Otimização do processo de dessulfuração de gusa em panela através de simulações numéricas computacionais

• Ano de defesa: 2022
• Autor(a) principal: Helton Jackson Costa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; ENG - DEPARTAMENTO DE ENGENHARIA METALÚRGICA; Programa de Pós-Graduação em Engenharia Metalúrgica, Materiais e de Minas - Mestrado Profissional; UFMG
• Palavras-chave em Português: Dessulfuração; Ferro gusa; Simulações numéricas; Simulação; CFD; Controle de processo; Otimização de processos; Tempo de mistura; Engenharia metalúrgica; Metalurgia extrativa; Simulação (Computadores); Dinâmica dos fluidos computacional; Otimização
• Link de acesso: http://hdl.handle.net/1843/46859

Sulfur in steel has been considered deleterious in its quality in most cases. Sulfur can cause loss of ductility, impact toughness, and worsening the properties of weldability and resistance to corrosion and can generate surface problems in billets or slabs. Recently, the demand for low sulfur steel grades has increased, and it is not uncommon grades with sulfur specifications below 70ppm. The source of sulfur in the steelmaking process are the fossil fuels that are being used in the ironmaking process, to react with the iron ore generating hot metal. During this process, sulfur is incorporated to the chemical composition of the metallic bath, and it causes the need of a pre-treatment of the hot metal before the primary refining (in ArcelorMittal Monlevade case it means Basic Oxygen Furnace), because the sulfur removal is favored in the absence of oxygen. There are several hot metal desulfurization processes that can be conducted in torpedo cars, or hot metal ladles. The efficiency of this process is of fundamental importance for the quality of the steel grades, because among all the subsequent processes of the steelmaking process, this is the one with the greatest sulfur removal capacity. Computational fluid dynamics (CFD) simulation has been used to modelling processes in which there is great difficulty in visualization and experimentation, using equations and mathematical models to predict the behavior of fluids in the system and with this information to be able to investigate possibilities of adjustments in the processes according to the target of each operation. Thus, the present work adopts CFD simulations to analyze the current process of ArcelorMittal Monlevade desulfurization station, to determine optimum conditions of injection lance heights and gas flow to minimize the mixing time, and to achieve the maximum efficiency for the desulfurization process. In addition to the simulations, industrial tests were performed to validate the results obtained through the computer simulations, and through the study and tests it was identified the possibility of obtaining process efficiency gains minimizing the nitrogen consumption without penalizing the removal of sulfur in the process, from the use of predictions obtained through computer simulations.