Wensheng Wang , Baoyin Liu , Guojin Tan , Hanbing Liu , Yubo Jiao , Dongye Lv , Hua Wang , Da Shi , Shanping Zhang
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引用次数: 0
Abstract
Bond performance is an important guarantee for the structural integrity and long-term service performance of reinforced concrete, which is seriously threatened by the reinforcing bar corrosion in corrosive environments. This study employs an experimental framework combining macroscopic pull-out test, microscopic scanning electron microscopy (SEM), microscopic X-ray photoelectron spectroscopy (XPS), and acoustic emission (AE) monitoring to investigate bond behavior evolution in corroded reinforced concrete with HRB400 ribbed reinforcing bar. Pull-out tests were conducted on specimens with varying corrosion extents (CE: 0 %, 3 %, 5 %, 8 %), complemented by SEM-XPS to elucidate spatial micro-mechanisms. AE technology was employed to monitor real-time damage progression, with Mel-frequency cepstral coefficients (MFCC) enabling precise segmentation of bond damage stages. Based on MFCC segmentation, the bond failure stages and modes are quantitatively classified by leveraging RA-AF values and Gaussian mixture model (GMM) clustering. Results revealed a 24.2 % decline in bond strength at CE = 8 % compared to uncorroded specimens, accompanied by a transition in failure modes from splitting to hybrid splitting-pull-out debonding. Low corrosion (≤3 %) enhances initial friction with ductile failure via rust compaction, while higher corrosion (≥5 %) causes abrupt brittle failure due to corrosion-induced cracking that degrades bond integrity. Microscopic characterization analysis showed that corrosion products (e.g., porous FeO and brittle Fe(OH)3) reduced mechanical interlock, while microcrack propagation and stress redistribution accelerated interfacial debonding. The bond-slip process was quantitatively divided into four stages using MFCC analysis, in which higher CE values led to the disappearance of some stages. GMM clustering of RA-AF values successfully differentiated shear-dominated (low CE) and tensile-shear mixed (high CE) failure modes. Based on Pearson correlation coefficient, an established predictive model for bond behavior demonstrated high accuracy (R2 > 0.9) in predicting bond strength and slip. This study bridges multi-scale mechanisms, providing some references for durability assessment and maintenance strategies of corrosion-affected reinforced concrete infrastructure.
期刊介绍:
The Journal of Materials Research and Technology is a publication of ABM - Brazilian Metallurgical, Materials and Mining Association - and publishes four issues per year also with a free version online (www.jmrt.com.br). The journal provides an international medium for the publication of theoretical and experimental studies related to Metallurgy, Materials and Minerals research and technology. Appropriate submissions to the Journal of Materials Research and Technology should include scientific and/or engineering factors which affect processes and products in the Metallurgy, Materials and Mining areas.