Numerical Analysis of the Reactivity of Raw Materials Used in Blast Furnace Ironmaking

Abstract The metallurgical properties of raw materials—particularly their reactivities—can significantly influence blast furnace (BF) performance. However, due to variations in reactivity among different raw materials, it remains unclear whether existing reaction models can reliably describe each material. To address this, numerical models are developed to simulate laboratory-scale experiments measuring indirect reduction, coke reactivity, and softening–melting (S&M) behavior. First, the reactivities of coke and individual iron-bearing materials, including sinter, pellets, and lump ore, are sequentially measured and evaluated. By combining numerical modeling with experimental measurements, widely used reaction models are modified to better capture the reactivity of each material. The reactivity of ore mixtures is further investigated, demonstrating that the indirect reducibility of mixed burden can be derived from the reactivities of its individual components. Subsequently, all the modified reaction models, together with the measured S&M properties, are incorporated into simulations of the coke–ore coupled reaction–softening–melting process, and the results are validated against experimental data. In addition, the direct reduction model between melts and coke is verified under conditions of measured bed shrinkage. These results indicate that, while existing reaction models can qualitatively describe the reactivities of typical sinter, pellets, and lump ore, material-specific calibration is required for accurate quantitative predictions. The integration of lab-scale measurements with numerical modeling provides a robust framework for obtaining reliable calibrating parameters, which can be further extended to full-scale BF ironmaking applications.