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Title: Estimating Bridge Reliability by Using Bayesian Networks
Authors: Groeneveld, Andrew B.
Wood, Stephanie G.
Ruiz, Edgardo
Roberts, Jeffery M.
Keywords: Bridges
Bayesian networks
Bayesian statistical decision theory
Material defects
Load rating
Concrete bridges--Design and construction
Reliability (Engineering)--Statistical methods
Bridges--Maintenance and Repair
Publisher: Geotechnical and Structures Laboratory (U.S.)
Engineer Research and Development Center (U.S.)
Series/Report no.: Technical Report (Engineer Research and Development Center (U.S.));no.ERDC/GSL TR-21-1
Abstract: As part of an inspection, bridge inspectors assign condition ratings to the main components of a bridge’s structural system and identify any defects that they observe. Condition ratings are necessarily somewhat subjective, as they are influenced by the experience of the inspectors. In the current work, procedures were developed for making inferences on the reliability of reinforced concrete girders with defects at both the cross section and the girder level. The Bayesian network (BN) tools constructed in this work use simple structural m echanics to model the capacity of girders. By using expert elicitation, defects observed during inspection are correlated with underlying deterioration mechanisms. By linking these deterioration mechanisms with reductions in mechanical properties, inferences on the reliability of a bridge can be made based on visual observation of defects. With more development, this BN tool can be used to compare conditions of bridges relative to one another and aid in the prioritization of repairs. However, an extensive survey of bridges affected by deterioration mechanisms is needed to confidently establish valid relationships between deterioration severity and mechanical properties.
Description: Technical Report
Gov't Doc #: ERDC/GSL TR-21-1
Rights: Approved for public release; distribution is unlimited
Size: 67 pages / 7.76 MB
Types of Materials: PDF
Appears in Collections:Technical Report

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