摘要
为研究入口压力对天然气混合物超声速液化特性的影响规律,建立了三维双组分天然气混合物超声速凝结流动数学模型,对Laval喷管内双组分混合物凝结流动进行了数值模拟,得出了沿Laval喷管轴向的参数分布,通过开展双可凝组分气体凝结相变实验,对比发现数值模拟与实验结果基本一致,说明了所建立的数学模型及计算方法的正确性。还研究了入口压力对甲烷-乙烷混合物超声速液化特性的影响,结果表明,保持Laval喷管入口温度及组成不变,增大入口压力,混合气体成核位置前移,成核率、平均液滴半径、液相质量分数均随之增大,即入口压力越大,混合气体在Laval喷管内越易发生凝结,在实际生产中可以通过调节入口压力来促进天然气的凝结,提高Laval喷管的液化效率。
In this paper,to find out about how the inlet pressure influences the supersonic liquefaction of natural gas mixtures,we established a three-dimensional mathematical model for the supersonic condensation flow of the methane-ethane mixture gas,obtained the axial parameters along the Laval nozzle,and conducted experiments to verify the gas condensate phase transition of double condensable components.It was found that the numerical simulation is in good agreement with the experimental results,thereby proving the mathematical model and the calculation method as correct.We also investigated the influences of the inlet pressure on the supersonic liquefaction of methane-ethane mixtures.The results indicate that,when the temperature and composition of the Laval nozzle inlet remain the same,the nucleation position of the mixed gas moves forward,the nucleation rate,the mean droplet radius and the liquid mass fraction all increase with the increase of the inlet pressure.The greater the inlet pressure,the more apt for the condensation of the gas mixture in the Laval nozzle to occur.In the actual production,the condensation of natural gas mixtures can be promoted by adjusting the inlet pressure,and the liquefaction efficiency of the Laval nozzle will be improved.
作者
边江
曹学文
杨文
于洪喜
尹鹏博
BIAN Jiang;CAO Xuewen;YANG Wen;YU Hongxi;YIN Pengbo(College of Pipeline and Civil Engineering, China University of Petroleum ,Qingdao 266580 ,China;South China Branch ,Sinopec Sales Co. ,Ltd. ,Guangzhou 510620 ,China;Huguang Branch ,Sinopec Xinjiang Coal Gas Pipeline Co. ,Ltd. ,Changsha 410016, China)
出处
《高压物理学报》
EI
CAS
CSCD
北大核心
2018年第3期1-7,共7页
Chinese Journal of High Pressure Physics
基金
国家重点研发计划专项(2016YFC0802301)
国家自然科学基金(51274232
51406240)
山东省自然科学基金(ZR2014EEQ003)