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304不锈钢氩氧脱碳精炼过程中炉渣成分预测模型

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针对304不锈钢氩氧脱碳(Argon-Oxygen Decarburization,AOD)精炼过程中存在炉渣成分难以测量等问题,本研究综合考虑了顶枪吹氧、供气比例变化、物料熔化速度以及初始渣量对渣-钢反应和精炼炉渣成分的影响,建立了炉渣成分预测模型,并用于计算精炼过程中的炉渣和钢液成分变化.此模型计算的渣成分与钢液硫含量与实测值吻合较好,AOD精炼终点渣中SiO2含量平均偏差为1.434%,CaO含量平均偏差为1.848%,Cr2O3含量平均偏差为0.080%,MnO含量平均偏差为0.016%,钢液终点S含量平均偏差为0.002%.
Prediction model for slag composition in argon oxygen decarbonization refining process of 304 stainless steel
This paper presents a model for predicting slag composition during the 304 stainless steel argon-oxygen decarburization(AOD)refining process.The model considers the effects of top gun oxygen blowing,changes in gas supply ratio,material melting rate,and initial slag amount on the slag-steel reaction and refining slag composition.It is used to calculate the refining process of slag and steel composition changes during the refining process.The slag composition and sulfur content of the molten steel,as calculated by the model,are consistent with the measured values.The average deviation for SiO2 content is 1.434%,for CaO content is 1.848%,for Cr2O3 content is 0.080%,for MnO content is 0.016%,and for S content is 0.002%at the end of the AOD refining.

argon-oxygen decarburization304 stainless steelslag compositionprediction model

林文志、李晶、史成斌、蔡俊

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北京科技大学绿色低碳钢铁冶金全国重点实验室,北京 100083

氩氧脱碳 304不锈钢 炉渣成分 预测模型

2024

江西冶金
江西省冶金集团公司 江西省金属学会

江西冶金

影响因子:0.117
ISSN:1006-2777
年,卷(期):2024.44(2)
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