Monitoring, Modeling, and Assessment of a Self-Sensing Railway Bridge during Construction
Publication: Journal of Bridge Engineering
Volume 23, Issue 10
Abstract
This study shows how integrating fiber optic sensor (FOS) networks into bridges during the construction stage can be used to quantify preservice performance. Details of the installation of a large FOS network on a new steel–concrete composite railway bridge in the United Kingdom are presented. An overview of the FOS technology, installation techniques, and monitoring program is also presented, and the monitoring results from several construction stages are discussed. A finite-element (FE) model was developed and a phased analysis was carried out to simulate strain development in the bridge during consecutive construction stages. The response of the self-sensing bridge to the time-dependent properties of the concrete deck was evaluated by comparing FOS measurements to predicted results according to several model code formulations implemented in the FE model. The preservice strain distribution due to dead loading is typically assumed to act uniformly along the bridge length; however, the monitoring results revealed that the distribution was highly variable as a result of the complex interactions between gravity loading, bridge geometry, time-dependent concrete properties, and temperature effects. Moment utilization of the main girders and composite beams, during preservice conditions, was assessed and found to be between 19.3 and 24.9% of the respective design cross-section capacities. Quantifying preservice performance via integrated sensing also provided a critical baseline for the bridge, which enables future data-driven condition assessments.
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Acknowledgments
The authors gratefully acknowledge the Engineering and Physical Sciences Research Council (EPSRC) and Innovate UK for funding this research through the Cambridge Centre for Smart Infrastructure and Construction (CSIC) Innovation and Knowledge Centre (EPSRC Grant EP/L010917/1); the on-site assistance of Jason Shardelow of CSIC; the technical assistance in sensor development, procurement, and deployment planning from Cedric Kechavarzi and Philip Keenan of CSIC; James Oliver, Matthew Timmis, Brad Stanaway, and Phil Holland of Laing O'Rourke, Ruth Platt, and Mike Henwood of Atkins, for providing their invaluable support for this project. Monitoring data related to this publication are available at the University of Cambridge data repository.
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© 2018 American Society of Civil Engineers.
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Received: Dec 7, 2017
Accepted: Apr 16, 2018
Published online: Jul 25, 2018
Published in print: Oct 1, 2018
Discussion open until: Dec 25, 2018
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