Method for developing and updating deterioration models for concrete bridge decks using GPR data

Farzad Ghodoosi, Ashutosh Bagchi, Tarek Zayed, M. Reza Hosseini

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)


This study presents a workable procedure for developing and updating deterioration prediction models based on the results of a Non-Destructive Evaluation (NDE) technique, Ground Penetrating Radar (GPR). To this end, a system reliability based deterioration model was developed for a simply-supported reinforced concrete bridge deck, designed according to the Canadian Highway Bridge Design Code (CHBDC-S6). The superstructure element-level deteriorated conditions for different time intervals were applied in the non-linear finite element model developed for the entire bridge deck, and the system level reliability indices were estimated accordingly. The salt contamination was assumed to affect the top surface, soffits of the deck, and beams due to infusion of de-icing salt material. The resulting primary deterioration model was updated based on a GPR test localized defect map that was obtained for an existing bridge with similar plan dimensions. The results indicate that the assumed conservative uniformly defected superstructure is reliable in this case, that is, the estimated reliability indices for the uniform and localized defect plans do not differ considerably.
Original languageEnglish
Pages (from-to)133-141
Number of pages9
JournalAutomation in Construction
Publication statusPublished - 1 Jul 2018
Externally publishedYes


  • Canada
  • Defect map
  • Ground Penetration Radar test
  • Non-destructive evaluation (NDE)
  • Reinforced concrete
  • Reliability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction


Dive into the research topics of 'Method for developing and updating deterioration models for concrete bridge decks using GPR data'. Together they form a unique fingerprint.

Cite this