Investigating the Increase in Load Rating and Reliability of a Prestressed Concrete Bridge When Utilizing Field-Derived Distribution and Impact Factors
Publication: Journal of Bridge Engineering
Volume 29, Issue 3
Abstract
When the load rating of a bridge is less than 1.0 for AASHTO HL-93 live load and state-specific legal trucks, the bridge is posted. Posting a bridge causes an inconvenience to the public and may result in trucks taking longer routes. Thus, this paper investigated the effects of field-derived distribution factor (DF) and impact factor (IM) from static and dynamic load tests using computer vision and deflection measurements, instead of AASHTO factors, on the bridge load rating and component as well as system reliability for posting avoidance. The reliability approach used Monte Carlo simulations to account for uncertainties in calculating the flexural strength limit state (Strength I). Both Flexural strength I and serviceability (Service III) limit states were investigated. The bridge’s superstructure was studied in as-built, repaired, and damaged condition scenarios. For that, AASHTO HL-93, Florida legal trucks, and emergency vehicles were considered. In this regard, load rating distributions and component and system reliability indices were computed using both AASHTO and field-derived DF and IM. The increase in load rating and reliability was investigated. By using field-derived factors, a load rating increase of up to 17% was achieved. The component reliability also increased significantly. For example, the damaged case’s component reliability increased by 1.0 when replacing DF and IM, which indicates a major reduction in the probability of failure. The increase in system reliability was most significant because using the field-derived DF increased the capacity contribution from other girders. A 2.12 increase in system reliability was achieved in the damaged condition when only substituting DF, providing even higher system reliability as a result of a reduction in the system probability of failure.
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Data Availability Statement
Bridge owner files such as bridge as-built and inspection reports are not available. All other data are available from the corresponding author of this paper upon request.
Acknowledgments
This study was supported by the U.S. National Science Foundation (NSF) Division of Civil, Mechanical and Manufacturing Innovation (Grant Number 1463493), Transportation Research Board of the National Academies-IDEA Project 222, and National Aeronautics and Space Administration (NASA) Award No. 80NSSC20K0326 for the research activities and particularly for this paper. The research presented here was carried out at the Civil Infrastructure Technologies for Resilience and Safety (CITRS) Lab of the University of Central Florida. Several other scholars, graduate students, and undergraduate assistants contributed to the work, and the authors acknowledge these CITRS members for their support and contributions.
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Published In
Journal of Bridge Engineering
Volume 29 • Issue 3 • March 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jun 1, 2023
Accepted: Oct 5, 2023
Published online: Dec 21, 2023
Published in print: Mar 1, 2024
Discussion open until: May 21, 2024
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