Technical Name |
Hydrogen metallurgy: Hydrogen-rich Blast Furnace Digital Twin System |
Project Operator |
National Cheng Kung University Hierarchical Green-Energy Materials (Hi-GEM) Research Center |
Project Host |
林士剛 |
Summary |
This technology combines the "Blast Furnace Thermodynamic Calculation Software" with the "Visualized Reduction Kinetics Model." The former utilizes real-time data obtained from blast furnace monitoring to predict the chemical reactions occurring inside the furnace. The latter simulate the kinetic transport phenomena of mass transfer, chemical reactions, diffusion,heat conduction during iron ore reduction. It accurately models the reaction behavior of iron ore within the blast furnace. |
Scientific Breakthrough |
Previous academic model proved inadequate in predicting real-world scenarios. Another approach involved collecting extensive data to train AI models, but their limited generalization capabilities failed to adapt to the variations in hydrogen-rich blast furnaces. Our "Hydrogen-rich Blast Furnace Digital Twin System" combines theorybig data to create the world's first intelligent blast furnace system, accurately predicting real-world scenariosperforming theoretical calculations. |
Industrial Applicability |
Our technology uses digital twinsadvanced simulations to achieve accurate visualized analysis of hydrogen-rich blast furnaces. By incorporating thermodynamickinetic theoriesmonitoring big data, we calculate complex chemical reactions in real-time. This provides operational guidance for frontline personnelhelps reduce carbon emissions by 1.55 million tons in the ironmaking process by 2025. |
Keyword |
Digital Twin Net Zero Emissions Hydrogen metallurgy Blast Furnace CALPHAD Computational Fluid Dynamics Iron-Making Steel Industry Hydrogen Python |