Blast-furnace Smelting Research Articles

BLASTFURNACESINTHEAGEOFDECARBONIZATION: THESEARCHFOR COKE ALTERNATIVES

The aim of this work is to analyze the prospects of using hydrogen as an alternative to coke in blast furnaces in the context of decarbonizing the steel industry, particularly considering the introduction of the Carbon Border Adjustment Mechanism (CBAM). It is shown that the widespread notion of a complete replacement of coke with hydrogen needs clarification, as there are technological limitations and economic challenges. According to the analysis of global experience, the use of hydrogen in blast furnaces allows for a reduction of CO2 emissions by 10-70%, which is particularly relevant in the context of CBAM, but requires significant capital investments in the modernization of production and the creation of infrastructure for the production and transportation of hydrogen. It is shown that the efficiency of hydrogen use, and therefore its potential for reducing the cost of carbon quotas within the CBAM framework, depends on the technology of its production, the method of injection into the blast furnace, and the conditions of blast furnace smelting.

Improvement of the efficiency of blast furnace smelting technology with pulverized coal fuel injection

Improvement of the efficiency of blast furnace smelting technology with pulverized coal fuel injection

Prediction model of permeability index for blast furnace based on WD-NL-transformer

The permeability index is an important variable to reflect the operating state of a blast furnace quickly, intuitively and comprehensively. Given the multi-scale, nonlinear and massive characteristics of the blast furnace smelting process data, a prediction model of permeability index based on the WD-NL-transformer (wavelet de-noising-nonlinear-transformer) method was proposed. The key variables affecting permeability index were selected from multiple perspectives by Pearson correlation coefficient and copula entropy. The extreme outliers were optimised using box plots and Lagrange linear interpolation. A data set was constructed after wavelet de-noising to build the prediction model with nonlinear processing capability, time-series prediction capability, and early stopping method. The results show that the MSE of WD-NL-transformer is 0.0093, with the RMSE of 0.0086. Meanwhile, the R2 is 0.9859, and the running time is 19.59 s, which means the model has great prediction accuracy and inference speed. The proposed model could provide theoretical support for advanced control of permeability index, which is of practical significance to ensure the stability of blast furnace smelting and accelerate the metallurgical process of intelligent automation.

Numerical Simulation of Vanadium–Titanium Blast Furnace under Different Smelting Intensities

The blast furnace smelting of vanadium–titanium ore plays a crucial role in the efficient utilization of vanadium-titanium resources. In this research, a detailed numerical simulation study of the temperature, velocity, and concentration fields during the smelting process in a vanadium–titanium blast furnace was conducted. The actual production data from a 1750 m3 vanadium–titanium blast furnace was utilized, combined with softening and dripping parameters and material balance calculations, to develop a two-dimensional blast furnace model. This model was employed to analyze the effects of varying smelting intensities on the internal operating conditions of the furnace. The study found that as smelting intensity increased, significant changes occurred in the temperature fields and CO concentration fields within the furnace, thereby affecting the reduction efficiency of the burdens. Additionally, this research also shows that increasing the proportion of Baima pellets in the furnace will lead to the expansion of the soft melting zone and the upward movement of the soft melting zone. This investigation not only revealed the variations in the internal physical fields of the blast furnace under different operating conditions but also provided theoretical foundations and references for optimizing the design and operation of vanadium–titanium blast furnaces. By comparing the velocity field under different smelting intensities, it was found that the difference was small, which was mainly related to the expansion behavior of the pellets. These findings provide an important scientific basis for further improving the efficiency of blast furnace smelting and reducing costs.

Investigation of Basicity on Compressive Strength and Oxidation Induration Mechanism of Vanadium–Titanium Magnetite Pellets

Currently, the typical charge structure for blast furnace smelting of vanadium–titanium magnetite (VTM) is the addition of acidic pellets, high‐basicity sinters, and lumps. To increase the percentage of pellets entering the blast furnace, it is necessary to transfer the basicity burden to the pellets. In this study, the effect of basicity on the phase transition and oxidation hardening mechanism of VTM pellets is investigated. In the results, it is indicated that when the preheating temperature is 950 °C, the preheating time is 15 min, the roasting temperature is 1260 °C, and the roasting time is 15 min, with the basicity (CaO/SiO2) increasing from 0.08 to 1.3, the compressive strength of pellets shows a trend of “increasing first and then decreasing,” with the highest value reaching 3159 N pellet−1 at basicity of 0.5. As the basicity increases, calcium ferrate can be generated by CaO in the liquid phase with Fe2O3 in addition to silicate with SiO2, which will increase the amount of the liquid phase. With the increase of basicity, the oxide‐bonded induration is gradually weakened, and the slag‐bonded induration is gradually enhanced. A moderate amount of liquid phase can play the role of bonding and filling, thereby improving compressive strength.

