Abstract Due to the high-quality steel demand, especially for ultra-low Sulfur steel, RH desulfurization has been practiced. Based on this, mathematical and physical modeling have been applied to study steel desulfurization by reagent addition in the RH degasser vacuum chamber. The main result of cold modeling, using water and oil emulating steel and slag, respectively, was to assess the influence of density difference between the continuous and disperse phases on oil droplet behavior. It is shown that its flow tends to be more restricted near the down snorkel when the density difference increases. Moreover, these results provide the basis for CFD modeling validation, which enabled the determination of slag drop residence time inside steel on RH and the average value of the rate of dissipation of turbulent kinetic energy inside the RH ladle. These two parameters were used to develop a kinetic model, which reaches a good agreement with industrial trial results available in literature. The optimum desulfurization degree of 31.44% was achieved for a gas flow rate of 90 Nm3/h, according to the kinetic model. This value can be useful in some steel grade production, where the required S content is less than 10 ppm. Even in common steel grade production, if some punctual chemical adjustment is necessary, this technique is also useful. The main kinetic parameter for steel desulfurization is the steel circulation rate. For best results, it should be reduced in the desulfurization stage, and after that, the normal operation can be resumed, so that the production cycle is not affected.

Abstract Synthetic slag has been added during BOF tapping in order to modify the physicochemical properties of resulting slag with the aim of assessing the influence on inclusion density, composition and size distribution. Viscosities and activities of slag oxides were calculated by FactSage 7.2, using the FToxid database and Viscosity module. All heats were treated under vacuum in an RH degasser for 15 minutes. A comparative analysis of top slags with two levels of FeO+MnO (> 10% and ≤ 10%) was carried out. The higher level of FeO+MnO led to almost thrice more inclusion than the lower level. Top slags after treatment with synthetic slag brought the best result of inclusions features thanks to their higher CaO activity, lower viscosity and lower activity of Al2O3. These heats presented smaller inclusions and lower initial inclusion density at ladle arrival at RH. Based on these evidences, top slags with synthetic slags added during the tapping and FeO+MnO content ≤ 10% conferred the best condition in steel cleanliness.

Abstract In order to improve steel quality, it is necessary to increase the cleanliness of the liquid steel; that is, to reduce the number and size of the inclusions in the liquid steel, as well as to control their chemical composition. For this purpose, processes (with different operating costs) are used, such as the bubbling of inert gas in the steel ladle and its treatment in the vacuum degasser RH. This article deals with inclusion removal through an argon purging process and RH treatment, and provides a comparison of their effectiveness using industrial data and a mathematical model. The inclusion count shows a strong exponential decay for RH treated heats with chemical heating, as expected. The same behavior is not seen for RH treated heats without chemical heating as well as an argon purging process. It is suggested that in the later cases, there could exist competition between inclusion removal and inclusion generation from sources, such as refractory-slag-metal interaction and open eye atmosphere metal interaction. It has been concluded that the RH and the argon purging processes are both able to reduce the amount of inclusions. However, the bubbling process would require a much smaller gas flow rate to avoid open eye formation.

Abstract The developed model is an association of thermodynamic calculations for dissolution of alloys, slag formers and the deoxidation reaction in the molten steel with two artificial neural network (ANN) models trained with industrial data, to predict the molten steel temperature drop from the blowing end of the BOF until the first measurement at secondary metallurgy. To calculate the associated energy for deoxidation, an experiment was designed to set up the parameters for oxygen partitioning among deoxidants, with timed aluminum addition during teeming being the main parameter. The temperature control in the teeming stage presented a standard deviation for the error of prediction of 5.46 ºC, for transportation from the rinsing station to the secondary metallurgy of 2.79 ºC. The association of all calculations presented an error standard deviation of 7.49 ºC. The operational validation presented superior accuracy compared with the current method for controlling the temperature, resulting in a reduction in the aluminum consumption for heating at secondary metallurgy with a potential economy of U$ 4.07 million per year for a steel shop producing 5 million tons of steel yearly. The artificial neural network model confirmed its capacity for modeling a complex multivariable process and the separation of thermodynamic calculation provides a better adaptability to different steel grades with different teeming strategies.

Abstract In the steel industry, lime is used as a desulfurizing agent and fluorspar as flux in the hot metal desulfurization process. However there are environmental concerns regarding the use of fluorspar, even when its harmful effects are not fully known. In order to reduce such risks and also to anticipate possible future restrictions, which could undermine the sustainability of steel production, it is proposed to replace the fluorspar for alternative materials in the composition of the desulfurizing lime based mixture. For this purpose new mixtures using aluminum dross, ilmenite, sodalite and ulexite were tested, comparing them with a reference mixture containing fluorspar. The impact of these mixtures on the refractories commonly used in hot metal pretreatment was also checked, since this is an important cost parameter for the steel industries. The laboratory tests showed ulexite as a feasible substitute since the lime (84.03%) - ulexite (10.97%) - graphite (5%) mixture presented the highest desulfurization ratio and low refractory wear (less than the standard fluorspar mixture). The sodalite mixture was the worst by comparison. The ilmenite and aluminum dross mixtures showed similar behavior when compared to the fluorspar mixture.

Estudou-se o emprego da resina PUROLITE S-930 como substrato para a remoção de níquel e cobalto de soluções sulfúricas. Experimentos de adsorção com diferentes razões [Ni]/[Co] mostraram uma maior seleção da resina em soluções mais ricas em níquel (Ni 600 mg/L - Co 800 mg/L). Isotermas de adsorção mostraram um aumento na capacidade de adsorção da resina em temperaturas mais elevadas (q max Ni 0,28 mol/L, a 70ºC e q max Co 0,18 mol/L, a 60ºC). Os valores de ∆H indicaram uma fisiossorção endotérmica. Para modelar a cinética de carregamento da resina, em leito fixo, utilizou-se o modelo de difusão superficial homogênea (Homogeneous Surface Diffusion Model - HSDM). Os resultados mostram um bom ajuste ao modelo, com k f = 5,2x10-6 m/s e D S = 4,5x10-12 m²/s, indicando que o carregamento da resina baseia-se em difusão na camada-limite e difusão nos poros da resina.

A study concerning the resin PUROLITE S-930 as a substrate to remove nickel and cobalt from sulphuric solution is herein presented. The influence of nickel and cobalt concentrations was studied, and the results have shown a greater selection of the resins for solutions rich in nickel (Ni 600 mg/L - Co 800 mg/L). The adsorption isotherms showed an increase in the resin adsorption capacity at higher temperatures (q max Ni 0.28 mol/L, at 70ºC and q max Co 0.18 mol/L, at 60ºC). The enthalpy values suggested endothermic physisorption. The Homogeneous Surface Diffusion Model (HSDM) was chosen for modeling the adsorption kinetics of metals in a fixed-bed column. The results showed good agreement with the model. Both, k f = 5.2x10-6 m/s and D S = 4.5x10-12 m²/s indicated that resin loading is based on transport through the boundary layer and porous diffusion in the resin.