Brogden, Matthew

The detection of rebar corrosion in reinforced concrete is important due to the high costs of corrosion related damages to infrastructure. One such method of rebar corrosion lies in the use of non-destructive ultrasonic testing. To date, acoustic methods require either the training of an artificial neural network or a theory of acoustic wave propagation. Using a more complete acoustic model such as the Biot-Stoll model avoids algorithm training requirements by directly modeling the acoustic environment. A problem with this method lies in the complexity of the model and the selection of free parameters. The problem of parameter selection is addressed by a series of targeted measurements using ultrasonic transducers on a set of existing reinforced concrete samples placed in a saltwater solution. This data can then be analyzed by a non-linear least squares solver to produce a better fit for the acoustic signal.