Mathematical and physical modeling of thermal stratification phenomena in steel ladles

Putan, Vasile; Vîlceanu, Lucia; Socalici, Ana; Putan, A

doi:10.1088/1757-899x/294/1/012004

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Currently, there are various systems for diagnosing and controlling technological equipment and processes [2,3]. Existing systems have a large functional set.…”

Section: Introductionmentioning

confidence: 99%

Information System for Diagnosing the Condition of the Complex Structures Based on Neural Networks

et al. 2022

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In this paper, we describe the relevance of diagnosing the lining condition of steel ladles in metallurgical facilities. Accidents with steel ladles lead to losses and different types of damage in iron and steel works. We developed an algorithm for recognizing thermograms of steel ladles to identify burnout zones in the lining based on the technology and design of neural networks. A diagnostic system structure for automated evaluating of the technical conditions of steel ladles without taking them out of service has been developed and described.

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“…Currently, there are various systems for diagnosing and controlling technological equipment and processes [2,3]. Existing systems have a large functional set.…”

Section: Introductionmentioning

confidence: 99%

Information System for Diagnosing the Condition of the Complex Structures Based on Neural Networks

et al. 2022

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Thermal Mixing Analysis in a Ladle Utilizing Physical and Numerical Modeling through Planar Laser-induced Fluorescence (PLIF) Technique

Amaro-Villeda,

Dutta,

Guevara-Castillo

et al. 2024

ISIJ Int.

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Numerical Study on Heat Transfer Characteristic of Hot Metal Transportation before EAF Steelmaking Process

Chen,

Hu,

Wang

et al. 2024

Metals

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The temperature of hot metal (HM) is crucial for the energy input and smelting in the electric arc furnace (EAF) steelmaking process with HM and scrap as the charge structure. However, due to the influence of many factors in the heat dissipation in HM transportation before the EAF steelmaking process, the temperature drop of HM before charged is usually fluctuating and uncertain. This situation is not conducive to the input energy control and energy optimization of the EAF steelmaking process. In this paper, a three-dimensional numerical model of a 90-ton hot metal ladle is established to simulate the heat transfer characteristic of HM transportation through ANSYS Fluent 2023 and verified by on-the-spot testing and sample analysis. The effects of ambient temperature, air velocity, slag thickness and furnace cover thickness on the temperature drop of HM are investigated and quantitatively analyzed in 30 numerical schemes. The results indicate that slag thickness is the most influential factor, followed by furnace cover thickness, air velocity and ambient temperature. In the case of 50 min transport time, the temperature drop of HM is 55.2, 15.06, 12.08, 10.38, 10.29 and 10.26 °C when the slag thickness is 0, 50, 100, 150, 200 and 250 mm, respectively. While HM is not covered by slag, the furnace cover can also greatly reduce the temperature drop. Based on the simulated data, a prediction model of HM temperature drop is obtained through the multi-factor coupling analysis and mathematical fitting. This study can help develop targeted insulation measures and determine the temperature of HM, which is expected to control the input energy for deep energy-saving optimization in the EAF steelmaking process.

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Mathematical and physical modeling of thermal stratification phenomena in steel ladles

Cited by 3 publications

References 5 publications

Information System for Diagnosing the Condition of the Complex Structures Based on Neural Networks

Information System for Diagnosing the Condition of the Complex Structures Based on Neural Networks

Thermal Mixing Analysis in a Ladle Utilizing Physical and Numerical Modeling through Planar Laser-induced Fluorescence (PLIF) Technique

Numerical Study on Heat Transfer Characteristic of Hot Metal Transportation before EAF Steelmaking Process

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