Coupling digital image correlation with dynamics metrics for fracture assessment in lightly reinforced concrete

Reliable assessment of damage in lightly reinforced concrete structures requires monitoring approaches that capture both local fracture behaviour and its impact on global structural performance (e.g., natural frequencies). Conventional vibration-based Structural Health Monitoring (SHM) methods are effective for detecting stiffness degradation but offer limited insight into crack mechanics. In contrast, vision-based techniques such as Digital Image Correlation (DIC) provide high-resolution measurements of crack initiation and propagation, yet do not directly quantify the associated loss in structural capacity. This study presents an integrated monitoring framework that combines full-field DIC with vibration-based frequency measurements to investigate their relationship. Local crack initiation, propagation, and crack opening displacement are quantified using DIC and linked to global stiffness degradation through shifts in natural frequency obtained from dynamic testing via hammer impact excitation. An integrated fracture-based model is further employed to interpret how observed crack geometry influences structural stiffness. Results demonstrate that increasing crack opening leads to measurable reductions in natural frequency, with the most pronounced changes occurring during the changeable crack rotation phase prior to failure. By experimentally linking local fracture processes to global modal behaviour, this study provides a stronger physical basis for interpreting dynamic response data, particularly in vehicle-assisted SHM applications. The proposed approach enables more reliable, mechanism-informed drive-by damage detection in reinforced concrete structures.