A Numerical Study on the Production Status Changes of Hydrogen‐Based Shaft Furnace during H2 Replacement of Coke Oven Gas

Continuous increase of the annual amount of steel scrap generated presents a problem to the sustainability of human society. The effective utilization of scrap is a serious problem to be solved in the near future, and the optimization of the global system of steel production should be considered from various viewpoints, particularly those of environmental load and material efficiency. For the consideration of a global system that contains many different kinds of flow, a criterion for evaluating the efficiency of the system is necessary for optimizing the utilization of materials in the system. The concept of exergy was adopted in this study and the application of exergy analysis to the evaluation of a complicated system was considered. A simulation model was developed for the steel industry in Japan and the exergy analysis of the Blast Furnace-LD converter (BF-LD) process and the Electric Arc Furnace (EF) process was conducted. The exergy loss was expressed as a function of parameters, such as the mixing rate of pig iron in the EF process and the total exergy loss in the system was calculated. The applicability of exergy as a criterion for the analysis of a production process and for evaluating material efficiency was discussed. Environment and recycling become important keywords in the consideration of a new industry structure for optimizing material efficiency and environmental load for production and utilization of materials. In the present study, a methodology for evaluating the degree of optimization in the system includ- ing material recycling was investigated. The Blast Furnace- LD converter (BF-LD) process for the production of high- grade steel and the Electric Arc Furnace (EF) process for the production of low-grade steel are the main steel produc- tion processes used in Japan. This division occurs because of contamination by tramp elements as impurities, which is inevitable in processes using low-grade scrap as feed. The percentage of EF steel in the total production of crude steel in Japan is about 33%, 1) and the total amount of the accumula- tive steel stock in Japan is increasing continuously. Generally, processes that consume large amounts of electric energy for heating and smelting are wasteful from the viewpoints of ef- fective energy use and environmental load. However, the op- timum steel production ratio in BF-LD and EF processes has not been investigated clearly. For the further improvement of steel productivity, it is necessary to optimize the steel pro- duction system from various viewpoints such as the suitable selection of feed materials, the total demand for steel products in society, and the impurities limit in the steel product. The recent state of the steel industry in Japan is that the amount of scrap is increasing annually and its quality is de- creasing. Therefore, the effective use of iron resources orig- inating from iron ore for the dilution of scrap has recently become a principal subject in the EF steel industry, together with the improvement of scrap recovery technology. Recent electric furnaces are operated with a high mixing rate of pig iron, from 20 to 50%, as iron feed, and other furnaces have been combined with a converter to enable the hybrid steel- making process. 2) Since it is very important for the steel in- dustry in Japan to utilize the iron stock effectively as valu- able resource, the optimum ratio of EF product to BF product and that of scrap utilized in the EF process to that utilized in the converter were investigated in this study in terms of the efficiency of the use of iron resources originating from iron ore for the dilution. A model of the iron and steel recycling system including material flow was constructed, and the ther- modynamic property of exergy was applied to estimate the measure of optimization for the steel production system. 2. The Concept of Exergy

Cost and life cycle analysis for deep CO2 emissions reduction of steelmaking: Blast furnace-basic oxygen furnace and electric arc furnace technologies

Study of biomass applied to a cogeneration system: A steelmaking industry case

Slag foaming directly affects the productivity and quality of steel during the electric arc furnace (EAF) process. Therefore, the slag foaming height needs to be monitored in real-time. However, direct measurement of the slag foaming height is difficult to achieve because the inside of the EAF consists of harsh environments, i.e., high temperature and the presence of gas and dust. A stepwise regression model of the slag foaming height was created using sensor data from the EAF. A total of 272 operational data sets from the EAF process were used to develop and validate the regression model. This data came from 140ton DC-EAF of Dongkuk Steel in Pohang, Korea. We randomly selected 80% of the data for developing the regression model; the remaining 20% of data were used for model validation. The model was validated using the validation benchmark coefficient of determination (R2) and correlation coefficients. As a result, the important variables of slag foaming were statistically selected a priori. Using the regression model, the slag foaming height can be predicted without additional sensors. Based on the developed model, the effects of oxygen injection and carbon injection on the slag foaming height of EAF were predicted and are discussed herein.

Effect of temperature on the slag/refractory interfacial reaction with directed reduced iron (DRI) addition in an electric arc furnace (EAF) process: Diffusional growth of magnesiowüstite layer by Boltzmann-Matano analysis

Gas phase reactions have a significant effect on the composition and heat content of the off-gas in the electric arc furnace (EAF) process. In this work, a previously developed dynamic scrap melting and heat transfer model was coupled with a gas phase reaction module based on Gibbs energy minimization. The gas phase reaction module retrieves the necessary thermodynamic data from a previously developed thermochemistry module. The gas phase reaction module has been used to improve the description of the gas burners and the freeboard of the EAF. The implementation of the gas phase reaction module has been found to be in good agreement with commercially available software (HSC Sim) for calculations assuming a gas phase equilibrium.

