Two-phase flow pattern identification in horizontal gas-liquid swirling pipe flow by machine learning method
文献类型：期刊论文
| 作者 | Liu, Wen1,2; Lv, Xiaofei3; Jiang, Sheng3; Li, Huazheng3; Zhou, Hao3; Dou, Xiangji3 |
| 刊名 | ANNALS OF NUCLEAR ENERGY
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| 出版日期 | 2023-04-01 |
| 卷号 | 183页码:10 |
| 关键词 | Gas-liquid Swirling flow Flow pattern identification Void fraction Horizontal pipe |
| ISSN号 | 0306-4549 |
| DOI | 10.1016/j.anucene.2022.109644 |
| 通讯作者 | Liu, Wen(liuwenlw1988@163.com) |
| 英文摘要 | Gas-liquid two-phase swirling flow has been widely used in nuclear industry. Its flow pattern is fundamental to investigate the two-phase flow. Although flow patterns of non-swirling flow in a horizontal pipe have been investigated for a long history, flow patterns of swirling flow in the pipe are rarely reported. In this paper, gas-liquid two-phase flow patterns of swirling flow generated by a vane-type swirler inside a horizontal pipe were investigated by a visualization experiment. Five swirling flow patterns were observed and recorded by the backlight imaging method. Then image processing method was used to obtain void fraction, and the statistical analysis (CDF and PDF) of void fraction for each swirling flow patterns was performed. Owing to the distin-guished and stable feature of PDF signals, four parameters describing the characteristics of PDF signals have been proposed as the indicator of machine learning method. Finally, five algorithms of machine learning method have been used to identify the swirling flow patterns, and RUSBoost tree algorithm performs best with an accuracy of 97.4%. |
| WOS关键词 | PRESSURE-DROP ; SPIRAL FLOW ; SEPARATION ; REGIME ; PARTICLE |
| 资助项目 | Key Laboratory of Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences[E229kf17] ; National Natural Science Foundation of China[52004038] ; Scientific Research Project of Education Department of Guangdong Province[2022KCXTD029] ; open project of Jiangsu Key Laboratory of Oil-Gas Storage and Transportation Technology[CDYQCY201905] ; open project of Jiangsu Key Laboratory of Oil-Gas Storage and Transportation Technology[CDYQCY202004] |
| WOS研究方向 | Nuclear Science & Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000906277800001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | Key Laboratory of Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences ; National Natural Science Foundation of China ; Scientific Research Project of Education Department of Guangdong Province ; open project of Jiangsu Key Laboratory of Oil-Gas Storage and Transportation Technology |
| 源URL | [http://ir.giec.ac.cn/handle/344007/38180]  |
| 专题 | 中国科学院广州能源研究所 |
| 通讯作者 | Liu, Wen |
| 作者单位 | 1.Chinese Acad Sci, Guangzhou Inst Energy Convers, Key Lab Gas Hydrate, Guangzhou 510640, Guangdong, Peoples R China 2.Foshan Univ, Sch Mechatron Engn & Automation, Foshan 528001, Guangdong, Peoples R China 3.Changzhou Univ, Jiangsu Key Lab Oil & Gas Storage & Transportat Te, Changzhou 213164, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Wen,Lv, Xiaofei,Jiang, Sheng,et al. Two-phase flow pattern identification in horizontal gas-liquid swirling pipe flow by machine learning method[J]. ANNALS OF NUCLEAR ENERGY,2023,183:10. |
| APA | Liu, Wen,Lv, Xiaofei,Jiang, Sheng,Li, Huazheng,Zhou, Hao,&Dou, Xiangji.(2023).Two-phase flow pattern identification in horizontal gas-liquid swirling pipe flow by machine learning method.ANNALS OF NUCLEAR ENERGY,183,10. |
| MLA | Liu, Wen,et al."Two-phase flow pattern identification in horizontal gas-liquid swirling pipe flow by machine learning method".ANNALS OF NUCLEAR ENERGY 183(2023):10. |
入库方式： OAI收割
来源：广州能源研究所
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