds 50 m. However, the occurrence of such serious damage induced by any seismic vibrations ever recorded is unlikely. "There's no art to find the mind's construction in the face," so King Duncan said. However, we can consider the search for structural damages on concrete surfaces a form of art. The presence of cracks proves the life of a reinforced concrete building, similar to a person's history engraved as wrinkles and scars on their face. Our novel parallel numerical scheme, namely, the discrete-like crack model (DLCM), traces not only the long history of a building starting from its construction but also resolves the issue of unexpected near-fault pulse-type earthquakes into detailed profiles. In this case study, DLCM is employed to assess structural damage using a percentage of cracks that extend up to 100 km on the entire concrete surfaces of a 50-story residential building. The profiles of cracks, stresses, and strains articulate the building's past and current status and render the possibility to improve the quality of living in the future. [ABSTRACT FROM AUTHOR]

The coupling behavior in the structural response caused by the multicomponents of ground motions in friction pendulum base-isolated buildings can change the response of nonstructural contents. This research investigates the seismic performance of freestanding nonstructural components in a hypothetical 4-story reinforced concrete triple friction pendulum (TFP) base-isolated medical facility using a suite of 11 ground-motion pairs, including their vertical components. Floor accelerations in vertical and horizontal directions were employed as excitation for the rocking response of rigid blocks. In comparison with the horizontal-only floor accelerations, the horizontal-vertical (H-V) coupling behavior in the floor accelerations had a substantial effect on the rocking response of nonstructural contents, small and slender ones in particular. Consequently, the direct effect of vertical ground motions and the H-V coupling phenomenon on the seismic performance of nonstructural components need to be carefully evaluated for critical facilities, especially the friction pendulum–type base-isolated buildings, to quantify the damage level of unanchored components. [ABSTRACT FROM AUTHOR]

Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield‐based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES' internal activations, which we call "seismic vectors", correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake. Plain Language Summary: Have you ever heard something through the grapevine? It often takes you by surprise to hear a message from someone other than the original source. You might have felt an earthquake in a similar way: experiencing shaking (the message) at your location rather than movement along a fault (the source). We apply grapevine‐style communication to earthquake early warning (EEW). The goal of EEW is to warn people to prepare for earthquake shaking before damaging seismic waves arrive at their location. We build on recent work that used deep learning and large earthquake data sets to predict earthquake shaking. We developed a deep learning algorithm called GRAPES which predicts shaking in a manner similar to a game of seismic telephone: when a seismic sensor detects shaking, it sends a message to its neighboring sensors, warning them to expect shaking soon. These sensors then pass on the message to their more distant neighbors along the grapevine. We show that the messages GRAPES learned to send between sensors are like seismic status updates: "I'm seeing this type of seismic wave right now". We applied GRAPES to the 2019 M7.1 Ridgecrest, CA earthquake and it predicted shaking accurately and quickly. Key Points: A deep learning network trained to predict ground motion learned an internal representation of the seismic wavefieldIndividual neurons within the network activate with the arrival of P waves, S waves, surface waves, coda waves, and ambient noiseWhile trained on earthquakes in Japan, the model generalizes well to predicting ground motions for the 2019 Ridgecrest, CA earthquake [ABSTRACT FROM AUTHOR]

The seismic performance of arch bridges is dependent on the strength of bridges and the built-on soil site types. To investigate the influence of soil-structure interaction (SSI) on the seismic response of an arch-foot arch bridge with a sand-gravel soil site, several shaking-table tests for a 1/90 downscaled arch-foot model placed on sand-gravel soil were conducted based on the engineering prototype of the third Pingnan Bridge with a long-span concrete-filled steel-tube (CFST) arch bridge. The test results showed the following: (1) The seismic acceleration response of both the sand-gravel soil site and arch foot were amplified, which is related to both the non-linear dynamic behavior of sand-gravel soil and frequency-spectrum characteristics of the input seismic waves. (2) The sliding displacement of the arch foot under strong ground motions increased accompanied with a settlement of the soil surface. However, the safety risk of the arch foot may be underestimated in seismic design. (3) The dynamic shear stress-strain loops of sand-gravel soil exhibited a high-energy dissipation capacity, and the energy-transfer mechanism at the interface between the model soil and arch foot was integrated. The results obtained are expected to provide insights into the dynamic interaction behavior of the gravel soil and arch bridge systems and the seismic design of arch bridges built on sand-gravel soil sites in practical engineering. [ABSTRACT FROM AUTHOR]

To simulate the ground motions of 2D arbitrary sites subjected to plane SV waves, we put forward a numerical method combining the multi-transmitting formula (MTF) and spectral element method (SEM). The investigation results demonstrate a high simulation accuracy of the presented method. Most importantly, the MTF exhibits a notably superior stability performance in the SEM than in traditional finite-element method (FEM). Without any additional treatment, high-frequency instability does not occur when controlling the Courant number value C and the ratio between the MTF parameter S and C; the upper limit value of this ratio is significantly smaller than that of the SH-wave problem. In addition, a preliminary stability criterion for the MTF in SEM is given based on the homogeneous half-space model. For low-frequency stability, the occurrence time of instability is considerably lagged when no interventions are adopted. Moreover, the low-frequency instability can be readily eliminated by using smaller modification parameter in the SEM compared with the FEM. [ABSTRACT FROM AUTHOR]

