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作 者:宋仕容 刘宏臣 米晓天 许超 杨梅[2] 尧超群 SONG Shirong;LIU Hongchen;MI Xiaotian;XU Chao;YANG Mei;YAO Chaoqun(School of Environmental and Chemical Engineering,Xi’an Polytechnic University,Xi’an 710048,Shaanxi,China;Dalian Institute of Chemical Physics,Chinese Academy of Sciences,Dalian 116023,Liaoning,China)
机构地区:[1]西安工程大学环境与化学工程学院,陕西西安710048 [2]中国科学院大连化学物理研究所,辽宁大连116023
出 处:《化工学报》2024年第2期566-574,共9页CIESC Journal
基 金:国家自然科学基金项目(22208256);陕西省科技厅一般项目(2021JQ-671);西安工程大学科研启动基金项目(107020460)。
摘 要:研究了同轴微通道内水-硅油体系的液滴生成过程。在不同的连续毛细数Ca_(c)和分散相Weber数Wed下,观察到滴出流和喷射流两种不同的流型。实验考察了两相流量、黏度和内管结构对液滴尺寸和液滴生成频率的影响。结果表明液滴尺寸随着分散相流量增加而增大,而随着连续相流量和黏度的增加而降低。此外,随着Wed的增加,流型会从滴出流过渡到喷射流,而更大尺寸的内管会更早过渡到喷射流,从而得到更大的液滴尺寸。对于液滴生成频率,其随Ca_(c)和Wed的增加均呈现先快速增加后变缓的趋势。当内管通道尺寸基本相同时,不同结构的内管通道在固定Ca_(c)时其液滴生成频率相差不大,且随着通道尺寸的减小,液滴生成频率逐渐增加。基于实验结果,建立了液滴尺寸预测模型,预测值与实验值吻合较好。The droplet generation process of the water-silicone oil system in the coaxial microchannel was studied.Under different continuous capillary number Ca_(c)and dispersed phase Weber number Wed,two different flow patterns,dripping flow and jet flow,were observed.Experiments examined the effects of two-phase flow,viscosity,and inner tube structure on droplet size and droplet generation frequency.The results showed that droplet size increased with the increase of dispersed phase flow rate and decrease of flow rate and viscosity of continuous phase.Additionally,with the increase of Wed,jetting occurrence was found to be easier in relatively larger capillary,which in turn generated larger droplets.The generation frequency of droplet increased fast firstly then slow down to a plateau with the increasing of Ca_(c)and Wed.When the hydraulic diameters of inner channel were almost same,the deviation in the generation frequency of droplet obtained from different geometries of inner channel was small at fixed Ca_(c).And the generation frequency of droplet increased with the decrease in the hydraulic diameters of inner channel.Based on the obtained results,an empirical correlation was proposed to predict the droplet size with good prediction performance.
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