Abstract Regarding the predictive analysis of water inflows in tunnels and underground caverns, the permeability coefficients of seepage fields have great spatial differences induced by developed geological structures such as joints and fissures around rock masses. It is difficult to accurately simulate an actual situation by a deterministic method, and it is more realistic to regard it as a random field. In this paper, a numerical calculation was conducted using the FLAC3D finite difference software and considering random characteristics of the permeability coefficient caused by the randomness of joints and fissures in a rock mass, and based on the random field theory, the permeability coefficient was introduced as a random variable to carry out a numerical simulation analysis on seepage by giving a random permeability coefficient to each unit of the random field. The results show that the prediction of water inflows in the seepage field in underground caverns will be more accurate and reasonable when considering the spatial anisotropy. Based on a comparison of simulation results, calculation results by the empirical formula and field monitoring statistics, the application conditions of the random seepage field simulation are presented, providing a reference for water inflow prediction in practical engineering.
Abstract：
Regarding the predictive analysis of water inflows in tunnels and underground caverns, the permeability coefficients of seepage fields have great spatial differences induced by developed geological structures such as joints and fissures around rock masses. It is difficult to accurately simulate an actual situation by a deterministic method, and it is more realistic to regard it as a random field. In this paper, a numerical calculation was conducted using the FLAC3D finite difference software and considering random characteristics of the permeability coefficient caused by the randomness of joints and fissures in a rock mass, and based on the random field theory, the permeability coefficient was introduced as a random variable to carry out a numerical simulation analysis on seepage by giving a random permeability coefficient to each unit of the random field. The results show that the prediction of water inflows in the seepage field in underground caverns will be more accurate and reasonable when considering the spatial anisotropy. Based on a comparison of simulation results, calculation results by the empirical formula and field monitoring statistics, the application conditions of the random seepage field simulation are presented, providing a reference for water inflow prediction in practical engineering.
2015, Vol. 52 