Basic Oxygen Furnace Steelmaking Research Articles

New trends in basic oxygen furnace dephosphorization

Except for special grades of steel where it is used as an alloying element, phosphorus is regarded as an impurity that must be removed. Considering the conventional integrated iron and steelmaking, there are primarily two processes for phosphorus removal. The first is a hot metal dephosphorization (DeP) process that is applied to a blast furnace for hot metal before the steelmaking process. The second is the basic oxygen furnace steelmaking (BOS), a unique method primarily used for steelmaking, with the exception of stainless steels. Hot metal phosphorus content has a direct impact on BOS. An increase of phosphorus in hot metal is mainly related to the use of high P2O5 containing iron ores. In the current literature review, new trends of phosphorus removal in converter steelmaking are outlined. The double-slag practice was reported to be successful when hot metal P content was larger than 0.100%. It was indicated that the tapping temperature was critical for the production of low-phosphorus grades for which maximum allowable P content was 0.007% and that high tapping temperatures should be avoided. The tap-to-tap time for the double-slag process was slightly longer than the conventional converter steelmaking. It was further reported that the double-slag practice would be more economical than an establishment of a separate hot metal dephosphorization unit, if low-phosphorus grades did not have a significant share in the product mix of a steelmaking company. Endpoint phosphorus prediction was one of the important recent trends of converter steelmaking. A mixed injection of CO2-O2 to a basic oxygen furnace was applied to enhance dephosphorization, and promising results were reported. Unfortunately, a successful process for recycling of BOS dephosphorization slag has not been reported yet.

Research on making micro-beads by gas quenching from re-melted modified BOF steelmaking slag

ABSTRACTThe influence of the addition amount of conditioning agent, gas quenching pressure, nozzle type and slag temperature on gas quenching effect of basic oxygen furnace (BOF) steelmaking slag were studied through the gas quenching system. The results show that the gas quenching rate basically increased with the increase in the amount of the conditioning agent by using BF slag as a conditioning agent. High gas quenching pressure and high Mach number of nozzle had a slight promotion effect on gas quenching rate. While the modified slag temperature had a significant influence on the gas quenching rate. The higher the slag temperature and the superheat degree, the higher the gas quenching rate. Gas-quenched steel slag micro-beads property is related to the amount of the conditioning agent. The granulation effect became worse and the mineral phases gradually changed to the glass phase with the increasing amount of the conditioning agent.

A Dynamic Analytics Method Based on Multistage Modeling for a BOF Steelmaking Process

This paper proposes a dynamic analytics method based on the least squares support vector machine with a hybrid kernel to address real-time prediction problems in the converter steelmaking process. The hybrid kernel function is used to enhance the performance of the existing kernels. To improve the model’s accuracy, the internal parameters are optimized by a differential evolution algorithm. In light of the complex mechanisms of the converter steelmaking process, a multistage modeling strategy is designed instead of the traditional single-stage modeling method. Owing to the dynamic nature of the practical production process, great effort has been made to construct a dynamic model that uses the prediction error information based on the static model. The validity of the proposed method is verified through experiments on real-world data collected from a basic oxygen furnace steelmaking process. The results indicate that the proposed method can successfully solve dynamic prediction problems and outperforms other state-of-the-art methods in terms of prediction accuracy. Note to Practitioners —With the development of cyber-physical systems, abundant real-time data have been collected from the converter steelmaking process. These data provide an opportunity to solve product quality prediction problems using data-driven models. This paper proposes a dynamic analytics method based on the least squares support vector machine with a hybrid kernel to address this challenging issue. To improve the model’s performance, a differential evolution algorithm is used to optimize its parameters. Because of the fierce physicochemical reaction in the converter furnace, it is difficult for a single-stage model to achieve accurate predictions. Thus, a multistage modeling strategy is proposed to address this difficulty, and a dynamic model based on feedback error is developed to realize real-time prediction. We verify the effectiveness of the proposed method using real data from a basic oxygen furnace (BOF) steelmaking process. The computational results reveal that the proposed method has a higher prediction accuracy than other methods, making it helpful in guaranteeing the specified product quality and in maintaining stable BOF operation.

