Reliability Estimation of Existing Concrete Bridge Based on Bayesian Dynamic Model

Shuangrui Chen1, Quansheng Yan2, *
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong, 510640, China

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© 2015 Chen and Yan

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


It is of great significance to timely and accurately forecast the safety state of the bridge as far as the maintenance is concerned. Bayesian forecasting is a method of deriving posterior distribution in accord with the sampling information and prior information, where real time online forecasting is realized by means of recursive algorithm and the stationary assumption. Bayesian dynamic linear model is created to forecast the reliability of the bridge on the basis of the observed stress information of a bridge structure. According to the observed information, the model created is a superposition of constant mean model and seasonal effect model. The analysis of a practical example illustrates that Bayesian dynamic linear modes can provide an accurate real time forecast of the reliability of the bridge

Keywords: Bayesian dynamic model, forecast, information updating, reliability.

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