University of Science and Technology Beijing

Jiangshan Zhang

Hui Li

Zicheng Xin

Chunhui Zhang

Yanshen Han

Junguo Zhang

Biao Tao

Huisheng Wang

Leilei Zou

A method for controlling a temperature of a molten steel during ladle furnace (LF) refining based on interpretable machine learning includes: acquiring process data of the LF refining and a target temperature of the molten steel during the LF refining; acquiring a prediction model for the temperature of the molten steel during the LF refining; calculating a base value for prediction of the temperature of the molten steel, SHapley Additive explanations (SHAP) values of key factor parameters, and a relationship trend between the key factor parameters and the SHAP values; and calculating a predicted value of the temperature of the molten steel during the LF refining, and acquiring a control result for the temperature of the molten steel during the LF refining according to the relationship trend and the predicted value of the temperature of the molten steel during the LF refining.

Method and device for controlling temperature of molten steel during ladle furnace (LF) refining based on interpretable machine learning

A secondary cooling control method for reinforcing surface solidification structure of microalloyed steel continuous casting bloom includes: in situ observing precipitation behavior of secondary phase particles of the microalloyed steel, and determining a concentrated precipitation temperature range; cooling the microalloyed steel at different cooling rates, obtaining a particle size and a volume fraction of the secondary phase particles of the microalloyed steel at different cooling rates; determining an optimal average cooling rate; determining an optimal average cooling rate r; determining an optimal average cooling rate; and determining an optimal average cooling rate range through intersection of the three optimal average cooling rates whereby the continuous casting secondary cooling is optimized. The present invention can enhance the surface solidification structure of continuous casting bloom and reduce surface and subsurface cracks of the microalloyed steel continuous casting bloom.

Secondary cooling control method for reinforcing surface solidification structure of microalloyed steel continuous casting bloom

A method and system for predicting an addition amount of slagging lime during ladle furnace (LF) refining, and an LF refining method are provided. The method includes: S: calculating an actual sulfur distribution ratio in combination with a Kungliga Tekniska H&#xf6;gskolan (KTH) model and a least square method by using LF refining parameters; S: calculating, according to a principle of sulfur mass conservation, a mass of final slag by using the LF refining parameters and the actual sulfur distribution ratio obtained in S; and S: calculating, according to a principle of material conservation during LF refining, an addition amount of slagging lime during the LF refining by using the LF refining parameters and the mass of the final slag obtained in S, thereby predicting the addition amount of the required slagging lime.

Method and system for predicting addition amount of slagging lime during LF  refining, and LF refining method

A method for improving center segregation and surface crack of continuous casting medium-thick slab of peritectic steel reduces the cooling intensity at the earlier stage of solidification and enhancing the cooling intensity at the final stage of solidification. For example, the cooling water amount of the wide face of the mould is 3400-3600 L/min, and the cooling water amount of the narrow face of the mould is 480-530 L/min. The cooling water amount of the wide face of the foot roller section is 239-298 L/min, and the cooling water amount of the narrow face of the foot roller section is 61-65 L/min. The total cooling water amount of the sector segment is 1517-2166 L/min.

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Beijing, China

Jiangshan Zhang