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Description
The burden distribution in the blast furnace has a major impact on the process and its stability. The iron bearing burden consists normally of several components, such as sinter, pellets, lump ore, silica addition and nut coke. Therefore, the exact composition at discrete positions and times in the blast furnace is of great interest. While the charging via a rotating chute is well investigated by computationally costly methods like Discrete Element Method, there is a lack of models with real time capabilities to track the burden materials. This holds especially if not only a single process is in the focus but the tracking incorporates blending operations on conveyer belts, in hoppers and finally on the chute and in the blast furnace. In the current work a concept to model the material flow along the process chain from stock house to blast furnace is presented. The focus of this paper is to simulate material discharging from the hopper and distributing of the material inside the blast furnace. The hopper is modelled with a cellular automaton, the material position after charging is calculated by a semi-empirical charging model. As additional information the material in the models can always be associated to information like the chemical analysis or the screen size. Both models are coupled and displayed via a web interface. The model enables for an offline optimization of the burden distribution from the hopper up to the blast furnace and also for online guidance and recommendations for the blast furnace operators.