Article
Construction & Building Technology
Hongyi Xu, Qiuming Gong, Jianwei Lu, Lijun Yin, Fengwei Yang
Summary: Establishing a suitable TBM performance prediction model based on rock mass classification parameters is essential for machine type selection, project scheduling, and budgeting. Regression equations using field penetration index or cutter force have been developed, but determining cutter load remains a challenge. The thrust force of the cutter is influenced by various factors, particularly ground conditions, and can be estimated using simple regression equations during the planning phase of a TBM tunneling project.
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
Computer Science, Artificial Intelligence
Zimu Li, Behnam Yazdani Bejarbaneh, Panagiotis G. Asteris, Mohammadreza Koopialipoor, Danial Jahed Armaghani, M. M. Tahir
Summary: This research aimed to propose an optimal predictor model of TBM performance using data-mining techniques such as neural networks, gene expression programming, and multivariate adaptive regression splines, along with field assessment and laboratory testing. The developed GEP and NN models provided more accurate predictive results compared to the MARS model, with an increase of 7.25% in PR value achieved through the optimized GEP equation.
Article
Engineering, Geological
Alireza Salimi, Jamal Rostami, Christian Moormann, Jafar Hassanpour
Summary: The study develops models for predicting TBM penetration rate by incorporating the effects of rock type, using field penetration index and machine learning algorithm. The models provide estimated FPIs based on different rock types, rock strength, and rock mass properties, presented in the form of graphs.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)
Article
Engineering, Environmental
Sarah Sissins, Chrysothemis Paraskevopoulou
Summary: The challenge of tunnelling through lithologically and geomechanically heterogeneous rock masses requires new approaches for assessing rock mass behavior and machine performance. Existing models lack parameter selection for heterogeneous rock masses, necessitating the development of new methods to determine TBM performance in such environments.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Engineering, Geological
Qiuming Gong, Hongyi Xu, Jianwei Lu, Fan Wu, Xiaoxiong Zhou, Lijun Yin
Summary: The Rock Mass Characteristics (RMC) model is a prediction model for TBM penetration rate that considers the interaction between the rock mass and cutters. The updated model incorporates comprehensive data from both laboratory tests and in site penetration tests to improve accuracy and optimization for TBM operation parameters. It accounts for factors such as cutter spacing, cutter shape, specific rock mass boreability index, and the exponent c to reflect different TBM cutting modes.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2022)
Article
Construction & Building Technology
Danial Jahed Armaghani, Saffet Yagiz, Edy Tonnizam Mohamad, Jian Zhou
Summary: This study successfully predicted the penetration rate and advance rate of tunnel boring machines in different weathering zones through the development of new equations, demonstrating the accuracy of these new models.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Engineering, Environmental
Jafar Hassanpour, Yavar Firouzei, Golnaz Hajipour
Summary: This paper analyzes the performance of a machine in excavating tunnels through sedimentary and low to medium grade metamorphic rocks in the Ghomrood water conveyance tunnel project. It proposes a prediction model based on the relationships between rock mass properties and machine performance parameters for future projects with similar geological conditions. Results show strong correlations between TBM performance and engineering geological conditions.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Construction & Building Technology
Liu-jie Jing, Jian-bin Li, Na Zhang, Shuai Chen, Chen Yang, Hong-bo Cao
Summary: This report proposes a new TBM advance rate prediction method, establishing models based on surrounding rock conditions and operator control factors, and validates the accuracy and feasibility of the method through actual engineering practice.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Geosciences, Multidisciplinary
Jian Zhou, Yingui Qiu, Danial Jahed Armaghani, Wengang Zhang, Chuanqi Li, Shuangli Zhu, Reza Tarinejad
Summary: This study aimed to develop hybrid models to predict TBM performance, with PSO-XGB technique identified as the best predictive model. Sensitivity analysis revealed that UCS, BTS, and TFC have the greatest impact on TBM performance.
GEOSCIENCE FRONTIERS
(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
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
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
Engineering, Environmental
Anshul Sindhwani, V. M. S. R. Murthy, Md. Raphique, A. K. Raina
Summary: This paper presents a systematic analysis of TBM performance based on the data collected from the MetroLine-3 UGC-01 project in Mumbai, India, and proposes performance prediction models for the Deccan Traps. The models indicate that UCS, RQD x Js, and thrust variables have significant influence on TBM ROP.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2023)
Article
Engineering, Civil
Gi-Jun Lee, Hee-Hwan Ryu, Gye-Chun Cho, Tae-Hyuk Kwon
Summary: This study investigates the impact of rock strength on the penetration rate and penetration depth in tunnel construction. The results show that thrust, cutterhead speed, and rock strength are important factors in determining the penetration depth. A predictive model for estimating the penetration depth is proposed.
