• Title/Summary/Keyword: tunnel support pressure

Search Result 104, Processing Time 0.024 seconds

Solution for surrounding rock of strain-softening considering confining pressure-dependent Young's modulus and nonlinear dilatancy

  • Liang, Peng;Gao, Yongtao;Zhou, Yu;Zhu, Chun;Sun, Yanhua
    • Geomechanics and Engineering
    • /
    • v.22 no.4
    • /
    • pp.277-290
    • /
    • 2020
  • This paper presents an elastic-plastic solution for the circular tunnel of elastic-strain softening behavior considering the pressure-dependent Young's modulus and the nonlinear dilatancy. The proposed solution is verified by the results of the field measuring and numerical simulation from a practical project, and a published closed-form analysis solution. The influence of each factor is discussed in detail, and the ability of Young's modulus and dilatancy characterizing the mechanical response of surrounding rock is investigated. It is found that, in low levels of support pressure, adopting the constant Young's modulus model will seriously misestimate the surrounding rock deformation. Using the constant dilatancy model will underestimate the surrounding rock deformation. When adopting the constant dilatancy model, as the dilation angle increases, the range of the plastic region increases, and the surrounding rock deformation weakens. When adopting the nonlinear dilatancy, the plastic region range and the surrounding rock deformation are the largest. The surrounding rock deformation using pressure-dependent Young's modulus model is between those resulted from two constant Young's modulus models. The constant α of pressuredependent Young's modulus model is the main factor affecting the tunnel displacement. The influence of α using a constant dilatancy model is much more apparent than that using a nonlinear dilatancy model.

Mechanical analysis of tunnels supported by yieldable steel ribs in rheological rocks

  • Wu, Kui;Shao, Zhushan;Qin, Su;Zhao, Nannan
    • Geomechanics and Engineering
    • /
    • v.19 no.1
    • /
    • pp.61-70
    • /
    • 2019
  • Yieldable steel ribs have been widely applied in tunnels excavated in rheological rocks. For further understanding the influence of yieldable steel ribs on supporting effect, mechanical behavior of tunnels supported by them in rheological rocks is investigated in this paper. Taking into account the deformation characteristic of yieldable steel ribs, their deformation is divided into three stages. In order to modify the stiffness of yieldable steel ribs in different deformation stages, two stiffness correction factors are introduced in the latter two stages. Viscoelastic analytical solutions for the displacement and pressure in the rock-support interface in each deformation stage are obtained. The reliability of the theoretical analysis is verified by use of numerical simulation. It could be concluded that yieldable steel ribs are able to reduce pressure acting on them without becoming damaged through accommodating the rock deformation. The influence of stiffness correction factor in yielding deformation stage on pressure and displacement could be neglected with it remaining at a low level. Furthermore, there is a linearly descending relationship of pressure with yielding displacement in linear viscoelastic rocks.

Derivations of Positive Pressure Condition for Development of Foldable Safe Pathway in Railway Tunnel Fires (철도터널화재용 접이식 대피통로 개발을 위한 양압 조건 도출)

  • Kim, JiTae;Ro, Kyoungchul
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.20 no.1
    • /
    • pp.284-289
    • /
    • 2019
  • The Korea Foldable safe pathway system is an evacuation support system to get temporary evacuation route in railway tunnel and large space fires. A prevention smoke screen is unfolded in fires and it is needed to prevent heat and smoke from fire source. Therefore, ventilation system for positive pressure condition is equipped with foldable safe pathway system. Numerical analyses of temperature and pressure distribution with distance from fire source were performed considering fire scenario of new train vehicle. The smoke temperatures did not exceed $200^{\circ}C$ that distance from the fire source was more than 20 m and smoke pressure was reduced with distance from fire source. Maximum smoke pressure was 14 Pa and average pressure was 6 Pa in position of prevention smoke screen. As results, to install foldable safe pathway system, ventilation system is need to maintain 6 Pa positive pressure condition.

Estimation of wind pressure coefficients on multi-building configurations using data-driven approach

