Abstract
Compared to conventional concrete self-consolidating concrete (SCC) has a higher cost due to the large content of cement, use of mineral fillers, and use of various chemical admixtures, resulting in relatively high material cost. The proper selection of material and mixture proportioning can enable reduction in cement and admixture contents, leading to savings in cost. This study investigates the potential of optimizing fresh properties and 28-day compressive strength of SCC incorporating fly ash (FA), silica fume (SF), and limestone powder (LP) as part of cement by mass in total powder content. The input parameters of mixtures were total powder content (P), percentage of FA, percentage of SF, percentage of LP, water to powder ratio (W/P), and percentage of superplasticizer (SP) whereas slump flow, L-box (H2/H1), segregation index, and 28-day compressive strength were the desirable responses. A total of ninety concrete mixes were designed using central composite design (CCD) concept and checked experimentally using artificial neural network (ANN) in MATLAB. Analysis of variance test (ANOVA) used to establish the mathematical models. Results indicated that fresh characteristics of SCC enhance with the increase in FA percentage while the 28-day strength decreases. Slump flow diameter and L-box (H2/H1) ratio decrease with the increase in SF percentage. Nevertheless, the increase in silica fume improves the resistance of SCC to segregation and increases the 28-day strength. Using limestone powder as a replacement of cement content resulting in negative impact on L-box (H2/H1) ratio and 28-day compressive strength while the resistance to segregation enhances. High relations between the responses and the constituent materials of SCC can be developed using response surface methodology (RSM) and the optimum values of variables can be estimated to achieve the desirable properties of responses.
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