He, Longxue, Liu, Yong, Bi, Sifeng, Wang, Li, Broggi, Matteo and Beer, Michael 
ORCID: 0000-0002-0611-0345
(2020)
Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating.
Underground Space, 5 (4).
pp. 315-323.
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Abstract
A probabilistic model is proposed that uses observation data to estimate failure probabilities during excavations. The model integrates a Bayesian network and distanced-based Bayesian model updating. In the network, the movement of a retaining wall is selected as the indicator of failure, and the observed ground surface settlement is used to update the soil parameters. The responses of wall deflection and ground surface settlement are accurately predicted using finite element analysis. An artificial neural network is employed to construct the response surface relationship using the aforementioned input factors. The proposed model effectively estimates the uncertainty of influential factors. A case study of a braced excavation is presented to demonstrate the feasibility of the proposed approach. The update results facilitate accurate estimates according to the target value, from which the corresponding probabilities of failure are obtained. The proposed model enables failure probabilities to be determined with real-time result updating.
| Item Type: | Article |
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| Uncontrolled Keywords: | Failure probability, Braced excavation, Bayesian networks, Stochastic model updating, Sensitivity analysis |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 21 Sep 2020 09:53 |
| Last Modified: | 18 Jan 2023 23:32 |
| DOI: | 10.1016/j.undsp.2019.07.001 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3101691 |
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