Seismic response of cross interchange subway stations in soft soil is studied through dynamic time history analysis. The inhomogeneous deformation and internal forces of the structure are examined under moderate earthquakes, considering intersecting effects and ground motion frequency. Findings indicate that the intersecting part of two-story and three-story sections creates a rigid connection, increasing stiffness and unique deformation patterns. This leads to an abrupt distribution of internal forces and significantly affects lateral drift ratio, requiring careful consideration in seismic design. Low-frequency ground motions demonstrate distinct heterogeneity in racking deformation distribution. Insights contribute to improved seismic design of soft soil subway stations. [ABSTRACT FROM AUTHOR]

A five story (G + 4) residential structure is positioned on 15°, 30°, and 45° slopes to be explored in this study in terms of vulnegrability and compared to the same structure resting on flat ground 0°. The RC frame models were constructed in accordance with Eurocode 8 and then subjected through a series of 10 ground motion records. In accordance with Vision 2000 performance limit states (PLS), this research provided the use of nonlinear static analysis (NL-SA) and nonlinear dynamic analysis (NL-DA) methodologies to assess seismic risk performance and vulnerability of structures resting on various slope angles. Incremental Dynamic Analysis (IDA) and Pushover Analysis (POA) capacity curves, as well as the fragility curve and the collapse margin ratio, are generated for the four selected models (M0, M15, M30, M45). The results show that the RC frame model M45, located on a 45°-degree incline, is the most vulnerable to damage. The risk of damage to the RC frame M0 is minimal because it is not elevated off the ground. To this end, the relative degrees of vulnerability among the frames were determined to be as follows: M45 > M30 > M15 > M0. [ABSTRACT FROM AUTHOR]

Predictive displacement models (PDMs) based on the Newmark sliding block method have been widely applied in earthquake-induced landslide hazard assessment (ELHA). Pulse-like ground motions (PLGMs) can cause significant structural damage. In this study, four PDMs that consider the probability of occurrence of PLGMs (PP) were created for strike-slip and non-strike-slip events. The results demonstrate that the model with PP has greater accuracy in non-strike-slip events than the model without PP, however, the effect of PP may be disregarded in strike-slip events. This result is applicable to the ELHA and can provide a basis for post-earthquake emergency and geological disaster mitigation. [ABSTRACT FROM AUTHOR]

The damage assessment of numerous buildings after the earthquake is still a challenge by traditional methods as it requires a significant amount of time and resources for carrying out building-by-building seismic damage assessment. This study presents the machine learning (ML)-based damage assessment of buildings after an earthquake. The applicability of the machine learning model will be limited considering only structural properties or ground motion characteristics. Thus, in this study, the applicability of different machine learning techniques is explored using real-world earthquake damage datasets considering both the structural properties and ground motion characteristics. Initially, the entire dataset is used to train the ML models to classify the building's damage into five categories ranging from null to slight damage to collapse. Later, the dataset is divided into three traffic light damage tags: green, yellow, and red. The performance of the ML model to classify the building's damage into three damage tags is found better than that of classifying it into five damage categories. This research aims to be beneficial in planning and decision-making for emergency response and recovery following an earthquake. [ABSTRACT FROM AUTHOR]

The sliding base (SB) technique is an efficient and economical approach to mitigating seismic damage of low-rise buildings in rural areas. Based on the previous work on single-story SB structures, this study investigates the earthquake forces acting on multistory SB structures. Response history analyses of SB structures subjected to three-component earthquake excitations were performed. The computed results indicate that the increase in the number of stories tends to reduce the mean value of the peak base shear but has little influence on the coefficient of variation of the peak base shear. The peak story shears of a multistory SB structure subjected to an earthquake ground motion are reached at different time instants for different stories. The distributions of the equivalent lateral forces for SB structures with different story numbers follow the same trend, and the equivalent lateral forces tend to concentrate at the upper floors as the normalized peak ground acceleration and mass ratio increase. Simplified equations for computing the distribution of equivalent lateral forces were developed for design purposes. [ABSTRACT FROM AUTHOR]

Affected by the near-fault pulse-like ground motions, the tunnels emerged in adverse geology, especially in an inhomogeneous strata are more vulnerable. However, the quantitative index effects on tunnel response during pulse identification are unclear and the propagation features of the near-fault pulse-like waves in a soft soil interlayer site are seldom revealed. In view of this, an improved energy-based pulse identification was used in this study to quantitatively extract the potential pulse energies emerged in velocity time-histories of ground motions. Subsequently, a series of numerical simulations were carried out to consider the critical parameters of soft soil layer and input ground motions. Finally, the dynamic response of the tunnel and interaction differences of soil and tunnel subjected to three types of ground motions were revealed. The result showed that the near-fault pulse-like ground motions pose a commonly severe damage to the tunnel, especially in the high pulse period ground motions based on the energy-based pulse identification method. The pulse energy of ground motions is an effective pulse index to analyze the seismic effects on tunnel when pulse periods of two different ground motions are uniform, and the index affects the tunnel in dynamic internal forces. More importantly, the existence of soft soil layer severely affects the propagation of input ground motions. At frequency domain, the ground response increases at high frequency component in the near-fault pulse-like ground motion, while the response shows a decreasing at low frequency component. [ABSTRACT FROM AUTHOR]

