Model of burden distribution in operating blast furnaces

Numerical investigation of burden distribution in ironmaking blast furnace

At blast furnace B at Salzgitter Flachstahl a series of innovative measuring techniques are installed to monitor the processes at the blast furnace top, making this furnace one of the best equipped furnaces in Europe. These techniques comprise full 2D measurement of the temperature profile of the top gas shortly above the burden surface, 3D radar scan of the whole burden surface and online measurement of the dust concentration in the top gas. After more than 5 years’ experience with most of these techniques, they enable to better understand the complex chemical and physical interrelations occurring in the BF stack between the ascending process gas and the descending solid burden. A couple of examples of incidents that were monitored are presented in this article, including influences of charging programmes on top gas temperature profiles and influences of disturbed gas solids interaction on the BF working state. The new measuring techniques with tailor-made data processing enable the operators to gain a better picture of the processes currently occurring in the blast furnace, consequently supporting them in keeping the blast furnace operation as stable and efficient as possible.

Obtaining a high-precision 3-D burden surface (BS) shape of a blast furnace (BF) is of significance for improving energy efficiency in the ironmaking process, and for stabilizing the operation of the BF. However, existing methods used for detecting the BS cannot provide precise data to guide the burden distribution operation of the BF effectively, because they cannot overcome the harsh environment inside the BF. Therefore, to obtain a reliable BS shape under a high-temperature, high-pressure, high-dust, and low-light environment, a 3-D high-temperature industrial endoscope with a large depth of field and wide field of view is proposed in this article. First, image-forming optical system indices are obtained by analyzing the environmental factors and geometry of the BF. Based on these indices, an optical system with a large depth of field, wide field of view, and low-light imaging capacity is designed. Next, a 3-D depth calculation method based on a virtual and real twin binocular optical system is used to obtain 3-D depth of feature points on the burden distribution ring. Furthermore, a functional relationship model between the image defocusing degree and depth of the BS is established, based on the 3-D depth. Finally, a monocular vision 3-D reconstruction method based on the depth from defocus parameter is used to realize the 3-D reconstruction of the BS. Experimental industrial applications of the proposed device demonstrate that it can provide data support for the BF burden distribution operation and has a significant industrial application value.

The blast furnace (BF) operation, as well as the steel‐shop downstream, can derive benefits from adjusting the slag alumina content with the proper addition of bauxite flux to its burden. Additions of 5‐15 kg of bauxite/t hot metal lead to a raise of the alumina content of the resultant BF‐slag from 10% to the level of about 12%. In Hellas extensive deposits of diasporic bauxite exist which, however, are under‐utilized by the alumina refineries due to their rather low solubility during the Bayer‐process. The above BF application, therefore, as an alternative use of the diasporic bauxite, is of great interest to the bauxite producers of Hellas.The influence of the bauxite additions on the metal/slag reactions under BF‐conditions was simulated in the laboratory by smelting BF‐slag with diasporic bauxite additions in a graphite crucible. It was achieved the production of BF‐slags with higher alumina contents under the condition of constant slag basicity. The results show the beneficial effect of the bauxite addition to the quality of the produced hot metal. In accordance to its desulphurization and desiliconization as well as the increase of BF‐slag sulphur capacity and fluidity, a thermodynamic evaluation of the metal/slag reaction in respect of SiO2 reduction and S‐transfer to the slag in relation to its Al2O3 content was carried out. This evaluation led to simple algebraic functions and graphs easily applicable by the BF operators. The attained metallurgical results were verified in comparison to industrial test heats with bauxite additions in the BF‐burden in USA, Canada and Europe.

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This review presents some of the recent advances in ironmaking technology in Australia. The first part of the paper summarises blast furnace operations in terms of productivity, fuel rate and hot metal chemistry in BHP. It is shown that in the recent past Australian furnace operations have been characterised by high productivity and low fuel rate. In the second part of the review, the main blast furnace research and development topics are presented. The first of two research streams, which is shorter term in focus, is associated with the development and implementation of computer models and associated sensors to assist present operations. Some of the developments which are reviewed in this field include burden distribution studies, models of the momentum, heat and mass transfer processes occurring in the furnace, raceway studies, opto-electronic and other sensor developments, and studies associated with hearth liquid drainage. The second stream, which addresses longer term strategies, is associated with studies on future blast furnace operations. In this stream, research work on the combustibility of pulverised coals in the blast furnace environment is described. The results shown indicate that Australian research has made a substantial contribution to knowledge in blast furnace ironmaking, and that the studies undertaken are of considerable benefit to Australian blast furnace operations.

