Bridge rating protocol using ambient trucks through structural health monitoring system

► The load rating protocol for a steel bridge under ambient trucks was developed. ► Procedures for generating the load rating distributions were detailed. ► Strain data was obtained via a structural health monitoring system. ► Ambient truck characteristics were identified using Weight-In-Motion data...

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Veröffentlicht in:Engineering structures 2013-01, Vol.46, p.569-580
Hauptverfasser: Seo, Junwon, Phares, Brent, Lu, Ping, Wipf, Terry, Dahlberg, Justin
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Wipf, Terry
Dahlberg, Justin
description ► The load rating protocol for a steel bridge under ambient trucks was developed. ► Procedures for generating the load rating distributions were detailed. ► Strain data was obtained via a structural health monitoring system. ► Ambient truck characteristics were identified using Weight-In-Motion data. ► The protocol was validated by comparing the ratings with a practical quantity. 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.
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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.</description><identifier>ISSN: 0141-0296</identifier><identifier>EISSN: 1873-7323</identifier><identifier>DOI: 10.1016/j.engstruct.2012.08.012</identifier><identifier>CODEN: ENSTDF</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Ambient trucks ; Applied sciences ; Bridge ; Bridges ; Bridges (structures) ; Buildings. 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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. 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subjects Ambient trucks
Applied sciences
Bridge
Bridges
Bridges (structures)
Buildings. Public works
Calibration
Composite bridges
Exact sciences and technology
Ground, air and sea transportation, marine construction
Health monitoring (engineering)
Mathematical models
Measurements. Technique of testing
Model calibration
Packages
Ratings
Road transportation and traffic
Strain
Stress concentration
Stresses. Safety
Structural analysis. Stresses
Structural capacity
Structural health monitoring system
Trucks
title Bridge rating protocol using ambient trucks through structural health monitoring system
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