THE APPLICATION OF SCT FOR CONCRETE MIX PROPORTIONS PREDICTION

This study helps to achieve concrete mix proportions by using methods of soft computing, including approaches and equation-driven artificial neural networks.Traditional concrete mix design methods consumes more time and it involves various trails and design parameters, this may leads new concrete mix designers struggle to choose the water cement ratio and super plasticizer amount.These challenges result in the inability to attain optimal concrete mix proportions.In this case study manually developed optimal concrete mix proportions of different parameters are used to generate coefficeints to predict concrete mix proportions using Gauss elimination techniques with minimal human effort. Similarly, artificial neural network (ANN) methodology is employed to create optimal weighted matrices. Thus, fresh civil engineers can predict concrete mix proportions using coefficients or weighted matrices. Hence, rather than conduction more number of samples of different mix proportions to be tested, utilizing soft computing techniques prediction of enables the optimal concrete mix proportions.