Predictive and Diagnostic Load Rating Model of a Prestressed Concrete Bridge
Publication: Journal of Bridge Engineering
Volume 15, Issue 4
Abstract
This paper presents a probabilistic model of the load rating process incorporated with field inspection observations applied to a prestressed concrete bridge to capture deterioration characteristics. The main computational tool used is a Bayesian network. The model is developed around the main load-carrying member, an interior beam, and the effects of corrosion of its interior steel. Bridge load ratings are calculated as variables based on the following design methodologies: allowable stress; load factor; and load and resistance factor design. Two investigations on an actual bridge are conducted that demonstrate the predictive and diagnostic capabilities of the model. The results show the usefulness of this model in bridge management.
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Acknowledgments
Support from NSF Career Development Award No. UNSPECIFIEDCMS-9702656 is appreciated. The work presented herein is designed to adapt to the use of quantifiable nondestructive test measurements. Thus, modest support from the NSF funded Center for Subsurface Sensing and Imaging Systems (CenSSIS; Award No. NSFEEC-9986821) is appreciated as well as the NSF funded IGERT project for Intelligent Diagnostics for Aging Civil Infrastructure Systems (Award No. NSFDGE-0654176).
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Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 15 • Issue 4 • July 2010
Pages: 399 - 407
Copyright
© 2010 ASCE.
History
Received: Oct 15, 2008
Accepted: Mar 26, 2010
Published online: Mar 30, 2010
Published in print: Jul 2010
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