Abstract

Tata Steel Netherlands (TSN) aims to reduce its CO2 emissions by 35–40 per cent by 2030 and become CO2 neutral by 2045. A first step to reach these targets is via the utilisation of an Electric Arc Furnace (EAF), which will run on a mixture of high proportion of Direct Reduced Iron (DRI) and scrap. For an EAF operation, optimisation of slag chemistry is important to achieve the right mix of basicity (for refining especially dephosphorisation), foaming, volume (rate) and refractory life. Slag composition and rate can vary widely depending on the process variables like charge mix, charge composition, feeding rate, oxygen lancing, external carbon injection/addition, fluxing and refractory erosion/corrosion. Moreover, it is important to note that the slag composition and rate are ‘transient’ parameters and change throughout the heat. This makes all the dependent phenomena and/or outcomes transient as well. To describe all these effects simultaneously and be able to realistically simulate the EAF operations, a validated dynamic process model is important in the absence of real plant data. In this study, a validated dynamic EAF process model based on the concept of Effective Equilibrium Reaction Zone (EERZ) has been utilised to analyse the impact of high DRI industrial scale EAF operations on the transient slag characteristics – including slag volume (rate), composition, phases, solid fraction and viscosity. Simultaneously, the model is able to predict the impact on steel and off-gas characteristics. Case studies were performed with 70 per cent DRI:30 per cent scrap mix considering both low and high-grade DRI. Both melting and refining aspects of the process including continuous feeding, arcing program, carbon addition, fluxing and oxy-lancing were considered.

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