An Innovative Modeling Approach for Predicting the Desulfurization Kinetics in an Argon-Stirred Ladle Furnace

Abstract

The ladle metallurgical furnace (LMF) is one of the most important secondary steel refining equipment to remove inclusions and produce clean low-sulfur steel. With the increasing demand for high desulfurization efficiency in the LMF process, it is very useful to predict the slag-steel interaction and the desulfurization behavior for providing assistance in the industrial process control. In this study, a modeling analysis tool for predicting the slag-metal reactions and desulfurization kinetics in gas-stirred ladles has been developed. The model consists of two uncoupled components: (i) a computation fluid dynamics (CFD) model for predicting fluid flow and slag-steel interface characteristics, and (ii) a multicomponent reaction kinetics model for predicting desulfurization. The slag eye behavior, slag-steel interface area, and mass transfer rates in the LMF were simulated by the CFD model. The desulfurization kinetics were predicted using the CFD simulation results together with the thermodynamic calculations. This approach is validated in terms of the evolution of the sulfur content based on industrial data. As the model can considerably decrease the computational time and cost for the analysis of the sulfur evolution during the LMF processing, it would be a very useful tool for the steel industry for quick and accurate predictions of the sulfur evolution in the ladle refining process.