• Title/Summary/Keyword: TBM 굴진성능

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Numerical simulations on electrical resistivity survey to predict mixed ground ahead of a TBM tunnel (TBM 터널 전방 복합지반 예측을 위한 전기 비저항 탐사의 수치해석적 연구)

  • Seunghun Yang;Hangseok Choi;Kibeom Kwon;Chaemin Hwang;Minkyu Kang
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.403-421
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    • 2023
  • As the number of underground structures has increased in recent decades, it has become crucial to predict geological hazards ahead of a tunnel face during tunnel construction. Consequently, this study developed a finite element (FE) numerical model to simulate electrical resistivity surveys in tunnel boring machine (TBM) operations for predicting mixed ground conditions in front of tunnel faces. The accuracy of the developed model was verified by comparing the numerical results not only with an analytical solution but also with experimental results. Using the developed model, a series of parametric studies were carried out to estimate the effect of geological conditions and sensor geometric configurations on electrical resistivity measurements. The results of these studies showed that both the interface slope and the difference in electrical resistivity between two different ground formations affect the patterns and variations in electrical resistivity observed during TBM excavation. Furthermore, it was revealed that selecting appropriate sensor spacing and optimizing the location of the electrode array were essential for enhancing the efficiency and accuracy of predictions related to mixed ground conditions. In conclusion, the developed model can serve as a powerful and reliable tool for predicting mixed ground conditions during TBM tunneling.

Numerical Analysis on Cutting Power of Disc Cutter with Joint Distribution Patterns (절리분포 양상에 따른 디스크커터의 절삭력에 관한 수치해석적 연구)

  • Lee, Seung-Joong;Choi, Sung-O.
    • Tunnel and Underground Space
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    • v.21 no.3
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    • pp.151-163
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    • 2011
  • The LCM test is one of the most powerful and reliable methods for designing the disc cutter and for predicting the TBM (Tunnel Boring Machine) performance. It has an advantage to predict the actual load on disc cutter from the laboratory test on the real-size large rock samples, however, it also has a disadvantage to transport and/or prepare the large rock samples and to need an extra cost for experiment. Moreover it is not easy to execute the test for jointed rock mass, and sometimes the design model estimated from the test can not be applied to the real design of disc cutter. In order to break this critical point, lots of numerical studies have been performed. PFC2D can simulate crack propagation and rock fragmentation effectively, because it is useful in particle flow analysis. Consequently, in this study, the PFC2D has been adopted for numerical analysis on cutting power of disc cutter according to the different angle of joint, the different direction of joint, and the different space of joint with jointed rock mass models. From the numerical analyses, it was concluded that the bigger cutting power of disc cutter was needed for reverse cutting direction to joint rather than for forward direction, and the cutting power of disc cutter was increased with decreasing the dip angle of joint and decreasing the space of joints in reverse cutting direction. The more precise numerical model for disc cutter can be developed from comparison between the numerical results and LCM test results, and the resonable guideline is expected for prediction of TBM performance and disc cutter.

A study on the utilization of abrasive waterjet for mechanical excavation of hard rock in vertical shaft construction (고강도 암반에서 수직구 기계굴착을 위한 연마재 워터젯 활용에 관한 연구)

  • Seon-Ah Jo;Ju-Hwan Jung;Hee-Hwan Ryu;Jun-Sik Park;Tae-Min Oh
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.5
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    • pp.357-371
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    • 2023
  • In cable tunnel construction using TBM, the vertical shaft is an essential structure for entrance and exit of TBM equipment and power lines. Since a shaft penetrates the ground vertically, it often encounters rock mass. Blasting or rock splitting methods, which are mainly used to the rock excavation, cause public complaints due to the noise, vibration and road occupation. Therefore, mechanical excavation using vertical shaft excavation machine are considered as an alternative to the conventional methods. However, at the current level of technology, the vertical excavation machine has limitation in its performance when applied for high strength rock with a compressive strength of more than 120 MPa. In this study, the potential utilization of waterjet technology as an excavation assistance method was investigated to improve mechanical excavation performance in the hard rock formations. Rock cutting experiments were conducted to verify the cutting performance of the abrasive waterjet. Based on the experimental result, it was found that ensuring excavation performance with respect to changing in ground conditions can be achieved by adjusting waterjet parameters such as standoff distance, traverse speed and water pressure. In addition, based on the relationship between excavation performance, uniaxial compressive strength and RQD, it was suggested that excavation performance could be improved by artificially creating joints using the abrasive waterjet. It is expected that these research results can be utilized as fundamental data for the introduction of vertical shaft excavation machines in the future.

Development of deep learning algorithm for classification of disc cutter wear condition based on real-time measurement data (실시간 측정데이터 기반의 디스크커터 마모상태 판별 딥러닝 알고리즘 개발)

  • Ji Yun Lee;Byung Chul Yeo;Ho Young Jeong;Jung Joo Kim
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.26 no.3
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    • pp.281-301
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    • 2024
  • The power cable tunnels which are part of the underground transmission line project, are constructed using the shield TBM method. The disc cutter among the shield TBM components plays an important role in breaking rock mass. Efficient tunnel construction is possible only when appropriate replacement occurs as the wear limit is reached or damage such as uneven wear occurs. A study was conducted to determine the wear conditions of disc cutter using a deep learning algorithm based on real-time measurement data of wear and rotation speed. Based on the results of full-scaled tunnelling tests, it was confirmed that measurement data was obtained differently depending on the wear conditions of disc cutter. Using real-time measurement data, an algorithm was developed to determine disc cutter wear characteristics based on a convolutional neural network model. Distributional patterns of data can be learned through CNN filters, and the performance of the model that can classify uniform wear and uneven wear through these pattern features.