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

Autor:	Mustafa Sivri, Hakan Ceylan, Metin Davraz
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Materials science Compressive strength Artificial neural network artificial neural network concrete compressive strength waste andesite powder Andesite General Engineering Composite material TA1-2040 Engineering (General). Civil engineering (General)
Zdroj:	Tehnički vjesnik Volume 28 Issue 4 Tehnički Vjesnik, Vol 28, Iss 4, Pp 1182-1186 (2021)
ISSN:	1848-6339 1330-3651
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e4bbef49b2903110fdd967218efa42e https://hrcak.srce.hr/260786 Zobrazit plný text záznamu