Permeability zoning in Amirkabir tunnel using Support vector machine

Document Type : Original Article

Authors

1 Mining Engineering Department, Faculty of Engineering, University of Kashan, Kashan, Iran,

2 University of Kashan

3 Kashan

Abstract

The rock mass permeability is one of the most important parameters regulating to the groundwater flow through the fracture’s rocks. The permeability distribution is an important part of estimating inflow into tunnels. The common methods to rock mass permeability estimation such as lugeon tests are expensive and very time consuming. The use of intelligent methods to estimate or classify data, especially in engineering problems, has been common in recent decades. Many algorithms have been designed and optimized for this purpose. Support vector machines (SVM) is one of these methods. In this paper, using the SVM method, the Amirkabir tunnel has been classified from the permeability point of view. In order to optimize the parameters of this algorithm, random search method has been selected. The results show that the accuracy of modelling using this method based on experimental data is around 94.59%. Based on this result, amount 85% of tunnel length is classified in the low permeability category and water inflow into tunnel from this part of tunnel is negligible

Keywords

References

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Scientific Quarterly Journal of Iranian Association of Engineering Geology
Volume 15, Issue 4
March 2023
Pages 19-29

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History

  • Receive Date: 21 August 2021
  • Revise Date: 26 February 2022
  • Accept Date: 12 June 2022

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