Dataset on predictive compressive strength model for self-compacting concrete

Publication date: Available online 9 February 2018
Source:Data in Brief
Author(s): O.M. Ofuyatan, S.O. Edeki
The determination of compressive strength is affected by many variables such as the water cement (WC) ratio, the superplasticizer (SP), the aggregate combination, and the binder combination. In this dataset article, 7, 28, and 90-day compressive strength models are derived using statistical analysis. The response surface methodology is used toinvestigate the effect of the parameters: Varying percentages of ash, cement, WC, and SP on hardened properties-compressive strengthat 7,28 and 90 days. Thelevels of independent parameters are determinedbased on preliminary experiments. The experimental values for compressive strengthat 7, 28 and 90 days and modulus of elasticity underdifferent treatment conditions arealso discussed and presented.These dataset can effectively be used for modelling and prediction in concrete production settings.



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