• Magazine of korean Tunnelling and Underground Space Association
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• v.17 no.1
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• pp.44-51
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• 2015

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.213-225
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• 2004

The number of tunnels are in fact increasing as a part of linear improvement project of general national highway and road enlargement and pavement project. Recently, collapses of portal slope are also occurring considerably, due to local raining from severe rain storm and abnormal weather. Accordingly, it was risen a necessity to efficiently respond to tunnel portal slope damage and maintenance in Korea and oversea nations. This paper is a basic proposal to execute a survey on the current status and state of the tunnel portal slopes that were already installed and are now being operated along general national highways, and also to execute state evaluation for the purpose of managing those effectively. As a research method, domestic tunnels were analyzed in accordance with geometrical shape such as access type, portal form, and tunnel type, etc. via field survey to analyze the types of tunnel portal slopes along national highways. State evaluation classification sheet is presented to divide classes for the danger state of the surveyed portal slopes, and then the related grades are divided. It is mainly aimed at classifying the tunnel portal slope along national highways with using this state evaluation, to use it as basic data so that continuous maintenance can be executed in the future in accordance with danger classes.

• Journal of the Korean Geotechnical Society
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• v.16 no.5
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• pp.117-127
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• 2000

터널 시공과 굴착과정에서 파쇄대, 절리, 연약대, 균열 등 암반에서의 불연속면은 중요한 역할을 한다. 본 연구에서는 지반 고유의 특징인 불확실성에 의한 터널 설계와 시공 과정에서 겪는 많은 시행오차를 최소화하기 위해서 국내의 터널 붕락 현장의 지반조사 자료를 분석하여 터널 붕락 유형 및 규모를 제시할수 있는 Geo-predict 시스템을 개발하였다. Geo-predict 시스템은 총 104개 터널 붕괴/붕락자료(국외84개, 국내20개)를 분석한 자료를 테이터베이스로 인공신경망 학습을 토해서 터널 붕괴 형태와 규모를 추론하는 시스템이다. 본 논문에서는 Geo-predict의 개발과정 및 구성.기능을 소개하였으며 104개 터널 현장 자료를 지반조건별로 분석하고 이를 데이터베이스화하여 인공신경함을 이용한 추론 시스탬을 구축하고, 2개 고속전철 터널현장과 1개 지하철 시공현장에 적용성 평가를 실시하여, 터널의 붕락 가능 및 붕락 규모를 추론하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.785-791
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• 2023

Risk management is essential for preventing accidents arising from uncertainties in TBM tunnel projects, especially concerning managing the risk of TBM tunnel collapse, which can cause extensive damage from the tunnel face to the ground surface. In addition, prioritizing risks is necessary to allocate resources efficiently within time and cost constraints. Therefore, this study aimed to establish a TBM risk database through case studies of TBM accidents and determine a risk priority for TBM tunnel collapse using the Bayes theorem. The database consisted of 87 cases, dealing with three accidents and five geological sources. Applying the Bayes theorem to the database, it was found that fault zones and weak ground significantly increased the probability of tunnel collapse, while the other sources showed low correlations with collapse. Therefore, the risk priority for TBM tunnel collapse, considering geological sources, is as follows: 1) Fault zone, 2) Weak ground, 3) Mixed ground, 4) High in-situ stress, and 5) Expansive ground. In practice, the derived risk priority can serve as a valuable reference for risk management, enhancing the safety and efficiency of TBM construction. It provides guidance for developing appropriate countermeasure plans and allocating resources effectively to mitigate the risk of TBM tunnel collapse.

• Tunnel and Underground Space
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• v.9 no.3
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• pp.214-220
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• 1999

In this study, the validity of items of RMR system is evaluated and the applicability of this system to the data measured in Korean sites if discussed. Database was constructed from 139 sites, which are composed of subways, railway tunnels and road tunnels. These sites are located nationwide. Analysis shows that original classification of Bieniawski is valid although it was derived empirically. But it has considerable rating difference (error) in the result of Korean application. Thus new classification systems of KRMRI and KRMR2 are suggested, which are deduced from the Korean database. The former includes adjusted ratings and the latter adopts two more items. These are deduced by artificial neural network because it is difficult to select \`characteristic value'to estimate rock quality.

• Magazine of korean Tunnelling and Underground Space Association
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• v.2 no.1
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• pp.130-138
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• 2000

본 연구에서는 수평보강재로 보강된 터널 막장의 거동에 관한 매개변수 연구결과를 다루었다. 매개변수 연구에서는 막장주변의 3차원 응력-변형율 거동을 보다 효율적으로 모델링하기 위해 3차원 유한요소해석 모형을 적용하였으며 보강패턴에 따른 막장의 거동을 고찰하기 위해 다양한 경계조건에 대한 해석을 수행하였다. 해석결과를 토대로 막장의 응력해방-변위거동의 관계를 고찰하였으며, 보강패턴과 막장 변위의 정성${\cdot}$정량적인 관계를 제시함과 아울러서 향후 수행될 반경험적 설계/해석법의 개발을 위한 데이터베이스를 구축하였다. 한편, 해석결과 보강재 타설수 및 길이 등 각 보강설계 인자에 대한 임계치가 존재하는 것으로 나타났으며 따라서 보다 안전하고 경제적인 설계를 위해서는 이를 고려하여야 할 것으로 판단된다.

• Tunnel and Underground Space
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• v.10 no.3
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• pp.418-429
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Economic and Environmental Geology
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• v.43 no.6
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• pp.649-659
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• 2010

In this study, a tunnel information database system was developed to optimize the process of assessing and analyzing geological information from the life cycle of tunnel construction. All data from every stage in tunnel construction can be put into the system and be utilized for the decision making. In the system, tunnel face mapping information can be managed by digital format which can be easily transformed into 3D visualization module and thus help analyzing geological discontinuities. The system was applied to waterway and road tunnel in domestic area to verify its effectiveness.

• Geotechnical Engineering
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• v.14 no.2
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• pp.107-126
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• 1998

Ground settlements induced by tunnel excavation cause the foundations of the neighboring building structures to deform. An expert system called NESASS( Neural network Expert System for Adjacent Structure Safety analysis) was developed to analyze the structural safety of such building structures. NESASS predicts the trend of ground settlements resulting from tunnel excavation and carries out a safety analysis for building structures on the basis of the predicted ground settlements. Using neural network technique. the NESASS learns the database consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. The NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure. and in turn, determines the safety of the structure. In addition, the NESASS predicts the patterns of cracks to be formed in the structure, using Dulacska model for crack evaluation. In this study, the ground settlements measured from Seoul subway construction sites were collected and classified with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to select the optimal neural network model for the database. A comparison of the ground settlement predicted by the NESASS with the measured ones indicates that the NESASS leads to reasonable predictions. The results of confidence evaluation for safety evaluation system of the NESASS are presented in this paper.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.171-181
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.