For a narrow-brand seismograph with a flat response range limited, it cannot precisely record the signal of a ground motion and output the records with the low-frequency components cut down. A transfer function is usually used to spread the spectrum of the narrow-brand seismic records. However, the accuracy of the commonly used transfer function is not high. The authors derive a new transfer function based on the Laplace transform, bilinear transform, and Nyquist sampling theory to solve this problem. And then, the derived transfer function is used to correct the narrow-band velocity records from the Hi-net. The corrected velocity records are compared with the velocities integrated from the synchronously recorded broad-band acceleration at the same station with Hi-net. Meanwhile, the corrected records are compared with those corrected by the Nakata transfer function. The results show that the calculation accuracy of the derived transfer function is higher than the Nakata transfer function. However, when the signal-to-noise ratio is below 24, its accuracy diminishes, and it is unable to recover signals within the 0.05–0.78Hz frequency band. [ABSTRACT FROM AUTHOR]

Concentrated solar towers are commonly designed as high-rise hybrid structures, which exhibit properties of non-uniform mass and rigidity along the height of the tower, and consequently are vulnerable to strong seismic ground motions. This study presents a comprehensive analysis of the seismic performance of a hybrid solar tower, which is one of the tallest hybrid solar towers in the world. The hybrid solar tower includes a reinforced concrete tube at the bottom and a steel-truss tube at the top and is subjected to near-fault pulse-like ground motions. A simulation technique that utilizes the stochastic point-source model and a velocity pulse model was introduced to generate stochastic pulse-like ground motions. The stochastic response of the hybrid solar tower to near-fault pulse-like ground motions was computed to estimate the tower's reliability. To enhance the efficiency of reliability estimation, an algorithm combining the Kriging surrogate and subset simulation (K-SS) was presented. The aggregate response of the tower was found to be significantly more damaging over the border of the reinforced concrete tube and the steel-truss tube than below the border. The study found that the hybrid solar tower has a reliability of 90.53% when subjected to stochastic near-fault pulse-like ground motions with a peak ground acceleration of 0.62 g. The findings of this study contribute to the understanding of the seismic performance of high-rise hybrid solar towers under near-fault pulse-like ground motions. [ABSTRACT FROM AUTHOR]

The paper proposes the use of supervised machine learning (ML) methods for quickly predicting the seismic response of rocking systems when subjected to seismic excitations. Different supervised ML algorithms are discussed, while a relatively simple and a more sophisticated algorithm are examined in detail. Specifically, the two algorithms compared are the k-Nearest Neighbor (k-NN) and the Support Vector Machine (SVM). The performance of the ML models is demonstrated considering both sine pulses and different sets of natural ground motion records. The results are practically perfect for sine pulses, while accurate results were also obtained for the case of natural ground motions. The proposed ML-based tool allows to quickly assess the risk of damage for rocking systems, while it is also very important when a large number of rocking blocks have to be studied, e.g. in the case of a building's inventory. [ABSTRACT FROM AUTHOR]

Seismic risk assessment of building portfolios has been traditionally performed using empirical ground motion models, and scalar fragility and vulnerability functions. The advent of machine learning algorithms in earthquake engineering and ground motion modelling has demonstrated promising advantages. The aim of the present study is to explore the benefits of employing artificial neural networks (ANNs) in earthquake scenarios for spatially-distributed building portfolios. To this end, several recent major seismic events in the Balkan region were selected to assess damage and economic losses, considering different modelling approaches. For the assessment of the seismic demand, the ANN developed in the companion study and common ground motion models for Europe were adopted. For the vulnerability component, recent ANN models and existing scalar fragility and vulnerability functions for the Balkans were used. The estimates of all modelling cases were compared against the aggregated damage and economic loss data observed in the aftermath of these events. The findings of this study suggest that overall, the ANNs led to damage and economic loss estimates closer to the observations. [ABSTRACT FROM AUTHOR]

The calculation of the spatial distribution of ground motion is one of the most important steps in earthquake scenarios. The advancements in machine learning algorithms and the release of new ground motion data can enable improvements in the reliability and accuracy of this component. We developed an artificial neural network (ANN) ground motion model using a compiled database from two subsets with measured Vs30 from the Pan-European strong motion database and the NGA-West2 database. The ANN model employs five input parameters: moment magnitude (Mw), hypocentral depth, Joyner–Boore distance (Rjb), shear wave velocity in the top 30 m (Vs30), and faulting type. The outputs of the ANN are the RotD50 horizontal components of common intensity measures used in seismic risk assessment: PGA, PGD, PGV, Arias Intensity, and 5% damped spectral acceleration at 27 periods from 0.01 to 4.0 s. A mixed-effects modelling approach was followed to train the ANN and partition the ground motion variability into between-event and between-site terms. The input parameter scaling relationships were studied and demonstrated physically sound trends of the ground motion with respect to Mw scaling, distance attenuation, and site amplification. The predicted median response spectra for several combinations of Mw and Rjb were compared to common ground motion models for Europe, and the results are discussed. The developed ANN is used in a companion study to calculate the hazard footprints for several historical earthquakes in the Balkan region. [ABSTRACT FROM AUTHOR]

