A System Model for the Lifecycle Monitoring of Bridges

Dori, G.; Wild, Matthias; Borrmann, André; Fischer, Olivier

doi:10.4203/ccp.103.14

Cited by 1 publication

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A few studies that account for the relationships between elements are available in the literature [33,34]. The fault tree and impact tree methods have been used to analyze how one element affects the other elements [35][36][37]. However, these methods are probability-based analyses with hypothetical quantities and did not use actual quantities measured from the Element-level Bridge Inspections.…”

Section: Literature Reviewmentioning

confidence: 99%

Co-Active Prioritization by Means of Contingency Tables for Analyzing Element-level Bridge Inspection Results and Optimizing Returns

Oyegbile¹,

Chorzepa²

2020

Infrastructures

View full text Add to dashboard Cite

An efficient prioritization of bridge actions such as preventive maintenance, rehabilitation, or replacement (MRR) that accounts for inter-element interactions will optimize a long-term return on investments (ROI) in terms of service life extension. What enables this return is the assignment of “Co-Active” elements. This study develops a methodology based on the concept of “Co-Active elements”. The word, “Co-Active”, is used to represent a small group of elements that act together to improve the Bridge Health Index (BHI). The Co-Active parameters for three major bridge groups in Georgia are presented. To illustrate how the Co-Active model works, 1439 in-service bridges’ Element-Level Bridge Inspection results from the state of Georgia in U.S.A., representing a concrete bridge group with six Co-Active elements, are studied. The analysis results indicate that the overall BHI improves by 20% over the subsequent 20 years when expansion joints are replaced. The effects of Co-Active elements on the BHI predictions are quantifiable and depend on factors such as the timing of MRR, the condition of bridge elements as well as the type of MRR. Furthermore, it is concluded that inter-dependent relationships among Co-Active elements are highly affected by Co-Active coefficients. They increase when the degree of dependency among elements increases. Finally, the proposed bridge Co-Active prioritization analysis accounts for a performance target and associated gaps and thus is able to identify critical elements that affect bridge service life the most.

show abstract