Return
Autogenous shrinkage mechanism and application potential of self-compacting concrete
S
F
DOI:10.1016/j.cscm.2026.e06392.png)
Abstract
En 中文
This study systematically investigated the autogenous shrinkage of self-compacting concrete (SCC) incorporating aeolian sand (AS) at 20%, 40%, and 60% and recycled coarse aggregate (RCA) at 25%, 50%, and 75%. The evolution of internal relative humidity was monitored throughout curing, and microstructure was characterized by scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) to elucidate relationships between macroscopic shrinkage and microscopic properties. The results indicated that a low AS dosage (≤ 20%) densified the pore structure via micro-filling effects, delayed the decline of internal relative humidity, and reduced autogenous shrinkage. However, when the AS dosage exceeded 40%, the sand’s high water absorption and clay mineral content exacerbated moisture loss and pore coarsening, which led to a significant increase in autogenous shrinkage. Prewetted RCA supplied internal curing water that mitigated self-desiccation. Notably, at a 75% RCA dosage, the increased formation of ettringite (AFt) contributed to early-age pore filling and slight expansion, which helped mitigate autogenous shrinkage. Porosity and most probable pore diameter were positively correlated with autogenous shrinkage, as confirmed by microscopic analysis. The optimal mix proportion (i.e., A20R50) exhibited the lowest total porosity (15.72% at 7 d and 11.71% at 120 d), a refined pore size distribution, and the lowest autogenous shrinkage. The findings elucidate the autogenous shrinkage mechanism of SCC under the synergistic effects of aeolian sand and RCA through a macro-micro correlation analysis. The results indicate that the mixture incorporating 20% aeolian sand and 50% RCA exhibits the optimal overall performance. These results provide a basis for the utilization of aeolian sand and RCA in SCC.
Keywords:
Aeolian sand
RCA
SCC
Autogenous shrinkage mechanism
Pore structure
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.6
Papers:
6.1K
Citations:
2.0W
