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Automated UAV based multi-hazard assessment system for bridges crossing seasonal rivers

  • Ozcan, Orkan (Eurasia Institute of Earth Sciences, Istanbul Technical University) ;
  • Ozcan, Okan (Department of Civil Engineering, Akdeniz University)
  • Received : 2020.01.28
  • Accepted : 2020.11.16
  • Published : 2021.01.25
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Abstract

An automated unmanned aerial vehicle (UAV) based multi-hazard performance assessment system was developed to respond to rapid performance evaluation and performance prediction needs for river crossing reinforced concrete (RC) bridges. In the developed system, firstly the seasonally acquired UAV measurements were used to obtain the three-dimensional (3D) digital elevation models (DEMs) of the river bed. In conjunction with the flood simulation, the hydraulic model was verified with the previous flood event which corresponded to Q50 and the scour depths after a probable flood (Q500) were predicted by HEC-RAS software. Afterward, the 3D finite element model (FEM) of the bridge was constituted automatically with the developed code considering the scoured piles. The flood loads were exerted on the modeled bridge with regard to the HEC-RAS flood inundation map and relevant water depth estimations around the bridge piers. For the seismic evaluation, nonlinear time history analyses (THA) were conducted by using several scaled earthquake acceleration records that were acting in both principal axes of the bridge simultaneously as compatible with the region seismicity. The Boğaçay-II Bridge that was located in Antalya, Turkey was selected as the case study. In the analyses, as the scour depth increased, the lateral displacements and the pile internal forces were observed to increase while the pier column internal forces kept approximately constant. Thus, it was monitored that the seismic displacement and load demands migrated from pier columns to piles with increasing scour. Therefore, the applicability of the proposed system was verified using the case study bridge.

Keywords

Acknowledgement

This work was supported by the Istanbul Technical University Scientific Research Project (ITU-BAP). Project No: MGA-2018-41393 and by the Akdeniz University Scientific Research Project (AU-BAP) Project No: FBA-2018-2877.

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