Abstract
The high melting point Al2O3 inclusions in steel can be modified to low melting point calcium aluminate by the calcium treatment process, which makes the inclusions easy to grow up by collision and float to remove, thus improving the cleanness of liquid steel. Taking the treatment of molten steel by SPHC in a steel mill as the research object, the budget models of molten steel composition and temperature, calm time, top slag composition, and the amount of molten steel calcium were established based on RH refining data using multiple linear and multiple nonlinear regression analysis methods. The results show that the hit ratio of the multiple linear and multiple nonlinear budget models is 83.8% and 94.6%, respectively, and the multiple nonlinear regression model has better fitting ability and higher hit ratio. The amount of calcium is mainly determined by the content of [Ca] and [Al]O and [S] in molten steel before calcium treatment. Therefore, in the actual process of calcium treatment, the amount of calcium should be precisely adjusted according to the specific composition of molten steel.KeywordsCalcium treatmentThe amount of calciumMultiple linear regressionSPHC steel
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