The pneumatic lime injection during the electric arc furnace (EAF) process by insufflation lances mounted on the furnace walls has gained much interest in the latest years. The main advantages, in comparison to the traditional procedure of lime lumps addition within the scrap bucket, can be summarized in raw materials consumption reduction, foaming benefits, operational cost benefits, and improvement in environmental aspects. In the proposed work, the advantages of a new lime injection system developed by Unicalce S.p.A. and installed on a 90 t EAF of Acciaierie di Calvisano are analyzed. Data from more than 1200 heats are acquired and compared with the traditional practice from an energetically and emissions point of view. To evaluate the benefits on the slag foamability, several slag samples, taken at the beginning and at the end of refining stage, are analyzed through isothermal solubility diagrams (ISDs). The ISD analysis results are then compared and validated with the total harmonic distortion (THD) of the arc in the corresponding heat. The upgrade to lime injection drives to considerable savings in electrical consumptions, oxygen, methane, and lime, with an overall save of more than 4,000 t year−1of equivalent CO2.

In the present study, the viscosity of the CaO–SiO2–FeO–Al2O3–MgO slag system was measured for the recovery of FeO in the electric arc furnace (EAF) process using Al dross. Considering the MgO-saturated operational condition of the EAF, the viscosity was measured in the MgO-saturated composition at 1823 K with varying FeO and Al2O3 concentrations. An increase in the slag viscosity with decreasing temperature was observed. The activation energy was evaluated, and the change in the thermodynamically equilibrated phase was considered. The changes in the aluminate structure with varying FeO and Al2O3 concentrations were investigated by Fourier-transform infrared spectroscopy, which revealed an increase in the [AlO4] tetrahedral structure with increasing Al2O3 concentration. Depolymerization of the aluminate structure was observed at higher FeO concentrations. The Raman spectra showed the polymerization of the silicate network structure at higher Al2O3 concentrations. By associations between the silicate and aluminate structures, a more highly polymerized slag structure was achieved in the present system by increasing the Al2O3 concentration.

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

The electric arc furnace (EAF) process for steelmaking of Cr and Ni high alloyed stainless steel grades differs significantly from the steelmaking process of carbon steel due to the special raw materials and generally lower oxygen consumption. The special slag chemistry in the EAF process affects slag foaming and refractory wear characteristics due to an increased content of CrOx. A special slag diagram is presented in order to improve monitoring and control of slag compositions for Cr alloyed heats, with special focus on saturation to MgO periclase and dicalcium silicate C2S in order to minimize MgO losses from the refractory lining and to improve slag refining capability by avoidance of stable C2S. With the same diagram different EAF process strategies can be efficiently monitored, either at elevated CaO and basicity with lower spinel concentration and more liquid process slags near C2S saturation or at lower CaO content and basicity with increased spinel concentration and stiffer slags at MgO saturation but certainly no C2S stability. Examples for three industrial EAFs are given.

An observational study of the electric arc furnace (EAF) process for austenitic stainless steel was performed. A comparison was made between two distinct EAF types: (1) an eccentric bottom tapping furnace (EBTF) and (2) a spout tapping furnace (STF). In order to study the slag evolution during the EAF process, per heat several slag samples were collected at consecutive process stages. They were subjected to electron probe microanalysis using energy dispersive spectroscopy (EPMA-EDS). Compositional and mineralogical data from 36 heats corroborate that both thermodynamic and kinetic conditions exert a strong influence on the final chromium oxide content of the slag. In the STF, chromium oxide reduction predominantly occurs during tapping, owing to the intimate mixing of steel and slag. A multivariate linear regression analysis reveals that the main parameters determining the overall chromium recovery are the slag basicity and the content of dissolved silicon of the steel. These parameters explain 70% of the observed variance in final chromium oxide levels and can be used as control parameters to improve the chromium recovery. For the EBTF, lower chromium recoveries are recorded due to the absence of sufficient mixing during tapping.

ABSTRACTAs an energy-intensive industry, iron and steel production are suffering from the resource and environmental issues. Blast furnace—basic oxygen furnace (BF-BOF) process and electric arc furnace (EAF) process are the two most common routes of steel production. Therefore, it is very important to quantify the industrial metabolism for the two routes. In this work, material flow analysis is used to comparatively investigate the energy efficiency, material efficiency, and emissions intensity at the enterprise level. The results show that the total energy consumption and material consumption per ton of steel of the BF-BOF route are 2.8 and 11 times larger than those of the EAF route, respectively. In addition, the emission intensities of dust, CO2, SO2, NO2 and CO of the BF-BOF route are 7.7, 2.6, 92.6, 33.5, and 12.0 times greater than those of the EAF route, respectively. To achieve a more sustainable steel industry, some policy recommendations are put forward finally.

