The improvement of industrial parameters like the basicity and sintering temperature and the selection of raw materials to form the acicular calcium ferrites become the hot topic in sintering production. However, the experimental with the sintering pot in the laboratory is still a main method up to now, no effective mathematical model or experience equations were developed. Factsage is a software for thermodynamic calculation in ironmaking and steelmaking. In present study, Factsage was used to calculate the liquid phases formulation during the sintering. The effect of the chemical compositions on the liquidus projection was also discussed. It was found that the content of liquid phase formed is about 25%-70% at 1 250°C due to their chemical composition. The more SiO2, the easier to form liquid phase. The experiments were carried out for the validation. It was found that the calculations of the mass of liquid phase generation cannot give a very good and accurate agreement with the measurement of the melting behavior of the sample quantificationally, however, for the ability of the liquid phase formation during the sintering, the calculations can give a good qualitative results, especially in the temperature of melting begin and the temperature of 50% shrinkage. The calculations reported in this study can be used to estimate the sintering behavior of the iron ores under a certain industrial condition to reduce the extra experiments. The experiments also shows that the calculations by Factsage can give some good explanations on the phenomenon of the melting behavior of different samples.

Together with the conventional granulation, a proposed pre-wetting granulation for two commercial sinter mixtures consisted of six different iron ores and other auxiliary materials has been investigated under controlled laboratory conditions. A method to describe the size variation of the granules between different granulation trials was proposed and studied in the granulation of this study. It is a method by drawing a cumulative undersized curve (CUS curve) and a differential cumulative undersized curve (Δ-CUS curve) into one figure. The results indicated that (1) with more water available for granulation, more particles in a sinter raw mixture would behave as the layering fines in granules and the upper size for these layering fines would increase from 1 mm to 4.5 mm in conventional granulation; (2) compared to the results from conventional granulation, the granulation with pre-wetting treatment on iron ore fines resulted in a tighter particle size distribution and a higher permeability before ignition. At similar moisture content, more particles can be shifted into the layering fines in pre-wetting granulation than in conventional granulation; (3) Due to the preferential granule growth and the deformation of the granules, a further increase in pre-wetting degree (PWD) from 65% to 80% had little influence on the optimal permeability before ignition. Furthermore, a sinter mixture with more materials that are high in moisture absorption capacity would lead to higher optimum moisture content in granulation.

The granulation property of iron ores was generally influenced by their wettability, surface roughness and shape of the iron ore. In this study, the surface roughness and shape of iron ores were characterized by the ratio of BET specific surface area (SBET) to specific surface area (SLS) calculated using size distribution obtained by a laser diffraction method. Wettability of ores was characterized by measuring the contact angle (θ ) between iron ore and water. Bed permeability was used as an evaluation index of granulation effect. A variety of materials were subjected to a granulation test under an actual production condition. Special attention was paid to four ores with different surface properties and wettabilities. Nine groups of mixtures were obtained by linear programming taking the basicity as the objective function. Granulation results showed that the optimum bed permeability of nine mixtures have a good linear relation with mass fraction of four ores studied. Slopes (k) of fitting lines were used to characterize the granulation properties of ores, binary linear regression equation was derived with the k used as dependent variable, θ and SBET/SLS used as independent variables: k=16.443-0.277×θ+0.058×(SBET/SLS), Granulation performance of iron ore gets better with decreasing the contact angle and increasing the ratio of SBET to SLS.