• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.173-180
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• 2006

The seismic responses of a building are affected by the base soil conditions. In this study, linear time-history seismic analysis and nonlinear pushover static seismic analysis were performed to estimate the base shear forces of 3-, 5-, and 7-story steel buildings, considering the rigid and soft soil conditions. Foundation soil stiffness, based on the equivalent static stiffness formula, is used for the damper, one of the Link elements in SAP 2000. The base shear forces of the steel buildings, estimated through time-history analysis using the general-purpose structural-analysis program of SAP 2000, were compared with those calculated using the domestic seismic design code, the UBC-97 design response spectrum. and pushover static nonlinear analysis. The steel buildings designed for gravity and wind loads showed elastic responses with a moderate earthquake of 0.11 g, while the elastic soft-soil layer increased the displacement and the base shear force of the buildings due to soil-structure interaction and soil amplification. Therefore, considering the characteristics of the soft-soil layer, it is more reasonable to perform an elastic seismic analysis of a building's structure during weak or moderate earthquakes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.1
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• pp.19-28
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• 2022

In this study, three types of combined isolator consisting of High Damping Rubber Bearing (HDRB) and wire isolator were developed for Uninterruptible Power Supply system (UPS). The dynamic characteristics of the combined isolator were investigated through one-axis shaking table test. The input acceleration were generated in accordance with ICC-ES AC156 code. Scale factors of the input acceleration were designed to be 0.5-2 times the required response spectrum defined in ICC-ES AC156. Based on the test results, damage and dynamic characteristics of the UPS were investigated: including natural frequency, damping ratio, acceleration time history response, dynamic amplification factor and relative displacement. Based on that, it was found that the combined isolator developed in this study could improve the seismic behavior of the UPS, in particular, the response acceleration.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• Structural Engineering and Mechanics
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• v.81 no.2
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• pp.219-230
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• 2022

Due to the large number of railway bridges along China's high-speed railway (HSR) lines, which cover a wide area with many lines crossing the seismic zone, the possibility of a HSR train running over a bridge when an earthquake occurs is relatively high. Since the safety performance of the train will be threatened, it is necessary to study the safety of trains running over HSR bridges during earthquakes. However, ground motion (GM) is highly random and selecting the appropriate ground-motion intensity measures (IMs) for train running safety analysis is not trivial. To deal this problem, a model of a coupled train-bridge system under seismic excitation was established and 104 GM samples were selected to evaluate the correlation between 16 different IMs and train running safety over HSR bridges during earthquakes. The results show that spectral velocity (SvT₁) and displacement (SdT₁) at the fundamental period of the structure have good correlation with train running safety for medium-and long-period HSR bridges, and velocity spectrum intensity (VSI) and Housner intensity (HI) have good correlation for a wide range of structural periods. Overall, VSI and HI are the optimal IMs for safety analysis of trains running over HSR bridges during earthquakes. Finally, based on VSI and HI, the IM thresholds of an HSR bridge at different speed were analyzed.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.151-157
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• 2022

The purpose of this study was to investigate the frequency characteristics of forced vibration considering the vehicle progress. And the vibration characteristics in frequency domain that occur, when vehicle passes the bump, were analyzed. The responses such as displacement, velocity and acceleration were obtained through numerical analysis, and FFT processing was performed to analyze the frequency response function(FRF) characteristics. In particular, the location of vehicle eigenmodes and external excitation modes was clearly shown and analyzed. In the forced vibration model by external force, the behavior of the eigenmode in power spectrum and real and imaginary parts were also analyzed. The mode characteristics were also analyzed in each FRF. It was approximated by assuming total excitation force by considering the exciting frequency using impulse and sine wave forces, which can give the amplitude and frequencies. The response characteristics of forced oscillations having different mass, damping and stiffness have been systematically discussed.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.4
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• pp.183-191
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• 2024