Within seismology, geology, civil and structural engineering, deep learning (DL), especially via generative adversarial networks (GANs), represents an innovative, engaging, and advantageous way to generate reliable synthetic data that represent actual samples' characteristics, providing a handy data augmentation tool. Indeed, in many practical applications, obtaining a significant number of high-quality information is demanding. Data augmentation is generally based on artificial intelligence (AI) and machine learning data-driven models. The DL GAN-based data augmentation approach for generating synthetic seismic signals revolutionized the current data augmentation paradigm. This study delivers a critical state-of-art review, explaining recent research into AI-based GAN synthetic generation of ground motion signals or seismic events, and also with a comprehensive insight into seismic-related geophysical studies. This study may be relevant, especially for the earth and planetary science, geology and seismology, oil and gas exploration, and on the other hand for assessing the seismic response of buildings and infrastructures, seismic detection tasks, and general structural and civil engineering applications. Furthermore, highlighting the strengths and limitations of the current studies on adversarial learning applied to seismology may help to guide research efforts in the next future toward the most promising directions. [ABSTRACT FROM AUTHOR]

Multi-camera systems for structure from motion (SfM) are widely deployed in many mapping applications. Existing solutions assume known rig calibration, synchronized frames among cameras, as well as overlapping field of views (FoVs). In this paper, we derive novel geometric constraints assuming minimal knowns about the multi-camera systems, to benefit low-cost and non-expert use cases where uncalibrated multi-camera systems with non-typical geometry setups present, i.e., no rig calibration, no overlapping FoVs. Assuming that these cameras are co-located and share the same motion of the platform, the proposed constraints utilize the parallelism and length proportionality of motion vectors of these co-located cameras and formulate them as translation constraints into the bundle adjustment (BA). The proposed constraints (called motion constraints) impose a first-order penalty to co-located cameras whose motion speeds and directions between frames do not match. With soft constraints, it can handle loosely synchronized frames (with an error within one second). The proposed constraints are integrated into the BA framework and experimented with different camera setups, i.e., on a group of casually co-located GoPro cameras with no rig calibration, and some with no overlapping views. Our results show that the constraints are extremely effective in improving the reconstruction and pose accuracy for ground motion images: in our self-collected open trajectories without loop closure, the proposed constraints are effective in correcting topographical errors (i.e., trajectory drifts) of the resulting models, and the dense point clouds achieve up to 11.34 m (86.12 %) of mean absolute error (MAE) improvement as compared to reference LiDAR point clouds; our results on KITTI-odometry and KITTI-360 datasets also show an improvement of up to 28.82 m (81.05 %) in terms of the root mean square error (RMSE) of absolute pose error (APE). We expect that the proposed constraints are significant not only as additional geometric constraints for image-based mobile mapping, but also will benefit the broader use of photogrammetry, since it empowers the possibility to harness the traditionally so-called low-quality stereo/multi-camera data (e.g., by non-photogrammetry citizen scientists) into improved 3D products. [ABSTRACT FROM AUTHOR]

As a famous deep and large fault in eastern China, the Tanlu Fault passes through Anhui, Jiangsu, and Shandong and into northeastern China. It is important to improve the understanding of seismic hazard assessments in areas near faults. We start a scenario earthquake simulation in the M7.5 earthquake potential area of the Xinyi-Sihong segment of the Tanlu Fault. The fault rupture length and width are constrained according to the scaling law of large intraplate earthquakes, the background normal stress is depth dependent, and the initial shear stresses are determined using trial and error by matching the earthquake magnitude. Considering the 120 km rupture length of the M7.5 earthquake, we compare the horizontal uniform stress model and self-similar stress perturbation model. Our findings reveal that the seismic source time function of the horizontal uniform stress model is similar to that of the Haskell model and that of the self-similar stress perturbation model is more similar to that of a real earthquake case. We compare the dynamic rupture simulation and ground motion results under four different stress conditions and find that the shorter the characteristic length of the self-similar function is, the rougher the initial stress. For the M7.5 earthquake with an epicenter in the vicinity of Suqian, the Xinyi-Tancheng segment, which is located in the IX-intensity zone north of the epicenter, vibrates more strongly on the northern side than on the southern side due to the influence of the low-velocity zone and the peak slip rate. The response spectra analysis at stations in the study area is useful for improving the earthquake resistance capability. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study carried out to develop a multi-severity casualty approach for predicting the number of fatalities and two levels of injuries resulting from an earthquake. The two levels of injuries are severity 1, which do not require hospitalization, and severity 2, which do require hospitalization. The method provides a probability distribution of casualty, which can assist policymakers and disaster management authorities in developing emergency response plans. The proposed approach takes into account two main sources of uncertainty: variations in ground motion values (by generating thousands of shaking maps considering the spatial correlation of intra-event uncertainty) and uncertainty in casualty rates (by using the fuzzy set theorem and random sampling). As a case study, the proposed method was applied to the Mosha fault seismic scenario (7.4 Mw) in Tehran, Iran. The results indicated that 200,300 people may lose their lives in that seismic scenario. Additionally, the number of injuries with severity 1 and severity 2 are estimated to be about 420,600 and 232,980, respectively. These numbers exceed the healthcare capacity in Tehran. The estimated number of fatalities was then compared with the results of some existing empirical models in the literature. This comparison revealed that the empirical models underestimate the number of fatalities due to various reasons, such as a lack of strong earthquakes in urban areas to be included in empirical models. Thus, the proposed approach has several advantages for estimating casualties in urban fabrics. [ABSTRACT FROM AUTHOR]

