Mechanical Mechanism of Main Tunnels and Cross Passage Construction - A 3D Numerical Investigation

Yoo, Chungsik,Shuaishuai, Cui,Ke, Wu,Qianjn, Zhang,Zheng, Zhang,Jiahui, Zhao Korean Geosynthetics Society 2019 한국지반신소재학회 논문집 Vol.18 No.1

This paper presents the results of a three-dimensional numerical investigation into the mechanical mechanism of main tunnels and cross passage construction. Aimed at the complex space structure composed of two main tunnels and cross passage, 3D numerical model of the structure and surrounding rock was built to analyze the influence. Comparative analysis of different buried depths were carried out. The results of the study indicate that the stress concentration was occurred in the intersecting linings, especially in the opening side lining, which leads to an unfavorable form of force that is pulled up by the upper and lower sections in the intersecting linings due to the construction of the cross passage. The excavation of the cross passage also destroys the stability of the original soil layer and causes settlement of the surface and main tunnels. Practical implications of the findings are discussed.

Development of AI-based Prediction and Assessment Program for Tunnelling Impact

Yoo, Chungsik,HAIDER, SYED AIZAZ,Yang, Jaewon,ALI, TABISH Korean Geosynthetics Society 2019 한국지반신소재학회 논문집 Vol.18 No.4

In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

Load Carrying Characteristics of a Surcharge-Loaded Tiered Segmental Retaining wall

Chungsik yoo,Sun-Bin Kim,Jae-Wang Kim 한국토목섬유학회 2008 한국토목섬유학회 학술발표회 Vol.2008 No.11

The load carrying characteristics of a two-tier geosynthetic-reinforced segmental retaining wall (GR-SRW) under a surcharge load was investigated in this study. A 3D finite element analysis was conducted on a 5.6-m-high two tier segmental retaining wall subject to a surcharge load well in excess of working load aiming at investigating the load carrying capacity of the tiered GR-SRW. The results of the analysis were examined in terms of the surcharge load induced wall performance. Demonstrated in this study was that a GR-SRW in tiered configuration has an excellent load carrying capacity. showing no sign of instability up to the maximum applied surcharge pressure of 1500 kPa. Practical implications of the findings are discussed.

Effect of spatial characteristics of a weak zone on tunnel deformation behavior

Yoo, Chungsik Techno-Press 2016 Geomechanics & engineering Vol.11 No.1

This paper focuses on the deformation behavior of tunnels crossing a weak zone in conventional tunneling. A three-dimensional finite element model was adopted that allows realistic modeling of the tunnel excavation and the support installation. Using the 3D FE model, a parametric study was conducted on a number of tunneling cases with emphasis on the spatial characteristics of the weak zone such as the strike and dip angle, and on the initial stress state. The results of the analyses were thoroughly examined so that the three-dimensional tunnel displacements at the tunnel crown and the sidewalls can be related to the spatial characteristic of the weak zone as well as the initial stress state. The results indicate that the effectiveness of the absolute displacement monitoring data as early warning indicators depends strongly on the spatial characteristics of the weak zone. It is also shown that proper interpretation of the absolute monitoring data can provide not only early warning for a weak zone outside the excavation area but also information on the orientation and the extent of the weak zone. Practical implications of the findings are discussed.

Artificial Intelligence (AI)-based Deep Excavation Designed Program

Yoo, Chungsik,Aizaz, Haider Syed,Abbas, Qaisar,Yang, Jaewon Korean Geosynthetics Society 2018 한국지반신소재학회 논문집 Vol.17 No.4

This paper presents the development and implementation of an artificial intelligence (AI)-based deep excavation induced wall and ground displacements and wall support member forces prediction program (ANN-EXCAV). The program has been developed in a C# environment by using the well-known AI technique artificial neural network (ANN). Program used ANN to predict the induced displacement, groundwater drawdown and wall and support member forces parameters for deep excavation project and run the stability check by comparing predict values to the calculated allowable values. Generalised ANNs were trained to predict the said parameters through databases generated by numerical analysis for cases that represented real field conditions. A practical example to run the ANN-EXCAV is illustrated in this paper. Results indicate that the program efficiently performed the calculations with a considerable accuracy, so it can be handy and robust tool for preliminary design of wall and support members for deep excavation project.

Variation of Pull-out Resistance of Geogrid with Degree of Saturation of Soil

Chungsik Yoo,TABISH ALI 한국지반신소재학회 2020 한국지반신소재학회 논문집 Vol.19 No.1

This paper presents the results of experimental investigation on the effect of degree of saturation of soil on the pullout behavior of a geogrid. Different test variables were taken into account while performing the experiment including the soil physical conditions based on water content and external loading applied. The soil used was locally available weathered granite soil. The tests included variations in saturation of about 90%, 80%, 70% and 45% (optimum moisture content). The pullout tests were performed according to ASTM standard D 6706-01. The results indicate that increasing the degree of saturation in the soil decreases the pull-out capacity, which in turn decreases the interface friction angle and interaction coefficient. The decrease in the pullout interface coefficient was observed to be around 12.50% to 33.33% depending on the normal load and degree of saturation of the soil. The test results demonstrated the detrimental effect of increasing the degree of saturation within the reinforce soil on the pullout behavior of reinforcement, thus on the internal stability. The practical inferences of the outcomes are analyzed in detail.

