• Computational Structural Engineering
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• v.26 no.3
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• pp.42-46
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• 2013

• Journal of the Korean Geosynthetics Society
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• v.17 no.2
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• pp.9-18
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• 2018

In this study, a field model experiment was performed to analyze the bahavior of slope during failure. It was analyzed through x-MR control chart method with inverse displacement and K-value. As a result, the portent was confirmed at 4 minutes before slope failure in Case 1. The change of the control limit line according to moving range was analyzed and it was effective to apply K = 3. Use of the inverse displacement and x-MR control chart method will be useful for the prediction of abnormal behavior through quick and objective judgment. Prediction of slope failure using control chart method can be used as basic data of slope measurement management standard, and it can contribute in reduction of life and property damage caused by slope disaster.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.76-85
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• 2015

We have developed a software to predict failure time of the rock slope based on analysis of the data from real time displacement measurements with respect to time. The software consists of four modules that play roles in analytical methods such as inverse velocity method, log time-log velocity method, log velocity-log acceleration method and nonlinear least square method to estimate failure time. VisualBasic.NET on the MS Visual Studio platform was utilized as a development tool to efficiently implement the modules and the graphical user interface of the software. Displacement data obtained from laboratory physical model studies of plane sliding were used to explore the applicability of the software, and to evaluate the possibility of predicting potential slope failure. It seems possible to estimate failure time using developed software for sliding plane having exponential type of deformability.

• Journal of the Korean GEO-environmental Society
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• v.13 no.8
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• pp.25-33
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• 2012

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to consider various geographies and geotechnical conditions. When the tunnel is under construction, examination of accurate safety and prediction of behavior are overcome the limits of predicting behavior by Artificial Neural Network in this study. First, construct the suitable structure after the data of field was made sure by the multi-layer back propagation, then apply with algorithm. Employ the result of measured data from database, and consider the influence factor of tunnel, like supporting pattern, RMR, Q, the types of rock, excavation length, excavation shape, excavation over, to carry out the reliable analysis through field applicability of Artificial Neural Network. After studying, using the ANN model to predict the shearing displacement, convergence displacement, underground displacement, Rock bolt output follow the excavation over of tunnel construction field, then determine the field applicability with ANN through field measured value and comparison analysis when tunnel is being constructed.

• Journal of the Korea Concrete Institute
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• v.23 no.5
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• pp.667-674
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• 2011

This paper discusses the analysis method of prestressed concrete girder integral abutment bridges for a 75-year bridge life and the development of prediction models for abutment displacements under thermal loading due to annual temperature fluctuation and time-dependent loading. The developed nonlinear numerical modeling methodologies considered soil-structure interaction between supporting piles and surrounding soils and between abutment and backfills. Material nonlinearity was also considered to simulate differential rotation in construction joints between abutment and backwall. Based on the numerical modeling methodologies, a parametric study of 243 analysis cases, considering five parameters: (1) thermal expansion coefficient, (2) bridge length, (3) backfill height, (4) backfill stiffness, and (5) pile soil stiffness, was performed to established prediction models for abutment displacements over a bridge life. The parametric study results revealed that thermal expansion coefficient, bridge length, and pile-soil stiffness significantly influenced the abutment displacement. Bridge length parameter significantly influenced the abutment top displacement at the centroid of the superstructure, which is similar to the free expansion analysis results. Developed prediction model can be used for a preliminary design of integral abutment bridges.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.15-26
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• 2003

Urban excavation requires highly reliable prediction technique for the design and construction of earth retaining structure in order to protect adjacent structures around deep excavation. Application of the pre-loading of bracing for deep excavation has been reported, and the known beneficial effects are not fully understood and recognized by many practitioners. Model tests have been carried out to evaluate the efficiency of pre-loading system in reducing ground settlement as well as prediction of structural damage around excavation in sand. The test results revealed that the applied pre-loading of 50% and 70% showed about 20% of reduction in horizontal wall displacement and 30∼40% reduction in ground settlement. Also, bracing forces and earth pressure distribution behind the wall have been monitored during pre-loading at various excavation stages.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.2
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• pp.95-101
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• 2017