This paper estimates a correlation model and joint distribution model of spectral accelerations of vertical ground motions based on the NGA-West2 ground motion database. The correlation model calculated via BC16 vertical GMPE in this study is compared with those published models via other vertical NGA-West2 GMPEs. It is verified that the calculated residuals of vertical ground motions at multiple periods follow the multivariate normal distributions via both a qualitative validation method and a set of quantitative validation methods. The correlation model and the joint distribution model of vertical spectral accelerations are the theoretical basis for research on the joint occurrence of spectral accelerations of vertical ground motions, and an example of applied research on joint occurrence of spectral accelerations of vertical ground motions is studied: the conditional mean spectrum of vertical ground motions. Finally, the effects of different vertical correlation models and ground motion prediction equations on vertical conditional spectra are investigated for wide application of the correlation model and the joint distribution model of spectral accelerations of vertical ground motions. [ABSTRACT FROM AUTHOR]

For regional hazard analysis or engineering applications, it is necessary to simulate a group of correlated ground motions containing information from given recordings. A new method is presented to conditionally generate ground motions at unobserved points using actual recordings in this localized region. This method is based on an extension of the traditional conditional simulation using a wavelet packet. Utilizing the advantages of wavelet-packet transformation, the time and frequency characteristics of ground motions are effectively identified. Besides by decomposing the signal into non-overlapping sub-frequency bands, it is possible to conditionally simulating stationary, space-time, and Gaussian random fields. These simulated motions are consistent with the actual recordings in terms of temporal variations in the frequency domain and its design spectrum, and their coherence functions satisfy the target coherence values. Two numerical examples have been provided to illustrate the capability of the proposed method: the simulation of ensembles of earthquake accelerograms using actual recordings and blind tests in SMART-1 array. [ABSTRACT FROM AUTHOR]

Earthquake early warning systems assess the size of an earthquake based on initial ground motion and provide warnings before the arrival of large waves. We employ the iterative regression to simultaneously estimate the station correlations and the corresponding linear relations for magnitude. We report the standard error reductions of the magnitude estimation based on the initial peak P-wave acceleration (${P_a}$ P a ), velocity (${P_v}$ P v ), and displacement (${P_d}$ P d ) as $14.52\% $ 14.52 % , $7.63\% $ 7.63 % , and $7.58\% $ 7.58 % , respectively. Factor analysis of the stationary correction reveals its correlation with several factors. This study shows that station correction can help to improve the precision of magnitude estimation in the future. [ABSTRACT FROM AUTHOR]

Irazú and Turrialba are a twin volcanic complex that marks a distinct stop in volcanism along the Central America volcanic arc. We present a new traveltime velocity model of the crust beneath Irazú and Turrialba volcanoes, Costa Rica, and interpret it considering the results of previous ambient noise tomographic inversions. Data were acquired by a temporary seismic network during a period of low activity of the Irazú–Turrialba volcanic complex in 2018–2019. Beneath the Irazú volcano, we observe low P -wave velocities (V P = 5 km s−1) and low velocity ratios (V P/ V S = 1.6). In contrast, below the Turrialba volcano, we observe low S -wave velocities (V S = 3 km s−1) and a high V P/ V S (= 1.85) anomaly. We found that locations of low V P and V S anomalies (−15 %) correspond well with shear wave velocity anomalies retrieved from ambient noise tomography. At shallower depths, we observe high V P and V S anomalies (+15 %) located between the summits of the volcanoes. Subvertical velocity anomalies are also observed at greater depths, with high V P and V S anomalies appearing at the lower limits of our models. We propose a complex structure of an intermediate magmatic reservoir, presenting multiphase fluid states of a liquid-to-gas transition beneath Irazú and a juvenile store of magmatic fluid beneath Turrialba, while shallow fluid transport provides evidence of magmatic–hydrothermal interactions. [ABSTRACT FROM AUTHOR]

This paper discusses the results of 1∶25 scale shake table tests evaluating the seismic response of multiblock tower structures (MTSs) conceived as energy storage systems. The tests described here are a part of a comprehensive research campaign involving smaller physical models, computational model validation, and the theoretical background required to compare results across scales. The 6.46-m-high MTSs consisted of over 7,000 concrete blocks stacked vertically without any bonding agent, interacting only by friction and rocking. Three MTSs were tested under two different ground motions. Dynamic digital image correlation (DIC) and low-cost micro electrical mechanical system (MEMS) accelerometers were used for dynamic response measurements. Towers 1 and 3, subjected to repeated strong-intensity earthquake ground motions, collapsed during the third repetition due to the accumulation of residual displacements. Tower 2 was subjected to a single near-fault ground motion representing an extreme event and collapsed during the test. Different collapse mechanisms were identified in the test program. Data collected from individual blocks showed in-plane and out-of-phase block rotation and sliding, which contributed to the system's energy dissipation during the tests. [ABSTRACT FROM AUTHOR]

