Dynamic-Based Corrosion Assessment and Smart Monitoring Strategies for Reinforced Concrete Structures

Corrosion of reinforcing steel in reinforced concrete structures represents one of the most critical challenges affecting the durability, safety, and service life of urban infrastructure. This process not only reduces the load-carrying capacity of structural elements but also alters their dynamic behavior and increases maintenance and rehabilitation costs. This review paper synthesizes findings from recent studies to examine vibration-based approaches for corrosion assessment, focusing on dynamic parameters such as natural frequencies, damping ratios, mode shapes, and modal flexibility. The reviewed literature indicates that variations in structural dynamic properties-particularly modal damping and natural frequencies―can serve as sensitive indicators for detecting and quantifying corrosion-induced damage. Corrosion-related cross-sectional loss of reinforcing bars and cracking in the surrounding concrete lead to stiffness degradation, which results in measurable shifts in modal characteristics that can be utilized for structural health monitoring. In addition, the paper reviews emerging mitigation and monitoring strategies, including artificial intelligence (AI)-assisted structural health monitoring systems, smart protective coatings, corrosion-resistant and sustainable construction materials, and intelligent monitoring technologies for urban infrastructure networks. Based on the synthesized knowledge, a comprehensive conceptual framework is proposed that integrates dynamic-based monitoring methods with advanced materials and data-driven technologies. The proposed framework provides guidance for more effective corrosion detection, monitoring, and durability enhancement of reinforced concrete structures in urban environments.

کلیدواژه ها:

Reinforcement corrosion ، structural health monitoring (SHM) ، vibration-based damage detection ، dynamic parameters ، artificial intelligence in infrastructure monitoring