Research on coherent jet oxygen lance in BOF steelmaking process

The properties of conventional supersonic oxygen jet and coherent jet were simulated by Fluent in this paper. Their velocity field and jet radius were analyzed comparatively. The attenuation of gas jet was slowed down by the coherent jet oxygen lance. Besides, the effects of annular flow rate on the central oxygen jet velocity were also researched. It is showed that the core of the jet is gradually prolonged with the increase of annular gas flow rate. Based on the simulations, the designed coherent jet oxygen lance was experimented in 35 ton converter. It is found that the end-point phosphorus content is decreased from 0.024 to 0.016%, and dephosphorization rate is increased significantly, the average consumption of steel material is reduced by 3.4 kg/t, and iron-loss of slag is also reduced, which is favorable to improve oxygen utilization and metallic yield. This research provides good foundation for coherent jet technology promotion and application in Basic Oxygen Furnace (BOF).

End-point Prediction of BOF Steelmaking Based on KNNWTSVR and LWOA

Basic oxygen furnace (BOF) steelmaking plays an important role in steelmaking process. Therefore, research on BOF steelmaking modeling is very necessary. In this paper, a novel combination prediction model has been proposed, which consists of a time series prediction model and a compensation prediction model. Both models are established by k-nearest neighbor-based weighted twin support vector regression (KNNWTSVR) algorithm. By introducing Levy flight algorithm and inertia weight, an improved algorithm of whale optimization algorithm (WOA) called Levy flight WOA has been initially proposed to solve the optimization problem in the objective function of KNNWTSVR. The simulation results show that the proposed models are effective and feasible. Within different error bounds (0.005% for carbon content model and 10 °C for temperature model), the strike rates of carbon content and temperature both achieve 93%, and a double strike rate of 86% is obtained, which can provide a significant reference for real BOF applications, and the proposed method is also appropriate for the prediction models of other metallurgical applications.

Comparative Study of Estimation Methods of the Endpoint Temperature in Basic Oxygen Furnace Steelmaking Process with Selection of Input Parameters

The basic oxygen furnace (BOF) steelmaking process in the steel industry is highly complicated, and subject to variations in raw material composition. During the BOF steelmaking process, it is essential to maintain the carbon content and the endpoint temperature at their set points in the liquid steel. This paper presents intelligent models used to estimate the endpoint temperature in the basic oxygen furnace (BOF) steelmaking process. An artificial neural network (ANN) model and a least-squares support vector machine (LSSVM) model are proposed and their estimation performance compared. The classical partial least-squares (PLS) method was also compared with the others. Results of the estimations using the ANN, LSSVM and PLS models were compared with the operation data, and the root-mean square error (RMSE) for each model was calculated to evaluate estimation performance. The RMSE of the LSSVM model 15.91, which turned out to be the best estimation. RMSE values for the ANN and PLS models were 17.24 and 21.31, respectively, indicating their relative estimation performance. The essential input parameters used in the models can be selected by sensitivity analysis. The RMSE for each model was calculated again after a sequential input selection process was used to remove insignificant input parameters. The RMSE of the LSSVM was then 13.21, which is better than the previous RMSE with all 16 parameters. The results show that LSSVM model using 13 input parameters can be utilized to calculate the required values for oxygen volume and coolant needed to optimally adjust the steel target temperature. (Received July 30, 2018; Accepted September 28, 2018)

Hydration of dicalcium silicate and diffusion through neo-formed calcium-silicate-hydrates at weathered surfaces control the long-term leaching behaviour of basic oxygen furnace (BOF) steelmaking slag

