A virtual lab for damage identification in concrete using coda waves

Identifying and preventing damage in concrete structures at an early stage of material degradation can significantly reduce costs associated with the maintenance and repair of concrete infrastructure. Weak material degradation, such as load-induced initiation and propagation of microcracks, is a precursor of localized damage (macrocracking) in concrete structures and can be detected by means of multiple-scattered late arriving ultrasonic signals, also called coda waves. In order to reliably identify and quantify damage initiation and propagation using coda waves, a systematic tool that translates ultrasonic coda signals into the state of damage is required. To this end, we systematically investigate the effect of material degradation on the coda variations at the specimen level using a combination of multiscale computational modeling, forward wave propagation simulations and feature extraction. At the specimen scale, damage initiation and propagation in realistic mesoscale concrete models is simulated using a virtual lab and a novel reduced order multiscale method. The concrete specimens subjected to specific level of damage in the virtual lab are subsequently analyzed by wave propagation simulations. Finally, a strategy for using specimen scale information for predicting the state of damage at the structural scale will be presented.