Study of the influence of blast humidity on the reduction processes performance in blast furnace smelting

Study of the influence of blast humidity on the reduction processes performance in blast furnace smelting

The method of reducing energy consumption in large blast furnace smelting by low-silicon smelting

Currently, achieving carbon peaking and neutrality poses significant challenges for China's iron and steel industry. Low-carbon smelting in large blast furnaces (BFs) is poised to be a pivotal element in attaining the “double carbon” goal. This study, grounded in the fundamental process theory of blast furnace ironmaking, employs data analysis to investigate production technology across 25 large blast furnaces in China exceeding 4000 m3 in 2021. It specifically examines the correlation between pig iron silicon content and fuel consumption, elucidating strategies and techniques for low-silicon smelting. By exemplifying the reduction of silicon content in a 5050 m3 blast furnace of a Chinese enterprise, the study systematically delineates the low-silicon smelting process, including specific parameters and standards concerning fuel consumption, raw material conditions, and operational systems. The findings demonstrate that a reduction of 0.1% in pig iron silicon content can decrease carbonaceous fuel consumption by at least 5 kg/t. Given current raw material conditions and equipment levels, it is feasible to reduce the silicon content of iron in large-scale blast furnaces exceeding 4000 m3 in China to 0.3%.

Electric dehydration of coal tar – a by-product of coke production for blast furnace smelting

Electric dehydration of coal tar – a by-product of coke production for blast furnace smelting

Influence of preheating lump ore on blast furnace smelting energy saving and consumption reduction

The ironmaking process often produces a certain amount of waste heat and pressure, the use of this surplus energy to preheat the lump ore is a commonly used process, but the quality of each process of the material, or the stability of production, the performance optimisation of the lump ore after treatment, there are certain defects, based on practice, through the use of rotary kiln to preheat the lump ore gradually becomes a green environmental protection process measure, the application of the rotary kiln, makes the efficient utilisation of the lump ore possible, but for its optimisation principle is still little research, this paper through the pretreatment of the basic physical properties, metallurgical properties of the lump ore before and after experimental analysis. At the same time, combined with production practice, the relevant smelting parameters of the blast furnace after the application of different lump ore were compared and analysed, and the excellent impact of lump ore preheating on blast furnace smelting was determined and finally based on the calculation of carbon emissions, the industrial application prospect of preheated lump ore was evaluated from the perspective of environmental protection, and the impact of comprehensive scientific analysis, field practice, theoretical calculation and comprehensive analysis of the impact on lump preheating technology was carried out.

ВПЛИВ РУДНОВУГІЛЬНИХ КОМПОЗИЦІЙ У СКЛАДІ ШИХТИ НА ФОРМУВАННЯ ТЕРМІЧНО РЕЗЕРВНОЇ ЗОНИ ДОМЕННОЇ ПЕЧІ

The object of research is the technology of iron smelting when using ore-coal compositions. The purpose of the work is the effect of changing the composition of the blast furnace charge on the thermal state of the formation of the thermal reserve zone. Research methods - theoretical studies are based on the basic principles of physical chemistry and the theory of metallurgical processes. Experimental studies were carried out in laboratory and industrial conditions. Scientific novelty - there is a "coupling phenomenon" between recovery and gasification - this is a close contact between small particles of iron oxides and carbon, which is formed in the ore-coal composite, which ensures an increase in the efficiency of blast furnace smelting. Reduction of fuel consumption and, accordingly, the amount of gases per unit charge of modern blast furnace smelting, the height of the reserve zone is reduced; this zone is not observed in the vertical elements of the furnace with the maximum ore load. Practical significance - the use of ore-coal composites provides a high speed of iron recovery and carbon gasification reactions and a low initial temperature of carbon gasification of 250-420ºС, which is ensured by gas recirculation in the under burden, due to the short distance between the parts of iron-containing and carbon composites and their sizes, where the distance between them is short and the limit of the reaction is "visible" to both.

