Modelling Transient Inclusion Behaviour During Refining of Si-Mn Killed Steel

Abstract

Certain non-metallic inclusions are known to cause deleterious effects in steel products and affect the production efficiency of steelmaking if not controlled. Most of these are oxide inclusions formed during deoxidation in refining processes, especially in the ladle metallurgy furnace (LMF), an understanding of which is essential for process control. The composition of these inclusions changes subsequently while interacting with other phases like slag, alloy additions, and refractories. The efficient removal and composition control of inclusions are important variables to consider for any steelmaker. Moreover, desulphurisation of steel is another aspect that needs attention since excess sulphur can precipitate sulfide inclusions while cooling. Hence, tracking the composition evolution of different phases in a ladle furnace is beneficial for the steelmaking industry. Previous researchers in the authors’ laboratory developed a model that could be used to predict the kinetics of steel-slag-inclusion reactions in aluminium (Al) killed steel. The current work focusses on developing a kinetic model that can be used to describe the inclusion evolution during ladle treatment of silicon-manganese (Si-Mn) killed steel. For this, first, the formation of complex oxides in Si-Mn-killed steel was analyzed using a mathematical model of nucleation and growth of particles in melts. The results revealed that spontaneous nucleation of complex oxides occur during alloy additions, resulting in different compositions of oxide nuclei, based on the local supersaturation conditions. Sensitivity analysis with different parameters was carried out to understand the influence of physicochemical variables on the model. Following this, two kinetic models were built: 1) average inclusion composition tracking method; and 2) multi oxide inclusion (MOI) composition tracking method. The latter approach included the thermodynamics and kinetics of each inclusion formation and could further incorporate the total inclusion number density variation in steel. The MOI model can be used to predict the changes in not only the average inclusion composition but also the type of inclusions precipitating in steel. Following this, laboratory deoxidation experiments were carried out using FeSi and FeMn to understand the inclusion behaviour post alloy additions. The MOI model showed good potential in simulating these laboratory deoxidation experiments and was then coupled with a previously developed steel-slag model to simulate actual ladle refining reactions. The calculated results were compared with different industrial data and showed good agreement with what is observed in reality, showing the success of this new approach. Similar to previous investigations, the rate-determining step could be attributed to the availability of solutes in steel (from slag or alloys) along with their transport to the steel-inclusion interface. The overall model was also able to simulate the desulphurization behaviour in steel. The effects of different processing conditions such as [Al], [O] content, reoxidation, and stirring conditions, were also examined and discussed through a parametric analysis.