This paper presents an extensive numerical study on the seismic performance of steel eccentrically braced frames (EBFs) designed according to the ASCE 7-16 standard. A series of EBF building structures ranging from 2 to 12 stories located in downtown Los Angeles are designed with different yielding links, including conventional and replaceable links. The performance of the structures is investigated through nonlinear time-history analyses (NLTHAs) under a suite of 40 ground motions, selected and scaled to match the target uniform hazard spectrum. The peak deformations are first examined to assess the performance of the buildings as well as the design procedure. Residual deformations are also evaluated and critically compared with acceptable limits, to provide insight into the downtime and recovery time of EBFs after major earthquakes. Previous studies have demonstrated that the response of stable yielding systems to major earthquakes is often accompanied by significant residual deformations, and that residual drifts exceeding 0.5% can cause hindrance to the buildings occupants. In EBFs, in addition to residual drifts, residual link rotations are also relevant and expected to be more severe due to the localization of inelastic deformations in the yielding link. For replaceable modular yielding links, significant residual link rotations after major earthquakes will hinder repairs and the link replacement process, which is one of the important design objectives. The performance of EBFs is also compared with what was observed in previous studies for buckling restrained braced frames and special moment resisting frames. In the end, the results from the extensive NLTHAs are used to establish a relationship between peak drifts and peak link rotations in EBFs. [ABSTRACT FROM AUTHOR]

In recent decades, research on renewable energy has been boosted by the emerging awareness of energy security and climate change and their consequences, such as the global cost of adapting to the climate impacts. Both onshore and offshore wind turbine farms have been considered as one of the main alternatives to fossil fuels. Their development currently involves seismic-prone areas, such as the Californian coastline and East Asia, where the risk of soil liquefaction is significant. Onshore wind turbines (OWTs) typically are founded on shallow rafts. Their operation can be affected strongly by the simultaneous presence of intense earthquakes and wind thrust, which may cause remarkable permanent tilting and loss of serviceability. In these conditions, accurate evaluation of the seismic performance of these structures requires the development of well-validated numerical tools capable of capturing the cyclic soil behavior and the build-up and contextual dissipation of seismic-induced pore-water pressures. In this paper, a numerical model developed in OpenSees, calibrated against the results of dynamic centrifuge tests, was used to evaluate the influence of some ground motion intensity Measures of the seismic behavior of OWTs included the amplitude, frequency content, strong-motion duration, and Arias intensity (energy content) of the earthquake, together with the effect of a coseismal wind thrust, which is not well explored in the literature. The seismic performance of an OWT was assessed in terms of peak and permanent settlement and tilting, the latter of which was compared with the threshold of 0.5° typically adopted in practice. [ABSTRACT FROM AUTHOR]

To accurately and rapidly predict seismic responses, including the maximum displacement (MaxD) and maximum acceleration (MaxA), of the isolated structure considering the soil–structure interaction (SSI), five ensemble learning models, i.e. random forest (RF), gradient boosting regression tree (GBRT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM) and stacking model, are constructed. Firstly, a total of 96 000 nonlinear time history analyses of the isolated structure considering the SSI are conducted with the aid of OpenSees. The generated database is used for training and testing ensemble learning models. The ensemble learning models have 12 input variables in four categories, i.e. ground motion parameters, structural parameter, isolation parameters and soil parameter, and two output variables, i.e. MaxD and MaxA. The study shows that all ensemble learning models have excellent prediction performance for both training and testing datasets. The determination coefficients are larger than 0.96 and root-mean-square errors (RMSEs) are relatively small. Among the five ensemble learning models, the stacking model exhibits the best performance. In addition, the calculation method of feature importance score for the stacking model is provided. According to the feature importance analysis, the ground motion parameters have greater impact on seismic responses than other three categories of inputs. Finally, six ground motions are randomly selected to verify the generalization ability of the proposed ensemble learning models. The results show that the stacking model has a favorable generalization ability with relatively small prediction errors. [ABSTRACT FROM AUTHOR]

The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subjects (age: 23.17 ± 2.04, height: 174.17 ± 6.46 cm) participated in a controlled environment data collection and performed a series of gait tasks with both systems attached to each ankle. A total of 2820 strides were analyzed. The results show a median absolute stride length error of 1.86 cm between the IMU-based wearable device reconstruction and the motion capture ground truth, with the 75th percentile at 3.24 cm. The median absolute stride horizontal velocity error was 1.56 cm/s, with the 75th percentile at 2.63 cm/s. With a measurement error to the reference system of less than 3 cm, we conclude that there is a valid physical recovery of stride length and horizontal velocity from data collected with the IMU-based wearable Syde® device. [ABSTRACT FROM AUTHOR]

In order to avoid the casualties caused by damaged buildings during strong earthquakes, it's important and essential to understand the seismic design specifications of buildings. The motion of a building depends on the interferometry of building and ground motion, the coupling between building and ground, and the mechanical properties of the building. We applied deconvolution technique to the motion recorded to separate the building response and calculated the structural parameters (including traveling wave velocity, resonant frequency and attenuation parameter). Therefore, we can check medium's state by tracking these parameters to avoid damaged building collapse in the next mega-earthquake. We deployed a seismograph array in the building to record the earthquakes and few months of ambient noise data. In addition, we divided the structure into lower and higher floors to calculate the layering velocity. We found that the wave velocities of the lower and higher floors are significantly different but the former exhibit stable variation. For the monitoring phase, we tried different stacking time-lengths and calculated the related traveling wave velocities which are similar to the analysis in earthquakes. From the above results, we concluded that the physical parameters of the building can monitor the healthy condition of structure. Finally, we hope these results would be helpful to build a long-term monitoring of building's healthy status and the assessment of seismic hazard. [ABSTRACT FROM AUTHOR]