Alkalinity generation and toxic trace metal (such as vanadium) leaching from basic oxygen furnace (BOF) steel slag particles must be properly understood and managed by pre-conditioning if beneficial reuse of slag is to be maximised. Water leaching under aerated conditions was investigated using fresh BOF slag at three different particle sizes (0.5–1.0, 2–5 and 10 × 10 × 20 mm blocks) and a 6-month pre-weathered block. There were several distinct leaching stages observed over time associated with different phases controlling the solution chemistry: (1) free-lime (CaO) dissolution (days 0–2); (2) dicalcium silicate (Ca2SiO4) dissolution (days 2–14) and (3) Ca–Si–H and CaCO3 formation and subsequent dissolution (days 14–73). Experiments with the smallest size fraction resulted in the highest Ca, Si and V concentrations, highlighting the role of surface area in controlling initial leaching. After ~2 weeks, the solution Ca/Si ratio (0.7–0.9) evolved to equal those found within a Ca–Si–H phase that replaced dicalcium silicate and free-lime phases in a 30- to 150-μm altered surface region. V release was a two-stage process; initially, V was released by dicalcium silicate dissolution, but V also isomorphically substituted for Si into the neo-formed Ca–Si–H in the alteration zone. Therefore, on longer timescales, the release of V to solution was primarily controlled by considerably slower Ca–Si–H dissolution rates, which decreased the rate of V release by an order of magnitude. Overall, the results indicate that the BOF slag leaching mechanism evolves from a situation initially dominated by rapid hydration and dissolution of primary dicalcium silicate/free-lime phases, to a slow diffusion limited process controlled by the solubility of secondary Ca–Si–H and CaCO3 phases that replace and cover more reactive primary slag phases at particle surfaces.

Mechanism of Vanadium Leaching during Surface Weathering of Basic Oxygen Furnace Steel Slag Blocks: A Microfocus X-ray Absorption Spectroscopy and Electron Microscopy Study.

Basic oxygen furnace (BOF) steelmaking slag is enriched in potentially toxic V which may become mobilized in high pH leachate during weathering. BOF slag was weathered under aerated and air-excluded conditions for 6 months prior to SEM/EDS and μXANES analysis to determine V host phases and speciation in both primary and secondary phases. Leached blocks show development of an altered region in which free lime and dicalcium silicate phases were absent and Ca-Si-H was precipitated (CaCO3 was also present under aerated conditions). μXANES analyses show that V was released to solution as V(V) during dicalcium silicate dissolution and some V was incorporated into neo-formed Ca-Si-H. Higher V concentrations were observed in leachate under aerated conditions than in the air-excluded leaching experiment. Aqueous V concentrations were controlled by Ca3(VO4)2 solubility, which demonstrate an inverse relationship between Ca and V concentrations. Under air-excluded conditions Ca concentrations were controlled by dicalcium silicate dissolution and Ca-Si-H precipitation, leading to relatively high Ca and correspondingly low V concentrations. Formation of CaCO3 under aerated conditions provided a sink for aqueous Ca, allowing higher V concentrations limited by kinetic dissolution rates of dicalcium silicate. Thus, V release may be slowed by the precipitation of secondary phases in the altered region, improving the prospects for slag reuse.

Preparation of hybrid porous carbon using black liquor lignin impregnated with steelmaking slag and its performance in SO2 removal

A hybrid porous adsorbent was produced by mixing black liquor lignin (BL) with basic oxygen furnace steelmaking slag (SS) followed by carbonization at 860°C for removal of trace sulfur dioxide (SO2) from air. The effects of BL percentage, carbonization temperature, carbonization duration and the binary combined effect of each individual process parameter on the removal of SO2 have been statistically analyzed. The optimal preparation conditions were 48% = BL/(BL + SS), carbonized at 860°C for 50 minutes (labeled BL‐SS‐48‐860‐50). The crystallite CaO and MgO phases remained in the hybrid matrix. A carbonization temperature over 800°C facilitated gasification reaction between the carbon matrix and the CO2 emitted from the decomposition of calcium and magnesium carbonate, which led to the pore formation and enlargement in the carbon matrix. The prepared hybrid adsorbent showed good SO2 removal performance. The kinetic model demonstrated satisfying results in predicting SO2 adsorption kinetics with good prediction within a relative large range of SO2 inlet concentration. The mass transfer coefficient k = 537 (s−1) was obtained by fitting the model to the experimental breakthrough curve. © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1417–1427, 2017

