Abstract

Structural concrete is the most widely used construction material in the world. After an extreme event such as an earthquake, fast and reliable condition assessment of buildings and bridges is key to ensure effective and safe disaster relief missions. This is of particular concern for the Pacific Northwest with a megathrust earthquake waiting to occur. Accurate and reliable non-destructive testing (NDT) tools represent an important solution to aid in this task. Ground penetrating radar (GPR) uses electromagnetic waves and is especially useful in identifying and locating embedded steel reinforcing bars in the concrete. Ultrasonic (US) arrays, on the other hand, use stress waves that strongly reflect at concrete-air interfaces such as internal voids and back walls. Advances in medical imaging and machine learning offer opportunities to fuse these measurements and create novel diagnosis tools. This poster describes the first phase of a multi-disciplinary research project. It discusses how signals from both modalities, i.e. GPR and US, are obtained from a set of concrete reference specimens, how the signals are then processed to generate a visual representation of the interior, and finally how a high resolution image is obtained by image fusion to reveal details such as the location of the rebars, air voids, and the geometry of the specimen.

How to Cite:

Mehdinia, S., Schumacher, T., Wan, E. & Song, X., (2019) “Diagnostic imaging of structural concrete”, Review of Progress in Quantitative Nondestructive Evaluation .