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邯钢250 t转炉吹炼参数对传质能力影响的实验研究
引用本文:邓建军,林路.邯钢250 t转炉吹炼参数对传质能力影响的实验研究[J].北京科技大学学报,2016(Z1):213-218.
作者姓名:邓建军  林路
作者单位:1. 中国钢研集团,北京100081; 邯钢集团公司,邯郸056000;2. 北京科技大学国家板带生产先进装备工程技术中心,北京,100083
摘    要:渣钢间传质速度决定了熔池元素的反应速度(尤其是脱碳和脱磷反应速度),并直接影响元素在渣钢间分配.本文以邯钢250 t转炉为研究对象,利用相似比1﹕9建立水模型,考虑供气流量、枪位和底吹位置因素研究转炉内传质能力.结果表明:加大顶吹供气强度和底吹供气强度能够大大提高熔池元素在渣钢间的分配;渣钢间传质系数随底吹气体流量降低而明显降低,建议底吹气体流量不低于0.06 m3·t-1·min-1;底吹孔数越多,渣钢间传质系数越大;底吹流量分配方案优于流量平均分配方案,建议采用.

关 键 词:炼钢  转炉  传质系数  水模型  影响因素

Experimental study on the effect of operating parameters on the mass transfer ability of Hangang 250 t converter
DENG Jian-jun,LIN Lu.Experimental study on the effect of operating parameters on the mass transfer ability of Hangang 250 t converter[J].Journal of University of Science and Technology Beijing,2016(Z1):213-218.
Authors:DENG Jian-jun  LIN Lu
Abstract:The mass transfer rate between steel and slag determines the reaction rates of elements in a molten bath ( especially the reaction rates of desulphurization and dephosphorization) , and has direct impact on the distribution ratios of elements between steel and slag. In this article, Hangang 250 t converter was taken as the research object. Factors such as gas flow, lance position and bottom blowing location were taken into consideration to study the mass transfer ability of the convertor by a water model whose similarity ratio was 1﹕9. The results show that increasing the top-blowing intensity and the bottom-blowing intensity can greatly improve the distribu-tion ratios of elements in the molten bath between steel and slag. The mass transfer coefficient between steel and slag decreases obvi-ously with the drop of bottom-blowing air flow, thus a bottom-blowing air flow not lower than 0. 06 m3·t-1·min-1 is suggested. The more the bottom-blowing holes are, the larger the mass transfer coefficient between steel and slag gets. A distribution plan of bottom-blowing air flow is presented, which is superior to the equal distribution plan of air flow.
Keywords:steelmaking  converters  mass transfer coefficient  water models  influencing factors
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