Abstract

The bridge inspection process has multiple steps. One obvious element is for inspectors to identify defects in the main components of the structural system and assign condition ratings. These condition ratings are somewhat subjective because they are influenced by the experience of the inspector. In the current work, processes were developed for making inferences on the reliability of prestressed concrete (PC) girders with defects at the girder component level. The Bayesian network (BN) tools constructed in this study use simple structural mechanics to model the capacity of girders. Expert opinion is used to link defects that can be observed during inspections to underlying deterioration mechanisms. By linking these deterioration mechanisms with changes in mechanical properties, inferences on the reliability of a bridge can be made based on visual observation of defects. The BN can then be used to directly determine the rating factor (RF) of individual structural elements. Examples are provided using BNs to evaluate an existing older PC bridge currently behaving as two simply supported spans. The bridge is modeled using two scenarios with the spans acting as simply supported, and then also with the link block (continuity joint) repaired so that the spans are continuous for live load. The spans are considered simply supported for all dead load.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Applicable items are Netica BN models.

Acknowledgments

The authors thank the US Army Corps of Engineers for the use of as-built data for bridges in the current inventory. Additionally, support from the US Army and Corps (through participation in ERDC-University and funding of Projects 476923 and 154349) is acknowledged.

References

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Go to Practice Periodical on Structural Design and Construction
Practice Periodical on Structural Design and Construction
Volume 29Issue 4November 2024

History

Received: Jun 28, 2023
Accepted: Apr 2, 2024
Published online: Jul 17, 2024
Published in print: Nov 1, 2024
Discussion open until: Dec 17, 2024

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Jeffery M. Roberts, Ph.D., P.E., M.ASCE https://orcid.org/0000-0002-3505-0580 [email protected]
Civil Engineer (Structural), US Army Corps of Engineers, Portland District, 333 SW 1st Ave., Portland, OR 97204 (corresponding author). ORCID: https://orcid.org/0000-0002-3505-0580. Email: [email protected]
Thomas Schumacher, Ph.D., P.E., M.ASCE https://orcid.org/0000-0003-0118-9119 [email protected]
Professor, Dept. of Civil and Environmental Engineering, Portland State Univ., 1930 SW 4th Ave., Portland, OR 97201. ORCID: https://orcid.org/0000-0003-0118-9119. Email: [email protected]
Research Civil Engineer, US Army Engineer Research and Development Center, Geotechnical and Structures Laboratory, 3909 Halls Ferry Rd., Vicksburg, MS 39180. ORCID: https://orcid.org/0000-0001-8083-7414. Email: [email protected]
Stephanie G. Wood, Ph.D. [email protected]
Research Civil Engineer, US Army Engineer Research and Development Center, Geotechnical and Structures Laboratory, 3909 Halls Ferry Rd., Vicksburg, MS 39180. Email: [email protected]
Senior Project Manager, Fickett Structural Solutions, Inc., 3148 Deming Way, Suite 160, Middleton, WI 53562; formerly, US Army Engineer Research and Development Center, Vicksburg, MS 39180. ORCID: https://orcid.org/0000-0002-3718-8321. Email: [email protected]

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