Optimized Prediction Model for the Granulation Effectiveness of Sintering Mixtures

Abstract

The optimization model is proposed on the basis of the Litster's granulation model for the prediction of the granulation effectiveness of the sinter feed. Formulas are proposed to calculate parameters for the adhesive layer of the granules, including its mass‐averaged particle size and the water saturation. Based on small‐scale granulation and sieving experiments, a functional correlation is established that relates the granules properties to the distribution coefficient curve, confirming the validity of the model. The prediction of model is discussed with adhesive layer boundary conditions of −0.25, −0.5, and −1.0 mm, and when the boundary is −0.5 mm, the relative error is minimal. The optimization of the distribution coefficient curve based on the binomial interpolation method can make the model achieve a hit rate of 92.9%. Based on this model, the granulation effectiveness of the mixtures could be evaluated.