A Simplified Approach Based on Cellular Automata for Describing Direct Reduced Iron Production in Different Reducing Conditions

• Published in: Steel research international Vol. 95; no. 3
• Main Authors: Mapelli, Carlo, Dall’Osto, Gianluca, Mombelli, Davide, Romano, Matteo Carmelo, Scaccabarozzi, Roberto, Spinelli, Maurizio
• Format: Journal Article
• Language: English
• Published: Weinheim Wiley Subscription Services, Inc 01.03.2024
• Subjects: Cellular automata; Diffusion coefficient; Direct reduced iron; Gas mixtures; Heat exchange; hydrogen‐based pre‐reductions; Iron ores; Oxygen; Pellets; Reducing agents; shaft furnace; simulation
• ISSN: 1611-3683; 1869-344X
• DOI: 10.1002/srin.202300411

A quick computation approach based on cellular automata is developed and implemented to describe the reduction of iron ore pellets by a mixture of reducing agents featured by different H2/CO ratios. The evolution of oxygen concentration inside the pellet is followed from the beginning to the end of contact between reducing agent and pellet. The variation of thermal state of pellets and gas mixture is computed based on their initial temperature, considering the heat involved and the convective heat exchange between pellet and gas mixture. The use of cellular automata and finite‐difference method to solve the diffusion equation point out the absence of any diffusion coefficient value, allowing to make the model fit the experimental trial, because the problem is that it is not ruled just by diffusion but also by the concentration variation of reducing agent inside the pellet due to porosity increasing during reduction. The updating of the reducing agents concentration implies a sharp decrease of oxygen concentration that the cellular automata model considers. The developed model is able to provide the in‐line control of reduction process and could be used to adjust the chemical concentration and temperature of injected reducing agents. A fast cellular automata model with low‐computational burden is developed to tackle the direct reduced iron production process under different conditions as a feasible tool for in‐line control of the reduction process. The robustness of the model is confirmed through comparison with industrial data of the final reduced product and that foreseen by the model.