Geotechnical Structure Analysis and Risk Assessment in Tunnel Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 2238

Special Issue Editor


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Guest Editor
College of Civil Engineering, Tongji University, Shanghai 200092, China
Interests: groundwater engineering; engineering groundwater; rock dynamic; rock engineering
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Dear Colleagues,

No structures above ground can be compared with tunnel engineering surrounded by rock and soil. The main load on the geotechnical structures and construction risk are all based on the interaction between the surrounding rock mass and underground structures. The complex geological materials, geological structures, complex excavation steps and thermal–hydraulic–mechanical–chemical (THMC) coupling environment make the tunneling even more challenging.

Under challenging conditions, numerous complex new tunnel construction methods produce new problems. Recent advances in deep, large-span, bifurcated, multi-arch tunnels under extremely unfavorable conditions in the rock mass, together with the shield tunnel, immersed tunnel and suspension tunnel in soil, produce lots of history knowledge and experiences. Meanwhile, the progress in numerical and physical analysis and emerging technology represented by artificial intelligence (AI) present us strong theoretical tools to solve the challenges.

All of the above new knowledge is encouraged to be shared and published in our Special Issue in the overlapping fields of: 

  • Tunneling case history analysis (long, deep, large-span, bifurcated, multi-arch tunnels under extremely unfavorable conditions).
  • Multi-scale tunnel geological structure analysis (investigation, surrounding rock classification, advance geological prediction, monitoring, laboratory experiment and on-site experiment).
  • Tunnel environment analysis (THMC and coupling effect).
  • Tunnel structure-surrounding rock interaction (load mode, excavation optimization, environment protection, risk motivation, new numerical simulation model and method).
  • Tunnel geotechnical risk mitigation (groundwater, karst, collapse, large deformation, gas and groundwater resource depletion risk analysis and mitigation).
  • New emerging technology applications (AI, machine learning, deep learning, big data, virtual reality (VR), internet of things (IoT), photogrammetry, BIM and robot).

Prof. Dr. Jianxiu Wang
Guest Editor

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Keywords

  • case history analysis
  • multi-scale geotechnical structure analysis
  • risk assessment of tunneling
  • geotechnical risk mitigation
  • new emerging technology

Published Papers (2 papers)

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Research

16 pages, 4969 KiB  
Article
Field Experiments on 3D Groundwater Flow Patterns in the Deep Excavation of Gravel-Confined Aquifers in Ancient Riverbed Areas
by Na Xu, Yujin Shi, Jianxiu Wang, Yuanbin Wu, Jianshen Lu, Ruijun Zhou, Xinlei Huang and Zhenhua Ye
Appl. Sci. 2023, 13(18), 10438; https://doi.org/10.3390/app131810438 - 18 Sep 2023
Viewed by 682
Abstract
In ancient riverbed areas, the hydro-geological conditions are extremely complex because of the cutting of ancient river channels during the sedimentary process. How to lower groundwater level in water-riched gravel-confined aquifer during deep excavation is vital for underground engineering. Groundwater flow patterns had [...] Read more.
In ancient riverbed areas, the hydro-geological conditions are extremely complex because of the cutting of ancient river channels during the sedimentary process. How to lower groundwater level in water-riched gravel-confined aquifer during deep excavation is vital for underground engineering. Groundwater flow patterns had to be understood during foundation pit dewatering. This paper presents a field case study conducted at the deep foundation pit of the Qianjiang Century City station on Hangzhou Metro Line 6, which is notable for its 52 m deep unclosed waterproof curtain. A total of 34 pumping wells were installed within the pit. During the tests, one well was subjected to a pumping well, while the others served as observation wells. The research included two sets of multi-depth pumping tests, which differed in terms of their filter lengths, aimed at investigating the flow pattern around pump wells and the roots of diaphragm walls. The study found that the use of longer filters, higher pump rates, and filters placed nearer to aquifer roofs enhances dewatering efficiency and minimizes impact on the surrounding geological environment. This paper introduces a novel concept known as the diaphragm wall–pumping well effect, which regulates the water head outside the pit and the subsidence, thereby optimizing the drawdown of the deep foundation pit with an unclosed waterproof curtain. The findings were applied in the foundation pit dewatering of Qianjiang Century City station, and the drawdown in and outside the pit was effectively controlled. Full article
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21 pages, 5950 KiB  
Article
Evaluation of Water Inrush Hazard in Karst Tunnel Based on Improved Non-Linear Attribute Variable Weight Recognition Model
by Xianhui Mao, Ankui Hu, Mengkun Wu, Shuai Zhou, Xinglin Chen and Yajing Li
Appl. Sci. 2023, 13(8), 5026; https://doi.org/10.3390/app13085026 - 17 Apr 2023
Cited by 1 | Viewed by 1086
Abstract
Water inrush in karst tunnels will cause casualties and economic losses. Thus, it is significant to objectively assess the water inrush risk level and adopt valid preventive measures to reduce losses from this disaster. The relationship between the factors affecting water inrush in [...] Read more.
Water inrush in karst tunnels will cause casualties and economic losses. Thus, it is significant to objectively assess the water inrush risk level and adopt valid preventive measures to reduce losses from this disaster. The relationship between the factors affecting water inrush in the dynamic coupling system is strong nonlinear, so the attribute recognition model, which lessens the mutation points and error and causes the evaluation results to be more reasonable and accurate, is improved nonlinearly in this paper. Firstly, the assessment system was established by selecting seven factors: formation lithology, unfavorable geological conditions, attitude of rock formation, landform and physiognomy, contact zones of dissolvable and insoluble rock, layer and interlayer fissures, and groundwater level. Secondly, the multi-factor interaction matrix, C-OWA operator, and variable weight theory are used to calculate the constant weight and variable weight of each evaluation index. In addition, the linear attribute measurement function of the attribute identification model is optimized by using the non-linear trigonometric function to distinguish the risk level of the water inrush. Finally, the proposed model was successfully used in Qiyueshan Tunnel. The evaluation results of the risk level are more accurate than other methods, and they are in agreement with the excavation results. The proposed model provides a valuable reference for the risk assessment and project management of tunnel construction. Full article
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