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Article . 2023
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Compressive Strength Prediction of Concrete Containing Used Cooking Oil Using Ann

Authors: Dumpala Suneel Kumar; B. Ajitha;

Compressive Strength Prediction of Concrete Containing Used Cooking Oil Using Ann

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)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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