ANN Model for Predicting Compressive Strength of Alkali Activated Slag ConcreteCured at Environmental Temperature

Volume 20 No 6 (2022)

Veeresh.Karikatti , M.V.Chitawadagi , Ishwaragouda S. Patil ,Sanjith J , Mahesh Kumar C L ,Kiran B M

DOI: 10.14704/nq.2022.20.6.NQ22044

Abstract

In alkali activated slag concrete, the alkaline activator technology is the most important factor. Ground Granulated Blast Furnace Slag (GGBS) is a type of slag with unique properties such as workability, strength, cost, time savings, and high construction efficiency. This research work concentrates on experimental analyses on mix design by varying different parameters such as binder ratio of 0.4, 0.5 & 0.6, percentage of superplasticizer as 1.5%, 2%, 3%,4% & 5% and percentage of extra water as 15% & 20% to get the optimum mix proportion for 100% GGBS

Keywords

Alkaline Activator; Alkali Activated Slag concrete; Binder ratio; Artificial Neural Network

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