Artigo Revisado por pares

Quantifying Bridge Deck Corrosion Using Ground Penetrating Radar

2015; Taylor & Francis; Volume: 27; Issue: 2 Linguagem: Inglês

10.1080/09349847.2015.1067342

ISSN

1432-2110

Autores

Nicole Martino, Ken Maser, Ralf Birken, Ming Wang,

Tópico(s)

Concrete Corrosion and Durability

Resumo

ABSTRACTCurrent visual bridge deck inspection techniques do not provide enough quantitative information about the deck's deterioration state to support maintenance and rehabilitation decisions. In recent years, ground penetrating radar (GPR) has shown promise in the ability to determine deterioration quantities, with data that can be collected quickly on multiple decks without lane closures. The work presented in this article seeks to develop a method to relate GPR analysis results to the level of active corrosion in a bridge deck. By multiplying the mean and skewness of the rebar reflection amplitudes of a variety of bridge decks, and comparing these values to corrosion quantities based on half-cell potential (HCP) measurements, a master curve with a correlation coefficient of 93% was developed. This article also presents a step-by-step procedure for developing an amplitude threshold for future deck assessments using GPR alone.KEYWORDS: Bridge deck assessmentrebar corrosionground penetrating radarhalf-cell potentialnon-destructive testing This article is part of the following collections: Research in Nondestructive Evaluation Outstanding Paper Award AcknowledgmentsThe authors would like to acknowledge the Massachusetts Department of Transportation, and particularly Tom Weil, District 4 Bridge Inspection Engineer, for providing access to the bridge decks along with design and inspection data. The authors would also like to acknowledge Tourney Consulting Group for providing access to the laboratory slabs exposed to controlled corrosion, and Clayton Hoak and Chuck Myers of HNTB for their assistance in extracting and providing the deck slabs from the Sabattus River Bridge. Finally, the authors would like to acknowledge the data collection contributions from Adam Carmichael, Infrasense Project Engineer and the following VOTERS project team members: Reid Vilbig, Hao Liu, Yiying Zhang, Yubo Zhao, Sindhu Ghanta, David Vines-Cavanau, Yifeng Lu, and Tzu-Yang Yu.FundingThis work is performed under the support of the U.S. Department of Commerce, National Institute of Standards and Technology, Technology Innovation Program, Cooperative Agreement Number 70NANB9H9012.Additional informationFundingThis work is performed under the support of the U.S. Department of Commerce, National Institute of Standards and Technology, Technology Innovation Program, Cooperative Agreement Number 70NANB9H9012.

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