  • Konka, Shruti;Govindray, Shanbhag Rahul;Rajasekharan, Sabareesh Geetha;Rao, Paturu Neelakanteswara
    • Wind and Structures
    • /
    • v.32 no.2
    • /
    • pp.127-142
    • /
    • 2021
  • Wind load acting on a standalone structure is different from that acting on a similar structure which is surrounded by other structures in close proximity. The presence of other structures in the surrounding can change the wind flow regime around the principal structure and thus causing variation in wind loads compared to a standalone case. This variation on wind loads termed as interference effect depends on several factors like terrain category, geometry of the structure, orientation, wind incident angle, interfering distances etc., In the present study, a three building configuration is considered and the mean pressure coefficients on each face of principle building are determined in presence of two interfering buildings. Generally, wind loads on interfering buildings are determined from wind tunnel experiments. Computational fluid dynamic studies are being increasingly used to determine the wind loads recently. Whereas, wind tunnel tests are very expensive, the CFD simulation requires high computational cost and time. In this scenario, Artificial Neural Network (ANN) technique and Support Vector Regression (SVR) can be explored as alternative tools to study wind loads on structures. The present study uses these data-driven approaches to predict mean pressure coefficients on each face of principle building. Three typical arrangements of three building configuration viz. L shape, V shape and mirror of L shape arrangement are considered with varying interfering distances and wind incidence angles. Mean pressure coefficients (Cp mean) are predicted for 45 degrees wind incidence angle through ANN and SVR. Further, the critical faces of principal building, critical interfering distances and building arrangement which are more prone to wind loads are identified through this study. Among three types of building arrangements considered, a maximum of 3.9 times reduction in Cp mean values are noticed under Case B (V shape) building arrangement with 2.5B interfering distance. Effect of interfering distance and building arrangement on suction pressure on building faces has also been studied. Accordingly, Case C (mirror of L shape) building arrangement at a wind angle of 45º shows less suction pressure. Through this study, it was also observed that the increase of interfering distance may increase the suction pressure for all the cases of building configurations considered.

A study on EPB shield TBM face pressure prediction using machine learning algorithms (머신러닝 기법을 활용한 토압식 쉴드TBM 막장압 예측에 관한 연구)

  • Kwon, Kibeom;Choi, Hangseok;Oh, Ju-Young;Kim, Dongku
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.24 no.2
    • /
    • pp.217-230
    • /
    • 2022
  • The adequate control of TBM face pressure is of vital importance to maintain face stability by preventing face collapse and surface settlement. An EPB shield TBM excavates the ground by applying face pressure with the excavated soil in the pressure chamber. One of the challenges during the EPB shield TBM operation is the control of face pressure due to difficulty in managing the excavated soil. In this study, the face pressure of an EPB shield TBM was predicted using the geological and operational data acquired from a domestic TBM tunnel site. Four machine learning algorithms: KNN (K-Nearest Neighbors), SVM (Support Vector Machine), RF (Random Forest), and XGB (eXtreme Gradient Boosting) were applied to predict the face pressure. The model comparison results showed that the RF model yielded the lowest RMSE (Root Mean Square Error) value of 7.35 kPa. Therefore, the RF model was selected as the optimal machine learning algorithm. In addition, the feature importance of the RF model was analyzed to evaluate appropriately the influence of each feature on the face pressure. The water pressure indicated the highest influence, and the importance of the geological conditions was higher in general than that of the operation features in the considered site.

Numerical evaluation of surface settlement induced by ground loss from the face and annular gap of EPB shield tunneling

  • An, Jun-Beom;Kang, Seok-Jun;Kim, Jin;Cho, Gye-Chun
    • Geomechanics and Engineering
    • /
    • v.29 no.3
    • /
    • pp.291-300
    • /
    • 2022
  • Tunnel boring machines combined with the earth pressure balanced shield method (EPB shield TBMs) have been adopted in urban areas as they allow excavation of tunnels with limited ground deformation through continuous and repetitive excavation and support. Nevertheless, the expansion of TBM construction requires much more minor and exquisitely controlled surface settlement to prevent economic loss. Several parametric studies controlling the tunnel's geometry, ground properties, and TBM operational factors assuming ordinary conditions for EPB shield TBM excavation have been conducted, but the impact of excessive excavation on the induced settlement has not been adequately studied. This study conducted a numerical evaluation of surface settlement induced by the ground loss from face imbalance, excessive excavation, and tail void grouting. The numerical model was constructed using FLAC3D and validated by comparing its result with the field data from literature. Then, parametric studies were conducted by controlling the ground stiffness, face pressure, tail void grouting pressure, and additional volume of muck discharge. As a result, the contribution of these operational factors to the surface settlement appeared differently depending on the ground stiffness. Except for the ground stiffness as the dominant factor, the order of variation of surface settlement was investigated, and the volume of additional muck discharge was found to be the largest, followed by the face pressure and tail void grouting pressure. The results from this study are expected to contribute to the development of settlement prediction models and understanding the surface settlement behavior induced by TBM excavation.

