Abstract
Iron ore sintering is a complex thermochemical process for bulk production of blast furnace raw material. The quality of sinter is very important for smooth operation and high productivity of the blast furnace since it improves the permeability and reducibility of the burden material. A detailed mathematical model for the process, considering all the important phenomena such as gas–solid reaction, melting and solidification, flow through the porous bed, heat and mass transfer, etc., has been used for process simulation and analysis. Optimisation using a genetic algorithm has then been applied to evaluate the operating condition of suction pressure at different bed positions for optimum quality, productivity and thermal efficiency of the process. The genetic algorithm has several advantages over traditional optimisation techniques, since it can identify global optima under multimodal conditions, and do away with the need for gradient evaluation.
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