Surface irregularities on the earth, such as hills and ridges, can amplify the ground motion caused by earthquakes and cause damage to buildings. Hence, it is crucial to study the ground motion amplification on hills and their environs under the effect of earthquakes. In this research, the seismic response of a triangular rocky hill subject to cylindrical horizontally polarized shear (SH) waves is investigated by means of a boundary integral equation method. A comparison is made to verify the feasibility of the present method. Parametric studies are performed to evaluate the influences of source location and hill shape on the ground accelerations on the hill and its environs under cylindrical SH waves of different frequencies. The results show that the ground accelerations near the hill are strongly relative to the source location. For a near-source scattering problem, the cylindrical wavefront assumption is more appropriate than the plane wave assumption. The thinner hill is more likely to cause multiple reflections of the seismic waves inside it, resulting in a stronger ground motion near the hillcrest. The acceleration response spectrum at the hillcrest is amplified in a wide period range of 0–4 s, and increasing the hill height will strengthen the amplification effect. The presence of the hill also results in the amplification of the acceleration response spectrum in the period range of 0–0.7 s on the flat ground surface. Highlights: The seismic response of a triangular hill to cylindrical SH waves was investigated. Necessity of cylindrical wavefront assumption for near-source problem was verified. Mechanism of ground motion amplification on a triangular hill was revealed. [ABSTRACT FROM AUTHOR]

We examined the seismic noise data collected from coastal and inland observatories in India, affected by the super cyclonic storm Amphan in the Indian Ocean, to understand the storm dynamics. Prominent disturbances in the 0.05–0.50 Hz frequency range were observed at the seismic stations, arising due to ocean‐continent interactions. The coastal stations displayed more pronounced ground motions contrary to the inland stations, with spindle‐shaped seismic wave envelopes intensifying as Amphan approached. The maximum ground displacements and energy occurred hours after the cyclone's eye, with maximum wind speed, moved away from the stations and not when it was close to the station. We observed significant variations in primary (0.05–0.10 Hz) and secondary microseism (0.10–0.50 Hz) energy during Amphan's directional changes. Secondary microseisms in short and long periods were found at 0.20–0.50 Hz and 0.10–0.20 Hz, respectively. Primary microseisms exhibited a simple pattern and were the weakest among the three energy bands. The CAL seismic station's seismic wave envelope showed an en‐echelon feature with increasing amplitude as Amphan approached, indicating the influence of ocean resonance and coastal wave reflection. This study demonstrates monitoring of the tropical cyclone paths based on seismic signatures obtained using microseisms recorded at seismic stations, a cost‐effective tool. Integrating these seismic signals with atmospheric observations in near real‐time would probably enable an effective monitoring of cyclones and timely issuance of their alerts. Key Points: Monitor the Super Cyclone Amphan in the Bay of Bengal using Coastal seismological ObservatoriesSecondary microseisms in the short and long periods were found at 0.20–0.50 Hz and 0.10–0.20 HzMicroseisms recorded at seismic stations can be potential source of information for cyclone tracking [ABSTRACT FROM AUTHOR]

This paper focuses on building a ground motion model (GMM) using artificial neural network technique driven by a synthetically generated database in a data poor region. A hybrid simulated method considering nonlinear site response is used to generate potential ground motions in Tianjin area. The synthetic database containing a total of 9267 ground motion records from 93 simulated earthquake events are utilized to develop the model. A back propagation neural network developed by genetic algorithm (GA-BPNN) is used to obtain the optimal weights and biases that most fit the target dataset without overfitting. The structure of GA-BPNN model consists of 322 unknowns including weights and biases that connect input and output parameters. The model is developed to predict PGA and 5% damped spectral acceleration (periods from 0.01 to 10 s). The input parameters consist of moment magnitude (Mw), strike (φ), dip (δ), rake angle (λ), focal depth (h), epicenter distance (R) and azimuth (θ). The model performance is observed to be within the appropriate error limits. It is found that the model has the ability to capture the parametric variation relationship. Additionally, the synthetically based model is compared with empirically based GMM relations derived from NGA-West2, finding it has similar performance and behavior to leading GMMs. The model application in Tianjin area demonstrates that this paper provides a scheme to utilize synthetic database and build GMMs in data poor regions. [ABSTRACT FROM AUTHOR]

Climate warming is degrading palsa peatlands across the circumpolar permafrost region. Permafrost degradation may lead to ecosystem collapse and potentially strong climate feedbacks, as this ecosystem is an important carbon store and can transition to being a strong greenhouse gas emitter. Landscape-level measurement of permafrost degradation is needed to monitor this impact of warming. Surface subsidence is a useful metric of change in palsa degradation and can be monitored using interferometric synthetic-aperture radar (InSAR) satellite technology. We combined InSAR data, processed using the ASPIS algorithm to monitor ground motion between 2017 and 2021, with airborne optical and lidar data to investigate the rate of subsidence across palsa peatlands in northern Sweden. We show that 55 % of Sweden's eight largest palsa peatlands are currently subsiding, which can be attributed to the underlying permafrost landforms and their degradation. The most rapid degradation has occurred in the largest palsa complexes in the most northern part of the region of study, also corresponding to the areas with the highest percentage of palsa cover within the overall mapped wetland area. Further, higher degradation rates have been found in areas where winter precipitation has increased substantially. The roughness index calculated from a lidar-derived digital elevation model (DEM), used as a proxy for degradation, increases alongside subsidence rates and may be used as a complementary proxy for palsa degradation. We show that combining datasets captured using remote sensing enables regional-scale estimation of ongoing permafrost degradation, an important step towards estimating the future impact of climate change on permafrost-dependent ecosystems. [ABSTRACT FROM AUTHOR]