Scale Model Studies for Stability Estimation of Twin Tunnels with Small Clearance (근접병설터널의 안정성 평가를 위한 모형실험 연구)

  • Kim, Pyoung Gi;Kim, Jong Woo
    • Tunnel and Underground Space
    • /
    • v.23 no.2
    • /
    • pp.130-140
    • /
    • 2013
  • In this study, scaled model tests were performed to investigate the stability of twin tunnels with small clearance, where the pillar widths were 0.5D and 0.25D, respectively. The tunnels were supposed to be constructed in anisotropic weathered rocks with $30^{\circ}$ inclined bedding planes, and the model tests were conducted under the condition of lateral pressure ratio, 1. Six types of test models which had respectively different pillar widths and support conditions were experimented, where crack initiating pressures, maximum pressures, failure modes of pillar and deformation behaviors around tunnels were investigated. The models with wider pillar were cracked under higher pressure than the models with shallower pillar. The models with lining support were cracked under higher pressure and showed less tunnel convergence than the unsupported models. The models with both lining and pillar reinforcement were proved to be most stable among the tested models. In particular, as the model of 0.25D pillar width with only lining support showed shear failure of pillar according to the existing bedding planes, so both lining and pillar reinforcement were thought to be indispensable in that case of tunnel.

A Study for the Stability Investigation of Three Parallel Tunnels Using Scaled Model Tests (삼병렬 터널의 안정성 검토를 위한 모형실험 연구)

  • Kim, Jong-Woo;Bae, Woo-Seok
    • Tunnel and Underground Space
    • /
    • v.18 no.4
    • /
    • pp.300-311
    • /
    • 2008
  • In this study, scaled model tests were performed to investigate the stability of three parallel tunnels. Seven types of test models which had respectively different pillar widths, tunnel sectional shapes, support conditions and ground conditions were experimented, where crack initiating pressures and deformation behaviors around tunnels were investigated. In order to evaluate the effect of pillar widths on stability, various models were experimented. As results, the models with shallower pillar widths proved to be unstable because of lower crack initiating pressures and more tunnel convergences than the models with thicker pillar widths. In order to find the effect of tunnel sectional shape on stability, the models with arched, semi-arched and rectangular tunnels were experimented. Among them rectangular tunnel model was the most unstable, where the arched tunnel model with small radius of roof curvature was more stable than semi-arched one. The model with rockbolt showed higher crack initiating pressure and less roof lowering than the unsupported model. The deformation behaviors of tunnels in the anisotropic ground model were quite different from those in the isotropic ground model. Futhermore, the results of FLAC analysis were qualitatively coincident with the experimental results.

Prediction of Rock Mass Strength Ahead of Tunnel Face Using Hydraulic Drilling Data (천공데이터를 이용한 터널 굴진면 전방 암반강도 예측)

  • Kim, Kwang-Yeom;Kim, Sung-Kwon;Kim, Chang-Yong;Kim, Kwang-Sik
    • Tunnel and Underground Space
    • /
    • v.19 no.6
    • /
    • pp.479-489
    • /
    • 2009
  • Appropriate investigation of ground condition near excavation face in tunnelling is an inevitable process for safe and economical construction. In this study mechanical parameters from drilling process for blasting were investigated for the purpose of predicting the ground condition, especially rock mass strength, ahead of tunnel face. Rock mass strength is one of the most important factors for classification of rock mass and making a decision of support type in underground construction. Several rock specimens which are considered homogeneous and having different strength values respectively were tested by hydraulic drill machines generally used. As a result, penetration rate is fairly related with rock mass strength among drilling parameters. It is also found that penetration rate increases along with the higher impact pressure even under same rock strength condition. It is finally suggested that new prediction method for rock mass strength using percussive pressure and penetration rate during drilling work can be utilized well in construction site.

A study on the development of tunnel soundness evaluation system using artificial neural network (인공신경망을 이용한 터널 건전도 평가시스템 개발)

  • 김현우;김영근;이희근
    • Tunnel and Underground Space
    • /
    • v.9 no.1
    • /
    • pp.48-55
    • /
    • 1999
  • One of the major roles of concrete lining is the supplementary support of ground load. Therefore, if there are cracks or deformation found in the lining, the causes should be carefully examined. Tunnel Soundness Evaluation System (DW-TSES) was developed to meet such requirements. Main facility of the system was intended to find the probable causes on the basis of the apparent changes in lining and the environmental conditions. It also includes facilities for evaluating the soundness of a tunnel and indicating the method for repair or reinforcement. The characteristic feature of damages is used for reasoning in case of deterioration and leakage, and artificial neural network is used in external pressure. This process depends on the results of the case analyses and FDM, which have a collection of the typical features of different types of damages as well as the unusual changes caused by the external pressure. The comparison of the outputs of this system with those of expert's diagnoses draws the following conclusions. 1) Artificial neural network was a suitable tool to find to causes of damages by external pressure. 2) The environmental conditions improved the accuracy in reasoning. 3) The result of finding causes and evaluating soundness was helpful to suggest effective methods concerning tunnel maintenance.

  • PDF