The top gas temperature is an apparent indicator of the distribution state of gas flow, and it is an important parameter to judge the furnace condition. It is related to the top equipment in addition to the charge characteristics and bottom-up generation and distribution. Therefore, the fluid-solid heat transfer model from burden surface -chute-rising ducts is established in this paper. The finite element method is used to calculate the flow and heat transfer of the gas at the top of the blast furnace, and the influence of the chute on the top gas temperature is analyzed. The accuracy of the model is verified by the actual blast furnace top temperature. The results show that the chute has a guiding effect on the gas flow. As the chute rotates, the top gas temperature fluctuates. This research is helpful for actual blast furnace operators to understand the top temperature and make the condition judgment more accurate.

Accurate measurement of the position and shape of the blast furnace (BF) burden surface (BS) is crucial for automated and intelligent BF control. The detection method based on key points of BS can improve the accuracy of radar BS detection in challenging environments with strong interference, ensuring long-term detection accuracy stability across long maintenance intervals. However, transferring a successfully applied detection model from the original BF to a new target BF requires sufficient sample collection in the target BF and model retraining. In practical scenario, data collection is often constrained by plenty of factors like time, space, and personnel. Thus, reducing the number of samples needed for retraining, or implementing model transfer based on small samples, can significantly boost BS detection efficiency. This paper proposes a Conv-Adapter Transfer Net (CATNet) designed for the transfer problem of key point detection models in BFBS and small sample scenarios. The CATNet adopts a newly designed parallel Conv-Adapter transfer module, a small-scale deep learning network with a minimal parameter quantity. Compared to fine-tuning the entire backbone model with a large number of parameters, retraining this transfer module requires far less training data. Therefore, CATNet is more suitable for model transfer in small sample scenarios. The experimental results demonstrate that the CATNet can exhibit strong transfer capability and higher prediction accuracy than the commonly used pretrain-finetune method in small sample scenarios, thereby enhancing the efficiency of model transfer across different BFs.

Model Predictive Control of Molten Iron and Slag Quality Indices in a Large-scale Ironmaking Blast Furnace using a Hybrid Dynamic Model*

Most of the waste plastics are incinerated and landfilled now, leading to much environmental problems. The technology of injection into the blast furnace was developed as a useful recycling method of waste plastics, and applied to the actual operation in several ironmaking companies. We carried out the test operation to inject continuously the two kinds of waste plastics through four tuyeres of the Foundry blast furnace in POSCO by 130 ton of total amount. From this test operation, we analyzed the coke replacement ratio, the permeability, the heat load and other changes of furnace conditions with the injection of waste plastics into the blast furnace. Some trials based upon the theoretical approaches were applied to examine the efficiencies of blast furnace.

Radar technology is performed to obtain the position and morphology of burden surface in blast furnace, which is conducive to the optimal process of decision-making over burden distribution. Considering the imaging of the of echo spectrum, includes the characteristics of local highlighting and low signal-to-noise ratio, the adaptive gray-scale compensation algorithm combined with multi-scale Retinex image enhancement is adopted for high-quality brightness adjustment and color correction. Then, in order to make the target burden surface prominent and distinguishable, the improved hot metal coding method is applied to conduct pseudo-color processing of the enhanced image as obtained previously. In the meantime, the guided image filtering algorithm is introduced to maintain the target boundary of the burden surface while ensuring the effective removal of noise. Finally, the fractal interpolation algorithm is employed in line with the principle of SAR imaging to reconstruct the radar image of burden surface in blast furnace. Moreover, a qualitative analysis is conducted during production of the major characteristics of burden surface.

Real-time and accurate measurement of blast furnace (BF) stockline is important for charging control and BF safety. However, traditional non-contact methods for stockline detection face many challenges such as low accuracy, poor anti-interference ability, and stability in harsh BF environments. The high-temperature novel industrial endoscope (NIE), a visible light detection equipment for BF burden surface (BBS), has captured real-time and continuous video streams of BBS, which provides a brand-new means and ideas for non-contact stockline detection. Based on this, a novel non-contact stockline detection method based on real-time burden surface video streams is proposed. First, an edge detection network based on bootstrap sampling and eigenvector coding clustering (ECC) is established to extract accurate edge distribution of burden surface video streams. Then, an actual imaging region model of the NIE is developed by the latitude circle method to quantify the relationship between the actual imaging region and the BF stockline. Finally, the edge of burden surface video streams is correlated with the corresponding actual imaging region through the NIE imaging model, and the non-contact stockline detection model is derived to realize the BF stockline detection based on video streams. Experiments and industrial applications show that the proposed method is superior to the traditional non-contact stockline detection methods in terms of detection accuracy, stability, and real-time performance.

