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Mathematical Problems in Engineering
Volume 2013, Article ID 706491, 9 pages
http://dx.doi.org/10.1155/2013/706491
Research Article

Predictions of Overbreak Blocks in Tunnels Based on the Wavelet Neural Network Method and the Geological Statistics Theory

College of Earth Science and Engineering, Hohai University, Nanjing, Jiangsu 210098, China

Received 8 November 2012; Revised 6 February 2013; Accepted 6 February 2013

Academic Editor: Tsung-Chih Lin

Copyright © 2013 Sun Shaorui et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Predicting overbreak blocks is a valid way to protect constructors, safeties in the process of tunnel excavation. In this paper, a prediction method of the overbreak blocks in tunnels is developed in the frame of the wavelet neural network of geological statistics models. Geometrical parameters of structural plane are first obtained by field survey. Then, a statistical model can be deduced from the measured geometrical parameters on the basis of the geological statistics theory. Furthermore, the volumes and distribution of the overbreak blocks are calculated by the theory of wavelet neural network. Finally, the valid support measurements can be designed according to the prediction results for all overbreak blocks appeared in tunnel excavation, and the amount of overbreak blocks can also be predicted. The code with respect to the method has been developed by the fortran language. The method proposed in this paper has been used in a tunnel construction. The results show that there exists an approximate 10%~30% difference between the prediction and the real volume of overbreak blocks. Therefore, the method can be well used to predict the volumes distribution and the overbreak blocks, and the accordingly support measurements can be also given according to the prediction results.