It is known that the site classifications are closely related to the damages caused by earthquakes in areas with increased seismic hazard. Additionally, another important parameter utilized to identify the damage is the Peak Ground Acceleration (PGA) value. While measurements and the GMPE are utilized to identify PGA values, site classification is usually conducted by using the Vs30 value. This study aims to identify the site classifications for Bursa province by using a different approach, namely, the H/V spectral ratio method based on the dominant periods. In this regard, 205 records belonging to 82 earthquakes recorded by 41 strong ground motion stations located in Bursa province were utilized. A mean H/V spectral ratio curve was developed for each station based on the Fourier and response spectra of these earthquake records. Generally, double or multiple peaks resulting from the site structure were observed in the H/V curves. Furthermore, for the station locations, the evaluations were conducted in accordance with the site classifications per the dominant period as it is suggested in the literature. The stations were identified as all of the site classifications suggested by (Zhao et al. Bull Seismol Soc Am 96:914–925, 2006), as SC-1, 2, 3 and 5 suggested by (Fukushima et al. J Earthquake Eng 11:712–724, 2007) and as CL I, II, III, IV and VII suggested by (Di Alessandro et al. Bull Seismol Soc Am 102:680–695, 2012). Additionally, various Spectral Acceleration estimations were made with different GMPE equations for scenario earthquakes, and the results were compared with the design spectra suggested by the Turkish Building Earthquake Code (TBEC 2018). As a result of the study, the H/V spectral curves were generated according to both Fourier and response spectra; using a great number of earthquake data, the hazard was assessed by the soil dominant period-based for the first time in Bursa province. [ABSTRACT FROM AUTHOR]

Numerous ground-motion models (GMMs) that predict the intensities of surface ground motions have been previously developed based on regression analysis (RA). This study develops GMMs to estimate 5% damped pseudo-spectral accelerations (PSAs) for 30 periods (0.01–7.0 s) for within-rock ground motions, based on machine learning (ML) methods (i.e., two ensemble methods (random forest (RF) and gradient boosting (GB)) and an artificial neural network (ANN)). GMMs are developed separately for four earthquake types (main and aftershocks of active crustal region events and those of subduction zone interface events), considering the differences in the characteristics of each earthquake type. We utilize 20,041 ground motions recorded at 575 borehole stations in Japan during 602 earthquakes with moment magnitudes greater than 5.0 and rupture distances shorter than 300 km. The prediction performances of GMMs based on RF, GB, ANN, and RA are evaluated by the standard deviations of the total, between-event, and within-event residuals. The GMMs based on the three ML methods (RF, GB, and ANN) perform better than the RA-based models. The RF-based GMMs resulted in the most accurate prediction of the PSAs of within-rock ground motions with a small bias and variance, which can enhance the seismic designs and seismic hazard assessments for underground structures. [ABSTRACT FROM AUTHOR]

The double-couple model of the earthquake source has been proven remarkably successful in explaining the radiation pattern in the low-frequency wavefield. However, the radiation pattern is distorted in the high-frequency wavefield. The frequency dependence of the radiation pattern is often interpreted as the path effects. The impact of earthquake sources on radiation patterns is uncertain. In our study, based on the fact that P waves vibrate along the radial direction and S waves vibrate along the transverse direction, the path effects modified model of radiation pattern is proposed based on the optimal ratio coefficient by measuring radial-to-transverse spectral ratios at multiple frequency ranges. Then, we found that the correlation coefficient decreases with the increase of frequency but remains stable with the increase of distance. This means the complexity of the earthquake source can distort the wavefield at higher frequencies and drive variability in the ground motion. [ABSTRACT FROM AUTHOR]

An optimisation-based calibration technique, using the area metric, is applied to determine the input parameters of a stochastic earthquake-waveform simulation method. The calibration algorithm updates a model prior, specifically an estimate of a region's seismological (source, path and site) parameters, typically developed using waveform data, or existing models, from a wide range of sources. In the absence of calibration, this can result in overestimates of a target region's ground motion variability, and in some cases, introduce biases. The proposed method simultaneously attains optimum estimates of median, range and distribution (uncertainty) of these seismological parameters, and resultant ground motions, for a specific target region, through calibration of physically constrained parametric models to local ground motion data. We apply the method to Italy, a region of moderate seismicity, using response spectra recorded in the European Strong Motion (ESM) dataset. As a prior, we utilise independent seismological models developed using strong motion data across a wider European context. The calibration obtains values of each seismological parameter considered (such as, but not limited to, quality factor, geometrical spreading and stress drop), to develop a suite of optimal parameters for locally adjusted stochastic ground motion simulation. We consider both the epistemic and aleatory variability associated with the calibration process. We were able to reduce the area metric (misfit) value by up to 88% for the simulations using updated parameters, compared to the initial prior. This framework for the calibration and updating of seismological models can help achieve robust and transparent regionally adjusted estimates of ground motion, and to consider epistemic uncertainty through correlated parameters. [ABSTRACT FROM AUTHOR]