Dephosphorization stability of hot metal by double slag operation in basic oxygen furnace

Wu, Wei; Dai, Shifan; Liu, Yue

doi:10.1016/s1006-706x(17)30133-4

Cited by 19 publications

(17 citation statements)

References 12 publications

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“…As mentioned above, there are few laboratorial investigations on the effect of the Fe2O3 addition amount on the dephosphorization of hot metal with CaO-FeO-SiO2-MgO-Al2O3 molten slag at 1623 K with the lower slag basicity of about 1.5, which is just corresponding to the dephosphorization conditions of the NDSP [12,22,23]. In our previous papers, the effects of basicity and temperature on the dephosphorization in the NDSP were investigated [20,21].…”

Section: Introductionmentioning

confidence: 99%

Effect of the Fe2O3 Addition Amount on Dephosphorization of Hot Metal with Low Basicity Slag by High-Temperature Laboratorial Experiments

Yang

Shi

et al. 2021

Metals

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In this paper, the influence of the Fe2O3 addition amount on the dephosphorization of hot metal at 1623 K with the slag of the low basicity (CaO/SiO2) of about 1.5 was investigated by using high-temperature laboratorial experiments. With increasing the Fe2O3 addition amount from 5 to 30 g, the contents of [C], [Si], [Mn] and [P] in the hot metal at the end of dephosphorization are decreased and the corresponding removal ratios increase. In dephosphorization slags, the phosphorus mainly exists in the form of the nCa2SiO4–Ca3(PO4)2 solid solution in the phosphorus-rich phase and the value of coefficient n decreases from 20 to 1. Furthermore, the oxygen potential and activity at the interface between the slag and hot metal are increased. When the oxygen potential and the oxygen activity at the interface are greater than 0.72 × 10−12 and 7.1 × 10−3, respectively, the dephosphorization ratio begins to increase rapidly. When the Fe2O3 addition amount is increased to 30 g, the ratio of the Fe2O3 addition amount to theoretical calculation consumption is around 175%, and the dephosphorization ratio reaches the highest value of 83.3%.

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Section: Introductionmentioning

confidence: 99%

Effect of the Fe2O3 Addition Amount on Dephosphorization of Hot Metal with Low Basicity Slag by High-Temperature Laboratorial Experiments

Yang

Shi

et al. 2021

Metals

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“…Together with the incorporation of petrographic analysis of the slag samples, it was concluded that average dephosphorization efficiency was found to increase to 91% with calcium ferrite fluxing. Moreover, calcium ferrite addition was reported to be beneficial for lowering the melting temperature of the converter slag and for decreasing the amount of free calcium oxide and metallic iron present in the final slag [41].…”

Section: New Trends Of Phosphorus Removal In Converter Steelmakingmentioning

confidence: 99%

New trends in basic oxygen furnace dephosphorization

Keskinkilic

2020

J min metall B Metall

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Except for special grades of steel where it is used as an alloying element, phosphorus is regarded as an impurity that must be removed. Considering the conventional integrated iron and steelmaking, there are primarily two processes for phosphorus removal. The first is a hot metal dephosphorization (DeP) process that is applied to a blast furnace for hot metal before the steelmaking process. The second is the basic oxygen furnace steelmaking (BOS), a unique method primarily used for steelmaking, with the exception of stainless steels. Hot metal phosphorus content has a direct impact on BOS. An increase of phosphorus in hot metal is mainly related to the use of high P 2 O 5 containing iron ores. In the current literature review, new trends of phosphorus removal in converter steelmaking are outlined. The double-slag practice was reported to be successful when hot metal P content was larger than 0.100%. It was indicated that the tapping temperature was critical for the production of low-phosphorus grades for which maximum allowable P content was 0.007% and that high tapping temperatures should be avoided. The tap-to-tap time for the double-slag process was slightly longer than the conventional converter steelmaking. It was further reported that the double-slag practice would be more economical than an establishment of a separate hot metal dephosphorization unit, if low-phosphorus grades did not have a significant share in the product mix of a steelmaking company. Endpoint phosphorus prediction was one of the important recent trends of converter steelmaking. A mixed injection of CO 2-O 2 to a basic oxygen furnace was applied to enhance dephosphorization, and promising results were reported. Unfortunately, a successful process for recycling of BOS dephosphorization slag has not been reported yet.

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“…The chemical reaction from the fluxes of burnt lime or dolomite can release considerable heat to raise the temperature in the furnace, but when the gas is transferred quickly into the molten iron, the blown O2 changes the carbon-rich content of the alloy into low-carbon steel. Thus, the strong chemical reaction promotes the removal of impurities, and reduces the C, silicon (Si), and other contents [32][33][34].…”

Section: Problem Descriptionmentioning

confidence: 99%

A Dynamic Analytics Method Based on Multistage Modeling for a BOF Steelmaking Process

Chang

Tang

Liu

et al. 2019

IEEE Trans. Automat. Sci. Eng.

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This paper proposes a dynamic analytics method based on a least squares support vector machine with a hybrid kernel to address real-time prediction problems in the converter steelmaking process. The hybrid kernel function is used to enhance the performance of the existing kernels. To improve the model's accuracy, the internal parameters are optimized by a differential evolution algorithm. In light of the complex mechanisms of the converter steelmaking process, a multistage modeling strategy is designed instead of the traditional single-stage modeling method. Owing to the dynamic nature of the practical production process, great effort has been made to construct a dynamic model that uses the prediction error information based on the static model. The validity of the proposed method is verified through experiments on real-world data collected from a BOF steelmaking process. The results indicate that the proposed method can successfully solve dynamic prediction problems and outperforms other state-of-the-art methods in terms of prediction accuracy.Note to Practitioners-With the development of cyber-physical systems, abundant real-time data have been collected from the converter steelmaking process. These data provide an opportunity to solve product quality prediction problems using data-driven models. This paper proposes a dynamic analytics method based on a least squares support vector machine with a hybrid kernel to address this challenging issue. To improve the model's performance, a differential evolution (DE) algorithm is used to optimize its parameters. Because of the fierce physicochemical reaction in the converter furnace, it is difficult for a single-stage model to achieve accurate predictions. Thus, a multistage modeling strategy is proposed to address this difficulty, and a dynamic model based on feedback error is developed to realize real-time prediction. We verify the effectiveness of the proposed method using real data from a BOF steelmaking process. The computational results reveal that the proposed method has a higher prediction accuracy than other methods, making it helpful in guaranteeing the specified product quality and in maintaining stable BOF operation.Index Terms-Dynamic analytics, multistage modeling, least squares support vector machine, hybrid kernel function, basic oxygen furnace.

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Dephosphorization stability of hot metal by double slag operation in basic oxygen furnace

Cited by 19 publications

References 12 publications

Effect of the Fe2O3 Addition Amount on Dephosphorization of Hot Metal with Low Basicity Slag by High-Temperature Laboratorial Experiments

Effect of the Fe2O3 Addition Amount on Dephosphorization of Hot Metal with Low Basicity Slag by High-Temperature Laboratorial Experiments

New trends in basic oxygen furnace dephosphorization

A Dynamic Analytics Method Based on Multistage Modeling for a BOF Steelmaking Process

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