Estimation of Corrosion Damage in Steel Reinforced Mortar Using Guided Waves

Author:

Reis Henrique1,Ervin Benjamin L.1,Kuchma Daniel A.2,Bernhard Jennifer T.3

Affiliation:

1. Department of General Engineering, University of Illinois at Urbana-Champaign, 104 S. Mathews Ave., Urbana, IL, 61801

2. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave.,Urbana, IL 61801

3. Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1406 W. Green St., Urbana, IL, 61801

Abstract

Corrosion of reinforced concrete is a chronic infrastructure problem, particularly in areas with deicing salt and marine exposure. To maintain structural integrity, a testing method is needed to identify areas of corroding reinforcement. For purposes of rehabilitation, the method must also be able to evaluate the degree, rate, and location of damage. Toward the development of a wireless embedded sensor system to monitor and assess corrosion damage in reinforced concrete, reinforced mortar specimens were manufactured with seeded defects to simulate corrosion damage. Taking advantage of waveguide effects of the reinforcing bars, these specimens were then tested using an ultrasonic approach. Using the same ultrasonic approach, specimens without seeded defects were also monitored during accelerated corrosion tests. Both the ultrasonic sending and the receiving transducers were mounted on the steel rebar. Advantage was taken of the lower frequency (<250kHz) fundamental flexural propagation mode because of its relatively large displacements at the interface between the reinforcing steel and the surrounding mortar. Waveform energy (indicative of attenuation) is presented and discussed in terms of corrosion damage. Current results indicate that the loss of bond strength between the reinforcing steel and the surrounding concrete can be detected and evaluated.

Publisher

ASME International

Subject

Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality

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