Numerical modeling has been used to investigate the influence of electromagnetic stirring on melting of a single piece of scrap in an eccentric bottom tapping (EBT) electric arc furnace (EAF). The heat transfer and fluid flow in the melt for both conditions with and without electromagnetic stirring were studied. The buoyancy and electromagnetic forces were considered as the source terms for momentum transfer in the studied conditions. The enthalpy-porosity technique was applied to track the phase change of a scrap piece defined in the EBT region of the furnace. Different scrap sizes, preheating temperatures, stirring directions and force magnitudes were considered, and the heat transfer coefficient was estimated from the heat transfer rate at the melt-scrap interface. The results showed that electromagnetic stirring led to a reduced melting time and an increased heat transfer coefficient by a factor of four. The results for Nusselt number versus Grashof number for natural convection and Reynolds number for electromagnetic stirring were compared with those obtained through correlations from previous studies.

The pressure on the steel industry to reduce its carbon footprint has led to discussions to replace coke as the main reductant for iron ore and turn to natural gas, bio-syngas or hydrogen. Such a major transition from the blast furnace-basic oxygen furnace route, to the direct reduction-electric arc furnace route, for steel production would drastically increase the demand for both suitable iron ore pellets and high-quality scrap. The value for an EAF plant to reduce the SiO2 content in DRI by 2 percentage points and the dirt content of scrap by 0.3 percentage points Si was estimated by using the optimization and calculation tool RAWMATMIX®. Three plant types were studied: (i) an integrated plant using internal scrap, (ii) a plant using equal amounts of scrap and DRI and (iii) a plant using a smaller fraction of DRI in relation to the scrap amount. Also, the slag volume for each plant type was studied. Finally, the cost for upgrading was estimated based on using mainly heuristic values. A conservative estimation of the benefit of decreasing the silica content in DRI from 4 to 2% is 20 USD/t DRI or 15 USD/t DR pellets and a conservative figure for the benefit of decreasing the dirt in scrap by 0.3 percentage points Si is 9 USD/t scrap. An estimate on the costs for the necessary ore beneficiation is 2.5 USD/t pellet concentrate and for a scrap upgrade, it is 1-2 USD/t scrap.

A static mass and energy balance model combined with a MgO saturation slag model is developed for electric arc furnaces. The model parameters including distribution ratios and dust factors are calibrated for a specific furnace using experimental data. Afterward, the model is applied to study the effect of charging different amounts of hot briquetted iron (HBI) on energy consumption, charged slag former amount, and slag composition. The following results were obtained per each 1% increase of HBI additions: (i) a 0.16 Nm3/t decrease in the amount of injected oxygen for metal oxidation, (ii) a 1.29 kWh/t increase in the electricity consumption, and (iii) a 34 kg increase in the amount of the slag.

Numerical modeling was used to study the capability of postcombustion in an electric arc furnace (EAF) equipped with virtual lance burners. The CO flow rate at the molten bath surface was estimated using the off-gas data obtained close to the outlet of an EAF. Then, the effect of the secondary oxygen flow rate on postcombustion was studied. The results show a CO flow rate of 0.6 kg·s−1 and 0.8 kg·s−1 for operation modes of burner and burner + lancing. Increase of the secondary oxygen flow rates of 60% and 70% result in 17% and 7% increase in the postcombustion ratio (PCR) for the burner and burner lancing modes, respectively.

A statistical model is developed in order to simulate the melt composition in electric arc furnaces (EAFs) with respect to uncertainties in 1) scrap composition, 2) scrap weighing and 3) element distribution factors. The tramp element Cu and alloying element Cr are taken into account. The model enables simulations of a charge program as well as backwards estimations of the element concentrations and their variance in scrap. In the backwards calculation, the maximum likelihood method is solved by considering three cases corresponding to the involved uncertainties. It is shown that the model can estimate standard deviations for elements so that the real values lie within the estimated 95% confidence interval. Moreover, the results of the model application in each target product show that the estimated scrap composition results in a melt composition, which is in good agreement with the measured one. The model can be applied to increase our understanding of scrap chemical composition and lower the charged material cost and carbon footprint of the products.