• Title/Summary/Keyword: TBM 세그먼트라이닝

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Development of optimized TBM segmental lining design system (TBM 세그먼트 라이닝 최적 설계 시스템 개발)

  • Woo, Seungjoo;Chung, Eunmok;Yoo, Chungsik
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.18 no.1
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    • pp.13-30
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    • 2016
  • This paper concerns the development of an optimized TBM segmental lining design system for a subsea tunnel. The subsea tunnel is normally laid down under the sea water and submarine ground which consists of soil or rock. The design system is the series of process which can predict segmental lining member forces by ANN (artificial neural network system), analyze suitable section for the designated ground, construction and tunnel conditions. Finally, this lining design system aims to be connected with a BIM system for designing the subsea tunnel automatically. The lining member forces are predicted based on the ANN which was calculated by a FEM (finite element analysis) and it helps designers determine its segmental lining dimension easily without any further FE calculations.

Prediction of TBM tunnel segment lining forces using ANN technique (인공신경망 기반의 TBM 터널 세그먼트 라이닝 부재력 평가)

  • Yoo, Chung-Sik;Choi, Jung-Hyuk
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.16 no.1
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    • pp.13-24
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    • 2014
  • This paper presents development of artificial neural network(ANN) based prediction method for section forces of TBM tunnel segment lining in an effort to develop an automatized design technique. A series of design cases were first developed and subsequently analyzed using the two-ring beam finite element model. The results were then used to form a database for use as training and validation data sets for ANN development. Using the database, optimized ANNs were developed that can readily be used to predict maximum sectional forces and their distributions. It is shown that the compute maximum section forces and their distributions by the developed ANNs are almost identical to the computed by the two-ring beam finite element model, implying that the developed ANNs can be used as design tools which expedite routine design calculation process. The results of this study indicate that the neural network model can be effectively used as a reliable and simple predictive tool for the prediction of segment sectional forces for design.

Influence of the joint stiffness on the segment design (이음부 강성계수가 세그먼트 설계에 미치는 영향)

  • Choi, Woo-Yong;Park, Jong-Deok;Lee, Seok-Won
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.16 no.1
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    • pp.63-74
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    • 2014
  • The lining of shield TBM tunnel is composed of segments, therefore segment joints are induced by connecting each segment. Segment joint is considered as joint stiffness in the design of TBM tunnel. Depending on the choice among the different stiffness equations, the joint stiffness values determined can be varied largely. Therefore, the influence of joint stiffness value on the design of segment lining should be verified. In this study, the joint stiffness values were determined firstly by using various equations and total change boundary was justified. Within the change boundary determined, the member forces were calculated by changing the joint stiffness through the numerical analysis and consequently the stability of segment lining was investigated by applying nominal strength. The results showed that the segment joint stiffness did not affect the design of segment lining largely.