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油页岩干馏瓦斯积碳影响因素的实验研究 被引量:1

Experimental Study on Influencing Factors for Oil Shale Retorting Gas Carbon Deposition
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摘要 采用自制的连续流动反应装置,以06Cr25Ni20不锈钢管为反应器,对不同温度(600,650,700,750℃)、不同反应时间(30,60 min)、不同瓦斯流量(10,20 m L/min)等条件下油页岩干馏瓦斯在反应器内的积碳情况进行了实验研究。实验结果表明,积碳量随着反应温度、反应时间和瓦斯流量的增加而增大。前者是由于反应由表面反应决定,受反应动力学控制;后两者由于积碳反应所需前驱体不断增多所致。过渡型催化金属表面积碳是积碳速率随着反应时间的增加而降低的主要原因。利用多因素混合水平方差分析方法分析了影响油页岩干馏瓦斯积碳的因素,分析结果显示,反应温度、反应时间和瓦斯流量对油页岩干馏瓦斯积碳的影响均极为显著,说明从事油页岩干馏瓦斯积碳的相关研究,此3种因素必须予以考虑。 Carbon deposition of oil shale retorting gas was carried out under different temperatures(600, 650, 700, 750 ℃), different reaction time(30, 60 min) and different gas flow(10, 20 m L/min) conditions in the stainless steel tube reactor of 06Cr25Ni20 in a home-made continuous flow reactor system. The results show that the amount of the carbon deposition increase as the increasing of the reaction temperatures, reaction time and the retorting gas flow rate. The former growth is mainly due to the rates of the carbon deposition are determined by the surface reactions and controlled by the reaction kinetics; the latter two due to the increase of the number of the precursors which required for the carbon deposition reactions. The carbon deposition rate decreases as the increasing of the reaction time. The reason is that the surface of the transition metal is continuously covered with the carbon deposition. The factors that influencing oil shale retorting gas carbon deposition are analyzed through the multiple factor mixed level variance analysis method, the results show that the reaction temperatures, the reaction time, and the gas flow are all extremely significant impact on the oil shale retorting gas carbon deposition. As shown above, if we want to do some corresponding study about oil shale retorting gas carbon deposition, this three factors must be taken into account.
出处 《中国电机工程学报》 EI CSCD 北大核心 2016年第2期474-479,共6页 Proceedings of the CSEE
基金 吉林省油页岩综合开发技术创新团队资助项目(201218119)~~
关键词 油页岩 干馏瓦斯 耐热合金 积碳 方差分析 影响因素 oil shale retorting gas heat-resistant alloys carbon deposit variance analysis influence factors
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