A new model to predict the optimal mix design of self-compacting concrete considering powder properties and superplasticizer type

• Published in: Journal of materials research and technology 2022-07, Vol.19, p.3980-3993
• Main Authors: Zhang, Jingbin, Han, Guoxuan, Shen, Dejian, An, Xuehui, Mendomo Meye, Serges
• Format: Article
• Language: English
• Subjects: Optimal mix design; Powder properties; Self-compacting concrete; Specific surface area; Superplasticizer type; Zeta potential
• ISSN: 2238-7854
• DOI: 10.1016/j.jmrt.2022.06.130

This study investigated the effect of powder materials and superplasticizer type on the optimal proportion of pastes and self-compacting concrete (SCC). Nine groups of power materials containing cement, fly ash (FA), limestone powder (LP), granulated blast furnace slag (GBFS), and modified phosphogypsum (MPG) were designed. The powder materials differed in their characteristics including specific surface area, zeta potential and density. Self-compacting paste zone (SCP zone) and the optimal proportion were obtained based on the paste rheological threshold theory. Quantitative relationships between the optimal proportion and powder characteristics were obtained by the linear regression method, which can help in the optimizing process of SCC. A new powder combination was designed to validate the relationships. The optimal water‒powder ratio by volume (VW/VP) and the optimal superplasticizer dosage by mass (SP%) could be calculated considering the physical and chemical properties of the powder combination. According to the optimal mix, the search area was narrowed and the SCP zone was obtained where a good SCC was obtained, which validated the effectiveness of the powder effect model. Finally, an improved powder effect model applicable to different superplasticizer types was proposed based on a good linear relationship between the optimal VW/VP and the basic VW/VP.