The steel industry is undergoing a transformative shift toward decarbonisation, necessitating increased reliance on electric arc furnace (EAF)-based production. This transition will significantly increase the demand for steel scrap, requiring strict control over charge quality to maintain steel integrity. Scrap quality is influenced by bulk density and surface-to-volume ratio, which dictates heat transfer efficiency, metallurgical loss, and productivity in EAFs. Pre-treatment processes (e.g. sorting and shredding) modify these parameters hence further affecting furnace performance. Accordingly, the mathematical model developed in this study aims to optimise the bulk density of shredded and hammer milled scrap by balancing two of the main EAF process parameters, namely hourly productivity and metallurgical loss. Optimal bulk density for scrap ranges between 400 to 600 kg/m³, ensuring the best compromise between productivity and metallurgical loss. Model validation through industrial-scale EAF experiments confirms predictive accuracy. Results suggest that continuous charging EAFs or single-charge furnaces with increased volume improve operational efficiency by reducing bucket loading frequency. As the final implication, the proposed model provides critical guidelines for the steel industry to enhance EAF efficiency, reduce energy consumption, and support decarbonisation goals.

Modelling the influence of scrap size on charge-to-melt time and metallic loss in EAFs

Mapelli, Carlo;Dall'Osto, Gianluca;Scolari, Sara;Bazri, Shahab;Mombelli, Davide
2025-01-01

Abstract

The steel industry is undergoing a transformative shift toward decarbonisation, necessitating increased reliance on electric arc furnace (EAF)-based production. This transition will significantly increase the demand for steel scrap, requiring strict control over charge quality to maintain steel integrity. Scrap quality is influenced by bulk density and surface-to-volume ratio, which dictates heat transfer efficiency, metallurgical loss, and productivity in EAFs. Pre-treatment processes (e.g. sorting and shredding) modify these parameters hence further affecting furnace performance. Accordingly, the mathematical model developed in this study aims to optimise the bulk density of shredded and hammer milled scrap by balancing two of the main EAF process parameters, namely hourly productivity and metallurgical loss. Optimal bulk density for scrap ranges between 400 to 600 kg/m³, ensuring the best compromise between productivity and metallurgical loss. Model validation through industrial-scale EAF experiments confirms predictive accuracy. Results suggest that continuous charging EAFs or single-charge furnaces with increased volume improve operational efficiency by reducing bucket loading frequency. As the final implication, the proposed model provides critical guidelines for the steel industry to enhance EAF efficiency, reduce energy consumption, and support decarbonisation goals.
2025
EAF; metallic charge; metallic loss; modelling; scrap density;
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1301268
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