Prediction of groundwater inflow into rock tunnels is one of the essential tasks of tunnel engineering. Currently, most of the methods used in the industry are typically based on continuum models, whether analytical, semi-empirical, or numerical. As a consequence, a regular flow along the tunnel is commonly predicted. There are also some discrete fracture network methods based on a discontinous model, which typically yield regular flow or random flow along the tunnel. However, it was observed that, in hard rock tunnels, flow usually concentrates in some areas, and much of the tunnel is dry. The reason is that, in hard rock, most of the water flows in rock fractures and fractures typically occur in a clustered pattern rather than in a regular or random pattern. A new method is developed in this work, which can model the fracture clustering and reproduce the flow concentration. After elaborate literature review, a new algorithm is developed to simulate fractures with clustering properties by using geostatistics. Then, a discrete fracture network is built and simplified. In order to solve the flow problem in the discrete fracture network, an existing analytical-numercial method is improved. Two case studies illustrate the procedure of fracture simulation. Several ideal tunnel cases and one real tunnel project are used to validate the flow analysis. It is found that fracture clustering can be modeled and flow concentration can be reproduced by using the proposed technique. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-08-1677 |
| Date | 09 November 2010 |
| Creators | Chen, Ran |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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