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Predicting anomalous zone ahead of tunnel face utilizing electrical resistivity: II. Field tests

Authors
Park, JinhoLee, Kang-HyunKim, Byung-KyuChoi, HangseokLee, In-Mo
Issue Date
9월-2017
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Tunnel resistivity prediction; Anomalous zone; Tunnel boring machine; Resistivity survey; Ahead of tunnel face
Citation
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, v.68, pp.1 - 10
Indexed
SCIE
SCOPUS
Journal Title
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
Volume
68
Start Page
1
End Page
10
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/82486
DOI
10.1016/j.tust.2017.05.017
ISSN
0886-7798
Abstract
In our companion paper (Park et al., 2016), a method was developed to predict the characteristics (i.e., location, thickness, permittivity ratio, and conductivity) of the anomalous zone ahead of a tunnel face by utilizing the electrical resistivity of the ground (hereafter referred to as the Ground Prediction Method). The prediction accuracy of the developed Ground Prediction Method is investigated via laboratory tests using artificially created anomalies. This paper is part two in the series of companion papers; it attempts to examine the prediction accuracy of the developed Ground Prediction Method via field testing. The field tests are performed at railway and highway construction sites, at which conventional tunneling methodology is employed for tunnel construction, as well as at a subway tunnel construction site, at which an earth pressure-balanced shield tunnel boring machine is used for tunneling work. At tunneling job sites using the conventional tunneling method, a relatively stronger and weaker zone are predicted ahead of the tunnel face at the railway and highway construction sites, respectively. On the other hand, a relatively stronger zone exhibiting lower permittivity than that of the rock adjacent to the tunnel face is predicted at the tunneling site employing the mechanized tunneling method. In conclusion, assessing the ground condition, ahead of the tunnel face via the newly developed Ground Prediction Method proves to be effective; prediction results of ground conditions show good agreement with those characterized via direct observation of the excavated face taken during tunneling work using conventional tunneling methods, in addition to those predicted from daily observations of muck conditions carried out in the process of tunnel construction using the mechanized tunneling method.
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공과대학 (건축사회환경공학부)
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