Article
Construction & Building Technology
Ebrahim Farrokh
Summary: Optimization in TBM cutterhead design is crucial for performance enhancement. Different lace designs, such as radial and spiral configurations, are commonly used by TBM manufacturers. A new uniformly distributed lace design is introduced in this paper, which shows efficient and symmetric distribution of cutters, buckets, and manholes with low unbalanced forces and moments.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Engineering, Geological
A. Dardashti, R. Ajalloeian, J. Rostami, J. Hassanpour, A. Salimi
Summary: Accurate prediction of TBM performance is crucial in mechanized tunneling for project scheduling and cost control. Existing models often overlook the actual cutting process and fail to accurately estimate TBM performance under subcritical loading conditions. This study utilizes statistical and machine learning methods, incorporating actual machine data and geological features, to develop a new TBM performance prediction model, enhancing the reliability and accuracy of TBM penetration rate under subcritical loading conditions.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Construction & Building Technology
Xin Wang, Hehua Zhu, Mengqi Zhu, Lianyang Zhang, J. Woody Ju
Summary: A comprehensive parameter prediction framework has been proposed in this study to effectively predict critical TBM operational parameters in hard rock tunneling. The framework was validated in a water conveyance tunnel project in China, demonstrating good predictive performance. Compared to traditional methods, the introduced TBM working phase extraction method helps accurately capture data characteristics.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Construction & Building Technology
Gabriel Lehmann, Heiko Kaeling, Sebastian Hoch, Kurosch Thuro
Summary: Analysing and predicting the advance rate of a tunnel boring machine (TBM) in hard rock is important for tunnelling projects. This study focuses on small-diameter TBMs and their unique characteristics, such as insufficient geotechnical information and special machine designs. A database of 37 projects with 70 geotechnically homogeneous areas is compiled to investigate the performance of small-diameter TBMs. The analysis shows that segment lining TBMs have higher penetration rates, and new approaches for the penetration prediction of pipe jacking machines in hard rock are proposed.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Engineering, Civil
Jian-Bin Li, Zu-Yu Chen, Xu Li, Liu-Jie Jing, Yun-Pei Zhang, Hao-Han Xiao, Shuang-Jing Wang, Wen-Kun Yang, Lei-Jie Wu, Peng-Yu Li, Hai-Bo Li, Min Yao, Li-Tao Fan
Summary: This review discusses the application scenarios of machine learning-supported prediction and optimization efficiency in tunnel boring machines (TBMs). It shows that machine prediction for rock mass grades is in reasonable agreement with the ground truth. The review also highlights successful predictions of collapse sections and preliminary studies on optimal penetration rate and cost. Furthermore, it presents the achievements of the Lotus Pool Contest and discusses future prospects for intelligent TBM construction based on big data and machine learning.
Article
Construction & Building Technology
Ye Zhang, Jinqiao Chen, Shuai Han, Bin Li
Summary: Translation: This article proposes a deep learning model based on the CNN architecture, bidirectional Long Short-Term Memory module, and the attention mechanism to predict the advance rate of a tunnel boring machine (TBM). The model extracts features from monitored data using CNN, captures time-dependent indicators using Bi-LSTM, and addresses significant features with the added attention mechanism. The model performs well in predicting the advance rate and outperforms traditional machine methods.
Article
Engineering, Geological
Fan Wu, Qiuming Gong, Zhigang Li, Haifeng Qiu, Cheng Jin, Liu Huang, Lijun Yin
Summary: A cutterhead vibration monitoring system for TBM tunnelling was developed, which analyzed the vibration data and its characteristics in relation to geological conditions and operating parameters, providing important guidance and reference for TBM tunnelling.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2021)
Article
Chemistry, Multidisciplinary
Hailei Zhao, Yongwei Quan, Jianjun Zhou, Liming Wang, Zhenxing Yang
Summary: Tunnel Boring Machine (TBM), the most advanced construction equipment for rock tunnels, has been widely used in various fields. However, its poor adaptability to complex geological conditions, especially in weak and fractured strata, poses a great challenge to TBM construction. Therefore, this paper provides a reference for safe and efficient TBM excavation in weak and fractured areas through research on equipment, excavation parameter control, and construction measures, based on the background of the TBM construction of the Gaoligongshan Tunnel.
