Importance of textural information in mathematical modelling of iron ore fines sintering performance. Issue 2 (3rd April 2018) - Donskoi, E.; Manuel, J. R.; Lu, L.; Holmes, R. J.; Poliakov, A.; Raynlyn, T. D.
ABSTRACT: Predicting the sintering performance of iron ore fines and the possibility of targeted optimisation of specific sinter properties are very important for the iron ore industry and related research organisations. A comprehensive database of pilot-scale sintering experimental results was established and empirical modelling conducted to predict values for sintering performance parameters such as Tumble Index, low temperature Reduction Disintegration Index and productivity. Together with other variables, the models developed include the abundances of several different ore textures which were combined into different textural factors corresponding to different sinter properties. Coefficients for the variables within specific regression equations can provide a better understanding of the effect of the variables on the corresponding sintering performance. The modelling results were also used to predict the sintering performance of tested mixtures that were not part of the database used to establish the models, so all models were thus verified on an independent set of data.