COMPLEX MATHEMATICAL MODEL OF THE PROCESS OF LOADING A MULTICOMPONENT CHARGE INTO A BLAST FURNACE

The rational mode of loading the blast furnace is the most important condition for its highly efficient operation. The selection of rational values of the control parameters of the load mode is carried out on the basis of information obtained with the help of instrumental tools and mathematical models. Mathematical models of the process of blast furnace loading are necessary components of expert (intelligent) control systems for blast furnace melting. The presented complex mathematical model of the process of loading a multicomponent charge into a blast furnace differs from known developments taking into account the redistribution of components into the volume of loaded portions during movement along the path "charge feed - blast furnace", which provides the possibility of obtaining calculated characteristics of the distribution of each component of the charge and determining the composition of the formed mixtures of charge materials in any given zone of the furnace. The existence of such a model opens up new opportunities in the management of the blast furnace smelting process, as well as in conducting analytical studies of the conditions of slag formation and the distribution of properties of melts across the section of the blast furnace.

Optimization of High-Alumina Blast Furnace Slag Based on Exergy Analysis

Raw material with a high Al2O3 content has led to an increase in the Al2O3 content in blast furnace slag, which has affected the normal operation of a blast furnace. The exergy analysis method is an important method for studying the energy utilization of high-alumina blast furnace smelting. In this paper, to investigate the impact of slag composition on exergy efficiency and optimize exergy efficiency during the smelting process of high Al2O3 iron ore, a gray box exergy analysis model of blast furnace smelting and an objective function for minimizing the total exergy loss were developed. The results indicated that the blast furnace smelting process had an exergy efficiency (η) of 28.29% for hot metal and slag; the exergy efficiency of the blast furnace did not significantly increase with the increasing w(MgO)/w(Al2O3) and R (w(CaO)/w(SiO2)), but the exergy efficiency of the blast furnace declined with increasing w(Al2O3). The regional optimal solution for the objective function method was 7129.42 MJ with slag compositions of R = 1.295, w(MgO)/w(Al2O3) = 0.545, and w(Al2O3) = 15%.

Combustion behavior of co-injecting flux, pulverized coal, and natural gas in blast furnace and its influence on blast furnace smelting

The integration of advanced high-ratio pellet ore smelting technology with flux injection at the blast furnace tuyere offers significant carbon emission and air pollution reductions for iron and steel manufacturers. This study presents a comprehensive thermogravimetric analysis and burnout rate assessment of Russian Bituminous Coal (RB) and flux mixtures across varying mass ratios, alongside a detailed exploration of the catalytic mechanisms of three distinct fluxes on RB combustion. The findings reveal that lime, when added to the coal-flux blend, markedly enhances the overall combustion characteristic index and catalytic impact, more so than limestone or dolomite. The optimal lime admixture of 5 % resulted in a peak S value of 6.30 and a burnout rate of 70.63 %, constituting an increase of 7.64 % over the base case without flux. Lime's superior catalytic performance is attributed to its higher content of calcium-containing compounds, which amplify catalytic activity through increased Ca2+ ion exchange with carboxyl groups. Mathematical model calculations considering the combustion rate of the pulverized coal show that: after the addition of 5 % lime, there is a 133.43 t/d increase in iron production, compared to the 11,323.98 t/d without the addition of flux. When the lime addition amount is 7 %, the proportion of sintered ore in the blast furnace decreases by 6.53 %, and the coke saving is 2.8 kg/t. This research is expected to enhance the understanding of pulverized coal combustion when amalgamated with basic fluxes and serve as a theoretical foundation for optimizing industrial applications.

ОСОБЕННОСТИ РАБОТЫ ДОМЕННОЙ ПЕЧИ НА АГЛОМЕРАТЕ РАЗНОЙ ОСНОВНОСТИ

The paper shows the peculiarities of blast furnace performance when different types of iron ore material are used. It is noted that the main types of iron ore raw materials are sinter and pellets, their advantages and disadvantages are given. The influence of increased pellet consumption on blast furnace smelting is indicated. The influence of sinter basicity on its strength and recoverability is noted. The results of calculating the indicators and the operation mode of the blast furnace at increased sinter basicity and an increased ratio between its consumption and pellets are presented.

