Survey on the electric arc furnace and ladle furnace electric system

Maia, Thales A. C.; Onofri, Virna C.

doi:10.1080/03019233.2022.2128550

Cited by 13 publications

(2 citation statements)

References 71 publications

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“…The 120-t ladle furnace in a steel plant is equipped with various operating equipment, including a Rogowski coil, integrator, PLC, and integrated proportional valve. [33] The Rogowski coil, a hollow toroidal coil uniformly wound on a nonferromagnetic material, is placed directly over the conductor to measure alternating current. [34,35] Its measurement principle is based on Faraday's law of electromagnetic induction and Ampere's law of loops.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Effect of Argon Flow Rate on Power Consumption of a 120‐t Ladle Furnace

Song,

Zhang,

Yin

et al. 2024

steel research int.

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To improve the phenomenon of serious power consumption of a ladle furnace, the impact of argon flow rate on power consumption in the refining process is investigated through theoretical calculations based on the principle of alternating current measurement using Rogowski coil and integrator circuit. The study divides the power supply phase into four distinct flow rate regions in a single furnace of DH36 steel, a low‐alloy, high‐strength ship plate steel commonly used in shipbuilding and offshore platforms. The analysis of active power, current, and voltage trends, along with average power consumption per second at each flow rate region, reveals a potential for efficient reduction in power consumption. Additionally, experiments with different argon flow rates (300, 400, and 500 NL min−1) during the power supply stages of multifurnace argon tests of AB/A steel show improvements in desulfurization rate, heating rate, processing time, and power consumption per ton of steel heated by 1 °C and power consumption per ton of steel per second.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Effect of Argon Flow Rate on Power Consumption of a 120‐t Ladle Furnace

Song,

Zhang,

Yin

et al. 2024

steel research int.

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“…Steel production occupies a leading position in the metallurgical sector worldwide [1][2][3][4][5]. The rapid growth of steel production on a global scale over the past 20-30 years has attracted the attention of experts to the increasingly harmful environmental impact of ferrous metallurgy enterprises [6][7][8], including the generation of hard-to-recycle humanmade waste [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Pyrometallurgical Technology for Extracting Iron and Zinc from Electric Arc Furnace Dust

Nemchinova

Patrushov²,

Tyutrin

2023

Applied Sciences

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This study is aimed at developing a technology for processing electric arc furnace dust (EAFD) into granulated cast iron and a zinc-containing product. The study object was the dust from the EAF of PJSC Magnitogorsk Iron and Steel Works (Magnitogorsk, Chelyabinsk region). It has been established that the dust contains valuable components in the form of ZnFe2O4 and ZnO. The processing of EAFD involves the reduction of Fe and Zn in a charge from their oxygen-containing forms with C and CO. The content of the charge components was calculated in % as follows: EAFD—17.44; scale—51.33; hard coal—20.61; quartz sand—4.71; lime—5.91. The experiments in the high-temperature LHT 08/17 furnace (Germany) allowed for defining the optimal temperature regime for reduction melting. As a result of laboratory tests, granulated pig iron samples were obtained, containing in wt%: Fe—95.27; C—4.4; S—0.07, and others. Captured zinc-containing product after calcination (to remove halogens) contained 90.21 wt% ZnO. The resulting granulated pig iron is recommended as one of the charge components in electrometallurgical steel production. The zinc-containing product is recommended as a raw material for Zn production and others.

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Enhancing Efficiency in Electric Arc Furnace Steelmaking: A Multi‐Objective Optimization Approach Using the Non‐Dominated Sorting Genetic Algorithm II

Yi,

Yue,

Dou

et al. 2024

steel research int.

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To realize the overall optimization of electric arc furnace (EAF) steelmaking system, a multi‐objective optimization model including smelting cost, energy consumption per ton of steel, and carbon emission per ton of steel is established. The model is optimized by multi‐objective genetic algorithm to improve the charging structure. At the same time, the data in the optimal solution set are used to analyze the influence of the change of scrap ratio on smelting cost, carbon emission per ton of steel, and smelting cycle. According to the actual working conditions and the demand of steel plant, the optimized results are selected. Compared with the actual production data, the proportion of scrap steel increases to 50.9%, the ratio of molten iron decreases to 38.8%, the smelting cost per ton of steel decreases by 12 Yuan, the energy consumption per ton of steel decreases by 4%, the carbon emission per ton of steel significantly decreases by 13%, and the smelting cycle is shortened by 2 min, but at the cost of increasing the power consumption per ton of steel. The optimized results and the analysis of the change of scrap ratio provide reference for the optimization of EAF steelmaking system.

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Survey on the electric arc furnace and ladle furnace electric system

Cited by 13 publications

References 71 publications

Effect of Argon Flow Rate on Power Consumption of a 120‐t Ladle Furnace

Effect of Argon Flow Rate on Power Consumption of a 120‐t Ladle Furnace

Pyrometallurgical Technology for Extracting Iron and Zinc from Electric Arc Furnace Dust

Enhancing Efficiency in Electric Arc Furnace Steelmaking: A Multi‐Objective Optimization Approach Using the Non‐Dominated Sorting Genetic Algorithm II

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