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Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Wang, Ruizi, Ma, Lin, Yan, Cheng, & Matthews, Joseph (2011) Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN). In Huang, Hong-Zhong, Zuo, Ming J., Jia, Xisheng, & Liu, Yu (Eds.) Proceedings of International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, IEEE - CD Rom, Xi’an International Conference Center, Xi'An, China, pp. 7-12.

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Abstract

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

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ID Code: 41791
Item Type: Conference Paper
Keywords: Structural Reliability, Limit State Functions, Dynamic Object Oriented Bayesian Network (DOOBN)
ISBN: 9781457712302
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Infrastructure Engineering and Asset Management (090505)
Divisions: Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2011 [please consult the authors]
Deposited On: 25 May 2011 08:16
Last Modified: 08 Jul 2011 05:01

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