GEOMECHANICS AND ENGINEERING
(2023)
Article
Construction & Building Technology
Zhi Ding, Xiao Zhang, Shao-Heng He, Yong-Jie Qi, Cun-Gang Lin
Summary: This study investigates the longitudinal behavior of a shield tunnel by designing and constructing a reduced-size indoor model. The results show that the longitudinal settlement of the tunnel follows a normal distribution, with the maximum settlement occurring at the central ring and increasing linearly with the applied load. Stress concentration typically occurs on the side of the tunnel waist under surcharge, resulting in transverse elliptical deformation of the entire structure.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Lucia Lopez-de-Abajo, Marcos G. Alberti, Jaime C. Galvez
Summary: Assessing and predicting concrete damage is crucial for infrastructure management. This study quantifies gas concentrations in urban tunnels to achieve this goal.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Chao He, Yinghao Cai, Chenqiang Pu, Shunhua Zhou, Honggui Di, Xiaohui Zhang
Summary: This paper investigates the impact of river channel excavation on adjacent metro tunnels and proposes protective measures based on an engineering project in Fuzhou, China. A three-dimensional finite element model is developed to calculate the displacements and distortion of tunnels under different excavation sequences and soil reinforcement measures. Real-time monitoring confirms that the vertical displacements and diametrical distortion of tunnels are primarily caused by the excavation of the river above the tunnels, while horizontal displacements are induced by the excavation next to the tunnels. The study recommends a combination of cement slurry with a portal form and concrete with a plate form for soil reinforcement and tunnel protection.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Yaosheng Liu, Ang Li, Feng Dai, Ruochen Jiang, Yi Liu, Rui Chen
Summary: In this study, a hybrid model based on a multilayer perceptron (MLP) and meta-heuristic algorithms was developed to improve blast performance during tunnel excavation. Precise prediction of post-blasting indicators was important for optimization, and a comparison of meta-heuristic algorithms was conducted to find the most suitable model. The results showed that the developed model effectively reduces overbreak areas and quantitatively analyzes the influence of geological conditions.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Xiang Shen, Yifan Chen, Liqiang Cao, Xiangsheng Chen, Yanbin Fu, Chengyu Hong
Summary: In this paper, a machine learning-based method for predicting the slurry pressure in shield tunnel construction is proposed. By considering the influence of fault fracture zones and setting the formation influence coefficient, the accuracy of the prediction is significantly improved.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Shuying Wang, Zihao Zhou, Xiangcou Zheng, Jiazheng Zhong, Tengyue Zheng, Changhao Qi
Summary: A real-time assessment and monitoring approach based on laser scanning technology and point cloud data analysis was proposed to address the hysteresis in assessing the workability of conditioned soils and the inefficiency in estimating the soil volume flow rate in tunnelling practice. The approach was successfully applied in identifying the workability of conditioned soil and its discharge rate in the EPB shield tunnelling project.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Peng Jiang, Benchao Liu, Yuting Tang, Zhengyu Liu, Yonghao Pang
Summary: This study introduces a novel deep learning-based electrical method that jointly inverses resistivity and chargeability to estimate water-bearing structures and water volume. Compared with traditional linear inversion methods, the proposed method demonstrates superiority in locating and delineating anomalous bodies, reducing solution multiplicity.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Haoyu Mao, Nuwen Xu, Zhong Zhou, Chun Sha, Peiwei Xiao, Biao Li
Summary: The study focuses on the delineation of rock mass damage zones and stability analysis of underground powerhouse in Lianghekou hydropower station. ESG monitoring system is used to monitor the inner micro-fracture activity of surrounding rock mass in real-time. Engineering analogy method is adopted to forecast the deformation period of surrounding rock mass and analyze the variation characteristics of seismic source parameters. The research results provide references for similar deep underground excavation engineering in terms of design and construction.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Junling Qiu, Dedi Liu, Kai Zhao, Jinxing Lai, Xiuling Wang, Zhichao Wang, Tong Liu
Summary: This study focuses on the construction surface cracks of large cross-section tunnels in loess strata of China. The mechanism of surface crack formation is analyzed, and factors such as settlement deformation, construction scheme, and surrounding soil environment are identified as the main contributors. Numerical simulations were conducted to gain a deeper understanding of the influence of factors on surface cracks in loess tunnel construction. Specific measures for prevention and treatment of construction surface cracks are proposed to provide new ideas for surface crack control in loess tunnels.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Ting Shang, Jiaxin Lu, Ying Luo, Song Wang, Zhengyu He, Aobo Wang
Summary: The study reveals significant variations in car-following behavior across different types of tunnels and consecutive sections of the same tunnel. As tunnel length increases, the driving stability of following vehicles decreases, but the level of driving safety risk is not positively correlated with tunnel length. Significant vehicle trajectory oscillation is observed within the inner sections of long and extra-long tunnels, and a significant relationship between the acceleration of following vehicles and the location within the tunnel section is found.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Rusi Zeng, Zhongwei Shen, Jun Luo
Summary: The urban underground complexes (UUCs) in China have been effective in solving urban problems, but users have expressed dissatisfaction with the internal physical environment. Personal characteristics and environmental factors play significant roles in determining users' satisfaction.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
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
Construction & Building Technology
Ting Ren, Ming Qiao, Jon Roberts, Jennifer Hines, Yang-Wai Chow, Wei Zong, Adrian Sugden, Mark Shepherd, Matthew Farrelly, Gareth Kennedy, Faisal Hai, Willy Susilo
Summary: Long-term exposure to coal and silica dust during underground tunnelling operations is a growing concern. To bridge the gap between knowledge in dust exposure monitoring and frontline workers, a virtual reality educational tool was developed to visualize ventilation and dust flow characteristics. This tool allows workers to better understand decision-making and best practices for dust controls.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Dong Lin, Zhipeng Zhou, Miaocheng Weng, Wout Broere, Jianqiang Cui
Summary: Metro systems play a vital role in the transportation, economic, environmental and social aspects of cities. The uncertainties in construction, passenger comfort and safety, as well as efficiency and reliability of the metro system, have been widely studied. Metro systems influence urban development and have a positive impact on housing prices, public health, and environmental quality. Further research is needed to fill the research gaps and make recommendations for future studies.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Construction & Building Technology
Wei Yu, Bo Wang, Xin Zi, Jie Dong
Summary: In this study, a whole-process analytical theory for the coupled deformation of deep circular tunnel surrounding rock and prestressed yielding anchor bolt (cable) system is derived and validated through numerical simulations. The results show that anchor bolts (cables) can significantly reduce the convergence of surrounding rock, and factors such as support timing and anchor cable length have important effects on the support effectiveness.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)