깊은굴착 설계를 위한 인공신경망 개발에 관한 연구

Yoo, Chungsik,Yang, Jaewon,Abbas, Qaisar,Aizaz, Haider Syed 한국지반신소재학회 2018 한국지반신소재학회 논문집 Vol.17 No.4

This research concerns the prediction method for ground movement and wall member force due to determination structural stability check and failure check during deep excavation construction. First, research related with excavation influence parameters is conducted. Then, numerical analysis for various excavation conditions were conducted using Finite Element Method and Beam-column elasto-plasticity method. Excavation analysis database was then constructed. Using this database, development of ANN (artificial neural network) was performed for each ground movements and using structural member forces. By comparing the numerical analysis results with ANN's prediction, it is validated that development of ANN can be used efficient for prediction of ground movement and structural member forces in deep excavation site. 본 연구에서는 깊은 굴착에 따른 인접구조물의 손상 평가 및 벽체 구조물의 안정성 평가를 하기 위한 지표의 거동 및 벽체 부재력의 효율적인 예측기법에 대한 내용을 다루었다. 우선적으로 지표의 거동 및 벽체 부재력에 영향을 미치는 매개 변수에 대한 연구를 수행하였고, 이를 토대로 다양한 굴착 조건에 대해 수치해석을 실시한 결과를 통해 데이터베이스를 구축하였다. 구축된 데이터베이스를 토대로 벽체의 부재력과 지표의 거동 각각의 해석 결과에 대한 인공신경망 엔진 학습을 수행하였으며 학습된 인공신경망을 이용하여 예측된 결과와 사용된 데이터베이스의 결과를 비교하여 인공신경망 엔진이 벽체의 부재력 및 지표의 거동예측에 효율적임을 검증하였다.

도심지 지하굴착 및 터널시공 예비설계를 위한 인공신경망 개발에 관한 연구

유충식(Chungsik Yoo),양재원(Jaewon Yang) 한국지반신소재학회 2020 한국지반신소재학회 논문집 Vol.19 No.1

본 본문에서는 도심지 지하굴착 및 터널현장의 예비설계 및 지반침하를 예측이 가능한 인공신경망 개발에 대한 내용을 다루었다. 인공신경망의 개발을 위해 먼저 다양한 도심지 터널 및 지하굴착 현장 계측자료를 수집하여 데이터베이스를 구축하고 이를 인공신경망 학습에 필용한 학습데이터를 구축하는데 활용하였다. 개발된 인공신경망은 학습에 활용되지 않은 검증 데이터 세트를 및 현장계측자료를 활용하여 결정계수(R²), 평균제곱근오차(Root Mean Square Error; RMSE), 절대평균오차(Mean Absolute Error; MAE) 등 통계적 파라메타를 근거로 하여 신뢰도를 검증하였다. 개발된 인공신경망은 도심지 굴착현장의 예비 설계 및 이에 따른 주변침하를 예측하는데 효율적으로 활용될 수 있는 것으로 평가되었다. In this paper development artificial neural networks (ANN) for preliminary design and prediction of urban tunnelling and deep excavation-induced ground settlement was presented. In order to form training and validation data sets for the ANN development, field design and measured data were collected for various tunnelling and deep-excavation sites. The field data were then used as a database for the ANN training. The developed ANN was validated against a testing set and the unused field data in terms of statistical parameters such as R², RMSE, and MAE. The practical use of ANN was demonstrated by applying the developed ANN to hypothetical conditions. It was shown that the developed ANN can be effectively used as a tool for preliminary excavation design and ground settlement prediction for urban excavation problems.

준연속체 구성모델을 이용한 절리암반 터널의 거동 해석

유충식(Yoo Chungsik),김종석(Kim Jong-Suk),이호(Lee Ho) 대한토목학회 2000 대한토목학회논문집 C Vol.20 No.6

축소모형실험을 이용한 Drilling Fluid의 공벽 붕괴 방지 성능 평가

유충식(ChungSik Yoo),최정혁(JungHyuk Choi),한윤수(Yun-Soo Han) 한국지반신소재학회 2014 한국토목섬유학회 학술발표회 Vol.2014 No.11

A series of reduced model tests were performed to investigate the performance of drilling fluid with different mix designs for use in bore hole collapse prevention. The model tests were carried out considering field procedures with various drilling fluids with different mix designs. It is shown that the addition of polymer to the bentonite based drilling fluid improves the performance of the drilling fluid for preventing the borehole collapse. Practical implications of the findings from this study are discussed in great detail.