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Compressive strength and slump prediction of two blended agro waste materials concretes

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dc.contributor.author Onikeku, Oluwaseye
dc.contributor.author Shitote, Stanley M.
dc.contributor.author Mwero, John
dc.contributor.author Adedeji, Adeola. A.
dc.contributor.author Kanali, Christopher
dc.date.accessioned 2023-03-16T06:29:52Z
dc.date.available 2023-03-16T06:29:52Z
dc.date.issued 2019
dc.identifier.uri http://dx.doi.org/10.2174/1874149501913010118
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/7342
dc.description.abstract Background Agro industrial wastes such as Bamboo Leaf Ash (BLA) and Bagasse Ash (BA) need to be employed so as to replace cement in order to produce cheaper concrete, which, in turn, save the environment. Objective This research focuses on the compressive strength and slump based on Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models for forecasting of compressive strength and slump value for concrete by blending BLA and BA as partial supplementary cement materials accordingly. Methods Three-layer perceptron was constructed through R (nnet package). A sum total of eleven artificial neural networks were formulated using 214 data sets attained from 27 laboratory concrete mixtures performed. Results The neural network model forecasted the compressive strength for training, testing and validation with predicted errors of 0.802 MPa and 1.380 MPa. The model over forecasted the compressive strength averagely by 0.644 MPa and 1.905 MPa. The forecasted compressive strength changed averagely by 2.328% and 3.946%. The average difference between the predicted and experimental values was 0.588 MPa and 1.050 MPa. The coefficients of determination were 0.961 and 0.905. The MLR model predicted the slump with predictive error values of 6.634 mm and 8.374 mm. The predicted slump deviated on average by 3.633% and 8.034%. The residual error was 3.075 on 12 degrees of freedom. The multiple R ² and adjusted R ² were 0.9336 and 0.9115. The P-value was found to be 5.639e-07. Conclusion The results show that ANN and MLR are potent tools for forecasting the compressive strength and slump of concrete blending bamboo leaf ash and baggage ash. Hence, this contributes towards forecasting of the compressive strength and slump of BLA and BA blended concrete. They extends 28 days compressive strength usually found in the literature to 56 and 90 days compressive strength and there was a remarkable improvement as curing age increases. The slump of combined effect of blending BLA and BA at different percentage replacements was tested. In this study, we used BLA blended with BA to produce concrete which is an innovation. en_US
dc.language.iso en en_US
dc.subject Compressive strength en_US
dc.subject Slump prediction en_US
dc.title Compressive strength and slump prediction of two blended agro waste materials concretes en_US
dc.type Article en_US


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