Modelling of Concrete Performance Based on Quality Attributes of Different Fine Aggregates

Abstract

Fine aggregate has extensively been used in the construction industry as a key component in concrete production. One of the major sources of fine aggregates is river sand. The use of river sand as the primary source of fine aggregate has resulted in over-exploitation leading to diminution and environmental degradation. This has led to exploration of other sources to safeguard depletion and reduce the negative impacts on the environment. This research was conducted on a variety of river sands and other fine aggregates used in Nairobi Metropolitan to assess their suitability for use in concrete manufacture. The fine aggregates were sourced from six locations that popularly supply the Nairobi Metropolitan area; natural river sands from Mwingi (S2), Kajiado (S3) and Machakos (S5); rock sand and quarry dust (S4 and S7) from Mlolongo and Sand from Naivasha quarry (S6). An experimental approach was adopted to test the physical, chemical and mineralogical properties of the fine aggregates and the resultant concrete strength after 7, 14, 28, 56, 112, 180 and 360 days was recorded. The physical properties were established in accordance with the British Standards test methods while chemical properties were obtained using Atomic Absorption Spectrometry (AAS) and validated using X-Ray Fluoresce (XRF) method. The mineralogical properties were determined using the X-Ray diffraction (XRD) method and counter checked with the secondary data on the geological formation of the catchment areas. Concrete mix design using the different samples was done for C30/37 concrete using Department of Environment (D.O.E.) /British method. A universal testing machine (UTM) was used to determine the compressive strength of the concrete. To achieve reliability, three cubes for each sample were crushed and the mean of the values taken as the compressive strength for that particular batch. All the fine aggregates not only had different physical and chemical properties but also failed to meet permissible limits for concrete production. The target mean strength of concrete 30/37 was achieved at different ages due to the variation in properties. Mlolongo rock sand (S4), Naivasha sand (S6) and Mlolongo quarry dust (S7) took longer to achieve the strength with S7 taking 180 days. A multiple linear regression analysis was conducted with the inclusion of Physical and chemical properties on the data sets to predict the compressive strength of concrete at 7, 14, 28, 56, 112, 180 and 360 days. The model yielded satisfactory coefficient of determination and curves were comparable to ACI and BS model.