Numerical modeling of rebar-matrix bond behaviors of nano-SiO2 and PVA fiber reinforced geopolymer composites

Geopolymer composites represent promising alternatives to ordinary Portland cement materials, whose properties can be improved by mixing polyvinyl alcohol (PVA) fibers and nano-SiO2 (NS). In this study, bond tests and numerical modeling were conducted to investigate the effects of PVA fibers and NS on the rebar-matrix bond behaviors of geopolymer composites. A modified mathematical model derived from the Harajli model and a finite element numerical model based on the Mori-Tanaka homogenization and the Tsai-Hill failure criterion were proposed. The prediction results of the numerical and modified mathematical models were compared to those of an existing model and the experiment. The results showed that PVA fibers and NS can effectively improve the bond strength and toughness of the geopolymer composites and that the bond behavior is optimized when the PVA fiber content is within 0.6%-0.8% and the NS content is 1.5%-2%. The numerical and modified mathematical models can effectively reflect the rebar-matrix bond behaviors of the NS and PVA fiber reinforced geopolymer composites. The proposed numerical model exhibits high prediction accuracy, providing an effective guide and reference for predicting the bond behaviors of rebar and geopolymer composites.

Automated summary

The effects of PVA fibers and NS on the rebar-matrix bond behaviors of geopolymer composites were investigated through experiments and numerical modeling. It was found that the addition of PVA fibers and NS within certain ranges can effectively improve the bond strength and toughness of the composites. The proposed numerical model exhibited high prediction accuracy, serving as an effective guide for predicting the bond behaviors of rebar and geopolymer composites.