An ironmaking blast furnace (BF) is a complex high-temperature moving bed reactor involving counter-, co- and cross-current flows of gas, liquid and solid, coupled with heat and mass exchange and chemical reactions. Two-dimensional (2D) models were widely used for understanding its internal state in the past. In this paper, a three-dimensional (3D) CFX-based mathematical model is developed for describing the internal state of a BF in terms of multiphase flow and the related thermochemical behavior, as well as process indicators. This model considers the intense interactions between gas, solid and liquid phases, and also their competition for the space. The model is applied to a BF covering from the burden surface at the top to the liquid surface in the hearth, where the raceway cavity is considered explicitly. The results show that the key in-furnace phenomena such as flow/temperature patterns and component distributions of solid, gas and liquid phases can be described and characterized in different regions inside the BF, including the gas and liquids flow circumferentially over the 3D raceway surface. The in-furnace distributions of key performance indicators such as reduction degree and gas utilization can also be predicted. This model offers a cost-effective tool to understand and control the complex BF flow and performance.

An actual direction in the development of blast-furnace smelting technology is the implementation of stable operating modes of blast furnaces in terms of the parameters of the used charge materials and hot combined blast. For this purpose, complex indicators characterizing the thermal and reduction modes of blast furnace smelting, and integral indicators of iron ore raw materials (IORM) quality are being studied. The object of the study is the blast furnace process under the conditions of PJSC NLMK. The database of the main indicators of the operation of blast furnaces No. 4, 6 and 7 for the period 2013–2018 was analyzed. The furnaces operate under raw material conditions, with similar combined blast parameters and coke consumption. When the consumption of natural gas, pulverized coal and process oxygen changes, the values of the degree of compensation (the ratio of the consumption of reducing additives to the consumption of process oxygen) are in the range of 0.9–1.1. This provides a constant level of hearth heating, stability of the gas-dynamic mode of melting and coke consumption. At the same time, the different level of development of the processes of indirect (Ri) and direct (rd) reduction in blast furnaces No. 4, 6 and 7 makes it possible to perform correct studies of the features of blast furnace smelting in a wide range of Ri and rd values. It has been established that under the conditions of stable operation of blast furnaces on raw materials from sinter and pellets using combined blast, the type of dependence of the sulfur and silicon content in pig iron on the values of the integrated iron ore raw materials quality index is determined by degree development level of direct reduction processes rd. It has been established that the mode of blast furnace smelting with natural gas, pulverized coal and process oxygen, characterized by the level of rd values less than 20–25 %, is distinguished by the presence of a pronounced extreme dependence of coke consumption and productivity on the parameters of the combined blast.

The application of carbon composite briquette (CCB) is considered to be an efficient method for achieving low-energy and low-CO2-emission blast furnace (BF) operations. In this research, a combined experimental and numerical study was conducted on the CCB reaction behavior in BF. The CCB used in this study had a composition of 20.10 wt.% carbon, 29.70 wt.% magnetite, 39.70 wt.% wüstite, and 1.57 wt.% metallic iron. Using the prepared CCB samples, isotherm reduction tests under a simulated BF atmosphere (CO-CO2-N2) were conducted and a reaction model was developed. Subsequently, the reaction behavior of CCB along the mid-radial solid descending path in an actual BF of 2500 m3 was analyzed by numerical simulations based on the experimental findings and the previous results of comprehensive BF modeling. The results of the experiments showed that the CCB model predictions agreed well with the experimental measurements. With respect to the BF, the results of the numerical simulations indicated that, along the path, before the CCB temperature reached 1000 K, the CCB was reduced by CO in the BF gas; when its temperature was in the range from 1000 to 1130 K, it underwent self-reduction and contributed both CO and CO2 to the BF gas; when its temperature was above 1130 K, it only presented carbon gasification. Moreover, these results also revealed that the reduction of iron oxide and the gasification of carbon inside the CCB proceeded under an uneven mode. The uneven radial distribution of the local reduction fraction and local carbon conversion were evident in the self-reducing stage of the CCB.