关键词: 裂隙岩体, 三维网络模拟, 随机-确定耦合, 渗流计算

Abstract: Since stochastic discrete fracture network (DFN) model can only consider statistical properties of discontinuities, it is difficult to incorporate other significant factors, such as geological genesis, structural pattern and feature. To fully characterize the true DFN of rock mass, non-negligible biases are introduced into the subsequent mechanical and seepage calculations based on a pure stochastic model. The Beishan granite, a well-studied rock type, from a Chinese high-level radioactive waste repository, is selected for the analysis. A new stochastic-deterministic DFN model is built up for Beishan granite in terms of the statistical properties of measured discontinuities, the inherent hierarchy of discontinuities with different scales, and their hydraulic interconnections. The deterministic part of this model is implemented after combining the unbiased stochastic model with manually identified structural patterns. Model validations are conducted using the graphical comparison and seepage simulation techniques. The results show that the amount of discontinuities in the new model is consistent with the measured data, with an increase in model accuracy by 48.8%. The flow path and flux calculated by the new model are more realistic and more consistent with testing data, with approximately a one-third increase in consistency compared with the traditional model results. In addition, in-situ seepage-pressure tests are conducted on different boreholes. Testing results show that the deterministic discontinuities have great influence on the seepage simulation compared with the stochastic ones. The regional seepage is primarily controlled by these deterministic discontinuities. The developed new model is beneficial for the future DFN simulations.

Key words: fractured rock mass, 3D network simulation, stochastic-deterministic coupling, seepage calculation