Simulation and Validation of Thickness of Slag Crust on the Copper Stave in the High-Temperature Area of Blast Furnace

The blast furnace is the dominant high-temperature reactor in the modern ironmaking industry. Iron oxide in iron ores can be converted to metallic iron through blast furnace smelting, and this high-temperature melting can be used to separate the molten iron from the gangue components. The formation and thickness of the hot-surface slag crust on the copper stave in the high-temperature area of the middle and lower parts of the blast furnace are crucial for the safe operation and long campaign of the blast furnace. To enhance the precision of determining the thickness of the slag crust in this specific region, samples were extracted from the hot surface of the copper cooler situated in the high-temperature area. This extraction was carried out during the maintenance procedure of the blast furnace stockline. Subsequently, the thermal conductivity and melting performance of the slag crust were measured. The slag crust thicknesses corresponding to the various temperature measurement sites of the stave were determined by developing a mathematical model for the heat transfer of the copper stave. The actual slag crust thickness measurement data were acquired while the blast furnace stockline was in operation, and the data were then utilized to corroborate the model’s predictions. A blast furnace with an effective volume of 3200 m3 was used to test the model. The average thickness of the hot-surface slag crust was computed for cases that occurred between 2020 and 2022. The data’s correlations with the blast furnace’s technical and economic indices during the same time period were examined. The findings indicated that the blast furnace’s operation indices improved with a thinner slag crust, but there was also a higher chance of damage to the copper stave’s internal cooling water pipes. Taking into account the technical and economic indices as well as a long campaign of the blast furnace, 150–200 mm is recommended as the appropriate average slag crust thickness on the surface of the copper stave in the high-temperature section.

Improved back propagation neural network method for predicting sulfur content in hot metal

Blast furnace smelting is a traditional iron-making process. Its product, hot metal, is an important raw material for the production of steel. Steelmaking efficiency can be improved and steel product quality can be stabilized by using proper hot metal. Sulfur is an important indicator reflecting the quality of hot metal, it is necessary to establish an accurate prediction model to predict the sulfur content of hot metal, to effectively guide the production process. There is a non-linear relationship among the factors influencing the desulfurization effect during the blast furnace smelting process, and the back propagation neural network (BPNN) model has a strong ability to solve nonlinear problems. However, BPNN has the disadvantages of slow convergence speed and easy to fall into local minima. To improve the prediction accuracy, an improved algorithm combining Kmeans and BPNN is proposed in this paper. The study showed that compared with the BPNN model and case-based reasoning (CBR) model, the Kmeans-BPNN model has the lowest RMSE and MAPE values, which indicates a high degree of fit and a low degree of dispersion. The Kmeans-BPNN model has the largest HR value, which indicates the highest prediction accuracy. The proposed Kmeans-BPNN prediction model achieves a hit rate of 96%, which is 4.5% higher than before the improvement. It can effectively improve the prediction accuracy of hot metal sulfur content.

Effects of pellet ratio on the burden movement and distribution characteristics in the BF throat

In order to solve the urgent problem of energy conservation and emission reduction in the iron and steel industry, the use of high proportion pellets in blast furnace smelting will be the trend of ironmaking development in recent years. In the present work, a geometric model of a serial-hopper bell-less type charging system based on the discrete element method was built, which was used to investigate the distribution behavior of burden under the condition of multi-ring charging and different pellet ratios. The results show: (1) the overall velocity and particle flow width of the burden at the chute outlet become larger which results the average radius of falling point increases. (2) The pellet ratio has a significant effect on the distribution characteristics and the burden profiles at the furnace throat. When the pellet ratio increases from 0% to 100%, the relative radius of peak position of the burden layer increases from 0.491 R to 0.639 R, while the peak height decreases from 0.860 m to 0.543 m. (3) The burden segregation occurs at both the radial and longitudinal positions of the layer. In the radial position, the distribution of pellets near the center is relatively concentrated compared with sinter and there is no burden segregation occurs near the relative radius of 0.590 R. In the longitudinal position, the pellets are mainly distributed at the bottom of the burden layer, while the upper part is relatively less distributed. The research content and results may give a reference for the charging operation of BF under the condition of large pellet ratio, and consequently reduce CO2 emission in ironmaking process.

