Eze O. K. and Nwankwo E.*
Department of Civil Engineering, Faculty of Engineering, University of Benin, Benin City, Edo State, Nigeria
*Corresponding Author: nwankwoebuka@yahoo.co.uk
Vol. 4 No. 1 | March 2020 | Pages 152 – 159
https://doi.org/10.36263/nijest.2020.01.0172
Abstract
ABSTRACT
Aggregates, though considered inert, are the primary components that define concrete’s thermal and elastic properties. It has been shown that factors such as maximum aggregate size, grading, shape, strength, water absorption capacity of coarse aggregates affect the properties of concrete. However, improper grading of coarse aggregate could have adverse effect on the amount of cement and water requirement for concrete production. Thus, impacting on the workability, pump-ability and durability of concrete. By maintaining a slump of 50 mm, the effect of varying sizes of coarse aggregates – 10 mm, 14 mm, 20 mm, and combination of these sizes – on the mechanical properties of concrete was obtained. Aggregates, which were used in this work, were sourced from quarries located in Auchi area of Edo State and had impact values between 16% and 28%. It was observed that the higher the coarse aggregate sizes the lower the water – cement (w/c) ratio required to obtain adequate workability. Also, the compressive strength of concrete was observed to be a function of the size of the coarse aggregates used in the concrete mix. It was observed that concrete made with equal proportions of 10 mm and 14 mm coarse aggregate had lower strengths compared to concrete made with 14 mm and 20 mm aggregates. This implies that combination of large sizes of aggregates produced stronger concrete when compared to combinations of smaller sizes of aggregates. It was also observed that density of concrete increased with increasing size of aggregates.
Keywords: Aggregate, grading, regression, compressive strength
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Eze O. K. and Nwankwo E., 2020. Effect of Local Binary Mixtures of Coarse Aggregates on the Compressive Properties of Concrete. Nigerian Journal of Environmental Sciences and Technology, 4(1), pp. 152-159. https://doi.org/10.36263/nijest.2020.01.0172