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Metals
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Advanced Metal Smelting Technology and Prospects
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Advanced Metal Smelting Technology and Prospects

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Extractive Metallurgy".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4964

Special Issue Editor

Dr. Dongdong Zhou

E-Mail Website
Guest Editor
Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China
Interests: metallurgy; machine vision; multispectral imaging; process optimization

Special Issue Information

Dear Colleagues,

Since the majority of the industry is still occupied by the lengthy iron and steel metallurgical process, of which ironmaking is the primary component, the focus of ironmaking technology development has switched to a low-carbon and green development model due to the quick development of typical low-carbon ironmaking technologies, including oxygen blast furnaces and hydrogen shaft furnaces. It is necessary to discuss innovative ironmaking technology through the Special Issue titled ‘Situation and Prospect of Ironmaking Processes’ to further promote the development of the ironmaking industry, addressing the industry's requirements for high-quality ironmaking technology, green and low-carbon development, quantitative control, and resource-intensive diversification. Papers on low-carbon ironmaking, intelligent detection, big data and mechanism fusion modeling, solid–gas–liquid simulation model, process optimization, and other associated technologies will be the main emphasis of this Special Issue.

Dr. Dongdong Zhou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • low-carbon ironmaking
  • intelligent detection
  • process optimization
  • new technology of ironmaking
  • simulation model
  • big data and mechanism fusion modeling

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Published Papers (5 papers)

