Compressive Strength Prediction of Concrete Containing Used Cooking Oil Using Ann
Dumpala Suneel Kumar1, B. Ajitha2
1Dumpala Suneel Kumar, PG Scholar, Department of Civil Engineering, JNTUA College of Engineering, Ananthapuramu, India.
2B. Ajitha, Associate Professor, Department of Civil Engineering, JNTUA College of Engineering, Ananthapuramu, India.
Manuscript received on 01 September 2023 | Revised Manuscript received on 12 September 2023 | Manuscript Accepted on 15 October 2023 | Manuscript published on 30 October 2023 | PP: 5-11 | Volume-12 Issue-11, October 2023 | Retrieval Number: 100.1/ijitee.K972710121123 | DOI: 10.35940/ijitee.K9727.10121123
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: To mitigate the detrimental impacts of disposing of used cooking oil (UCO) into the environment, which adversely affects marine life, human health, and agricultural outputs, this research proposes a novel approach incorporating this waste material into the concrete industry as a chemical admixture. To investigate this, an initial experimental program is designed to examine how used cooking oil affects various fresh properties and compressive strength at 3, 7, and 28 days of age of concrete. Concrete batches of M40 grade are meticulously prepared with varying proportions (ranging from 0% to 2%) of used cooking oil. To predict strength characteristics, an Artificial Neural Network (ANN) is employed, consisting of three layers. The input layer comprising quantities of cement, coarse aggregate, fine aggregate, water content, super plasticizer, and the percentage of the chemical admixture (UCO), hidden layer for predicting the network system and the output layer providing the concrete’s compressive strength.
Keywords: Compressive Strength, Used Cooking Oil, Artificial Neural Networks (ANN).
Scope of the Article: Artificial Neural Networks