• 한국지진공학회논문집
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• 제22권6호
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• pp.311-322
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• 2018

As a method of seismic-design for pile-supported wharves, equivalent static analysis, response spectrum analysis, and time history analysis method are applied. Among them, the response spectrum analysis is widely used to obtain the maximum response of a structure. Because the ground is not modeled in the response spectrum analysis of pile-supported wharves, the amplified input ground acceleration should be calculated by ground classification or seismic response analysis. However, it is difficult to calculate the input ground acceleration through ground classification because the pile-supported wharf is build on inclined ground, the methods to calculate the input ground acceleration proposed in the standards are different. Therefore, in this study, the dynamic centrifuge model tests and the response spectrum analysis were carried out to calculate the appropriate input ground acceleration. The pile moment in response spectrum analysis and the dynamic centrifuge model tests were compared. As a result of comparison, it was shown that the response spectrum analysis results using the amplified acceleration in the ground surface were appropriate.

• Earthquakes and Structures
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• 제9권5호
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• pp.983-997
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• 2015

This research evaluates the soil conditions for seismic stations situated in Romania using the horizontal-to-vertical spectral ratio (HVSR). The strong ground motion database assembled for this study consists of 179 analogue and digital strong ground motion recordings from four intermediate-depth Vrancea seismic events with $M_w{\geq}6.0$. In the first step of the analysis, the influence of the earthquake magnitude and source-to-site distance on the H/V curves is evaluated. Significant influences from both the earthquake magnitude and hypocentral distance are found especially for soil class A sites. Next, a site classification method proposed in the literature is applied for each seismic station and the soil classes are compared with those obtained from borehole data and from the topographic slope method. In addition, the success and error rates of this method are computed and compared with other studies from the literature. A more in-depth analysis of the H/V results is performed using data from seismic stations in Bucharest and a comparison of the free-field and borehole H/V curves is done for three seismic stations. The results show large differences between the free-field and the borehole curves. As a conclusion, the results from this study represent an intermediary step in the evaluation of the soil conditions for seismic stations in Romania and the need to perform more detailed soil classification analysis is highly emphasized.

• Earthquakes and Structures
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• 제27권2호
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• pp.83-95
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• 2024

The prediction of seismic behavior of the existing building stock is one of the most impactful and complex problems faced by countries with frequent and intense seismic activities. Human lives can be threatened or lost, the economic life is disrupted and large amounts of monetary reparations can be potentially required. However, authorities at a regional or national level have limited resources at their disposal in order to allocate to preventative measures. Thus, in order to do so, it is essential for them to be able to rank a given population of structures according to their expected degree of damage in an earthquake. In this paper, the authors present a ranking approach, based on Machine Learning (ML) algorithms for pairwise comparisons, coupled with ad hoc ranking rules. The case study employed data from 404 reinforced concrete structures with various degrees of damage from the Athens 1999 earthquake. The two main components of our experiments pertain to the performance of the ML models and the success of the overall ranking process. The former was evaluated using the well-known respective metrics of Precision, Recall, F1-score, Accuracy and Area Under Curve (AUC). The performance of the overall ranking was evaluated using Kendall's tau distance and by viewing the problem as a classification into bins. The obtained results were promising, and were shown to outperform currently employed engineering practices. This demonstrated the capabilities and potential of these models in identifying the most vulnerable structures and, thus, mitigating the effects of earthquakes on society.

• Geomechanics and Engineering
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• 제37권6호
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• pp.539-554
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• 2024

This study explores development of prediction model for seismic site classification through the integration of machine learning techniques with horizontal-to-vertical spectral ratio (HVSR) methodologies. To improve model accuracy, the research employs outlier detection methods and, synthetic minority over-sampling technique (SMOTE) for data balance, and evaluates using seven machine learning models using seismic data from KiK-net. Notably, light gradient boosting method (LGBM), gradient boosting, and decision tree models exhibit improved performance when coupled with SMOTE, while Multiple linear regression (MLR) and Support vector machine (SVM) models show reduced efficacy. Outlier detection techniques significantly enhance accuracy, particularly for LGBM, gradient boosting, and voting boosting. The ensemble of LGBM with the isolation forest and SMOTE achieves the highest accuracy of 0.91, with LGBM and local outlier factor yielding the highest F1-score of 0.79. Consistently outperforming other models, LGBM proves most efficient for seismic site classification when supported by appropriate preprocessing procedures. These findings show the significance of outlier detection and data balancing for precise seismic soil classification prediction, offering insights and highlighting the potential of machine learning in optimizing site classification accuracy.

