Computational study of non-isothermal slag eye formation and its effects on ladle refining

TL;DR

This study models non-isothermal slag eye formation during ladle refining, revealing how temperature-dependent properties influence slag flow and desulfurization kinetics, improving understanding of steel refining processes.

Contribution

It introduces a non-isothermal modeling approach for slag eye formation that accounts for temperature-dependent properties, enhancing accuracy over previous isothermal models.

Findings

Slag eye formation is affected by temperature-dependent thermophysical properties.

Changes in slag properties influence flow and desulfurization kinetics.

The model improves practical efficiency by avoiding complex species transport equations.

Abstract

Ladle refining is one of the most important aspects of high-quality steel production. Ladle argon purging which facilitates the refining process also leads to the unwarranted opening of the slag cover known as Slag Eye-opening and has a deleterious effect on the quality of steel. Slag eye-opening has been analysed in past under isothermal conditions whereas ladle refining is a transient and non-isothermal operation. The current study deals with the modelling of slag-eye opening and its effects on ladle refining under non-isothermal conditions. The bubble plume is modelled with the help of Discrete Phase modelling (DPM) coupled with a discrete random walk model for including the particle level turbulence. Temperature-dependent thermophysical properties of slag are obtained from FactSage. Opening of slag-metal interface cools the slag-eye region, which causes changes in the thermophysical properties of the slag phase. These changes are then reflected in the flow characteristics of this complex fluid. The slags flow profile and eye formation are compared and explained between cold modelling techniques and actual ladle metallurgy. The consequences of changing thermophysical prop during ladle refining manifest in their influence on the overall mass transfer coefficient and the kinetics of desulfurization. This can be achieved without the requirement to solve computationally demanding species transport equations, thereby enhancing the practical efficiency of this approach.