CO2 mineralization using basic oxygen furnace slag: process optimization by response surface methodology

The basic oxygen furnace steelmaking slag (SL) is employed for CO2 mineralization. Response surface methodology and the central composite design were employed in determining the optimal condition. The optimization goal in this paper has been set for maximum CO2 capturing. It was found that the reaction temperature and CO2 pressure and their combination were significant. A quadratic model was developed for process optimization and statistical experimental designs. The CO2 capture capacity could reach 126 g CO2/kg SL at optimal condition. The increased reaction temperature will lead to an obvious decrease of CaCO3 and increase of MgCO3. If deployed, this optimized indirect CO2 mineral sequestration process could permanently capture 252,000 tons of CO2 per annum based upon current 2 million tons of SL productivity per annum.

Understanding Characteristic of Abrasion of Refractory Lining Caused by Bath Oscillation in BOF Steelmaking

This paper presents a numerical study of the refractory abrasion occurring widely inside basic oxygen furnace (BOF) steelmaking. The mechanism of refractory abrasion is examined numerically referring to the bath oscillation with regard to flows, turbulence and wall shear stress inside a BOF. The simulation results reveal that the refractory abrasion tends to occur on the wall region between the slag/atmosphere and slag/metal interfaces due to the oscillation of the bath in the blowing process, which generally promotes slag-line erosion. The decreased nozzle angle, and either increased lance height or operation pressure can lead to more serious refractory erosion that occurs more likely during the slag-making period in the operation of BOF.

Influence of process parameters on carbonation rate and conversion of steelmaking slags – Introduction of the ‘carbonation weathering rate’

AbstractAlkaline industrial wastes are considered potential resources for the mitigation of CO2 emissions by simultaneously capturing and sequestering CO2 through mineralization. Mineralization safely and permanently stores CO2 through its reaction with alkaline earth metals. These elements are found in a variety of abundantly available industrial wastes that have high reactivity with CO2, and that are generated close to the emission point‐sources. Among all suitable industrial wastes, steelmaking slag has been deemed the most promising given its high CO2 uptake potential. In this paper, we review recent publications related to the influence of process parameters on the carbonation rate and conversion extent of steelmaking slags, comparing and analyzing them in order to define the present state of the art. Furthermore, the maximum conversions resulting from different studies are directly compared using a new index, the Carbonation Weathering Rate (CWR), which normalizes the results based on particle size and reaction duration. To date, the carbonation of Basic Oxygen Furnace steelmaking slag, under mild conditions, presents both the highest carbonation conversion and CWR, with values equal to 93.5% and 0.62 μm/min, respectively. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

Recent experiences with improving steel-to-hot-metal ratio in BOF steelmaking

After the American company U.S. Steel pulled out of Serbia, the Serbian government decided to continue the steel production in Železara Smederevo. Given the unfavorable market conditions, this decision requires taking all necessary steps to reduce production costs in the time to come. Since most of the production losses occur during Basic Oxygen Furnace (BOF) process, this paper focuses on this stage of steel production. We provide an overview of related experiences in other steel plants as well as earlier production experiences in Železara Smederevo, and propose cost saving measures that will improve the overall business position of the Serbia's only one steel producer. These measures do not require new investments.