Accurate seismic vulnerability assessment requires high quality and large amounts of ground motion data. Ground motion data generated from time series contains not only the seismic waves but also the background noise. Therefore, it is crucial to determine the high-pass cut-off frequency to reduce the background noise. Traditional methods for determining the high-pass filter frequency are based on human inspection, such as comparing the noise and the signal Fourier Amplitude Spectrum (FAS), f² trend line fitting, and inspection of the displacement curve after filtering. However, these methods are subject to human error and unsuitable for automating the process. This study used a deep learning approach to determine the high-pass filter frequency. We used the Mel-spectrogram for feature extraction and mixup technique to overcome the lack of data. We selected convolutional neural network (CNN) models such as ResNet, DenseNet, and EfficientNet for transfer learning. Additionally, we chose ViT and DeiT for transformer-based models. The results showed that ResNet had the highest performance with R² (the coefficient of determination) at 0.977 and the lowest mean absolute error (MAE) and RMSE (root mean square error) at 0.006 and 0.074, respectively. When applied to a seismic event and compared to the traditional methods, the determination of the high-pass filter frequency through the deep learning method showed a difference of 0.1 Hz, which demonstrates that it can be used as a replacement for traditional methods. We anticipate that this study will pave the way for automating ground motion processing, which could be applied to the system to handle large amounts of data efficiently.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.2
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• pp.145-151
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• 2008

The research so far has primarily analyzed efficiency improvement but in this research, it analyzes the characteristics of earthquake behavior, with changed pier heights, through ordinary and seismic analysis. For this, the kind of bridge bearing has been changed against PSC I-shaped bridge, which is mostly used in practice, and at all times earthquake analysis has been performed with through height of pier. Especially considering sectional power resulting from earthquake analysis, displacement of PSC I-shaped bridge bearing, diameter of pier pillar by earthquake load, and upper spare gap have been analyzed. In case of high-pear, seismic isolated device is decided as proper for cars' driving and for management of bridge since it decreases movement of upper structure, than elastic bearing, reducing size of elastic connect device, and it's been analyzed it is effective for improvement of fine view and economic efficiency reducing section of lower bridge structure. Finally, when design PSC I-shaped bridge bearing, for the proper structure and high-pier side, applying seismic isolated device through precise inner analysis is proper than applying equal elastic bearing.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.71-79
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• 2023

It is not efficient to install a maintenance system that measures seismic acceleration and displacement on all bridges and buildings to evaluate the safety of structures after an earthquake occurs. In order to maintain this, an on-site investigation is conducted. Therefore, it takes a lot of time when the scope of the investigation is wide. As a result, secondary damage may occur, so it is necessary to predict the safety of individual structures quickly. The method of estimating earthquake damage of a structure includes a finite element analysis method using approved seismic information and a structural analysis model. Therefore, it is necessary to predict the seismic information generated at arbitrary location in order to quickly determine structure damage. In this study, methods to predict the ground response spectrum and acceleration time history at arbitrary location using linear estimation methods, and artificial neural network learning methods based on seismic observation data were proposed and their applicability was evaluated. In the case of the linear estimation method, the error was small when the locations of nearby observatories were gathered, but the error increased significantly when it was spread. In the case of the artificial neural network learning method, it could be estimated with a lower level of error under the same conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.119-130
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• 2009

Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1503-1517
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• 2018

Mt. Baekdu is a stratovolcano located at the border between China and North Korea and is known to have formed through its differentiation stage after the Oligocene epoch in the Cenozoic era. There has been a growing interest in the magma re-activity of Mt. Baekdu volcano since 2010. Several research projects have been conducted by government such as Korea Meteorological Administration and Korea Institute of Geoscience and Mineral Resources. Because, however, the Mt. Baekdu volcano is located far from South Korea, it is quite difficult to collect in-situ observations by terrestrial equipment. Remote sensing is a science to analyze and interpret information without direct physical contact with a target object. Various types of platform such as automobile, unmanned aerial vehicle, aircraft and satellite can be used for carrying a payload. In the past several decades, numerous volcanic studies have been conducted by remotely sensed observations using wide spectrum of wavelength channels in electromagnetic waves. In particular, radar remote sensing has been widely used for volcano monitoring in that microwave channel can gather surface's information without less limitation like day and night or weather condition. Radar interferometric technique which utilized phase information of radar signal enables to estimate surface displacement such as volcano, earthquake, ground subsidence or glacial movement, etc. In 2018, long-term research project for collaborative observation for Mt. Baekdu volcano between Korea and China were selected by Korea government. A volcanic specialized research center has been established by the selected project. The purpose of this paper is to introduce about remote sensing techniques for volcano monitoring and to review selected studies with remote sensing techniques to monitor Mt. Baekdu volcano. The acquisition status of the archived observations of six synthetic aperture radar satellites which are in orbit now was investigated for application of radar interferometry to monitor Mt. Baekdu volcano. We will conduct a time-series analysis using collected synthetic aperture radar images.