• 한국지진공학회논문집
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• 제25권6호
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• pp.233-240
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• 2021

The stochastic method is applied to simulate strong ground motions at seismic stations of seven metropolises in South Korea, creating an earthquake scenario based on the causative fault of the 2016 Gyeongju earthquake. Input parameters are established according to what has been revealed so far for the causative fault of the Gyeongju earthquake, while the ratio of differences in response spectra between observed and simulated strong ground motions is assumed to be an adjustment factor. The calculations confirm the applicability and reproducibility of strong ground motion simulations based on the relatively small bias in response spectra between observed and simulated strong ground motions. Based on this result, strong ground motions by a scenario earthquake on the causative fault of the Gyeongju earthquake with moment magnitude 6.5 are simulated, assuming that the ratios of its fault length to width are 2:1, 3:1, and 4:1. The results are similar to those of the empirical Green's function method. Although actual site response factors of seismic stations should be supplemented later, the simulated strong ground motions can be used as input data for developing ground motion prediction equations and input data for calculating the design response spectra of major facilities in South Korea.

• Earthquakes and Structures
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• 제16권2호
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• pp.165-175
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• 2019

Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

• 터널과지하공간
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• 제34권4호
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• pp.301-311
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• 2024

우리나라는 2016년 경주 지진과 2017년 포항 지진 이후 지진 재해 방지 대책의 필요성이 증가하고 있으며, 지진 피해 정량화를 위해 신뢰성 있는 지진 재해도 해석 기법과 지반운동 모델이 요구된다. 최근 심층 지하 시설에 대한 수요가 증가하고 있다. 이에 따라 지하 암반층에서의 지진 재해 정량화 기법의 정확성 확보가 필요하다. 본 연구에서는 국내 시추공 관측소에서 계측된 지반운동 자료를 활용하여 지하 암반층에서의 지반운동을 예측할 수 있는 모델을 제안하였다. 스펙트럴 가속도의 0.01~10초 주기 중 17개를 대상으로 경험적 기법 중 회귀분석을 적용하여 지반운동 모델을 개발하였다. 지반운동 모델의 예측 성능을 평가 및 개선하기 위해 잔차 분석을 수행하고, 보정 인자를 모델식에 추가하였다. 제안된 모델을 적용하였을 때 잔차의 구간 평균이 0에 근접하였고, 기존 국외 모델들과 유사한 종합 잔차의 표준편차를 확인함으로써 제안된 모델의 신뢰성을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.226-229
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• 1999

We have been developing a method to build models for time series using Genetic Programming. The proposed method has been applied to various kinds of time series e.g. computer-generated chaos, natural phenomena, and financial market indices etc. Now we apply the prediction method to time histories of seismic ground motion i.e. one-step-ahead prediction of seismographic amplitude. Waves of earthquakes are composed of P-waves and S-waves. They propagate in different speeds and have different characteristics. It is believed that P-waves arrive firstly and S-waves arrive secondly. Simulations were performed based on real data of Hyuganada earthquake which broke out at southern part of Kyushuu Island in Japan. To our surprise, prediction model built using the earthquake waves in early time can enough precisely predict main huge waves in later time. Lots of experiments lead us to conclude that every slice of data involves P-wave and S-wave. The simulation results suggest the GP-based prediction method can be utilized in alarm systems or dispatch systems in an emergency.

• 한국지진공학회논문집
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• 제10권4호
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• pp.45-54
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• 2006

2005년 3월 20일 발생한 Fukuoka 지진 시 국내 및 일본에서 관측된 자료를 이용하여 지반운동 감쇄특성을 분석하였다. 또한 최근 국내 및 일본에서 제시된 지반운동 거리감쇄식을 이용한 예측값과의 비교를 통하여 국내 강지진동 예측 시 일본에서 개발된 감쇄식의 적용가능성을 평가하였다. 그 결과 동일 거리에 위치한 국내 및 일본 관측소에서 측정한 기록이 비교적 유사하게 나타났으며 국내 및 일본에서 제시된 지반운동 거리감쇄식의 예측값이 매우 유사하게 나타나 국내에서의 강지진동 예측 시 일본에서 제시된 지반운동 감쇄식을 200km 이상의 비교적 원거리에 대한 국내 감쇄식의 평가 등에 유용하게 활용할 수 있는 것으로 나타났다.

