Machine-Learning-Based Surface Ground-Motion Prediction Models for South Korea with Low-to-Moderate Seismicity

Ground-motion prediction models (GMPMs) have been developed to estimate seismic intensity considering earthquake magnitude, source-to-site distance, site condition, and so on. This study proposes GMPMs to predict 5% damped pseudospectral acceleration (PSA) for 27 periods ranging from 0.01 to 10 s in Korea, based on three machine-learning techniques (i.e., artificial neural network [ANN], random forest [RF], and gradient boosting [GB]). We use 1189 ground motions recorded at 50 surface stations during the 77 earthquakes with a local magnitude (M-L) greater than 3.0, including the Gyeongju and Pohang earthquakes with M-L of 5.8 and 5.4, respectively. We compare the performances of the three machine-learning-based models and the classical regression-based model in terms of the coefficient of determination (R-2), root mean square error (RMSE), mean absolute error (MAE), standard deviation of residuals, and between-event and within-event residuals. The GB-based model shows the best performance. In addition, we analyze the working process of the GB-based model using variable importance and partial dependence (PD) plots. Among the five independent variables (M-L, epicentral distance [R-epi], average shear-wave velocity of the upper 30 m [V-s30], focal depth, and slope angle) used in this study, M-L and R-epi are the most influential variables and show strong correlations with PSAs. We apply the GB-based model to three recent earthquakes larger than M-L 3.0, and the model accurately predicts the PSAs at various stations. We also generate maps of estimated PSA (PSA(eSt)) ) values for the four periods (T = 0.01, 0.1, 1, and 3 s) for the scenario earthquake with an M-L of 5.0. We provide a method for training the GB-based model using the Python library, which can enhance the ground-motion prediction not only in Korea but also worldwide, and an executable version of the validated GB-based model

Effects of pulse-like ground motions and wavelet asymmetry on responses of cantilever retaining wall

Fault-rupture processes produce pulse-like ground motions in near-fault regions. These motions are characterized as large-amplitude long-period pulsing that can cause severe structural damage. This study investigates their effect on cantilever retaining wall responses through finite-difference-based numerical simulations. We collect a suite of large-amplitude ground motions which are classified into pulse-like, non-pulse-like, and ambiguous using a pulse indicator. It turns out that relative wall movements by pulse-and non-pulse-like motions are not particularly different. Instead, relative wall movement is highly affected by ground motion Arias intensity, regardless of motion type. Additional simulations using original and reversed ground motion assess the effect of wavelet asymmetry (the ratio of peak amplitudes or energy values in wavelet positive and negative directions) on the wall response. Ground motion asymmetric to the wall movement direction generates larger wall displacement than ground motion asymmetric opposite to the wall movement direction. Relative wall displacements differ by up to approximately 46% depending on the direction of ground motion against the wall movement

Ground motion amplification models for Japan using machine learning techniques

Earthquake-induced ground motions can be altered by various factors that are associated with the characteristics of earthquake sources, paths, and sites. Conventionally, regression approaches have been used to develop empirical prediction models for ground motion amplifications. We developed models for ground motion amplifications based on three machine learning techniques (i.e., random forest, gradient boosting, and artificial neural network) using the database of the records at the KiK-net stations in Japan. The proposed machine learning based models outperforms the regression based model. The random forest based model provides the best estimation of amplification factors. Average shear wave velocity and the depth of the borehole are the two factors that influence the amplification model the most. Maps of the amplification factors for all KiK-net stations under moderate and large earthquake scenarios are provided. The three machine learning technique based models are also provided for the forward prediction of other earthquake scenarios

Seismic fragility assessment for cantilever retaining walls with various backfill slopes in South Korea

We evaluate seismic fragilities for cantilever retaining walls with three slope angles of backfill (i.e., 0, 10?, and 20?), subjected to the ground motions computed for four site classes (S2, S3, S4, and S5). We collect measured shear wave velocity profiles and select representative profiles. Using one-dimensional site response analyses, surface ground motions are computed corresponding to various site conditions. Numerical models are developed for a cantilever retaining wall with a height of 4 m using the FLAC2D software, and are verified by a comparison with an analytical solution. We analyze the correlations between the seismic behavior of the retaining wall and various ground motion parameters. A probabilistic seismic demand model is introduced to calculate the prob-abilities of exceeding three limit states of retaining walls, based on the relative wall displacements and settle-ments of the backfills. We propose a suite of seismic fragility curves which are functions of either the peak ground acceleration (PGA) or cumulative absolute velocity (CAV). In addition, we propose a suite of seismic fragility surfaces using dual ground motion parameters (PGA and CAV). The results highlight that the backfill slope angle and ground motion characteristics have a primary influence on the probabilities. When the backfill slope angle increases from 0 to 20?, the probabilities of exceeding the three limit states increase by up to approximately 1.7, 4.0, and 8.5 times, respectively. Additionally, the probabilities for S3 ground motions with a PGA of 0.4 g are higher than those for S2 motions with the same PGA by up to approximately 5, 16, and 36 times, respectively

Responses of a cantilever retaining wall subjected to asymmetric near-fault ground motions

Fault rupture produces pulse-like ground motions in the near-fault regions, which are significantly different from ordinary ground motions in the far-field regions with respect to both intensity and frequency contents. The pulse-like ground motions are characterized as high amplitude and long period pulses that could cause severe damage to structures. In this study, we investigated how the pulse-like ground motions have effects on the responses of a cantilever retaining wall by performing a series of numerical simulations. The seismic behaviors of the retaining wall were numerically modeled by adopting a finite difference scheme. High amplitude ground motions scaled to a fixed PGA were first collected as an input dataset and classified into pulse-like, non-pulse-like, and ambiguous motions by a pulse indicator. Then, differences in the development of displacements at the wall were quantitatively compared between the types of the motions. Additional simulations were carried out with the original and inverted input ground motions to investigate the effect of asymmetry of ground motion on the wall responses. It turned out that the asymmetrical ground motions with larger velocity amplitudes in the direction coincide with the relative wall movement could generate significant wall displacements

Effects of variability in ground motions and shear wave velocities on site response analyses for South Korea

Korea peninsula has been known as a safe zone from earthquake disasters. However, there has been a growing interest in earthquake research after the 2016 Gyeongju earthquake and the 2018 Pohang earthquake struck South Korea. In the seismic design, the seismic wave propagation characteristics are evaluated by the site response analysis(SRA), so it is necessary to obtain reliable SRA results. In this aspect, this study aimed to investigate the effect of uncertainty in shear-wave velocity and ground motions on the SRA results. The shear-wave velocity profiles obtained from the southeastern part of South Korea and seven suites of ground motions are used for the uncertainty quantification and nonlinear SRAs were also performed