- Volume 18 Issue 3
DOI QR Code
A probabilistic assessment of ground condition prediction ahead of TBM tunnels combining each geophysical prediction method
TBM 현장에서 막장전방 예측기법 결과의 확률론적 분석을 통한 지반상태 평가
- Lee, Kang-Hyun (Korea Expressway Corporation Research Institute) ;
- Seo, Hyung-Joon (Department of Engineering, University of Cambridge) ;
- Park, Jeongjun (Korea Railroad Research Institute) ;
- Park, Jinho (School of Civil, Environmental and Architectural Engineering, Korea University) ;
- Lee, In-Mo (School of Civil, Environmental and Architectural Engineering, Korea University)
- 이강현 (한국도로공사 도로교통연구원) ;
- 서형준 (케임브리지대학교 공과대학) ;
- 박정준 (한국철도기술연구원) ;
- 박진호 (고려대학교 건축사회환경공학부) ;
- 이인모 (고려대학교 건축사회환경공학부)
- Received : 2016.02.16
- Accepted : 2016.05.27
- Published : 2016.05.31
It is usually not an easy task to counter-measure on time and appropriately when confronting with troubles in mechanized tunnelling job-sites because of the limitation of available spaces to perform those actions with the existence of disk cutter, cutter head, chamber and other various apparatus in Tunnel Boring Machine (TBM). So, it is important to predict the ground condition ahead of a tunnel face during tunnel excavation. Efforts have been made to utilize geophysical methods such as elastic wave survey, electromagnetic wave survey, electrical resistivity survey, etc for predicting the ground condition ahead of the TBM tunnel face. Each prediction method among these geophysical methods has its own advantage and disadvantage. Therefore, it might be needed to apply several geophysical methods rather than just one to predict the ground condition ahead of the tunnel face in the complex and/or mixed grounds since those methods will compensate among others. The problem is that each prediction method will give us different answer on the predicted ground condition; how to combine different solutions into a most reasonable and representative predicted value might be important. Therefore, in this study, we proposed a methodology how to systematically combine each prediction method utilizing probabilistic analysis as well as analytic hierarchy process. The proposed methods is applied to a virtual job site to confirm the applicability of the model to predict the ground condition ahead of the tunnel face in the mechanized tunnelling.
Grant : 고수압 초장대 해저터널 기술자립을 위한 핵심요소 기술개발
Supported by : 국토교통부
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