Abstract:

Water leakage of tunnels is very popular and has serious adverse effect, therefore it has become one of the critical issues in the construction and maintenance of tunnels. Regarding the status of the water leakage of tunnels in China, the authors identify the main factors that influence the water leakage of tunnels by comprehensively analyzing the factors. The authors propose an evaluation index system consisting of 4 Grade I indexes (i.e., tunnel design and construction index, waterproofing and drainage index, surrounding rock mass and groundwater index and physical geography index), which include 10 factors. In addition, they establish an evaluation model based on BP neural network and verify the reliability of this model. This method offers a new way to improve the evaluation precision of the water leakage of tunnels.

Key words: BP neural network  , tunnel  , water leakage  , disaster grade