This book highlights the latest technologies and applications of intelligent construction in the domain of tunneling works. Rapid urbanization has surged the rapid development of underground infrastructures in major metropolitans around the world over the past decades. The development of urban tunnel systems is a challenging task with high complexity in terms of design, construction, and maintenance. Recent advancements in information and communication technologies (ICTs) have driven vast transformations around the world with successful implementations in many domains of science. Under the concept of industry 4.0, there are many attempts at intelligent construction using the latest ICTs, where the major applications in urban system development mainly focus on building information modelling (BIM), Internet of Things (IoT), deep learning, and computer vision. A tremendous transformation has taken place in the past years with the emerging intelligent construction applications in urban tunnel development. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in tunnel development but also enhancing construction competitiveness globally.

Autorentext

Dr. Zhang is currently a Professor at the School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology (HUST), China. Prior to his appointment at HUST in Dec. 2021, he served as an Assistant Professor at the School of Civil and Environmental Engineering, Nanyang Technological University (NTU), Singapore. He obtained his Bachelor, Master, and Doctor degrees from HUST in 2009, 2012, and 2014, respectively. His research interest involves Construction Informatics, Risk Analysis, and Urban Resilience. Dr. Zhang has published over 250 peer-reviewed SCI-indexed papers. He has been listed in Stanford University's Top 2% of Global Scientists. (E-mail: zlm@hust.edu.cn)

Dr. Pan is currently an Associate Professor at the School of Ocean and Civil Engineering, Shanghai Jiao Tong University, China. She earned her Bachelor's, Master's, and Doctoral degrees from Tongji University (China), Carnegie Mellon University (USA), and Nanyang Technological University (Singapore) in 2016, 2017, and 2021, respectively. Dr. Pan's research focuses on engineering informatization, data mining, and AI implementation particularly in underground engineering. (E-mail: panyue001@sjtu.edu.cn)

Mr. Lin is currently a Ph.D. candidate at the School of Civil and Environmental Engineering, Nanyang Technological University (NTU), Singapore. He obtained his Bachelor's degree from City University of Hong Kong, in 2018 and his Master's degree from National University of Singapore in 2019. His research interest involves Tunnel Construction and Safety Risk Analysis. (E-mail: penghui003@e.ntu.edu.sg)

Dr. Skibniewski is a Professor of Construction Engineering and Project Management in the Department of Civil and Environmental Engineering at the University of Maryland in College Park. Prior to his current appointment, he served as a Professor and Associate Provost at Purdue University in West Lafayette, Indiana. He received a M.Eng. degree from Warsaw University of Technology, and M.S. and Ph.D. degrees from Carnegie Mellon University, all in Civil Engineering. He specializes in advanced IT solutions for construction project management and in construction automation. He is the Honorary Editor-in-Chief of Automation in Construction and Co-Editor-in-Chief of Frontiers of Engineering Management. (E-mail: mirek@umd.edu

Inhalt

Introduction to intelligent construction.- Intelligent Geological Environment Perceptions.- Advance geological forecast.- Geological feature characterization.- Geological condition detection.- Tunnel face reliability modeling.- Intelligent TBM Operations.- Construction equipment selection.- TBM performance prediction.- Advanced TBM attitude control.- Synchronous excavation and segment assembly.- TBM fault detection.- Intelligent Proactive Decisions.- Tunnel line alignment.- Safety risk assessment.-Risk mitigation planning.- Digital twin platform development.- Conclusions and future directions.