期刊
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
卷 37, 期 -, 页码 62-78出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tust.2013.02.006
关键词
Construction time; Tunnel construction risk; Dynamic Bayesian Networks; Tunneling performance; Failure rate
资金
- Technology Agency of the Czech Republic [TA01030245]
- (CIDEAS research center) of the Ministry of Education, Youth and Sports of the Czech Republic [1M0579]
- DAAD
- Bayhost
A probabilistic model for estimating tunnel construction time is learnt with data from past tunnel projects. The model is based on the Dynamic Bayesian Network technique. The model inputs are determined through an analysis of data from three tunnels built by means of the conventional tunneling method. The data motivate the development of a novel probability distribution to describe the excavation performance. In addition, the probability of construction failure events and the delay caused by such failures are estimated using databases available in the literature. The model is applied to a case study, in which it is demonstrated how observations from the tunnel construction process can be included to continuously update the prediction of construction time. (C) 2013 Elsevier Ltd. All rights reserved.
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