Probabilistic predictions regarding key blocks using stochastic discrete fracture networks - Example from a rock cavern in south-east Sweden

被引：0

作者：

Starzec P. ^{[1
,2
]}

Andersson J. ^{[3
]}

机构：

[1] Swedish Geotechnical Institute

[2] Chalmers University of Technology

[3] JA Streamflow, Stockholm

来源：

Bulletin of Engineering Geology and the Environment | 2002年 / 61卷 / 04期

关键词：

Discrete fracture network; Key blocks; Predictions;

D O I：

10.1007/s10064-002-0154-5

中图分类号：

学科分类号：

摘要：

The natural variation of the fracture/joint network geometry and limited data access are the main sources of uncertainties in key block predictions. To make the uncertainties easily quantifiable the predicting variables should be presented as probability density functions. This paper illustrates the implementation of a stochastic fracture network to predict the amount and size of key blocks around the rock cavern of the Centralt Storage Facility for Spent Nuclear Fuel (CLAB-2, Central Lager Använt Bränsle) in south-eastern Sweden. The data used in the study were effectively limited to fracture mapping in boreholes. The stochastic fracture model was generated with a FracMan discrete fracture simulator by adopting random fracture locations. Subsequently, the key block statistics along a simulated tunnel positioned inside the fracture model were generated. To illustrate the value of the predictions made, block statistics were undertaken for two different tunnel orientations. The methodology presented offers the potential to optimize the excavation design.

引用

页码：363 / 378

页数：15