Hybrid Uncertainty Quantification for Probabilistic Corrosion Damage Prediction for Aging RC Bridges
Publication: Journal of Materials in Civil Engineering
Volume 27, Issue 4
Abstract
A systematic framework is proposed to quantify hybrid uncertainties (i.e., aleatory and epistemic uncertainty) for the probabilistic prediction of corrosion damage in aging reinforced concrete (RC) bridges when the initial statistical parameters of variable are not available, sparse or cannot be accurately obtained. The key idea is to use a likelihood-based approach to calculate the probability distribution function (PDF) of the variable described by sparse data and an entropy-based transformation method to obtain the PDF of variable described by expert-based information. Following this, a hybrid description of uncertainties is proposed using the marginal integration. The uncertainty quantification of important factors on corrosion initiation and propagation are discussed, and a time-variant corrosion cracking model is developed. The proposed methodology is illustrated and demonstrated by a numerical example of corrosion damage prediction of an existing RC bridge. The prediction results of corrosion damage agree well with the experimental observations.
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Acknowledgments
This work reported here was conducted with the financial supports from the National Science Foundation for Distinguished Young Scholars of Hunan Province (Grant No. 14JJ1022), New Century Excellent Talents in University of Ministry of Education of China (Grant No. NCET-12-0724), and the Special Fund of Excellent Doctoral Dissertations of China (Grant No. 201247). The supports are gratefully acknowledged. The assistance of Jian Yang with the integration-based method is also gratefully acknowledged.
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Published In
Journal of Materials in Civil Engineering
Volume 27 • Issue 4 • April 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Nov 13, 2013
Accepted: Apr 3, 2014
Published online: Jul 25, 2014
Discussion open until: Dec 25, 2014
Published in print: Apr 1, 2015
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