The steel industry has been forced to switch from the traditional blast furnace to the electric arc furnace (EAF) process to reduce carbon emissions. However, EAF still relies entirely on the operators’ proficiency to determine the electrical power input. This study aims to enhance the efficiency of the EAF process by predicting the tap temperature in real time through a data-driven approach and by applying a system that automatically sets the input amount of power to the production site. We developed a tap temperature prediction model (TTPM) with a machine learning (ML)-based support vector regression (SVR) algorithm. The operation data of the stainless EAF, where the actual production work was carried out, were extracted, and the models using six ML algorithms were trained. The model validation results show that the model with an SVR radial basis function (RBF) algorithm resulted in the best performance with a root mean square error (RMSE) of 20.14. The SVR algorithm performed better than the others for features such as noise. As a result of a five-month analysis of the operating performance of the developed TTPM for the stainless EAF, the tap temperature deviation decreased by 17% and the average power consumption decreased by 282 kWh/heat compared with the operation that depended on the operator’s skill. In the results of the economic evaluation of the facility investment, the economic feasibility was found to be sufficient, with an internal rate of return (IRR) of 35.8%. Applying the developed TTPM to the stainless EAF and successfully operating it for ten months verified the system’s reliability. In terms of the increasing proportion of EAF production used to decarbonize the steel industry, it is expected that various studies will be conducted more actively to improve the efficiency of the EAF process in the future. This study contributes to the improvement of steel companies’ manufacturing competitiveness and the carbon neutrality of the steel industry by achieving the energy and production efficiency improvements associated with the EAF process.

Steel is an alloy of iron and one or more element(s), namely carbon, nickel, chromium, manganese, vanadium, molybdenum, tungsten, and so on. Chemically, steels may be classified in two groups: plain carbon steels and alloy steels. The former comprises the alloys of iron and carbon, whereas the latter contains one or more elements in addition to carbon. The alloying elements improve the mechanical, magnetic and electrical properties, as well as the corrosion resistance of steels. Impurities like Si, Mn, S, P, Al, and O are invariably present in steels due to their association in pig iron obtained by reduction smelting of iron ore with coke and lime in the blast furnace. Essentially, steelmaking is the conversion of molten pig iron (hot metal) containing variable amounts of 4.0–4.5% carbon, 0.4–1.5% silicon, 0.15–1.5% manganese, 0.05–2.5% phosphorus (normally between 0.06 and 0.25%), and 0.15% sulfur (normally between 0.05 and 0.08%) to steel containing about 1% of controlled amount of impurities by preferential oxidation. Alternatively, steel can be produced from solid sponge iron obtained by solid-state reduction of iron ore in the shaft furnace or retort. Thus, basically two routes are adopted in the production of steels. The first one employs the basic oxygen furnace (BOF – LD/Q-BOP/Hybrid converters) for treatment of hot metal, and the second route uses the electric arc furnace (EAF) to treat steel scrap/sponge iron or direct reduced iron (DRI). Electric arc or induction furnaces are generally used in the production of alloy steels. Pig iron contains a total of about 10% of C, Si, Mn, P, S, and so on as impurities, whereas sponge iron contains gangue oxides of iron ore, such as Al2O3, SiO2, CaO, and MgO. The amount and number of impurities depend on the quality of the iron ore, coke, and lime stone used in smelting. The molten pig iron is refined to molten steel under oxidizing conditions using iron ore and/or oxygen. On the other hand, scrap and sponge iron are melted in electric furnaces and refined for steel production.

In the electric arc furnace (EAF) process, post-combustion (PC) technology is applied to utilize the chemical energy in the CO and H2 evolving off of the steel bath through the injection of oxygen. PC technology also improves productivity and helps to optimize the benefits of oxygen and fuel injection. In order to obtain insight on the characteristics of PC inside an electric-arc furnace, a computational fluid dynamics (CFD) model was developed to investigate the combustion characteristics in the EAF with a flat bath assumption. The natural gas is used in EAF operation process, however, the natural gas combustion is not included in this CFD model to simplify the model towards examining the effect of CO post-combustion. The eddy-dissipation (ED) was employed to model the combustion reactions. The CFD model was validated with literature on the flow velocity and temperature profiles. The effects of CO post-combustion and the oxygen mass flow rate on the furnace heat transfer efficiency in the EAF were studied.