Towards realistic DEM modeling of blast furnace mixture charging

Abstract

In blast furnace ironmaking, a mixture of iron ore pellets and sinter is charged in layers at the furnace top, with particle velocities reaching up to ∼10 m/s at the stock surface. The inherent differences in particle size, shape, and density between pellets and sinter pose challenges for maintaining a uniform mixture during this high-velocity charging, leading to segregation and uneven material distribution. This non-uniformity can negatively affect furnace efficiency and stability. Understanding segregation during charging is therefore crucial for optimizing the ironmaking process. The Discrete Element Method (DEM) can offer valuable insights, provided that the model parameters are calibrated and verified. This study presents a calibrated DEM model for a pellet–sinter mixture with a 50–50 mass ratio of both components. A novel high-velocity laboratory setup was used to simultaneously measure five different key performance indicators (KPIs) related to flow and packing behavior at various discharge heights, corresponding to different flow velocities. Calibration was performed at the highest flow velocity, representative of actual blast furnace conditions. The process involved creating response surface models for each KPI and using a multi-objective optimization approach with a desirability function to determine the model parameters. A step-wise calibration strategy was employed, first optimizing pellet and sinter interaction parameters individually, followed by calibration of the pellet–sinter interaction parameters. This approach proved effective, as the calibrated model accurately reproduced experimental data. Results also suggest that the calibration outcome is flow-invariant in this setup, with the model successfully predicting flow and packing behavior at lower discharge heights.