Synthesis of Computational Mesoscale Modeling of Cementitious Materials and Coda Wave Based Damage Identification

High costs for repair of concrete and reinforced structures can be prevented if damage at an early stage of degradation is detected and precautionary measures are applied. The multiple-scattered late arriving signals (so-called coda waves) contain rich information that can be used to detect weak changes in complex heterogeneous materials such as concrete. When subjected to external loads, microcracks in concrete initiate around aggregates and evolve until crack-coalescence and complete failure. In this contribution, a virtual testing environment using a synthesis of the mesoscale simulation of damage in concrete, wave propagation and deep learning is presented.