Automated bridge load rating determination utilizing strain response due to ambient traffic trucks: Fid-Bau Portal

Automated bridge load rating determination utilizing strain response due to ambient traffic trucks

Deng, Yaohua / Phares, Brent M.

Highlights • A novel automated bridge load rating determination approach is developed. • Uncertainties of truck characteristics on calibration/load rating results are considered. • The approach can be utilized to assist with decision making of bridge maintenance. • Adequacy of the approach is verified against results using Traditional Known Truck approach.

Abstract Approximately 11% of bridges in the United States are categorized as structurally deficient and there is a marked need of more accurately evaluating true structural capacity. Structural Health Monitoring (SHM) systems can provide a timely indication of the need for maintenance, repair, rehabilitation and replacement of bridges and can greatly improve the apportionment and management of limited resources. This paper presents an Automated Ambient Traffic (AAT) approach for determining load rating of bridges monitored by the BECAS SHM system under ambient traffic. The AAT approach was developed through a process integration of truck detection, bridge model calibration, and bridge load rating: (1) the quasi-static bridge strain response and the characteristics of associated trucks are collected; (2) multiple trucks are randomly sampled from a historic Weigh-In-Motion (WIM) database; and (3) for each combination of strain response and truck selection, an Finite Element (FE) model is calibrated and used to calculate a load rating. Sampling strategies were discussed for appropriately quantifying the influence of uncertainties of truck characteristics on the calibration and load rating results. To demonstrate this approach, a sample three-span, five-girder, and two-lane steel girder/concrete deck (I-80) bridge was utilized. A load rating of the I-80 Bridge using the Traditional Known Truck (TKT) approach was performed to provide benchmark results. The results of the calibration and load rating using the AAT approach were derived using three different sampling strategies and compared to those using the TKT approach. The sampling strategy, selecting strain response with a spectrum of higher peak girder strains, associated trucks with a spectrum of higher gross vehicle weights, and two truck events on south and north lanes respectively for a calibration, resulted in the best calibration and load rating results. It was concluded that the AAT approach using the BECAS SHM system is a reliable method for continuously estimating the load carrying capacity of bridges.