A comparative study on the compressive strength prediction models for High Performance Concrete containing nano silica and copper slag using regression analysis and Artificial Neural Networks

2016 ◽  
Vol 114 ◽  
pp. 528-535 ◽  
Author(s):  
S. Chithra ◽  
S.R.R. Senthil Kumar ◽  
K. Chinnaraju ◽  
F. Alfin Ashmita
2017 ◽  
Vol 8 (7) ◽  
pp. 67-73
Author(s):  
Acuna-Pinaud L. ◽  
Espinoza-Haro P. ◽  
Moromi-Nakata I. ◽  
Torre-Carrillo A. ◽  
Garcia-Fernandez F.

2021 ◽  
Vol 72 (1) ◽  
pp. 76-83
Author(s):  
Lam Le Hong ◽  
Lam Dao Duy ◽  
Huu Pham Duy

The demand for High Performance Concrete (HPC) is steadily increasing with massive developments. Conventionally, it is possible to use industrial products such as silica fume (SF), fly ash, as supplementary cementitious materials (SCM), to enhance the attributes of HPC. In recent years, nano-silica (NS) is used as an additive in added mainly to fill up the deviation arises with the addition of SF for HPC. This study aims to optimize the proportion of NS (produced in Vietnam) in the mixture used for fabricating 70 MPa high-performance concrete. SiO2 powder with particle size from 10 to 15 nm were used for mixing. A series of compressive strength test of HPC with nano-SiO2 varied from 0 to 2.8 percent of total of all binders (0%, 1.2%, 2%, 2.8%), and the fixed percentage of silica fume at 8% were proposed. Results show compressive strength increases with the increase of nano-SiO2, but this increase stops after reaching 2%. And at day 28 of the curing period, only concrete mixture containing of 8% silica fume and 2% nano-SiO2, had the highest compressive strength.


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