A differential strain-based approach for identifying prestress and moving forces in prestressed concrete bridges

Abstract Restressing force in prestressed concrete bridges (PCBs) is reduced due to ageing, and operational and environmental loading, and it can significantly impact on their load-carrying capacity. Existing dynamic methods are insensitive to the prestress force, and the identification accuracy is significantly affected by operational environments. This paper is to develop a novel differential strain-based time-domain inverse method for prestress force identification of PCBs under moving vehicles. Both prestress and moving forces are identified simultaneously from dual strain measurements on the bridge. A Vandermonde matrix-based convolution formula is constructed to ensure the accuracy of the least squares solution for ill-posed inverse problems. The proposed method is validated using numerical studies on a two-span continuously supported prestressed concrete T-beam and verified experimentally on a simply supported box girder bridge model. Field monitoring data, together with a calibrated finite element model of a three-span continuously supported PCB, is used to further verify the performance of the proposed method. To ensure accurate formulation of the prestressed bridge–vehicle system matrix for effective force identification, modal updating with Rayleigh damping is employed in the calibration process. The results demonstrate that the proposed method can simultaneously and accurately identify both prestress and moving forces, enabling reliable real-time structural condition assessment of the bridge.

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Publication Details

Journal
Advances in Bridge Engineering
Published
2026-07-02
DOI
https://doi.org/10.1186/s43251-026-00216-5
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A differential strain-based approach for identifying prestress and moving forces in prestressed concrete bridges

Tommy H.T. Chan, Khac-Duy Nguyen, Kunaratnam Jeyamohan, David Thambiratnam et al.
Advances in Bridge Engineering
Structural Health Monitoring Techniques
article

A differential strain-based approach for identifying prestress and moving forces in prestressed concrete bridges

Tommy H.T. Chan, Khac-Duy Nguyen, Kunaratnam Jeyamohan, David Thambiratnam, Xinqun Zhu, Di Wu, Erhua Zhang
article en

Abstract

Abstract Restressing force in prestressed concrete bridges (PCBs) is reduced due to ageing, and operational and environmental loading, and it can significantly impact on their load-carrying capacity. Existing dynamic methods are insensitive to the prestress force, and the identification accuracy is significantly affected by operational environments. This paper is to develop a novel differential strain-based time-domain inverse method for prestress force identification of PCBs under moving vehicles. Both prestress and moving forces are identified simultaneously from dual strain measurements on the bridge. A Vandermonde matrix-based convolution formula is constructed to ensure the accuracy of the least squares solution for ill-posed inverse problems. The proposed method is validated using numerical studies on a two-span continuously supported prestressed concrete T-beam and verified experimentally on a simply supported box girder bridge model. Field monitoring data, together with a calibrated finite element model of a three-span continuously supported PCB, is used to further verify the performance of the proposed method. To ensure accurate formulation of the prestressed bridge–vehicle system matrix for effective force identification, modal updating with Rayleigh damping is employed in the calibration process. The results demonstrate that the proposed method can simultaneously and accurately identify both prestress and moving forces, enabling reliable real-time structural condition assessment of the bridge.

Advances in Bridge EngineeringVol. 7(1)
University of Technology Sydney (AU), Queensland University of Technology (AU), Sichuan Highway Design and Research Institute (CN)
Australian Research Council
Sustainable cities and communities
Openalex Percentile: Top 13%
Structural Health Monitoring Techniques
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