OPTIMIZATION OF LOCALLY SOURCED COARSE AGGREGATES IN ANAMBRA STATE FOR CONCRETE PRODUCTION

W.C. Akugbe Anene, T.C Chukwudi Mbonu, P.C Oluwaseun Obiezue, C.E Kanayo-Chikwado, E.I Ononuju, C.J Chukwumereije

Abstract


 

In order to determine whether coarse aggregates from Ukpor, Onitsha, and Nkwelle-Ezunaka in Anambra State, Nigeria, are suitable as alternatives to traditional granite, this study examines the compressive strength behavior of concrete made with these aggregates. The goal is to promote the economical and sustainable use of regional resources in the production of structural concrete. Concrete cubes were cured for seven, fourteen, and twenty-one days after being cast using a mix ratio of 1:2:4 and a water–cement ratio of 0.6. Sieve analysis, slump, and compressive strength tests were among the laboratory experiments carried out in compliance with ASTM and BS standards. The impact of aggregate source and curing time on compressive strength was statistically assessed using Response Surface Methodology (RSM) and Two-Way Analysis of Variance (ANOVA).The aggregate source and curing period both had a substantial influence (p < 0.001), according to the ANOVA results; however, their interaction was not statistically significant (p > 0.05). Following Onitsha (18.03 N/mm²) and Nkwelle-Ezunaka (17.48 N/mm²), concrete manufactured with Ukpor aggregates achieved the highest mean compressive strength of 19.65 N/mm² at 21 days, according to Tukey's post-hoc comparison. With a high coefficient of determination (R² = 0.9242) and a strong quadratic relationship (? = 0.7167, p = 0.0028), the RSM model demonstrated that compressive strength increases with curing time. At approximately 38 days of curing and an aggregate quality index of 1.8, the optimal condition was predicted. The results show that, because of their higher strength performance, Ukpor aggregates are a dependable and readily available substitute for granite in reinforced concrete construction.

Keywords: Coarse aggregate, Curing time, Compressive strength, Two-Way ANOVA, and Response Surface Methodology (RSM).


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