From severe corrosion to structural recovery: A DIC-validated CFRP strategy for restoring bearing capacity of RC beams

Corrosion-induced degradation of steel reinforcement in concrete infrastructure poses critical safety and sustainability challenges, accelerating structural failures and generating billions in global reconstruction waste annually. While carbon fibre-reinforced polymer (CFRP) composites are widely used for rehabilitation, existing studies lack systematic data on their efficacy for high-strength reinforcement (A500C grade) under severe corrosion. Furthermore, traditional strain-monitoring methods lack spatial resolution for real-time damage assessment, hindering adaptive repair strategies. This study addresses these gaps by integrating CFRP strengthening with a combined non-contact monitoring framework - digital image correlation (DIC) and non-contact strain gauges - to enable cross-validated, high-resolution assessment of rehabilitated reinforced concrete (RC) beams. Key novelty centres on the integrated dual-functional application of artificial markers for synchronized cross-validation of multi-material deformations at the CFRP-concrete interface and mitigation of potential optical artifacts during high-resolution DIC monitoring. Twelve full-scale beams with Ø20 A500C reinforcement (damaged to 12–18 mm diameters) were retrofitted with Sika Carbodur S512 CFRP and tested under four-point bending. Results demonstrated CFRP restored 103–108% of the original bearing capacity for moderate corrosion (20–36% area loss) and 79–95% for severe cases (50–64% loss), reducing deflections by 14–32%. The non-contact monitoring system achieved < 7% inter-method deviation, confirming its reliability for infrastructure diagnostics. Crucially, CFRP retrofitting restored structural performance through localized rehabilitation rather than replacement, highlighting its potential for resource-efficient infrastructure maintenance. This work advances dual CFRP and non-contact sensing strategy that enhances structural resilience while enabling scalable, data-driven maintenance - a critical step toward resource-efficient infrastructure systems.