The Application of Computational Thermodynamics in the Understanding and Control of Clogging and Scum in Continuous Casting of Steel

Autor: A. Costa e Silva, Gabriel Evangelista Medeiros, G. L. Ramos, Thales Botelho
Rok vydání: 2017
Předmět:
Zdroj: Journal of Phase Equilibria and Diffusion. 38:201-207
ISSN: 1863-7345
1547-7037
DOI: 10.1007/s11669-017-0525-z
Popis: Non-metallic inclusions are present in small volume fractions in steel products. A significant portion of them is associated to the deoxidation process. The type and form of inclusions is, in general, directly connected to the deoxidation practice and to eventual reoxidation during processing. Besides influencing the steel properties, non-metallic inclusions can have an important effect on their processability. In this work, we review the processability questions associated with inclusions in the continuous casting of steel, with emphasis on long products. When solid inclusions are present during the casting of steel they may agglomerate and clog the valves used in the continuous casting equipment, limiting the number of sequential heats that can be casted and reducing casting speeds. Additionally, in some conditions, solid non-metallic inclusions may agglomerate and form surface defects in the continuous casting products, sometimes referred to as scum. As productivity and quality are essential to the profitability of steelmaking, avoiding these conditions is of paramount importance. Thus, we review the main thermodynamic conditions that may lead to the clogging of continuous casting valves, and discuss, from the thermodynamic point of view, the measures that can be taken to avoid the occurrence of these various conditions. Furthermore, we discuss the conditions that might cause to the formation of scum and the thermodynamics of its formation and elimination. It is concluded that the analysis of steelmaking conditions via computational thermodynamics can have an important role in avoiding problems in continuous casting and helping ensure productivity and quality in the process.
Databáze: OpenAIRE