Prediction of Compressive Strength of Normal Concrete with Partial Replacement of Sand by Waste Glass Using Fuzzy Model - Meggabi , Tigist; K. Hareru, Werku; Mulugeta, Demboba (International Journal of Sustainable Construction Engineering and Technology, 2022)
The objective of the study is a partial replacement of natural fine aggregate with crushed waste glass for M 30 concrete production. To determine the compressive strength of such concrete by using 10% 15%, 20%, and 25% of partial replacement including control samples using 0.45, 0.47, and 0.50 water-cement ratios. Quality tests, slump, compressive strength, density, permeability, and Ultrasonic pulse velocity test are performed; the cube of concrete mix design test follows the American Concrete Institution (ACI) guideline. And to develop a predictive model for the 7days and 28days compressive strength using a fuzzy model. The result has shown that the physical properties, of course, fine aggregate and crushed waste glass satisfy the standard specification, when the replacement percent increases, the compressive strength and ultrasonic pulse velocity of concrete are increased up to 15% of the replacement level Due to the angular nature of waste glass particles contributes more effective cement past. Thus reduction of microscopic voids in concrete. The study also found the depth of penetration for concrete indicates the increased replacement percent increase in the depth of penetration increase due to increase microscopic void space. It was concluded that the natural sand is effectively partially replaced by crushed waste glass, maximum compressive strength was achieved at 15% of the replacement level. The result showed that quite satisfactory in predicting the Compressive strength for 7 and 28 days strength of the M-30 concrete mix using the fuzzy logic technique with a coefficient of correlation, R2 of 0.87 and 0.85 respectively for the training and validation set. The significance of the study is that the compressive strength of concrete made with partial replacement of natural fine aggregate by the crushed waste glass can be predicted by using the predictive model developed.