Mathematical modeling and optimization of two-layer sintering process for sinter quality and fuel efficiency using genetic algorithm

Two-layer sintering by charging a green sinter mix with normal coke rate in the upper layer and reduced coke rate in the lower layer can substantially reduce the coke rate and improve the sinter quality by producing more uniform thermal profile throughout the bed height. The two-layer sintering process has been analyzed by numerical simulation using a detailed CFD-based model, considering all the important phenomena (i.e., gas-solid reaction, melting and solidification, flow through porous bed, heat, and mass transfer etc.). A genetic algorithm optimization technique is then applied to evaluate the optimum coke rate in the two layers of the bed to produce the ideal thermal profile and melting fraction in the sinter bed for optimum sinter quality. By this optimization method a high-quality sinter with minimum return fines can be achieved along with reduced coke rate. Application of genetic algorithm for this type of process optimization has several advantages over traditional optimization techniques, because it can identify the global optimum condition and perform multiobjective optimization very easily for a complex industrial process such as iron ore sintering.