Bridge extreme stress prediction based on Bayesian dynamic linear models and non-uniform sampling

Author:

Fan Xueping12

Affiliation:

1. Key Laboratory of Mechanics on Disaster and Environment in Western China (Lanzhou University), The Ministry of Education of China, Lanzhou University, Lanzhou, P.R. China

2. School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou, P.R. China

Abstract

Bridge monitoring systems produce a large amount of data, including uniform and non-uniform sampled data in the long-term service periods; the proper handling of these data is one of the main difficulties in structural health monitoring. To properly predict structural non-uniform extreme stress and deal with the uncertainties of the monitored data, the objectives of this article are to present (a) Bayesian dynamic linear models about non-uniform extreme stress, (b) monitoring mechanism about the Bayesian dynamic linear models based on single and cumulative Bayes’ factors, and (c) an effective use of the Bayesian dynamic linear models to incorporate the dynamic monitored data into structural non-uniform extreme stress prediction. The proposed models and procedure are applied to the monitored data obtained from the I-39 Northbound Bridge over the Wisconsin River in Wausau, Wisconsin, USA.

Funder

Natural Science Foundation of Gansu Province of China

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Mechanical Engineering,Biophysics

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