Determination of Cavity Dimensions Induced by Impingement of Gas Jets onto a Liquid Bath

This paper presents an experimental and theoretical study on the cavity profile induced by the impingement of top-blown multiple gas jets onto a water or oil/water bath. The depth and diameter of the cavity were measured with respect to the lance height, gas flow rate, jets inclination angle, and oil volume. The experimental results show that the cavity depth increases with the increase of gas flow rate or oil thickness but the decrease of lance height or jets inclination angle. The cavity diameter is much less affected by gas flow rate compared to other variables. Then, the importance of the surface tension in the modeling of the cavity was theoretically identified. It was found that in the cratering process, the effect of the liquid surface tension on the cavity depth could be remarkably significant for a basic oxygen furnace (BOF) cold model but negligible for a real BOF steelmaking system. An improved theoretical model was hence proposed and validated using the experimental data obtained from both the single- or two-layer liquid baths. The new model includes not only the explicit consideration of the liquid surface tension but also that of the energy utilization efficiency of the jets impinging kinetic energy contributed to the cratering process.

Recycling of basic oxygen furnace steelmaking dust by in-process separation of zinc from the dust

High zinc content in solid wastes from basic oxygen furnace steelmaking offgas cleaning systems is one of the main barriers for source recycling of the solid wastes back into ironmaking and steelmaking process. Over-limit zinc loadings to blast furnaces might damage blast furnace refractory materials, and hence shorten blast furnace campaign life. In addition, high zinc input into blast furnaces might also cause operation difficulties of the blast furnaces, and thus decrease blast furnace productivities. Therefore, how to separate zinc from the solid wastes in an economic way becomes a crucial step for recycling of the solid wastes in sintering–blast furnace ironmaking process. There are three general strategies of separating zinc from the solid wastes, which are referred to as before-process separation, post-process separation and in-process separation. In-process separation is to separate zinc from the solid wastes in the process while the solid wastes are being collected. In this research paper, industrial trials are reported on measuring zinc distributions in dry offgas cleaning systems of two ArcelorMittal basic oxygen furnace steelmaking plants. The results show that primary dusts contain negligible zinc and have good qualities comparable with virgin iron ores. Therefore, in-process separation strategy has a potential to be applied in existing basic oxygen furnace steelmaking offgas cleaning systems to make cleaner offgas byproducts without revamping the offgas cleaning systems. However, in order to recycle more of the solid wastes with low level of zinc, it will be needed to install high-efficiency primary dust collectors and more advanced offgas pre-conditioning mechanisms prior to the primary dust collectors.

Material Flow Analysis of CO2 Emissions from Blast Furnace and Basic Oxygen Furnace Steelmaking Systems in China

In China, iron and steel plants are confronted with increased demands to reduce their CO2 emissions. Data on CO2 emissions derived from iron and steel making is a basic requirement for a certificate of CO2 reduction. In the current paper, carbon flows from blast furnace and basic oxygen furnace (BF‐BOF) steelmaking systems are analyzed using Material Flow Analysis (MFA). The computation method is built and used to calculate CO2 emissions in three steel works. The amount of carbon flow and CO2 emission per ton of product () of each process in BF‐BOF steeling systems is obtained. The results show that the of each process varies significantly. As for the highest percentage of parts, the of the blast furnace iron making is greater than 700 kg on average; however, the of casting is only roughly 50 kg. The of the same process is more influenced by the firm size, and the main production equipment scale plays a small role. In the end, the input of coal and coke is decreased by using charcoal instead, CO2 is removed from blast furnace gas along with carbon capture and storage, and traditional energy saving approaches/technologies for CO2 reduction for the iron and steel industry are introduced.

Phosphorus: The Noose of Sustainability and Renewability in Steelmaking

With rising ore prices and the continued demand for higher quality steels, much work has been carried out into refining and control prospects of steel chemistry. As several technologies around the world are exploring the control of phosphorus with high priority, an overview of current knowledge, ongoing research, and specific interest areas is presented. The reliance of the basic oxygen furnace steelmaking on iron ore quality is considered with regard to impurity levels, as well as the phosphorus content of direct reduced iron introduction to the electric arc furnace process. This article reviews methods to control phosphorus in steelmaking and proposes a practical approach based on laboratory-scale equilibrium experiments. The article ends by exploring energy savings in steelmaking as well as speculating on further avenues of steel production profitability.

