Tunnel collapse hazard is a key issue in tunnel construction, which should be adequately assessed to prevent economic damage and casualty. The present study proposed a risk evaluation model for tunnel collapse based on a quantified grading system and influence factors that significantly affected the tunnel collapse hazard. For this purpose, 24 actual tunnel collapse cases were collected, and a database was established to select significant influence factors as the risk evaluation indices. The Analytic Hierarchy Process (AHP) technique and Delphi survey analysis were then adopted to quantify the influence factors and the grading system for the risk evaluation of tunnel collapse. The significant influence factors were selected using the grading guide based on the weight importance and rating score of each considered influence factor. As an evaluation criterion, the TR index based on the probability distribution of weighted influence factors was proposed to compare the risk of collapse using Monte-Carlo simulation. The proposed evaluation model and TR index were validated by comparing and analyzing the risk index calculated using the proposed grading system for actual tunnel cases with and without collapse. The evaluated risk indices were in good agreement with the measured result from field cases.
|Journal||Tunnelling and Underground Space Technology|
|Publication status||Published - 2022 Feb|
Bibliographical noteFunding Information:
This research was conducted with the support of the “National R&D Project for Smart Construction Technology (No.21SMIP-A158708-02)” funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport, and managed by the Korea Expressway Corporation. It was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2020R1A2C2011966).
© 2021 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Building and Construction
- Geotechnical Engineering and Engineering Geology