A comprehensive study on the impact of nano-silica and ground granulated blast furnace slag on high strength concrete characteristics: RSM modeling and optimization

Structures(2024)

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摘要
In light of the global climate change crisis, the imperative to mitigate carbon emission sources is growing in significance. Cement is a notable contributor to greenhouse gas emissions (GHG) due to its industrial manufacturing process, which results in the release of 0.9 kg of GHG per kilogram produced. Therefore, to reduce GHG by using Ground granulated blast furnace slag (GGBFS) as a substitution for cement in high strength concrete (HSC). However, the use of nano silica (NS) as nanomaterial in HSC to improve the mechanical and durability characteristics of HSC. Besides, Response Surface Methodology (RSM) was adopted to assess the workability test (slump), compressive strength (CS), splitting tensile strength (STS), flexural strength (FS), modulus of elasticity and water absorption (WA) of HSC blended with 5–20% of GGBFS with an 5% increment and 1–4% of NS with an 1% increment as nanomaterial. CS outcomes were obtained at 7 days, 28 days, 90 days while STS, FS, MOE, and WA assessments were observed at 28 days. From experimental outcomes, Slump and WA were found to be reduced with the addition of GGBFS and NS rises in HSC. Moreover, the highest CS, STS, FS, and MOE were observed by 91.78 MPa, 5.25 MPa, 5.05 MPa, 46.06 GPa at 10% of GGBFS and 3% of NS together in HSC at 28 days respectively. Additionally, the embodied carbon was found to be decreasing with the addition of GGBFS and NS increases in HSC. Furthermore, response prediction models were developed and verified using ANOVA with a significance level of 95%. The R-Square values for the models ranged from 93 to 99.50%. It has been concluded that the use of 10% of GGBFS as replacement for cement and 3% of NS together in HSC is providing optimum outcomes therefore, it is recommended for construction industry.
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关键词
High strength concrete,Nanao-Silica,GGBFS,Mechanical Properties,RSM modelling and Optimizations
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