Optimization Of Rheological And Mechanical Properties Of Concrete Made With Bambara Nut Shell Ash And Quarry Dust Using Artificial Neural Network (ANN):- Adenaike, Oluwaseun A

ABSTRACT

The environmental impact of disposal of agro-industrial waste materials is ofgreat concern. Bambara nut shell and quarry dust are two ofsuch products. Utilization ofthese discarded materials as concrete constituents reduces their detrimental effects on the environment, enhances the reduction of carbon dioxide emissions emanating from cement production and the depletion of non-renewable natural resources like sand. This study employed Artificial Neural Network (ANN) to investigate the compressive and flexural strength of concrete containing bambara nut shell ash and quarry dust as partial replacement of cement and sand respectively. This replacement was done at 0 - 50% using 2.5% interval with 1:2:4 mix proportion for 14, 21, 28 and 56 curing days. The optimum values were obtained at 22.5% replacement and mix ratio of 0.775: 0.225: 1.55: 0.45: 4. The optimum values of compressive strength recorded from experimental works at 14, 21, 28 and 56 curing age were 24.29 N/mm2, 24.78 N/mm2, 25.14 N/mm2, and 27.36 N/mm2 respectively. Optimum values for the flexural strength were 8.89 N/mm2, 9.32 N/mm2, 9.41 N/mm2 and 13.21 N/mm2. The ANN model had 6 neurons, 10 neurons, and 2 neuions in the input, hidden and output layers respectively. The modelled results were very close to the experimental outcome. The model’s adequacy was further tested using the Student’s T test. The calculated T-value (-2.74 and -3.45) for the compressive and flexural strength of BNSAQD concrete were less than that from the T-table (2.09) at 95% confidence level, certifying that the network predictions are suitable and reliable for prediction and optimization of BNSA-QD concrete.