Basic oxygen furnace steelmaking end-point prediction based on computer vision and general regression neural network

End-point prediction is one of the most difficult problems in basic oxygen furnace (BOF) steelmaking process. To address this problem, some researchers have proposed some methods based on flame image processing and pattern classification. Because of the dynamically changing flame and real-time needs during the blowing process, there are still some issues that need to be solved. We propose a novel method based on accurate and fast multi flame features extraction and general regression neural network (GRNN). Firstly, flame images were acquired, and then the background of each image was removed via color similarity determination algorithm; secondly, color, texture, and boundary features were extracted; the fast and robust boundary and texture features were extracted by using the proposed methods, and these features were tested for their validity to the end-point prediction via comparing them with some other similar methods; finally, the prediction model was built using multi-features and GRNN. The experimental results demonstrated that it is accurate and fast to use the proposed method to the BOF end-point predict.

Receptor modelling of airborne particulate matter in the vicinity of a major steelworks site

In this study, the Multilinear Engine (ME-2) receptor model was applied to speciated particulate matter concentration data collected with two different measuring instruments upwind and downwind of a steelworks complex in Port Talbot, South Wales, United Kingdom. Hourly and daily PM samples were collected with Streaker and Partisol samplers, respectively, during a one month sampling campaign between April 18 and May 16, 2012. Daily samples (PM10, PM2.5, PM2.5–10) were analysed for trace metals and water-soluble ions using standard procedures. Hourly samples (PM2.5 and PM2.5–10) were assayed for 22 elements by Particle Induced X-ray Emission (PIXE). PM10 data analysis using ME-2 resolved 6 factors from both datasets identifying different steel processing units including emissions from the blast furnaces (BF), the basic oxygen furnace steelmaking plant (BOS), the coke-making plant, and the sinter plant. Steelworks emissions were the main contributors to PM10 accounting for 45% of the mass when including also secondary aerosol. The blast furnaces were the largest emitter of primary PM10 in the study area, explaining about one-fifth of the mass. Other source contributions to PM10 were from marine aerosol (28%), traffic (16%), and background aerosol (11%). ME-2 analysis was also performed on daily PM2.5 and PM2.5–10 data resolving 7 and 6 factors, respectively. The largest contributions to PM2.5–10 were from marine aerosol (30%) and blast furnace emissions (28%). Secondary components explained one-half of PM2.5 mass. The influence of steelworks sources on ambient particulate matter at Port Talbot was distinguishable for several separate processing sections within the steelworks in all PM fractions.

Simulation of Flow Fluid in the BOF Steelmaking Process

The basic oxygen furnace (BOF) smelting process consists of different chemical reactions among oxygen, slag, and molten steel, which engenders a vigorous stirring process to promote slagging, dephosphorization, decarbonization, heating of molten steel, and homogenization of steel composition and temperature. Therefore, the oxygen flow rate, lance height, and slag thickness vary during the smelting process. This simulation demonstrated a three-dimensional mathematical model for a 100 t converter applying four-hole supersonic oxygen lance and simulated the effect of oxygen flow rate, lance height, and slag thickness on the flow of molten bath. It is found that as the oxygen flow rate increases, the impact area and depth increases, which increases the flow speed in the molten bath and decreases the area of dead zone. Low oxygen lance height benefits the increase of impact depth and accelerates the flow speed of liquid steel on the surface of the bath, while high oxygen lance height benefits the increase of impact area, thereafter enhances the uniform distribution of radial velocity in the molten steel and increases the flow velocity of molten steel at the bottom of furnace hearth. As the slag thickness increases, the diameter of impinging cavity on the slag and steel surface decreases. The radial velocity of liquid steel in the molten bath is well distributed when the jet flow impact on the slag layer increases.