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Risk analysis during tunnel construction using Bayesian Networks: Porto Metro case study

Author(s)
Sousa, Rita L.; Einstein, Herbert H.
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Abstract
This paper presents a methodology to systematically assess and manage the risks associated with tunnel construction. The methodology consists of combining a geologic prediction model that allows one to predict geology ahead of the tunnel construction, with a construction strategy decision model that allows one to choose amongst different construction strategies the one that leads to minimum risk. This model used tunnel boring machine performance data to relate to and predict geology. Both models are based on Bayesian Networks because of their ability to combine domain knowledge with data, encode dependencies among variables, and their ability to learn causal relationships. The combined geologic prediction–construction strategy decision model was applied to a case, the Porto Metro, in Portugal. The results of the geologic prediction model were in good agreement with the observed geology, and the results of the construction strategy decision support model were in good agreement with the construction methods used. Very significant is the ability of the model to predict changes in geology and consequently required changes in construction strategy. This risk assessment methodology provides a powerful tool with which planners and engineers can systematically assess and mitigate the inherent risks associated with tunnel construction.
Date issued
2011-08
URI
http://hdl.handle.net/1721.1/101601
Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Journal
Tunnelling and Underground Space Technology
Publisher
Elsevier
Citation
Sousa, Rita L., and Herbert H. Einstein. “Risk Analysis During Tunnel Construction Using Bayesian Networks: Porto Metro Case Study.” Tunnelling and Underground Space Technology 27, no. 1 (January 2012): 86–100.
Version: Author's final manuscript
ISSN
08867798

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