Original scientific paper

https://doi.org/10.17559/TV-20200604232451

Estimation of Compressive Strength of Waste Andesite Powder-Added Concrete Using an Artifical Neural Network

Hakan Ceylan* ; Isparta University of Applied Sciences, Technical Sciences Vocational School, Construction Department, 32260 Çünür/Isparta,Turkey
Metin Davraz ; Isparta University of Applied Sciences, Technical Sciences Vocational School, Construction Department, 32260 Çünür/Isparta,Turkey
Mustafa Sivri ; Isparta University of Applied Sciences, Technical Sciences Vocational School, Construction Department, 32260 Çünür/Isparta,Turkey

Abstract

In this study, the effects of using andesite powder wastes-produced from natural stone factories as mineral additives in concrete manufacturing-on the compressive strength of concrete were modeled using an Artificial Neural Network (ANN). To achieve this, cement mixtures were produced by using waste andesite powder (WAP) mixture at ratios of 0% (control), 10%, 15% and 20%. The effects of curing time were investigated by preparing specimens at 28 and 90 days. The training set was formed by using cement and the specified WAP mixtures and curing time parameters. It was observed that the results obtained from the training ANNs were consistent with the experimental data.

Keywords

artificial neural network; concrete compressive strength; waste andesite powder

Hrčak ID:

260786

URI

https://hrcak.srce.hr/260786

Publication date:

22.7.2021.

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