Evaluating prestress losses in a prestressed concrete girder railway bridge using distributed and discrete fibre optic sensors
Author | Ye, Cong |
Author | Butler, Liam J. |
Author | Elshafie, Mohammed Z.E.B. |
Author | Middleton, Campbell R. |
Available date | 2024-08-05T07:19:21Z |
Publication Date | 2020 |
Publication Name | Construction and Building Materials |
Resource | Scopus |
ISSN | 9500618 |
Abstract | This paper evaluates the data collected during a comprehensive monitoring campaign aimed at capturing the prestress loss behaviour of four 11.9 m prestressed concrete beams. These beams formed part of the superstructure of a newly-constructed railway bridge in Staffordshire, U.K. Two types of prestressed concrete beams were monitored, two TY7 internal beams and two TYE7 edge beams. Both distributed and discrete fibre optic sensor (FOS) systems were used to measure strain and temperature for the first two and a half years since the beams were cast. Prestress loss mechanisms were investigated in detail including immediate prestress losses due to elastic shortening of concrete and time-dependent prestress losses due to steel relaxation, concrete shrinkage and creep. Prestress loss predictions were calculated using both European and American standards, which were then compared with measured prestress losses. Both simplified and advanced time-step methods were used to provide more refined loss predictions by taking into account the interrelationships between various prestress loss mechanisms and the total prestress force at the time of interest. To provide better interpretation of the monitoring measurements, a sensitivity analysis was performed to evaluate the effects of various input parameter uncertainties on prestress loss predictions. It was found that (i) time-step methods produced prestress loss estimates that were lower compared with the simplified method; and (ii) code estimates of prestress losses using measured material properties gave reasonable agreement with the field measurements. As structurally-integrated FOS systems are becoming more commonplace and hold great potential, it is envisaged that they enable better understanding of field performance and thus facilitate data-informed asset management. |
Sponsor | The authors thank the EPSRC and Innovate UK for funding this research through the Cambridge Centre for Smart Infrastructure and Construction (CSIC) Innovation and Knowledge Centre ( EPSRC grant reference number EP/L010917/1 ); the invaluable facilitation of the installation work from Liam Brunning of Explore Manufacturing and his team; the on-site assistance of Niamh Gibbons (formerly of CSIC), Jason Shardelow and Peter Knott of CSIC, Mahul Patel of CH2M HILL (formerly of CSIC), Hyungjoon Seo of Xi'an Jiaotong-Liverpool University (formerly of CSIC) and Jules Birks of Mott MacDonald (formerly of CSIC); the technical assistance in sensor deployment and procurement of 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; and the Laing O'Rourke Centre for Construction Engineering and Technology ( University of Cambridge ) for facilitating and supporting this research. Additional data related to this publication is available at the University of Cambridge data repository. https://doi.org/10.17863/CAM.49678 . |
Language | en |
Publisher | Elsevier |
Subject | Fibre optic sensing Prestressed concrete Railway bridges Structural health monitoring |
Type | Article |
Volume Number | 247 |
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Civil and Environmental Engineering [851 items ]