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Blast furnaces are predominantly used for ironmaking, with more than 90% of the world’s clean iron units produced in these processes (Kogel et al., 2006). High-grade lump iron ore, high-grade ore fines, and concentrates from lower grade ores are utilized as feed to blast furnaces. These ore fines are agglomerated typically through sintering or pelletization to improve the blast furnace burden permeability, reducing the coke consumption rate and improving reduction rate. Sinter is used as blast furnace feed at percentages of up to 90%, and contributes to reduced operating costs (Kogel et al., 2006). Research and development for the sintering process on the laboratory or pilot scale is typically conducted by means of a sinter pot test. The VIU (Value In Use) team at Kumba Iron Ore routinely uses sinter pot tests to evaluate new sinter raw materials, primarily in terms of production rate, coke consumption, and product sinter physical properties. Optimum sinter blends can be investigated as well as the impact of changes in sinter blends on the sintering performance and sinter quality, providing information for marketing of the iron ore. As such, the VIU sinter pot test equipment is in high demand. Sinter pot tests are time-consuming, thus the turnaround time can be slow. The tests are also very costly. For these reasons, it is clear that a modelling tool that could predict the key outcomes of sinter tests with a reasonable level of accuracy would be a valuable tool for assessing the performance of sinter blends in the initial phases of a project. It is not expected that the model could replace the pot test, but that it would complement the pot test work and possibly reduce the number of actual tests required. This paper discusses the work done to date towards this goal.

A finite difference model of the iron ore sinter process