炼焦煤流态化分级及其数值模拟  

Classification of coking coal in a fluidized bed and its numerical simulation

作　　者：赵斌[1,2] 么强[2] 王庆功[1] 卢闪 吕俊复[1] 岳光溪[1] 

机构地区：[1]清华大学热能工程系热科学与动力工程教育部重点实验室,北京100084 [2]河北联合大学现代冶金技术教育部重点实验室,河北唐山063009

出　　处：《中国矿业大学学报》2015年第2期326-331,共6页Journal of China University of Mining & Technology

基　　金：国家重点基础研究发展计划(973)项目(2012CB214904)

摘　　要：了解炼焦煤的原始粒度分布,有益于改善焦化工序的安全经济性.以500 μm为分级粒度,采用Wen-Chen模型、CPFD数值模拟,结合气固流化床分级试验对分级过程进行研究.结果表明：当流化风速为3.27 m/s时,粗、细颗粒分离效果最为显著,上排逃逸细颗粒中目标粒子含量高达99.7％,下排成品煤中目标粒子含量仅为28.7％.上排逃逸细颗粒的Wen-Chen模型预测值和数值模拟值同试验结果相比的最大偏差分别为16.18％和7.08％,下排成品煤的Wen-Chen模型预测值和数值模拟值同试验结果相比的最大偏差分别为27.25％和9.25％.模拟结果发现,对目标粒子含量分级影响最大的颗粒粒径为1 500～2 000 μm.To realize particle size distribution of coking coal will improve the economy and safe- ty of the coking process. With 500 μm as a target classification size, the particles classification in a fluidized bed was studied using experimental measurements, Wen-Chen model prediction and CPFD numerical simulation. The results show that the best classification effect occurred under a fluidizing air velocity of 3.27 m/s. The content of coal particles was 99.7% in the fine escaping samples, and only 28.7% in the discharged samples. Compared with the experimental value, for the fine escaping samples, the maximum deviation of prediction values by Wen-Chen model and CPFD numerical simulation was 16. 18% and 7. 08%, respectively. For the dis- charged samples, the maximum deviation was 27.25% and 9.25%, respectively. The numeri- cal simulation results also show that the coal sample of 1 500～2 000 μm is the most effective on the classification effect.

关 键 词：炼焦煤 分级 气固流化床 Wen-Chen模型 

分 类 号：TD922.4[矿业工程—选矿]