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Multi-Objective Optimization of Nano-Silica Modified Cement-Based Materials Mixed With Supplementary Cementitious Materials Based on Response Surface Method

This paper investigates the effect of supplementary cementitious materials (SCMs) on the fresh and mechanical properties of nano-silica modified cement-based materials (NSMCBM) based on the response surface method (RSM). Fly ash (FA), ground granulated blast-furnace slag (GGBFS), and silica fume (SF...

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Bibliographic Details
Published in:Frontiers in materials 2021-10, Vol.8
Main Authors: Zhang, Xiuzhi, Lin, Liming, Bi, Mengdi, Sun, Hailong, Chen, Heng, Li, Qinfei, Mu, Ru
Format: Article
Language:English
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Summary:This paper investigates the effect of supplementary cementitious materials (SCMs) on the fresh and mechanical properties of nano-silica modified cement-based materials (NSMCBM) based on the response surface method (RSM). Fly ash (FA), ground granulated blast-furnace slag (GGBFS), and silica fume (SF) were selected and the Box-Behnken design (BBD) method was used to design mix proportion. Besides, the quadratic term model was used to describe the relationship between independent variables and responses including fluidity, yield stress, plastic viscosity, thixotropy, and 3, 7, 28, and 56 d compressive strength. Based on the quadratic term model, the response surface of each response was drawn to understand the influence of SCMs. Results showed that FA had significant effect on fluidity and thixotropy while three kinds of SCMs had extremely significant effect on plastic viscosity. Response surface plot showed that NS could increase the plastic viscosity of NSMCBM to 1.445 Pa•s (M16). However, the addition of FA and GGBFS decreased the plastic viscosity to 0.9 Pa•s, which was comparable with the reference sample (M17). Such value was 37.7% lower than that of M16. Meanwhile, NS complemented the reduction of compressive strength caused by SCMs. Thus, the synergy effect of SCMs and NS could improve both fresh and mechanical properties. At last, multi-objective optimization was utilized to optimize the proportion of SCMs considering the interaction between SCMs to achieve desirable parameters.
ISSN:2296-8016
2296-8016
DOI:10.3389/fmats.2021.712551