Hybrid process modeling of secondary steelmaking

As part of global decarbonization efforts, the transition to more sustainable steel production presents a significant challenge. A crucial step in this process will be the further optimization of secondary metallurgy, which is responsible for refining steel before continuous casting. This process plays a central role in modern steel production sites, ensuring the final alloy composition, required casting temperature, and modification of non-metallic inclusions. Using modeling techniques to simulate these processes is becoming increasingly important, as it allows for more precise control and optimization. With the advent of powerful, computer-assisted thermodynamic databases and the innovative kinetic approach of the Effective Equilibrium Reaction Zone method, which is used to describe reaction zones within metallurgical systems, promising opportunities arise for simulating the entire secondary metallurgy process. This method enables a more accurate representation of the chemical reactions and behaviors occurring during the process. At the same time, ongoing digitalization and the increasing availability of production data provide new opportunities to gain a deeper understanding of metallurgical processes through the use of data mining and statistical learning techniques. The planned work focuses on the development of a software tool (i-clean) for modeling secondary metallurgical refining processes (ladle furnace and Ruhrstahl-Heraeus degassing unit). A particular focus is placed on the architecture of the application and optimizing the algorithmic representation of metallurgical processes such as deoxidation, desulfurization, and degassing within the software. The goal is to model the entire process flow from tapping to the end of secondary metallurgy and better understand the influence of various processes or treatment sequences on steel and slag’s temperature and chemical composition.