In the recent years, a revolution of the worldwide development policies has taken place, mainly driven by the idea of achieving the sustainable development scenario (SDS). The electric steelmaking route mainly based on the scrap recycling can be already considered as a successful example of circular economy: the possibility of recycling metallic scraps a theoretically infinite number of times allowed the increase of crude steel production by electric arc furnace (EAF) especially in the Eastern and developing countries. Therefore, the optimization of the charge mix, by empirical mathematical models, has become a fundamental practice aimed at decreasing the metallic loss, increasing the furnace performance and obtaining a proper melt chemistry. Herein, regression modeling is used to investigate the relationship between the metallic loss and the charging material. For the calibration and validation of the model, the data regarding 56 experimental heats, performed by a continuous charging EAF, are used. In particular, the model developed to foresee the metallic loss starting from a given charge mix, highlighting, furthermore, the interactions among the several charging materials.

Modeling of a Continuous Charging Electric Arc Furnace Metallic Loss Based on the Charge Mix

Mombelli D.;Dall'Osto G.;Mapelli C.;Gruttadauria A.;Barella S.
2020-01-01

Abstract

In the recent years, a revolution of the worldwide development policies has taken place, mainly driven by the idea of achieving the sustainable development scenario (SDS). The electric steelmaking route mainly based on the scrap recycling can be already considered as a successful example of circular economy: the possibility of recycling metallic scraps a theoretically infinite number of times allowed the increase of crude steel production by electric arc furnace (EAF) especially in the Eastern and developing countries. Therefore, the optimization of the charge mix, by empirical mathematical models, has become a fundamental practice aimed at decreasing the metallic loss, increasing the furnace performance and obtaining a proper melt chemistry. Herein, regression modeling is used to investigate the relationship between the metallic loss and the charging material. For the calibration and validation of the model, the data regarding 56 experimental heats, performed by a continuous charging EAF, are used. In particular, the model developed to foresee the metallic loss starting from a given charge mix, highlighting, furthermore, the interactions among the several charging materials.
2020
electric arc furnaces
linear regression
metallic charges
metallic losses
scraps
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1169567
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