New insights into the influence of hydrogen on important parameters of blast furnace

In the pursuit of curbing carbon dioxide emissions, hydrogen is being explored as a substitute for coke in the blast furnace smelting process. This research delved into the potential of hydrogen to mitigate carbon emissions, employing a hydrogen-rich blast furnace model for calculations. A novel approach for preheating hydrogen through blast furnace injection was proposed, accompanied by a more scientifically rigorous CO2 assessment method. This approach encompassed not only CO2 generation during blast furnace smelting but also factors in CO2 emissions from the hot blast stove and hydrogen preheating stove. Simulation outcomes underscored the significant carbon reduction potential of hydrogen. However, it's noteworthy that introducing preheated hydrogen into the blast furnace didn't guarantee lower CO2 emissions. For hydrogen volumes below 300 m³/THM, CO2 emissions rose as hydrogen temperature increased. Conversely, when hydrogen injection surpasses 300 m3/THM, elevated hydrogen temperatures correspond with decreased CO2 emissions. The most significant reduction in CO2 emissions, amounting to 26.1%, occurred when hydrogen at 1250 °C was blown at a rate of 350 m³/THM. These findings contribute to a more comprehensive understanding of hydrogen's potential for emissions reduction, underscoring the importance of intricate factors in optimizing its implementation in the blast furnace smelting process.

Detoxication and recycling of chromium slag and C-bearing dust via composite agglomeration process (CAP)-blast furnace method

The utilization of virulent chromium slag has always been a worldwide problem, and lots of C-bearing dust produced in steel industry has not been utilized efficiently. Sintering is a potential method to treat these two kinds of solid wastes, but it is limited by small treatment capacity, incomplete detoxification of Cr(Ⅵ) when they were directly added into sintering process. In this study, an innovative technology of co-processing chromium slag and C-bearing dust via composite agglomeration process (CAP)-blast furnace method was put forward and systematically investigated. In the CAP, the chromium slag and C-bearing dust were first made into composite pellets and added into the matrix feed for co-sintering. The results showed that, 20% chromium slag and 5% C-bearing dust could be co-disposed by the CAP without destroying the quality of the sinters. Cr(VI) was completely reduced to Cr(III) or metal Cr. 12.83% Cr existed as metal Cr, and the rest of Cr existed in spinel as (Mg, Fe)(Cr, Al)2O4 or in silico-ferrite of calcium and alumina as Cr(Ⅲ). After blast furnace smelting, 90.22% Cr in sinters entered stainless mother liquor to be recycled.

Research and Application of Coupled Mechanism and Data-Driven Prediction of Blast Furnace Permeability Index

In order to ensure the stable operation of blast furnace production, it is necessary to keep abreast of the trends in the gas permeability index of the blast furnace. As one of the key parameters to be monitored in the process of blast furnace smelting, the gas permeability index directly reflects the performance of the blast furnace in the actual production of the furnace. Continuous monitoring of the permeability index is required in the actual production of the blast furnace in order to effectively guarantee the stable and smooth operation of the blast furnace. The aim of this study is to accurately predict the trend in the blast furnace gas permeability index by constructing an intelligent prediction model and utilizing a data-driven approach to monitor the gas permeability index and ensure the stable operation of the blast furnace. First, based on the actual production data of a #2 blast furnace of an iron and steel enterprise, an isolated forest algorithm is applied to detect and eliminate the outliers in the original data, and then a data driver set is constructed after normalization of the deviation. Second, by analyzing the coupling mechanism between the blast furnace permeability and gas flow, as well as Spearman correlation analysis and MIC maximum information coefficient (MIC) analysis, key parameters are screened out as feature variables from the data-driven set. Finally, a wavelet neural network algorithm is used to construct an intelligent prediction model of the blast furnace gas permeability index. Compared with a BP neural network (BP), a particle swarm-optimized BP neural network (PSO-BP), and XGBoost, the wavelet neural network shows obvious advantages when the error is controlled in the range of ±0.1, and the prediction accuracy can reach 95.71%. The model is applied to the actual production of a #2 blast furnace of an iron and steel enterprise, and the results show that the predicted value of the blast furnace permeability index is highly consistent with the actual value of real-time blast furnace production, which verifies its excellent characteristics.