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Research

12 pages, 3428 KiB  
Article
Kinetic Analysis of Molten Oxide Reduction Using Bottom-Blown Hydrogen Injection
by Lijin Lu, Feng Wang, Haifeng Wang, Jian Qiu and Xiaodong Ping
Metals 2024, 14(11), 1255; https://doi.org/10.3390/met14111255 - 5 Nov 2024
Viewed by 424
Abstract
Hydrogen-based smelting reduction has received widespread attention as an important technology for realizing low-carbon development in hydrogen metallurgy. In this study, the thermodynamics of smelting reduction was firstly analyzed by using FactSage 8.1 thermodynamic software, on the basis of which smelting reduction experiments [...] Read more.
Hydrogen-based smelting reduction has received widespread attention as an important technology for realizing low-carbon development in hydrogen metallurgy. In this study, the thermodynamics of smelting reduction was firstly analyzed by using FactSage 8.1 thermodynamic software, on the basis of which smelting reduction experiments of iron oxides by using bottom-blown hydrogen were carried out. The experiments used oxidized pellets as experimental materials, and the effects of the reduction process were analyzed in terms of the reduction temperature, the reduction time, and the hydrogen flow rate. The experimental results show that under the experimental conditions of a temperature of 1550 °C and a hydrogen flow rate of 0.2 Nm3/h, the reduction rate of iron oxides in the process of reducing iron oxides by hydrogen is significantly faster in the first 10 min than after 10 min. The hydrogen utilization rate reached a maximum of 41.87%, then decreased continuously and finally maintained at about 20%. Using the method of model fitting, it was found that the hydrogen-based molten reduction conformed to the phase boundary reaction model (Gα=1−(1−α)1/2), the corresponding mechanism function is fα=2(1−α)1/2, where α stands for the reduction conversion, and the reaction rate constant k(T) is 2.37 × 10−4 s−1 under the experimental conditions. Full article
(This article belongs to the Special Issue Advanced Metal Smelting Technology and Prospects)
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15 pages, 4289 KiB  
Article
Fluid Dynamics Studies on Bottom Liquid Detachment from a Rising Bubble Crossing a Liquid–Liquid Interface
by Xiangfeng Cheng, Gele Qing, Zhixing Zhao and Baojun Zhao
Metals 2024, 14(9), 1005; https://doi.org/10.3390/met14091005 - 2 Sep 2024
Viewed by 610
Abstract
The detachment regimes and corresponding detachment height of lower liquid from a coated bubble during the bubble passage through an immiscible liquid–liquid interface were studied. High-speed imaging techniques were used to visualize the lower liquid detachment from a rising bubble near the interface. [...] Read more.
The detachment regimes and corresponding detachment height of lower liquid from a coated bubble during the bubble passage through an immiscible liquid–liquid interface were studied. High-speed imaging techniques were used to visualize the lower liquid detachment from a rising bubble near the interface. Analysis of industrial slag samples by a scanning electron microscope (SEM) was also carried out. The results indicate that the detachment height of lower liquid from a rising bubble showed a distinct correlation to penetration regimes. Bubble size and a fluid’s physical properties exerted a significant influence on the detachment height of the lower liquid. The detachment height for medium bubbles (Weber number: 4~4.5; Bond number: 2.5~7.5) varied significantly with increasing bubble size, which contributes to the lower liquid entrainment in the upper phase due, significantly, to the higher detachment height and large entrainment volume. The maximum detachment height for large bubbles is limited to approximately 100 mm due to the early detachment with the liquid column at the interface though large bubbles transporting a larger volume of lower liquid into the upper phase. Full article
(This article belongs to the Special Issue Advanced Metal Smelting Technology and Prospects)
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27 pages, 7644 KiB  
Article
Research on Molten Iron Quality Prediction Based on Machine Learning
by Ran Liu, Zi-Yang Gao, Hong-Yang Li, Xiao-Jie Liu and Qing Lv
Metals 2024, 14(8), 856; https://doi.org/10.3390/met14080856 - 26 Jul 2024
Cited by 1 | Viewed by 1102
Abstract
The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction [...] Read more.
The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production. Full article
(This article belongs to the Special Issue Advanced Metal Smelting Technology and Prospects)
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27 pages, 2854 KiB  
Article
Research on Blast Furnace Ingredient Optimization Based on Improved Grey Wolf Optimization Algorithm
by Ran Liu, Zi-Yang Gao, Hong-Yang Li, Xiao-Jie Liu and Qing Lv
Metals 2024, 14(7), 798; https://doi.org/10.3390/met14070798 - 8 Jul 2024
Viewed by 838
Abstract
Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, [...] Read more.
Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, this study examines the optimization of the ingredient ratio. In this paper a model of the blast furnace ingredients is established by considering cost of per ton iron, CO2 emissions, and the theoretical coke ratio as the objective functions; ingredient parameters, process parameters, main and by-product parameters as variables; and the blast furnace smelting theory and equilibrium equation as constraints. Then, the model is solved by using an improved grey wolf optimization algorithm and an improved multi-objective grey wolf optimization algorithm. Using the data collected from the steel mill, the conclusion is that multi-objective optimization can consider the indexes of each target, so that the values of all the targets are excellent; we also compared the multi-objective solution results with the original production scheme of the steel mill, and we found that using the blast furnace ingredient scheme optimized in this study can reduce the cost of iron per ton, CO2 emissions per ton, and the theoretical coke ratio in blast furnace production by 350 CNY/t, 1000 kg/t, and 20 kg/t, respectively, compared with the original production plan. Thus, steel mill decision makers can choose the blast furnace ingredients according to different business strategies and the actual needs of steel mills can be better met. Full article
(This article belongs to the Special Issue Advanced Metal Smelting Technology and Prospects)
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15 pages, 8991 KiB  
Article
Study of Tuyere Combustion Flame Temperature in Vanadium and Titanium Blast Furnaces by Machine Vision and Colorimetric Thermometry
by Haoyu Cai, Ziming Zhu and Dongdong Zhou
Metals 2024, 14(5), 499; https://doi.org/10.3390/met14050499 - 25 Apr 2024
Cited by 1 | Viewed by 1278
Abstract
The steel industry is an important foundation of the national economy and the livelihood of the people, producing a large amount of carbon dioxide gas, accounting for about 70% of the carbon dioxide gas generated in the steel industry, which occurs during the [...] Read more.
The steel industry is an important foundation of the national economy and the livelihood of the people, producing a large amount of carbon dioxide gas, accounting for about 70% of the carbon dioxide gas generated in the steel industry, which occurs during the ironmaking process. Therefore, the key technology to reduce the pollution and improve competitiveness is to increase the stability of blast furnace production and the quality of hot metal. Since the operation requirements for temperature control in the vanadium-titanium blast furnace are dramatically different compared to the traditional ones due to the low fluidity of vanadium-titanium slag, maintaining the required hot metal temperature within a narrow range with smaller fluctuations is essential. In addition, the adjustment parameters of the lower part have a significant influence on the tuyere combustion flame temperature during the daily operation of blast furnaces. At present, there is no relevant research on the online detection and analysis of vanadium-titanium blast furnace tuyere combustion flame temperature. In this study, the temperature of four tuyeres in a 500 m3 vanadium and titanium blast furnace at Jianlong Steel was detected by an online detection system. The tuyere combustion flame temperature was then calculated using colorimetric temperature measuring methodology at various times and at four distinct locations. After that, the calibration analyses, imaging parameter and the temperature tendencies in different directions of the blast furnace were investigated. This study not only offers new methods for understanding the regularity of operation and increasing the degree of visualization in vanadium and titanium smelting blast furnaces but also provides technical support for intelligent and low-carbon operation in blast furnaces. Full article
(This article belongs to the Special Issue Advanced Metal Smelting Technology and Prospects)
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