• 한국지반공학회논문집
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• 제35권11호
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• pp.121-129
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• 2019

지진조기경보는 빠르게 도달하는 P파를 감지하고 이보다 느리게 전파되는 S파가 도달하기 전 알림을 주는 기술이다. 초기에 도달한 P파의 진폭과 우세주기를 통해 신속하게 규모와 진원을 추정하고 이를 기준으로 경보 혹은 속보를 전송하기에 P파의 분석은 신속한 지진정보에 생산에 중요한 요소이다. 하지만, 국외에서 발생한 큰 규모의 지진이 국내 관측망에서는 P파의 진폭이 크게 감쇠되어 관측되며, 이는 초기 분석단계에서 실제 규모보다 작은 국내 발생 지진으로 오분석 될 수 있다. 오분석의 결과가 그대로 수요자(국민)에게 오경보(false alarm)로 발송될 경우 지진조기경보서비스의 신뢰도를 저하 시킬 수 있으며, 신속대응이 필요한 사회 인프라시설 및 산업시설에는 경제적 손실을 야기할 수 있다. 따라서 이러한 오분석을 최대한 줄이기 위한 기술개발이 필요한 실정이다. 본 연구에서는 주파수-이격거리에 따른 감쇠특성을 이용한 필터뱅크(Filter Bank)를 사용하여 국내외 지진에 대한 분류 가능성을 검토하였다. 이를 위해 기상청 지진관측소에 기록된 2 < M_L ≦ 3의 국내지진 463개, 44개(3 < M_L ≦ 4), 4개(4 < M_L ≦ 5), 3개(M_L > 5)와 국외지진 89개를 사용하여 각 주파수영역에 따른 최대 P_v값을 산정하고 이를 분석하였다. 분석결과, 기본 설정 값보다 3번(6-12Hz)과 6번(0.75-1.5Hz) 밴드를 사용할 때 국내외 지진을 정확하게 분류할 수 있는 것으로 나타났다.

• 한국지진공학회논문집
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• 제13권2호
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• pp.47-58
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• 2009

본 연구에서는 변전소 시스템의 지진취약도 분석을 수행하여 변전소에 대한 지진취약도 함수를 제시하였다. 변전소는 여러 개의 설비와 구조물이 복합적으로 구성되어 있는 시스템이므로 각 설비에 대한 지진취약도 분석을 수행하여 이를 바탕으로 고장수목을 작성하여 변전소 전체의 파괴확률을 산정함으로써 변전소에 대한 지진취약도 평가를 수행하였다. 이를 위하여 국내 변전소의 현황을 파악하여 지진피해추정을 위한 변전소의 분류형식을 결정하였으며, 결정된 대표변전소 형식에 대한 평가대상 기기를 선정하였다. 대표 변전소 형식으로는 765kV, 345kV, 154kV 변전소의 GIS형 변전소로 결정하였다. 각 변전소의 취약도 검토대상 기기로는 변압기와 절연 애자를 선택하였다. 각 변전소의 변압기와 절연애자의 파괴모드와 파괴기준을 설정하여 지진취약도 곡선을 도출하였다. 최종적으로 변전소에 대한 고장수목을 이용하여 각 기기의 지진취약도 곡선으로부터 변전소 전체의 파괴확률을 산정하여 정의된 손상상태별 변전소의 지진취약도 함수를 산정하였다.

