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A mathematical model for predicting the size distributions of iron ore granules after granulation was developed by Litster et al. (1986). This model was initially tested using a limited range of iron ores, as well as on simple mixtures of the iron ores and for moisture contents not exceeding 5.4% (by weight). However, since the development and testing of the model, a much wider range of iron ores has become available. Granulation experiments have been carried out at different moisture contents for this wider range of iron ores, as well as for three simple and four complex blends made from the ores and added fluxes. Granulation experiments were also carried out on two of the four complex blends with Ores N and Y replaced with Ore W. The Sauter mean diameters and size distributions of the granules formed were compared with the values predicted by the mathematical model. In all the cases where there was sufficient moisture for granulation, the agreement between the Sauter mean diameters predicted by the model and those obtained from experimental results was within ± 10%. There was also good correlation between the model‐predicted and experimentally determined granule size distributions. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd.

We have examined the small strain response of an inverse ferrofluid system, consisting of micron-sized inert particles dispersed in a ferrofluid, which is a magnetisable liquid consisting of single domain magnetite nanoparticles. Under a magnetic field the inert particles will form elongated aggregates in the field direction, analogous to a magnetorheological fluid. It was found that the fluid appeared to have a Bingham fluid-like yield stress when analysed using the flow curve. However careful study of the behavior at very low shear rates revealed an ever decreasing shear stress. In addition, the behavior of conventional magnetorheological fluids at large strains under steady shear flow and constant magnetic field was also studied, and the results compared to particle-level computer simulations.

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