Technical Papers
Jul 20, 2021

Predicting the Remaining Useful Life of Corroding Bridge Girders Using Bayesian Updating

Publication: Journal of Performance of Constructed Facilities
Volume 35, Issue 5

Abstract

This paper developed a model for predicting the temporal failure probability of prestressed concrete (PC) highway bridges. The model updates predictions based on data from nondestructive testing and visual inspections. Chloride-induced corrosion is taken as the main cause for deterioration, and a gamma process describes the reduction in structural capacity. A nonhomogeneous Poisson process models vehicle arrival, in which the vehicle load variability follows a two-peak lognormal mixture distribution. After each inspection, Bayesian inference updates select model parameters and, consequently, the associated temporal structural resistance. Bridge managers can use the updated failure probability predictions to evaluate the remaining useful life of the bridge and determine the maintenance scheme and budget accordingly. A real bridge example illustrated the methodology and justified the probability distributions used for deterioration and vehicle load. Through comparisons with three existing methods, we argued that the proposed model provides more-conservative recommendations, yet existing methods tend to underestimate failure probabilities.

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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 (the bridge design drafts and the inspection data).

Acknowledgments

The authors thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for the financial support under Grant No. RGPIN-2018-0.

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Go to Journal of Performance of Constructed Facilities
Journal of Performance of Constructed Facilities
Volume 35Issue 5October 2021

History

Received: Oct 19, 2020
Accepted: Apr 21, 2021
Published online: Jul 20, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 20, 2021

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Ph.D. Candidate, Dept. of Mechanical and Industrial Engineering, Univ. of Toronto, Toronto, ON Canada M5S 1A1. ORCID: https://orcid.org/0000-0003-0708-211X. Email: [email protected]
Assistant Professor, Dept. of Mechanical and Industrial Engineering and Dept. of Civil and Mineral Engineering, Univ. of Toronto, Toronto, ON Canada M5S 1A1 (corresponding author). ORCID: https://orcid.org/0000-0003-2559-8566. Email: [email protected]

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Cited by

  • Mechanistic Modeling of Construction Defects in Concrete Decks Subject to Corrosion-Induced Deterioration, Journal of Bridge Engineering, 10.1061/JBENF2.BEENG-6636, 29, 9, (2024).
  • Comparison of Markovian-Based Bridge Deterioration Model Approaches, Journal of Bridge Engineering, 10.1061/JBENF2.BEENG-5920, 28, 8, (2023).
  • Data-driven optimization of repair schemes and inspection intervals for highway bridges, Reliability Engineering & System Safety, 10.1016/j.ress.2022.108779, 228, (108779), (2022).

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