This study introduces a novel approach that integrates Acoustic Emission monitoring with fractal analysis to assess and predict damage progression in FRP-strengthened reinforced concrete beams subjected to corrosion-induced deterioration. By combining AE signals with fractal measures, specifically the correlation dimension, the research provides an effective tool for tracking internal damage evolution and offering early-warning indicators for structural health. The developed damage model identifies three distinct stages of damage: initial damage, damage evolution, and sustained growth. The study reveals that corrosion accelerates both the accumulation and rate of damage, with AE ring counts significantly increasing in moderately to severely corroded beams, indicating heightened crack activity and reduced structural capacity. The correlation dimension shows a strong relationship with the degree of damage, with higher values corresponding to more disordered internal damage. The correlation dimension evolves from an initial increase to a decrease as damage progresses, marking the transition from early to advanced degradation. These findings highlight that corrosion not only accelerates damage but also lowers the detection threshold for significant structural damage.

Carbon fiber reinforced polymer (CFRP) has emerged as an effective material for strengthening reinforced concrete (RC) structures due to its high tensile strength, corrosion resistance, and ease of installation. However, in square or rectangular RC columns, stress concentrations at corners hinder the development of uniform confinement, thereby reducing strengthening efficiency. This study presents a comprehensive experimental and theoretical investigation into the performance of CFRP-confined RC square columns with varying anchor configurations. Six full-scale column specimens were tested under monotonic axial compression, each externally wrapped with one layer of CFRP sheet and installed with zero to four CFRP anchors. All columns were chamfered with a 30 mm radius to mitigate corner stress concentrations. The experimental results demonstrated that CFRP anchors significantly enhanced load-bearing capacity and ductility, improved lateral confinement, and modified the failure mechanisms. The specimen with three anchors exhibited optimal performance, with a 51.5 % increase in peak load (from 879.9 kN to 1333.2 kN) and a 29.9 % improvement in ductility index compared to the unconfined control. The failure mode transitioned from brittle global instability to ductile localized damage, accompanied by more uniform hoop strain distribution. However, excessive anchoring introduced stress interference and local cracking, leading to performance degradation. To characterize the mechanical response, a modified stress–strain model was developed, incorporating a reduction factor to account for confinement weakening caused by anchor installation. The model exhibited strong agreement with experimental data (R² > 87 %) in predicting both peak and ultimate stresses. This study provides valuable insights into the mechanical enhancement mechanisms of CFRP anchoring systems and offers a rational design basis for strengthening non-circular RC columns in structural rehabilitation.

This study presents a damage pattern recognition approach for corroded steel beams strengthened by CFRP anchorage system based on acoustic emission clustering analysis. The proposed method includes four steps: acoustic emission signal acquisition, feature extraction, clustering analysis, and damage pattern recognition. Four corroded beams with different corrosion levels and strengthening schemes were tested under four-point bending loading. The acoustic emission signals were collected during the loading process and analyzed using Gaussian mixture model clustering method. The results showed that the collected AE data were analyzed using clustering analysis, successfully distinguishing the distinct damage patterns associated with each mode. The AE signals exhibited distinct characteristics for different damage modes: concrete matrix damage had high-frequency and low-energy characteristics, CFRP-matrix debonding showed intermediate values for all parameters, and CFRP tearing had longer durations, lower peak frequencies, and high-energy characteristics. Besides, the study identified three stages of the damage process: an initial stage with fewer low-intensity AE signals, a damage development stage characterized by an increase in concrete-matrix damage and CFRP – matrix debonding signals, and a continuous damage growth stage with significant AE signals associated with three damage modes. Furthermore, the degree of corrosion significantly influenced the cumulative AE energy of damage modes. Lower degrees of corrosion led to higher cumulative energy from concrete matrix damage and CFRP-matrix debonding. These findings provide valuable insights for understanding the damage evolution and failure mechanisms of CFRP-strengthened corroded beams. The use of AE techniques for damage pattern recognition can enhance the evaluation and design of CFRP anchorage systems, leading to more effective rehabilitation strategies for corroded structures.