A recent study published in Engineering introduces a new approach to evaluating the performance of reinforced concrete (RC) structures using self-sensing steel fiber-reinforced polymer composite bars (SFCBs). Led by Yingwu Zhou, this research could significantly enhance how we monitor and maintain the structural integrity of buildings and infrastructure.
Detail of self-sensing steel fiber-reinforced polymer composite bars. Image Credit: Zenghui Ye et al.
Structural health monitoring (SHM) is essential for ensuring the safety and longevity of structures. Traditional point sensors have limitations in assessing complex components, while distributed fiber optic sensing (DFOS) technology provides a more comprehensive solution. By integrating DFOS with SFCBs, the researchers developed a composite bar that not only reinforces structures but also enables real-time damage detection.
The study introduces a multilevel damage assessment method that evaluates RC structures in terms of safety, durability, and usability. Stiffness serves as a key metric for defining damage variables, and the researchers established relationships between SFCB strain and key performance characteristics such as moment, curvature, load, deflection, and crack width. Threshold values for different damage levels were determined based on peak loading, mid-span deflection limits, and crack width constraints.
To enhance damage detection accuracy, the team developed a modified fiber damage model that accounts for stiffness degradation over a structure’s service life. DFOS strain data is used to refine the model, improving its predictive capability. The study validated its theoretical and numerical models through three-point flexural tests on SFCB-reinforced RC beams.
Experimental results showed that increasing the reinforcement ratio lowers damage thresholds across all levels and improves a beam’s ability to manage structural stress. The proposed crack width prediction method effectively estimated crack formation before yielding, while the simplified theoretical model accurately predicted key performance parameters. The modified fiber damage model also successfully tracked the progression of structural damage.
This research marks a significant step forward in structural intelligence. The multilevel damage assessment method enables rapid evaluation of safety, serviceability, and durability using real-time SFCB strain data and material parameters. Beyond improving RC structure design, these findings could reduce maintenance costs and help prevent catastrophic failures.
The development of self-sensing SFCBs and this advanced damage assessment framework represent major progress in structural health monitoring. As the technology evolves, it is likely to play an increasingly vital role in ensuring the safety and resilience of our built environment.
Journal Reference:
Ye, Z. et. al. (2025) Performance Assessment of Reinforced Concrete Structures Using Self-Sensing Steel Fiber-Reinforced Polymer Composite Bars: Theory and Test Validation. Engineering. doi.org/10.1016/j.eng.2024.11.022