Bayesian updating of KJHH model for prediction of maximum ground settlement in braced excavations using centrifuge data |
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| Institution: | 1. MOE Key Laboratory of Road and Traffic Engineering, College of Transportation Engineering, Tongji University, Shanghai 201804, China;2. Faculty of Engineering, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China;3. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA;4. Department of Civil Engineering, National Central University, Jhongli 32001, Taiwan;1. School of Civil Engineering and Architecture, Nanchang University, 999 Xuefu Road, Nanchang 330031, PR China;2. Engineering Risk Analysis Group, Technische Universität München, Arcisstr. 21, 80290 München, Germany |
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| Abstract: | In this paper, a Bayesian approach for updating a semi-empirical model for predicting excavation-induced maximum ground settlement using centrifuge test data is presented. The Bayesian approach involves three steps: (1) prior estimate of the maximum ground settlement and model bias factor, (2) establishment of the likelihood function and posterior distribution of the model bias factor using the settlement measurement in the centrifuge test, and (3) development of posterior distribution of the predicted maximum settlement. This Bayesian approach is demonstrated with a case study of a well-documented braced excavation, and the results show that the accuracy of the maximum settlement prediction can be improved and the model uncertainty can be reduced with Bayesian updating. |
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