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Synergic identification of prestress force and moving load on prestressed concrete beam based on virtual distortion method

  • Xiang, Ziru (School of Civil Engineering and Built Environment, Queensland University of Technology (QUT)) ;
  • Chan, Tommy H.T. (School of Civil Engineering and Built Environment, Queensland University of Technology (QUT)) ;
  • Thambiratnam, David P. (School of Civil Engineering and Built Environment, Queensland University of Technology (QUT)) ;
  • Nguyen, Theanh (School of Civil Engineering and Built Environment, Queensland University of Technology (QUT))
  • Received : 2016.03.15
  • Accepted : 2016.04.30
  • Published : 2016.06.25

Abstract

In a prestressed concrete bridge, the magnitude of the prestress force (PF) decreases with time. This unexpected loss can cause failure of a bridge which makes prestress force identification (PFI) critical to evaluate bridge safety. However, it has been difficult to identify the PF non-destructively. Although some research has shown the feasibility of vibration based methods in PFI, the requirement of having a determinate exciting force in these methods hinders applications onto in-service bridges. Ideally, it will be efficient if the normal traffic could be treated as an excitation, but the load caused by vehicles is difficult to measure. Hence it prompts the need to investigate whether PF and moving load could be identified together. This paper presents a synergic identification method to determine PF and moving load applied on a simply supported prestressed concrete beam via the dynamic responses caused by this unknown moving load. This method consists of three parts: (i) the PF is transformed into an external pseudo-load localized in each beam element via virtual distortion method (VDM); (ii) then these pseudo-loads are identified simultaneously with the moving load via Duhamel Integral; (iii) the time consuming problem during the inversion of Duhamel Integral is overcome by the load-shape function (LSF). The method is examined against different cases of PFs, vehicle speeds and noise levels by means of simulations. Results show that this method attains a good degree of accuracy and efficiency, as well as robustness to noise.

Keywords

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