基于遗传算法DRI竖炉内流场的影响因素  

Influencing Factors of DRI Shaft Furnace Flow Field Based on Genetic Algorithm

作　　者：葛俊礼[1] 白明华[1] 朴英敏 王健[1] 符远翔[1] 徐宽[1] 

机构地区：[1]燕山大学国家冷轧板带装备及工艺工程技术研究中心,河北秦皇岛066004

出　　处：《钢铁》2014年第1期22-27,共6页Iron and Steel

基　　金：科技型中小企业技术创新基金无偿资助项目(12C26211300726);河北省科技型中小企业技术创新资金资助项目(12C1303351003)

摘　　要：气基直接还原铁(DRI)竖炉内的气流分布对DRI生产过程有着重要影响。利用分析软件ANSYS对直接还原铁竖炉内还原气气流分布规律及其影响因素进行研究。模拟分析中将球团矿简化为多孔介质,通过试验测得的惯性阻力系数和黏性阻力系数作为模拟过程的一个基础输入参数。将计算结果通过神经网络找到相互的映射关系,得到气基竖炉部分工艺参数与炉内压强、过渡段串流情况的关系。通过遗传算法优化,得出竖炉内理想气流分布时的状态影响因素。研究结果显示,炉内气流分布状况与状态影响因素有直接关系,并得出影响竖炉内合理流场的主要状态影响因素为炉顶压强和冷却气出口压强。The gas distribution in direct reduction iron （DRI） shaft furnace has an important influence on DRI production process. Using the fluid analysis software ANSYS, the distribution of reducing gas flow and relative influencing factors in DRI shaft furnace were investigated. In the simulation analysis, pellets were simplified as porous media. The viscous resistance coefficient and inertial resistance coefficient measured in the experiment were used as the basic input parameters of the simulation process. The calculation results by the neural network to find the mapping relationship between the reduction part average pressure, transition part average velocity and the gas-based direct reduction shaft furnace process parameters. Finally, the shaft furnace ideal air distribution influencing factors are obtained through the calculation results by genetic algorithm optimization. The results show that the airflow distribution in the furnace has a direct relationship with the state of the factors which include the furnace top pressure and cooling gas outlet pressure. They impact the reasonability of the flow field in the shaft furnace.

关 键 词：气基直接还原竖炉 气流分布 多孔介质 遗传算法 数值模拟 

分 类 号：TF554[冶金工程—钢铁冶金]