• Smart Structures and Systems
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• 제8권1호
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.327-344
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• 2013

Beam string structure (BSS) is introduced as a new type of hybrid prestressed string structures. The composition and mechanics features of BSS are discussed. The main principles of wavelet packet transform (WPT), principal component analysis (PCA) and support vector machine (SVM) have been reviewed. WPT is applied to the structural response signals, and feature vectors are obtained by feature extraction and PCA. The feature vectors are used for training and classification as the inputs of the support vector machine. The method is used to a single one-way arched beam string structure for damage detection. The cable prestress loss and web members damage experiment for a beam string structure is carried through. Different prestressing forces are applied on the cable to simulate cable prestress loss, the prestressing forces are calculated by the frequencies which are solved by Fourier transform or wavelet transform under impulse excitation. Test results verify this method is accurate and convenient. The damage cases of web members on the beam are tested to validate the efficiency of the method presented in this study. Wavelet packet decomposition is applied to the structural response signals under ambient vibration, feature vectors are obtained by feature extraction method. The feature vectors are used for training and classification as the inputs of the support vector machine. The structural damage position and degree can be identified and classified, and the test result is highly accurate especially combined with principle component analysis.

• 한국지진공학회논문집
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• 제11권1호
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• pp.59-65
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• 2007

IBC와 KBC의 지반분류는 ft-kips 단위체계를 기본으로 하고, 지반종류를 단일 지반특성값이 아닌 지반특성값 범위로 규정하여 지반종류에 따른 전단파속도와 지반계수들 간의 불명확한 관계 때문에 지반계수의 선형보간이 쉽지 않다. 또한, KBC의 지반분류에서 각 지반종류에 대한 지반특성값 범위가 너무 넓어서 구조기술자들이 다양한 지반의 실제적인 지반계수를 추정하는데 어려움을 격고 있다. 이 연구에서는 SI 단위체계를 고려한 새로운 지반분류체계를KBC등 차세대 내진설계기준을 위해 제안하였고, 제안된 새로운 지반분류에 따라 지반계수들의 선형보간 가능성을 검토하기 위해 $F_{a},\;F_{v}$, 지반계수들의 비교에 관한 연구를 수행하였다. 연구결과에 의하면, SI 단위체계와 얕게 묻힌기초 밑 30m 지반의 지반특성을 고려한 새로 제안한 지반분류체계를 이용하는 것이 지반계수의 선형보간을 위해서 보다 합리적이고, 설계스펙트럼 가속도계수의 선형보간도 각 지반을 대표하는 전단파속도에 따라 지반계수를 규정함으로써 보다 합리적으로 수행할 수 있다. 연구결과에 따라 KBC 내진설계기준을 위한 새로운 지반분류체계와 선형보간이 가능한 설계스펙트럼 가속도 계수를 제안하였다.

• 한국지리정보학회지
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• 제13권4호
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• pp.32-49
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• 2010

1978년 10월 7일 규모 5.0의 지진 발생으로 구조물 피해가 발생한 홍성 지역을 대상으로 지진 부지효과 관련 지진 지반운동을 평가하기 위하여 지질 및 지반 조건에 관한 지반 특성을 평가하였다. 현장에서는 16 개소의 부지에 대해 시추조사와 전단파속도 분포를 획득하기 위한 탄성파 시험의 다양한 지반 조사를 수행하였다. 홍성 및 인근에서의 지반 조사와 추가 수집을 통해 확보한 지반 자료를 토대로, 지반 정보 관련 전문가 시스템을 공간 GIS 기법을 적용하여 구축하였다. 소도시 지역의 지진운동 평가 목적의 GIS 기반 지반정보 시스템의 실질적 활용을 위하여, 기반암심도 및 부지 주기와 같은 지반 특성 변수의 공간 지진재해 구역화 지도를 홍성읍 행정 영역 전체에 걸쳐 작성하고 지진 취약도의 공간 분포를 확인하였다. 부지 주기 기반의 부지 분류 체계를 적용하여 내진설계 시 부지 증폭계수를 결정할 수 있는 공간 구역화를 수행하였다. 홍성 지역의 지진재해 구역화 연구로부터 지반 조사 기반의 GIS가 내륙 소도시의 지진 지반운동의 지역적 예측에 매우 유용함을 확인하였다.