RETRACTED: Prediction of the effects of nanoparticles on early-age compressive strength of ash-based geopolymers by fuzzy logic

In the present work, compressive strength of ash-based geopolymers with different mixtures of % rice husk ash, fly ash, nano alumina and nano silica has been predicted by fuzzy logic. The alkali activating was done by a mixture of sodium hydroxide and sodium silicate solution. It was found that oven curing temperature and sodium hydroxide concentration together with SiO2 nanoparticles has the main effects on compressive strength of the specimens. The fuzzy logic model was constructed by 12 input parameters including the water curing time, the rice husk ash content, the fly ash content, the water glass content, sodium hydroxide content, the water content, the aggregate content, SiO2 nanoparticles content, Al2O3 nanoparticles content, oven curing temperature, oven curing time and test trial number. The value for the output layer was the compressive strength. According to the input parameters in fuzzy model, the input data were trained, validated and tested. The results indicate that fuzzy model is a powerful tool for predicting the effect of nanoparticles on compressive strength of the geopolymers in the considered range.