Self compacting concrete (SCC) is a highly flowable type of concrete that spreads into form without the need of mechanical vibration. This paper presents a comparative study between two methodologies which have been applied on two different data sets of SCC mixtures, which were gathered from the literature, using artificial neural network (ANN). The two methodologies aim to get the best prediction accuracy for the SCC ingredients using the 28-day compressive strength and slump flow diameters as inputs of the ANN. In the first methodology, the ANN model is constructed as a multi input â multi output neural network with the six ingredients as outputs. In the second methodology, the ANN model is constructed as a multi input â single output neural network where the six ingredient outputs are predicted separately from six different neural networks of multi input â single output type. Also, the influence of the mixes homogeneity on the prediction accuracy is investigated through the second data set. The results demonstrate the superiority of the second methodology in terms of accuracy of the predicted outputs. Moreover, the uniformity of the training data assures the accuracy of the predicted ingredients. Keywords: Self compacting concrete (SCC), Artificial neural network (ANN), Concrete mix design, Concrete compressive strength, Slump flo

This research investigates the means to improve the compressive strength of mortar mixtures through using novel mixtures. These mixtures include magnetic water (MW) and fly ash (FA). MW was obtained by circulating tap water (TW) through a magnetic field. The magnetization duration was represented by the number of cycles, the content of FA was replaced with cement, and the super plasticizer percentage (SP) and the curing age were used and evaluated experimentally for producing the mortar mixtures. Mortar flow, crushing compressive strength, and ultrasonic pulse velocity (UPV) tests were applied to evaluate the performances of mixing characteristics. The results demonstrate that the MW-treated mortar mixtures show higher compression strength results than those prepared by TW. The compressive strength was increased up to 60% with 150 cycles, a dose of 0.5% of SP and no FA content at the age of 56 days. The dose of SP can be cut down by a maximum of 40% to 50% in cementitious mortar. the workability was enhanced by a percentage of 70%.