Abstract
A protocol for the development of a set of load rating distributions for a steel I-girder bridge will be presented. The critical regions of the bridge were instrumented using strain sensors to measure the real-time strain time history resulting from ambient trucks. This study focused on five-axle trucks traveling the south-lane of the bridge. Strain time history data was used to calibrate finite element models according to two scenarios: known and unknown truck characteristic selections. These truck characteristics identified from Weight-In-Motion (WIM) data obtained from Iowa state highways were used in the model calibration. The calibrated models, along with standard HS-20 trucks following AASHTO Load Factor Rating (LFR) method, were used to calculate a set of load ratings for each strain set as per the scenarios. Multiple load rating distributions created for strain sets were combined into a single holistic distribution. For the proposed protocol verification, the distribution was compared to that obtained from a rating package currently used by the Iowa Department of Transportation (Iowa DOT). The resulting distribution sets had means of 1.36 and 1.41 for known and unknown truck selections, respectively and subsequently were 24% and 27% greater than those values obtained from the Iowa DOT rating package. The distribution can be used not only to statistically evaluate structural capacity of such bridges, but also provide essential information for assigning retrofit prioritization of such bridges.
Original language | English |
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Pages (from-to) | 569-580 |
Number of pages | 12 |
Journal | Engineering Structures |
Volume | 46 |
DOIs | |
State | Published - Jan 2013 |
Bibliographical note
Funding Information:The authors acknowledge the support of this work via a pooled fund project administered by the Iowa DOT. Other study participants include CALTRANS, Illinois DOT, the USDA Forest Products Laboratory, and the Federal Highway Administration.
Keywords
- Ambient trucks
- Bridge
- Model calibration
- Structural capacity
- Structural health monitoring system
ASJC Scopus subject areas
- Civil and Structural Engineering