Introduction: Estimating groundwater inflow into a tunnel before and during the excavation process is an important task to ensure the safety and schedule during the underground construction process.
Case Description: Here we report a case of the forecasting and prevention of water inrush at the Jinping II Hydropower Station diversion tunnel groups during the excavation process. The diversion tunnel groups are located in mountains and valleys, and with high water pressure head. Three forecasting methods are used to predict the total water inflow of the #2 diversion tunnel. Furthermore, based on the accurate estimation of the water inrush around the tunnel working area, a theoretical method is presented to forecast the water inflow at the working area during the excavation process.
Discussion And Evaluation: The simulated results show that the total water flow is 1586.9, 1309.4 and 2070.2 m(3)/h using the Qshima method, Kostyakov method and Ochiai method, respectively. The Qshima method is the best one because it most closely matches the monitoring result. According to the huge water inflow into the #2 diversion tunnel, reasonable drainage measures are arranged to prevent the potential disaster of water inrush. The groundwater pressure head can be determined using the water flow velocity from the advancing holes; then, the groundwater pressure head can be used to predict the possible water inflow. The simulated results show that the groundwater pressure head and water inflow re stable and relatively small around the region of the intact rock mass, but there is a sudden change around the fault region with a large water inflow and groundwater pressure head. Different countermeasures are adopted to prevent water inrush disasters during the tunnel excavation process.
Conclusion: Reasonable forecasting the characteristic parameters of water inrush is very useful for the formation of prevention and mitigation schemes during the tunnel excavation process.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4899345 | PMC |
http://dx.doi.org/10.1186/s40064-016-2336-9 | DOI Listing |
Sci Rep
January 2025
Ordos Institute of Liaoning Technical University, Liaoning Technical University, Ordos, 017000, China.
This study focuses on the construction and interpretation of a mine water inrush source identification model to enhance the precision and credibility of the model. For water inrush source identification and feature analysis, a novel method combining XGBoost and SHAP is suggested. The model uses Ca, Mg, K + Na, HCO, Cl, SO, Hardness, and pH as discriminators, and the key parameters in the XGBoost model are optimized by introducing the improved sparrow search algorithm.
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January 2025
Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran.
Mechanized tunneling in harsh environments faces many hazards, which can stop tunneling operations for a long time. Due to the high investment volume in tunneling projects, it is imperative to predict and assess the geotechnical hazards. This research has tried to evaluate and introduce the most dangerous section of the Kerman water conveyance tunnel (KWCT) using multi-index decision-making techniques including PROMETHEE II, WASPAS, and CoCoSo models.
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December 2024
School of Resources & Safety Engineering, Central South University, Changsha, 410083, Hunan, China.
To explore the mechanism of water inrush from the mine roof strata, a series of seepage-acoustic emission (SAE) experiments on red sandstone disc samples were carried out. The effects of the height to diameter ratio (H/D) and pore pressure on the mechanical, hydraulic and crack propagation properties of red sandstones were investigated. Test results show that, the peak load of rock samples declines with the decreasing H/D and increasing pore pressure.
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November 2024
Polish Geological Institute-National Research Institute, Lower Silesian Branch, 53-122 Wrocław, Poland.
Geothermal energy is a crucial component contributing to the development of local thermal energy systems as a carbon-neutral and reliable energy source. Insights into its availability derive from knowledge of geology, hydrogeology and the thermal regime of the subsurface. This expertise helps to locate and monitor geothermal installations as well as observe diverse aspects of natural and man-made thermal effects.
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November 2024
Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, T6G 2W2, Canada.
Ultrasonic detection has emerged as a rapid method for acquiring rock mass sound velocity and converting it into an elastic modulus parameter, a pivotal technique for investigating the in-situ mechanical properties of rock masses. Despite its significance, accurately deducing rock mass strength from elastic modulus remains a formidable challenge and a pressing issue in the realm of protorock parameter research. This study introduces an innovative artificial intelligence-driven methodology for transforming elastic modulus and strength parameters specific to coal measures through rigorous data analysis and experimental validation.
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