| Abstract Scope |
Oxide particle dissolution in the silicate melt is of vital importance for steel manufacturing. Initially, the oxide dissolution is investigated by the rotating dip test. With the development of confocal laser scanning microscope, new insights have been obtained due to in-situ image observation characteristics and precise process control. Comprehensive studies have been adapted to investigated effects of oxide type, slag composition, temperature, etc. on the dissolution kinetics. On the other hand, the theoretical study has also been developed by the supply of more reliable experimental data. Shrinking core (SRC) model is one of the classical method, which is usually proposed through a proper fitting with the experimental data. The different shape dissolution profiles indicate different mechanisms. This work develops a new SRC model which combines different mechanisms in one equation. Furthermore, machine learning method is integrated with the new physical model for a comprehensive study in this field. |