APPLIED SCIENCES-BASEL
(2023)
Article
Construction & Building Technology
Z. H. Xu, W. Y. Wang, P. Lin, L. C. Nie, J. Wu, Z. M. Li
Summary: The study focuses on the challenges of TBM jamming caused by adverse geological conditions in tunnel construction. Factors contributing to TBM jamming are analyzed, with shield TBM being the most commonly used type. The impact of fractured zones and groundwater on TBM jamming is highlighted, along with the most common hazard mode of surrounding rock collapse. Case studies on Gaoligongshan Tunnel provide practical insights for predicting and controlling TBM jamming, with proposed countermeasures at different stages of TBM tunnel construction. The study serves as a reference for understanding TBM jamming mechanisms and implementing safe excavation practices in challenging geological conditions.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Construction & Building Technology
A. Khetwal, J. Rostami, P. P. Nelson
Summary: Several models, including statistical analysis models and discrete event simulation models, have been developed to predict the utilization of Tunnel Boring Machines (TBMs). The CSM2020 model, using Arena(C) software, offers more accurate estimation of machine utilization and flexibility, while the MATLAB DES model provides better data tracking and analysis capabilities.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Construction & Building Technology
A. Flor, F. Sassi, M. La Morgia, F. Cernera, F. Amadini, A. Mei, A. Danzi
Summary: In this paper, we investigate the possibility of using machine learning models to accurately predict the Penetration Rate of a Tunnel Boring Machine (TBM) based on machine parameters. Two datasets from the Brenner Base Tunnel Project were utilized for comparison of two different Artificial Neural Network architectures. We also identified the most impactful features for penetration rate estimation and explored the potential of cross-tunnel prediction with promising results.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhun Fan, Zehao Zheng, Biao Xu, Wenji Li, Yonggang Zhang, Zhifeng Hao
Summary: This paper presents a constrained multi-objective optimization model and its solving method for the hard rock Tunnel Boring Machine (TBM). The paper introduces two push and pull search (PPS) based algorithms to solve the problem. Experimental results show that the presented method outperforms other algorithms in terms of performance.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Yadong Xue, Jiaxuan Wang, Mingliang Zhou, Jie Liu, Yongfa Guo, Jiaxu Wang
Summary: The research proposes a TBM penetration prediction model based on the optimum SE principle, establishes a dataset for optimum penetration strategies through experiments and numerical simulations, and successfully applies it to a tunnel project.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Engineering, Geological
Liangjie Gu, Xia-Ting Feng, Rui Kong, Chengxiang Yang, Qiang Han, Yuelin Xia
Summary: The excavation of deep hard rock tunnels can cause disturbances in the initial stress balance, leading to rockburst, spalling, and collapse. This study analyzes and summarizes engineering cases to divide the surrounding rock of deep tunnels into high-, medium-, and low-risk fracture zones and generalize the excavation stress paths of these zones. The study reveals that the stress difference caused by excavation stress paths determines the level of surrounding rock fracture. The research proposes a method for evaluating the influence of excavation stress paths on rock fracture anisotropy. The findings provide insights into the mechanism of excavation stress paths affecting rock burst disasters in deep hard rock tunnels and offer guidance for selecting support schemes.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Engineering, Geological
Qi Geng, Fei He, Maoxun Ma, Xiaohui Liu, Xuebin Wang, Zeyu Zhang, Min Ye
Summary: This study introduces a rarely reported full-scale experimental cutterhead system that combines in situ penetration tests and laboratory rock-breaking tests to investigate TBM penetration performance. The study provides insight into the cutting force, chipping performance, and boreability of the cutterhead system, and proposes models to predict cutter normal force and boreability index.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)