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Weigh-in-motion implementation in an old metallic railway bridge
•Numerical modeling of the global and local behavior of an old riveted metallic railway bridge.•Weigh-in-motion and bridge-weigh-in-motion implementation.•Long term monitoring campaign.•Estimation of traffic.•Estimation of real train loads, velocities and axle spacing. The structural assessment of o...
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Published in: | Engineering structures 2016-09, Vol.123, p.15-29 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Numerical modeling of the global and local behavior of an old riveted metallic railway bridge.•Weigh-in-motion and bridge-weigh-in-motion implementation.•Long term monitoring campaign.•Estimation of traffic.•Estimation of real train loads, velocities and axle spacing.
The structural assessment of old metallic bridges is a challenge for civil engineers. This is mainly due to difficulties in identifying material properties and vehicle characteristics. A great number of these bridges were built with materials that are no longer used in modern structures and are presently subjected to loads very different from the ones considered in the design. In this context, structural monitoring can be an important tool to characterize the structural behavior and to support the safety assessment. In this paper, the steps taken to implement a Bridge-Weigh-in-Motion algorithm for traffic characterization in a railway bridge are presented. For that purpose, a long term monitoring system based on strain gauges was installed in the Portuguese Trezói Bridge. The measurements from a period of approximately two years were used to obtain axle loads, axles spacing and velocities of the trains that crossed the bridge during this period, enabling the accurate characterization of the real traffic conditions. This was achieved applying a method for traffic characterization based on the research developed by Moses (1979) and also based on the recent research developed by Liljencrantz et al. (2007) and Quilligan (2003), which was enhanced by an optimization algorithm implemented to minimize the error of the simulated response when compared to the measured response of the structure, thus allowing the estimation axle loads, axle spacing and speed. |
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ISSN: | 0141-0296 1873-7323 |
DOI: | 10.1016/j.engstruct.2016.05.016 |