Prediction of water inflow to mechanized tunnels during tunnel-boring-machine advance using numerical simulation

Golian, Mohsen; Teshnizi, Ebrahim Sharifi; Nakhaei, Mohammad

Prediction of water inflow to mechanized tunnels during tunnel-boring-machine advance using numerical simulation | Prévision des débits de venues d’eau dans les tunnels mécanisés, au cours du creusement au tunnelier, à l’aide de simulations numériques Predicción mediante simulación numérica del flujo de agua a túneles mecanizados durante el avance de la máquina perforadora de túneles 利用数值模拟预测隧道掘进机开挖期间隧道的涌水 پیش‌بینی آب ورودی به تونل‌های مکانیزه به ازای پیشروی حفاری دستگاه TBM به روش شبیه‌سازی عددی

2018

Golian, Mohsen | Teshnizi, Ebrahim Sharifi | Nakhaei, Mohammad

An accurate estimate of the groundwater inflow to a tunnel is one of the most challenging but essential tasks in tunnel design and construction. Most of the numerical or analytical solutions that have been developed ignore tunnel seepage conditions, material properties and hydraulic-head changes along the tunnel route during the excavation process, leading to inaccurate prediction of inflow rates. A method is introduced that uses MODFLOW code of GMS software to predict inflow rate as the tunnel boring machine (TBM) gradually advances. In this method, the tunnel boundary condition is conceptualized and defined using Drain package, which is simulated by dividing the drilling process into a series of successive intervals based on the tunnel excavation rates. In addition, the drain elevations are specified as the respective tunnel elevations, and the conductance parameters are assigned to intervals, depending on the TBM type and the tunnel seepage condition. The Qomroud water conveyance tunnel, located in Lorestan province of Iran, is 36 km in length. Since the Qomroud tunnel involved groundwater inrush during excavating, it is considered as a good case study to evaluate the presented method. The groundwater inflow to this tunnel during the TBM advance is simulated using the proposed method and the predicted rates are compared with observed rates. The results show that the presented method can satisfactorily predict the inflow rates as the TBM advances.

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