Application of Ultrasonic Surface Wave Techniques for Concrete Bridge Deck Condition Assessment

Abstract

Ultrasonic surface wave (USW) is a well-established technique for the performance monitoring of concrete structures. In order to investigate the capability and reliability of this technique for concrete bridge deck condition assessment, a portable seismic property analyzer (PSPA) with USW capabilities was used to assess the condition of a reinforced concrete bridge deck exhibiting visible evidence of significant deterioration. After the investigation was completed, variable thicknesses of concrete were removed from upper surface of the concrete deck by milling and hydrodemolition, with greater thickness being removed where the concrete was more deteriorated. The thickness of removed concrete during the hydrodemolition process was mapped by Light Detection and Ranging (LiDAR). A comparison of the thickness of concrete removed and the USW data indicates that there is a qualitative correlation between the USW results at each test location and the thickness of concrete removed at those same test locations. Results suggest that the PSPA, and comparable USW techniques, could be potentially effective for estimating the thicknesses of concrete that would be removed during milling and hydrodemolition, although more work is needed to study the relationship between USW and removal thickness data in order to be used for quantity estimations.

Department(s)

Geosciences and Geological and Petroleum Engineering

Second Department

Civil, Architectural and Environmental Engineering

Keywords and Phrases

Concrete Bridge Deck; Hydrodemolition; Light Detection And Ranging; Portable Seismic Property Analyzer; Ultrasonic Surface Wave; Estimation; Milling (Machining); Optical Radar; Reinforced Concrete; Seismology; Surface Waves; Ultrasonic Applications; Condition Assessments; Performance Monitoring; Seismic Properties; Significant Deteriorations

International Standard Serial Number (ISSN)

0926-9851

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 Elsevier, All rights reserved.

Publication Date

01 Mar 2016

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