Applied Sciences (Jul 2023)

Flexural Behavior of Corroded High-Speed Railway Simply Supported Prestressed Concrete Box Girder

  • Yachuan Kuang,
  • Jiahui Yang,
  • Haiquan Jing,
  • Runan Tian,
  • Kexiang Niu,
  • Zhiwu Yu

DOI
https://doi.org/10.3390/app13148396
Journal volume & issue
Vol. 13, no. 14
p. 8396

Abstract

Read online

Simply supported prestressed concrete (PC) box girders have been widely adopted in high-speed railway bridges. In complex climatic environments, the corrosion of the prestressing strands always occurs and deteriorates the flexural behavior of PC box girders. In the present study, six T-shaped scaled beams were designed and fabricated according to the specifications for a high-speed railway PC box girder. The corrosion process of the prestressing strand in scaled beams was experimentally simulated by using the constant current accelerated corrosion method. The flexural behavior of corroded high-speed railway simply supported PC box girders was then investigated through four-point bending tests and theoretical investigation. The experimental results showed that strand corrosion significantly decreased the flexural behavior of the test beams. When the mass loss was 12.30%, the cracking load, ultimate load, and ductility decreased by 27.8%, 29.9%, and 11.5%, respectively. The effect of strand corrosion on flexural stiffness displayed a difference before and after concrete cracking. The failure mode changed when strand mass loss was above a critical value (7%). The flexural bearing capacity degradation law of corroded PC beams could be divided into two distinct stages. A strand mass loss of less than 7% could lead to a linear degradation law with a relatively slight reduction. As mass loss increased, it exhibited an exponential and sharp declining trend. An analytical model including the effects of strand cross-section reduction, strand property deterioration, and concrete cracking was also proposed to predict the flexural behavior of corroded PC beams. By comparison with the experimental data, it was found that the model could predict the cracking moment, flexural bearing capacity, and failure mode well.

Keywords