An Emphasis of Geopolymer Concrete with Single Activator and Conventional Concrete with Recycled Aggregate and Data Analyzing using Artificial Neural Network. Issue 1 (December 2020)

• Record Type: Journal Article
• Authors: Rao, G. Mallikarjuna; Kumar, K. Satheesh; Poloju, Kiran Kumar; Srinivasu, Kota
• Is Part Of: IOP conference series. Volume 998:Issue 1(2020)
• Publication Date: 2020-12
• Subjects: Geopolymer concrete -- Fly Ash -- GGBS -- Compressive Strength -- Geo-activator and Artificial Neural Network; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/998/1/012060
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: The emphasis of concrete in the advancement of construction industry is essential. Due to the rapid increase in the development of infrastructure, there is a considerable demand for the construction materials. The construction materials drained gradually due to continue use in construction and there is a degree for the advancement of these development materials. Therefore, in this context, a rapid increase in the price of conventional construction materials and various governments have put restrictions on fine aggregates. In this circumstance, the investigation attempted to determine the appropriateness of the substitute materials in concrete development because these materials are eas ily available at very low cost as compared to conventional fine and coarse aggregates. The effect of recycled aggregates on the strength of conventional concrete and Geo-polymer concrete was studied. The natural aggregates are replaced by the crushed aggregates of intervals of 10%, 20%, 30%, 40 %, and 50% in both geo-polymer and conventional concrete. The different strengths of 20MPa, 40MPa, and 60MPa werestudied in this research work. The conventional concrete cubes were cured in normal water and geopolymer concrete cubes cured in ambient room temperature. The coarse aggregates used were of size 20mm and 10mm sieved and the recycled aggregates contains a cement mortar attached to it. The outcomes show that a slight decline in the strength of conventional concrete and high strength found with 30% substitution of coarse aggregate and eventually the prediction of data was analyzed using Artificial Neural Network