In this study, we derived theoretical equations for the zigzag movement of a leading vehicle, which is the most frequent behavior in train accidents, by using a simplified spring-mass model for the rolling stock. In order to solve the equations of motion, we applied the Runge-Kutta method, which is the typical numerical analysis method used for differential equations. Furthermore, the lateral displacement of the wheel-set at the wheel-rail interface was estimated using kinetic energy. In order to verify the derived equations, we compared the theoretical and simulated results under various collision conditions. The maximum relative deviations of the lateral displacements were 0.8 [%] ~ 4.7 [%] in light collisions and 0.6 [%] ~ 5.1 [%] under derailment conditions. When an accident is simulated, these theoretical equations can be used to predict the overall behavior and obtain the offset of the body-to-body link as the initial perturbation.

• Journal of the Korean GEO-environmental Society
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• v.19 no.9
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• pp.29-36
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• 2018

Several studies have been conducted on monitoring system and automatic measuring instruments to prevent slope failure in advance in Korea and overseas. However, these studies have quite complex structure. Since most of the measurement systems are installed on the slope surface, the researches are carried on the measurement system that detects sign of slope collapse in advance and alerts are still unsatisfactory. In this study, slope collapse experiments were carried out to understand the slope failure mechanism according to rainfall conditions. The water content and displacement behavior at the early stage of the slope failure were analyzed through the measurement of the ground displacement and water content. The results of this study can be used by local government as a basic data for the design of slope failure alarm system to evacuate residents in case of slope failure or landslide due to heavy rainfall.

• Journal of the Korean GEO-environmental Society
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• v.24 no.8
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• pp.13-20
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• 2023

Tunnelling through the geological anomalies has widely known to have many difficulties such as bottom heave, crack of lining, squeezing and so on. To stabilize the tunnel during the construction or after construction, various reinforcing methods have been introduced and applied such as micropiling at the bottom of tunnel to prevent the bottom heave. In this study, long-term behavior of tunnel in the presence of geological anomalies was predicted using numerical analyses. To this end, material properties for swelling rock model capable of representing the rock swelling behavior was obtained using matching process with measured data to validate the adopted model. After the model validation, simulations were performed to predict the long-term behavior of tunnel in the geological anomalies.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.59-70
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• 2008

도심지 터널의 설계, 시공 그리고 유지관리에 있어서 지반 변위 억제와 변형거동 예측은 중요하다. 국내 외 연구자들은 다양한 수치해석적인 기법과 현장 계측 결과를 이용하여 터널 시공과 관련된 변형거동 예측을 시도하였다. 하지만, 설계물성치의 산정과 지반 모델링 그리고 수치해석기법과 관련된 사용상의 어려움에 의해 아직까지 만족스러운 결과를 얻지는 못하였다. 본 논문은 수치해석적인 기법과 인공신경망을 이용하여 도심지 NATM 터널의 설계 물성치 산정과 변형거동 예측에 관한 방법을 제안하였다. 인공신경망 모델 개발을 위한 학습과 테스트과정은 데이터베이스된 수치해석결과를 이용하였다. 개발된 인공신경망 모델은 입력변수인 지반변위와 결과변수인 설계 물성치 간의 상호관계를 적절히 인식할 수 있다. 수치해석은 지반의 연화거동을 모사할 수 있는 변형률 연화모델을 적용하였다. 사례분석에 있어서 굴착 초기단계의 계측 값을 개발된 인공신경망 모델에 입력하여 설계 물성치를 계산하였으며, 수정된 설계 물성치는 수치해석을 통하여 다음 굴착단계에서의 터널 주변의 지반 변형거동을 예측하였다. 본 논문에서 제안된 방법을 토대로 시공조건이 엄밀한 도심지 터널의 설계물성치의 정량적인 평가 및 변형거동 예측이 계측이 입수된 초기 굴착단계에서 가능할 것으로 기대된다.