Shanchao Gao

Blast furnace (BF) ironmaking is a complex multiphase process involving gas–solid flow, heat transfer, chemical reactions, burden movement, and phase transformation under high-temperature conditions. Since many internal states of the blast furnace cannot be directly observed during operation, numerical simulation and mathematical modeling have become important tools for understanding furnace behavior and optimizing operational parameters. This paper reviews recent advances in blast furnace numerical simulation and internal state reconstruction methods. Existing approaches, including packed-bed flow models, cohesive zone reconstruction methods, burden distribution models, and temperature field prediction methods, are summarized and discussed. In addition, the evolution of blast furnace mathematical models from early one-dimensional steady-state formulations to modern three-dimensional multifluid and hybrid simulation approaches is reviewed. Recent developments in computational fluid dynamics (CFD), the discrete element method (DEM), digital twin, and data-driven modeling are also discussed. Compared with traditional simplified models, modern multidimensional and hybrid approaches show improved capability in describing asymmetric furnace inner states, multiphase transport behavior, and operational parameter effects under industrial conditions. However, challenges still remain in achieving computational efficiency, parameter calibration, multiphase coupling, and real-time industrial application. Future studies are expected to focus on the integration of mechanism-based simulation and intelligent data-driven methods to improve prediction accuracy, operational adaptability, and intelligent control capability in blast furnace ironmaking.

In this study, the thermodynamic conditions governing TiC formation were systematically investigated based on Gibbs free energy and interaction parameter theory. The effects of temperature and furnace atmosphere on interaction parameters were explicitly incorporated, enabling an improved thermodynamic description of TiC formation under realistic blast furnace conditions. Furthermore, compared with conventional two-dimensional equilibrium analyses, a three-dimensional Ti-C-temperature thermodynamic precipitation surface was established to quantitatively evaluate the effects of temperature, titanium content, and carbon content on TiC precipitation behavior. The results indicate that titanium is the dominant controlling factor for TiC formation, while carbon plays a secondary synergistic role. Compared with dissolved carbon, solid carbon provides more favorable thermodynamic conditions, suggesting that TiC preferentially forms via interactions with high-activity carbon sources such as coke or refractory materials. Based on the modified thermodynamic framework and boundary conditions, a quantitative precipitation criterion was established as 100 × w[Ti]_% + w[C]_% ≥ 10, which ensures TiC precipitation prior to molten iron solidification under representative blast furnace hearth conditions. The proposed criterion provides a practical guideline for titanium addition and carbon regulation in blast furnace ironmaking and improves the thermodynamic prediction capability for titanium-bearing protective phase formation in complex high-temperature metallurgical environments.

The temperature and concentration dependences of viscosity for blast furnace molten iron were theoretically studied in this paper. Afterwards, a series of semi-empirical viscosity prediction models were compared, and several of which that are suitable for blast furnace molten iron were optimized. The Fe-C system was used as the only benchmark during the whole research to quantify the relationship between component content and melt viscosity. Then, the component action coefficient of viscosity was introduced by fitting the previous viscosity results of iron-based melt. In terms of verification, the viscosity of blast furnace molten iron was measured by using an oscillating cup viscometer, and five semi-empirical viscosity models were selected to calculate the viscosity based on the corresponding concentration of experimental samples. Consequently, by comparing the experimental and calculation results of viscosity, it was concluded that the Hirai model based on the Andrade quasi-crystal theory is the most suitable viscosity prediction model of molten iron in a blast furnace.