DOI QR코드

DOI QR Code

FE model of electrical resistivity survey for mixed ground prediction ahead of a TBM tunnel face

  • Kang, Minkyu (School of Civil, Environmental and Architectural Civil Engineering, Korea University) ;
  • Kim, Soojin (Department of Micro/Nano System, Korea University) ;
  • Lee, JunHo (School of Civil, Environmental and Architectural Civil Engineering, Korea University) ;
  • Choi, Hangseok (School of Civil, Environmental and Architectural Civil Engineering, Korea University)
  • 투고 : 2021.12.27
  • 심사 : 2022.03.08
  • 발행 : 2022.05.10

초록

Accurate prediction of mixed ground conditions ahead of a tunnel face is of vital importance for safe excavation using tunnel boring machines (TBMs). Previous studies have primarily focused on electrical resistivity surveys from the ground surface for geotechnical investigation. In this study, an FE (finite element) numerical model was developed to simulate electrical resistivity surveys for the prediction of risky mixed ground conditions in front of a tunnel face. The proposed FE model is validated by comparing with the apparent electrical resistivity values obtained from the analytical solution corresponding to a vertical fault on the ground surface (i.e., a simplified model). A series of parametric studies was performed with the FE model to analyze the effect of geological and sensor geometric conditions on the electrical resistivity survey. The parametric study revealed that the interface slope between two different ground formations affects the electrical resistivity measurements during TBM excavation. In addition, a large difference in electrical resistivity between two different ground formations represented the dramatic effect of the mixed ground conditions on the electrical resistivity values. The parametric studies of the electrode array showed that the proper selection of the electrode spacing and the location of the electrode array on the tunnel face of TBM is very important. Thus, it is concluded that the developed FE numerical model can successfully predict the presence of a mixed ground zone, which enables optimal management of potential risks.

키워드

과제정보

This research was conducted with the support of the "National R&D Project for Smart Construction Technology (No.22SMIP-A158708-03)" funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation.

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