Clustering-based threshold model for condition assessment of concrete bridge decks with ground-penetrating radar

Kien Dinh, Tarek Zayed, Sami Moufti, Ahmad Shami, Ahmad Jabri, Mona Abouhamad, Thikra Dawood

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)


Ground-penetrating radar (GPR) has been extensively studied for condition assessment of concrete bridge decks in North America. Although several methods for analyzing GPR data have been proposed, the commonly accepted method evaluates the condition of concrete bridge decks on the basis of the difference between reflection amplitudes of the top rebar layer. It is assumed in the method that strong reflection indicates sound concrete, whereas the area with high-amplitude attenuation is associated with concrete corrosion. The final result is a contour map of reflection amplitude in decibel scale with the thresholds selected arbitrarily to define the severity of concrete deterioration. Because subjective determination of threshold values may lead to inconsistency in the result obtained, this paper proposes a robust method for resolving that issue. Specifically, after depth correction was performed for top rebar amplitudes, on the basis of K-means clustering technique these amplitude data were grouped into a number of condition categories. Through two case studies in North America, the methodology was implemented and compared with the results provided by other technologies, namely, concrete resistivity, half-cell potential, and laboratory chloride content analysis. The implementation showed that while the proposed method was simple to employ, it still provided reasonable results that were in line with the outputs provided by the other techniques.
Original languageEnglish
Pages (from-to)81-89
Number of pages9
JournalTransportation Research Record
Publication statusPublished - 1 Jan 2015
Externally publishedYes

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering


Dive into the research topics of 'Clustering-based threshold model for condition assessment of concrete bridge decks with ground-penetrating radar'. Together they form a unique fingerprint.

Cite this