A Transient Discrete Element Method‐Based Virtual Experimental Blast Furnace Model

Abstract

Intensive heat and mass transfer between continuum fluids and discrete particulate materials occur in the current working‐horse blast furnace (BF) ironmaking process. To optimize the operation, its energy efficiency and sustainability, discrete particle models are very helpful when they are incorporated with flow, heat and mass transfer, and chemical reaction models. Herein, a transient discrete element method‐based virtual BF model is developed through scaling. The scaled model simulates the process significantly faster and makes it practical to track the whole process of iron ore reduction from burden charge to the cohesive zone (CZ). The model is applied to an experimental BF and the predictions are tested against available experimental results and those of computational fluid dynamics models. The results demonstrate that the scaled virtual BF model can reasonably predict in‐furnace flow state, temperature distribution, iron ore reduction, and the characteristics of the CZ. The particle‐scale BF model provides detailed information of particle motion, temperature, and chemical reactions, enabling fundamental understanding and further optimization and control of the process. The scaled BF model can be extended to study the effects of raw material properties and operation parameters on BF performance.