Investigating the parameters that influence the behaviour of natural iron ores during the iron production process

University dissertation from Stockholm : KTH Royal Institute of Technology

Abstract: In the iron production processes, sinters and pellets are mostly used as raw materials due to their consistency with respect to physical and chemical properties. However, natural iron ores, as mined, are rarely used directly as a feed material for iron processing. This is mainly due to the fact that they have small contents of iron and high concentration of impurities. Moreover, they swell and disintegrate during the descent in the furnace as well as due to low melting and softening temperatures. This work involves an investigation of the parameters that influence the use of natural iron ores as a direct feed material for iron production. Furthermore, it points out ways in which these can be mitigated so as to increase their direct use in iron production.Natural iron ore from Muko deposits in south-western Uganda was used in this study. Initially, characterisation of the physical and chemical properties was performed, to understand the natural composition of the ore. In addition, investigations were done to study the low temperature strength of the ore and its behaviour in the direct reduction zone. Also, simulations were performed with three models using the experimental data from the direct reduction experiments in order to determine the best model for predicting the direct reduction kinetics of natural iron ores.Chemical analyses showed that the Muko ore represents a high grade of hematite with an Fe content of 68% on average. The gangue content (SiO2+Al2O3) in 5 of the 6 investigated iron ore samples was < 4%, which is within the tolerable limits for the dominant iron production processes. The S and P contents were 0001-0.006% and 0.02-0.05% respectively. These can be reduced in the furnace without presenting major processing difficulties. With respect to the mechanical properties, the Muko ore was found to have a Tumble Index value of 88-93 wt%, an Abrasion Index value of 0.5-3.8 wt% and a Shatter Index value of 0.6-2.0 wt%. Therefore, the ore holds its form during the handling and charging processes.Under low temperature investigations, new parameters were discovered that influence the low temperature strength of iron oxides. It was discovered that the positioning of the samples in the reduction furnace together with the original weight (W0) of the samples, have a big influence on the low temperature strength of iron oxide. Higher mechanical degradation (MD) values were obtained in the top furnace reaction zone samples (3-25% at 500oC and 10-21% at 600oC). These were the samples that had the first contact with the reducing gas, as it was flowing through the furnace from top to bottom. Then, the MD values decreased till 5-16% at a 500oC temperature and 6-20% at a 600oC temperature in the middle and bottom reaction zones samples. It was found that the obtained difference between the MD values in the top and other zones can be more than 2 times, particularly at 500oC temperature. Furthermore, the MD values for samples with W0 < 5 g varied from 7-21% well as they decreased to 5-10% on average for samples with W0 ? 5 g. Moreover, the MD values for samples taken from the top reaction zone were larger than those from the middle and bottom zones.During direct reduction of the ores in a H2 and CO gas mixture with a ratio of 1.5 and a constant temperature, the reduction degree (RD) increased with a decreased flow rate until an optimum value was established. The RD also increased when the flow rate was kept constant and the temperature increased. An optimum range of 3-4g was found for natural iron ores, within which the highest RD values that are realised for all reduction conditions. In addition, the mechanical stability is greatly enhanced at RD values > 0.7. In the case of microstructure, it was observed that the original microstructure of the samples had no significant impact on the final RD value (only 2-4%). However, it significantly influenced the reduction rate and time of the DR process.The thermo-gravimetric data obtained from the reduction experiments was used to calculate the solid conversion rate. Three models: the Grain Model (GM), the Volumetric Model (VM) and the Random Pore Model (RPM), were used to estimate the reduction kinetics of natural iron ores. The random pore model (RPM) provided the best agreement with the obtained experimental results (r2 = 0.993-0.998). Furthermore, it gave a better prediction of the natural iron oxide conversion and thereby the reduction kinetics. The RPM model was used for the estimation of the effect of original microstructure and porosity of iron ore lumps on the parameters of the reduction process.