Bayesian Updating of Soil Parameters for Braced Excavations Using Field Observations
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 139, Issue 3
Abstract
A Bayesian framework using field observations for back-analysis and updating of soil parameters in a multistage braced excavation is presented. Because of the uncertainties originating from the poorly known soil parameters, the imperfect analysis model, and other factors such as construction variability, the soil parameters can only be inferred as probability distributions. In this paper, these posterior distributions are derived using the Markov chain Monte Carlo (MCMC) sampling method implemented with the Metropolis-Hastings algorithm. In the proposed framework, Bayesian updating is first realized with one type of response observation (maximum wall deflection or maximum settlement), and then this Bayesian framework is extended to allow for simultaneous use of two types of response observations in the updating. The proposed framework is illustrated with a quality excavation case and shown effective regardless of the prior knowledge of soil parameters and type of response observations adopted.
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Acknowledgments
The study on which this paper is based was supported in part by National Science Foundation Grant No. CMMI-1200117. The authors thank the Journal’s anonymous reviewers for constructive comments. The results and opinions expressed in this paper do not necessarily reflect the view and policies of the National Science Foundation.
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Information & Authors
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 139 • Issue 3 • March 2013
Pages: 395 - 406
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Sep 26, 2011
Accepted: May 23, 2012
Published online: May 25, 2012
Published in print: Mar 1, 2013
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