• 한국지반환경공학회 논문집
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• 제9권4호
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• pp.53-61
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• 2008

지진파는 진원지로부터 지표면으로 전파되는 과정에서 전파경로와 부지증폭정도의 차이, 그리고 비균질한 지반에서의 지진파 산란 등으로 인하여 공간적으로 변이하게 된다. 공간적으로 변이하는 지진파는 교량과 터널과 같이 종단방향 길이가 긴 구조물에 큰 영향을 미칠 수 있다. 지진파의 공간적 변이성이 교량에 미치는 영향에 대해서는 잘 알려져 있지만 터널에 미치는 영향에 대해서는 체계적인 연구가 수행된 바 없다. 본 연구에서는 공간적으로 변이하는 지진파에 대한 터널의 응답을 예측하기 위한 새로운 기법을 개발하였다. 개발된 기법의 핵심은 이격거리별 계산된 공간적으로 변이하는 지진파의 시간이력으로부터 생성되는 종단방향 변위 주상도이다. 종단방향 변위 주상도는 일련의 3차원 유사정적 유한요소해석을 수행하는데 사용되었다. 해석결과, 공간적으로 변이하는 지진파는 터널에 종단방향 휨을 유발하며 터널 라이닝에 큰 축력이 발생할 수 있는 것으로 나타났다. 이는 특히 지반의 특성이 변이하는 경계면에서 영향이 큰 것으로 나타났다.

• 한국구조물진단유지관리공학회 논문집
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• 제6권2호
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• pp.195-202
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• 2002

Urbanization and development of industry makes people concerned about quality of circumstances. Problems of vibration are on the rise. Vibration makes inhabitants feel unpleasant and involves structural damage. The purpose of this study is to assess damage of reinforced concrete structures due to ground motions as the parameters of frequency, duration time and aspect ratio of structures are changed. Ground motions were modeled as sine waves. To compare sine waves with real ground motions, two cases are selected; one is blast loading case and the other is earthquake loading. It was intended to provide means to assess R/C structure damage due to ground motions.

• Earthquakes and Structures
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• 제7권4호
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• pp.485-510
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• 2014

In performance-based seismic design procedures Peak Ground Acceleration (PGA) and pseudo-Spectral acceleration ($S_a$) are commonly used to predict the response of structures to earthquake. Recently, research has been carried out to evaluate the predictive capability of these standard Intensity Measures (IMs) with respect to different types of structures and Engineering Demand Parameter (EDP) commonly used to measure damage. Efforts have been also spent to propose alternative IMs that are able to improve the results of the response predictions. However, most of these IMs are not usually employed in probabilistic seismic demand analyses because of the lack of reliable Ground Motion Prediction Equations (GMPEs). In order to define seismic hazard and thus to calculate demand hazard curves it is essential, in fact, to establish a GMPE for the earthquake intensity. In the light of this need, new GMPEs are proposed here for the elastic input energy spectra, energy-based intensity measures that have been shown to be good predictors of both structural and non-structural damage for many types of structures. The proposed GMPEs are developed using mixed-effects models by empirical regressions on a large number of strong-motions selected from the NGA database. Parametric analyses are carried out to show the effect of some properties variation, such as fault mechanism, type of soil, earthquake magnitude and distance, on the considered IMs. Results of comparisons between the proposed GMPEs and other from the literature are finally shown.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.401-413
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• 2022

The collapse of civil infrastructure due to natural disasters results in financial losses and many casualties. In particular, the recent increase in earthquake activities has highlighted on the importance of assessing the seismic performance and predicting the seismic risk of a structure. However, the nonlinear behavior of a structure and the uncertainty in ground motion complicate the accurate seismic response prediction of a structure. Artificial intelligence can overcome these limitations to reasonably predict the nonlinear behavior of structures. In this study, a deep learning-based algorithm was developed to estimate the time-history seismic response of bridge structures. The proposed deep neural network was trained using structural and ground motion parameters. The performance of the seismic response prediction algorithm showed the similar phase and magnitude to those of the time-history analysis in a single-degree-of-freedom system that exhibits nonlinear behavior as a main structural element. Then, the proposed algorithm was expanded to predict the seismic response and fragility prediction of a bridge system. The proposed deep neural network reasonably predicted the nonlinear seismic behavior of piers and bearings for approximately 93% and 87% of the test dataset, respectively. The results of the study also demonstrated that the proposed algorithm can be utilized to assess the seismic fragility of bridge components and system.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 춘계 학술발표회
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• pp.146-153
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• 2009

One dimensional site response analysis is widely used in prediction of the ground motion that is induced by earthquake. Equivalent linear analysis is the most widely used method due to its simplicity and ease of use. However, the equivalent linear method has been known to be unreliable since it approximates the nonlinear soil behavior within the linear framework. To consider the nonlinearity of the ground at frequency domain, frequency dependent algorithms that can simulate shear strain - frequency dependency have been proposed. In this study, the results of the modified equivalent linear analysis are compared to evaluate the degree of improvement and the applicability of the modified algorithms. Results show the novel smoothed curve that is proposed by this study indicates the most stable prediction and can enhance the accuracy of the prediction.