Determining Bridge Deck Chloride Quantities Using Ground Penetrating Radar

Abstract

<p>Chlorides from deicing salts attack the steel reinforcement in bridge decks which can ultimately cause delamination and deterioration of the concrete. For transportation agencies, the repair cost from these defects are estimated to exceed $5B per year in USA and make up between 50% - 85% of bridge maintenance budgets. While, the removal and replacement of chloride contaminated concrete is the most long-lasting and cost-effective remediation, few methods exist to determine chloride content in bridge decks. This research describes an entirely new method for determining chloride quantity in bridge decks using ground penetrating radar (GPR) technology and establishes and quantifies the relationship between chlorides in concrete (which cause corrosion of reinforcing steel and delamination of concrete) and the effect on GPR signal propagation. Specifically, it shows that there is a deterministic relationship between radar signal attenuation and the amount of chloride and moisture in bridge deck concrete, and that when moisture content is known it is possible to estimate chloride quantity based on signal loss or attenuation measurements. Our research also demonstrates the practical application of this concept by utilizing GPR along with limited coring (three or more core samples) and laboratory chloride measurements to produce an accurate and quantitative, spatial mapping of chlorides in bridge decks.</p>

Automatic classification of underground utilities in Urban Areas: A novel method combining ground penetrating radar and image processing

“…This shape was caused by the reflection of the electromagnetic wave previously sent by the instrument from the object, as recorded by the ground penetrating radar. There are available algorithms that enable the extraction of the selected geometric properties of hyperbolas, that is, the depth, position, and radius of an underground object and its 3D representation [14][15][16][17]. However, the use of deep learning in extracting hyperbolas from radargrams has proven to be an effective method for extracting information from radargrams and recognizing hyperbolas using a large dataset of labeled images [18][19][20][21][22][23].…”

Development of new GPR methodologies for soil and cement concrete pavement assessment

“…The condition of the bridge decks and other concrete structures is evaluated by developing GPR antennas system, pulse generators and collection of data from realistic tests (P. Warhus, 1994), concrete bridge deck (J. Hugenschmidt et al, 2009;Johannes et al, 2006), using high resolution antenna in concrete deterioration in bridge deck (Parrillo & Roberts, 2006;Sławski et al, 2016), and ancient bridge is investigated and results were combined with numerical modelling (M. Solla et al, 2012).…”

“…Results showed the proficiency of GPR in locating tendon ducts of up to 50 cm depth, void detection, layer thickness and detachment in quality and damage assessment of building. (Parrillo & Roberts, 2006). (Viriyametanont et al, 2008) This research focused on detection of steel reinforcement rebars in concrete structure by using GPR.…”