Strength Prediction of Self-Consolidating Concrete Containing Steel Fibre with Different Fibre Aspect Ratio

The present study presents the effects of steel fibre aspect ratio on the fresh and strength properties of self-consolidating concrete (SCC). Steel fibre having three different aspect ratios (50, 65 and 80) with the inclusion rate of 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% was considered, and the effects o...

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Bibliographic Details
Published in:Journal of nanomaterials 2022, Vol.2022 (1)
Main Authors: Ganapathy, Ganesh Prabhu, Keshav, Lakshmi, Ravindiran, Gokulan, Razack, Nasar Ali
Format: Article
Language:English
Subjects:
Aggregates
Aspect ratio
Cement
Compressive strength
Datasets
Fiber reinforced materials
Mechanical properties
Nanomaterials
Regression models
Steel fibers
Sulfur
Tensile strength
Variance analysis
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Summary:The present study presents the effects of steel fibre aspect ratio on the fresh and strength properties of self-consolidating concrete (SCC). Steel fibre having three different aspect ratios (50, 65 and 80) with the inclusion rate of 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% was considered, and the effects of aspect ratio and the fibre inclusion rate on the fresh and strength properties of SCC were investigated. Central composite design (CCD) of RSM modeling was considered to propose a regression model to predict the 28-day compressive strength of SCC and steel fibre-reinforced SCC (SFSCC) incorporating different supplementary cementitious materials (SCMs). 94 data sets retrieved from various literatures and the experimental data set (SCC and SFSCC) of this present study have been used to develop the regression model. Further, cement content, powder content, water to binder ratio, and coarse aggregate to fine aggregate ratio were considered as basic variables to propose the model, and their influence on the strength properties of SCC was prioritized using analysis of variance (ANOVA) and Pareto chart. The findings of regression model have been compared with the results of 94 data sets, and the experimental data set of this present study and the comparisons confirm that the proposed regression model are very realistic and precise to predict the compressive strength of SCC and SFSCC with different aspect ratio.
ISSN:1687-4110
1687-4129
DOI:10.1155/2022/7604383