Oil–water two-phase flow pattern analysis with ERT based measurement and multivariate maximum Lyapunov exponent
Oil–water two-phase flow patterns in a horizontal pipe are analyzed with a 16-electrode electrical resistance tomography（ERT） system. The measurement data of the ERT are treated as a multivariate time-series, thus the information extracted from each electrode represents the local phase distribution...
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| Veröffentlicht in: | Journal of Central South University 2016, Vol.23 (1), p.240-248 |
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| creator | 谭超 王娜娜 董峰 |
| description | Oil–water two-phase flow patterns in a horizontal pipe are analyzed with a 16-electrode electrical resistance tomography（ERT） system. The measurement data of the ERT are treated as a multivariate time-series, thus the information extracted from each electrode represents the local phase distribution and fraction change at that location. The multivariate maximum Lyapunov exponent（MMLE） is extracted from the 16-dimension time-series to demonstrate the change of flow pattern versus the superficial velocity ratio of oil to water. The correlation dimension of the multivariate time-series is further introduced to jointly characterize and finally separate the flow patterns with MMLE. The change of flow patterns with superficial oil velocity at different water superficial velocities is studied with MMLE and correlation dimension, respectively, and the flow pattern transition can also be characterized with these two features. The proposed MMLE and correlation dimension map could effectively separate the flow patterns, thus is an effective tool for flow pattern identification and transition analysis. |
| doi_str_mv | 10.1007/s11771-016-3067-3 |
| format | Article |
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The measurement data of the ERT are treated as a multivariate time-series, thus the information extracted from each electrode represents the local phase distribution and fraction change at that location. The multivariate maximum Lyapunov exponent（MMLE） is extracted from the 16-dimension time-series to demonstrate the change of flow pattern versus the superficial velocity ratio of oil to water. The correlation dimension of the multivariate time-series is further introduced to jointly characterize and finally separate the flow patterns with MMLE. The change of flow patterns with superficial oil velocity at different water superficial velocities is studied with MMLE and correlation dimension, respectively, and the flow pattern transition can also be characterized with these two features. The proposed MMLE and correlation dimension map could effectively separate the flow patterns, thus is an effective tool for flow pattern identification and transition analysis.</description><identifier>ISSN: 2095-2899</identifier><identifier>EISSN: 2227-5223</identifier><identifier>DOI: 10.1007/s11771-016-3067-3</identifier><language>eng</language><publisher>Changsha: Central South University</publisher><subject>Engineering ; ERT ; Metallic Materials ; 两相流 ; 多元时间序列 ; 多变量时间序列 ; 最大Lyapunov指数 ; 水油 ; 流型分析 ; 测量数据</subject><ispartof>Journal of Central South University, 2016, Vol.23 (1), p.240-248</ispartof><rights>Central South University Press and Springer-Verlag Berlin Heidelberg 2016</rights><rights>Copyright © Wanfang Data Co. Ltd. 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Cent. South Univ</addtitle><addtitle>Journal of Central South University of Technology</addtitle><description>Oil–water two-phase flow patterns in a horizontal pipe are analyzed with a 16-electrode electrical resistance tomography（ERT） system. The measurement data of the ERT are treated as a multivariate time-series, thus the information extracted from each electrode represents the local phase distribution and fraction change at that location. The multivariate maximum Lyapunov exponent（MMLE） is extracted from the 16-dimension time-series to demonstrate the change of flow pattern versus the superficial velocity ratio of oil to water. The correlation dimension of the multivariate time-series is further introduced to jointly characterize and finally separate the flow patterns with MMLE. The change of flow patterns with superficial oil velocity at different water superficial velocities is studied with MMLE and correlation dimension, respectively, and the flow pattern transition can also be characterized with these two features. The proposed MMLE and correlation dimension map could effectively separate the flow patterns, thus is an effective tool for flow pattern identification and transition analysis.</description><subject>Engineering</subject><subject>ERT</subject><subject>Metallic Materials</subject><subject>两相流</subject><subject>多元时间序列</subject><subject>多变量时间序列</subject><subject>最大Lyapunov指数</subject><subject>水油</subject><subject>流型分析</subject><subject>测量数据</subject><issn>2095-2899</issn><issn>2227-5223</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kM1KAzEUhYMoWKoP4C64lWh-mqRZSqk_UChI9yEzzbQjM5lpMtOZuvIdfEOfxJQpunN1c8P57uEcAG4IvicYy4dAiJQEYSIQw0IidgZGlFKJOKXsPL6x4ohOlboE1yHkCWaECiaUGIHdMi--P78601gPm65C9dYEC7Oi6mBtmvjroHGmOIQ8wC5vtnD-toJJ1KxhaU1ovS2ta6Im7m3R5Hvj83gMlqbPy7aEi4OpW1ftoe3rykXpFbjITBHs9WmOweppvpq9oMXy-XX2uEAp46RBE8oNsYYzrmRGMsHWHDOaSikTzhIrKU1pzCHVNE3TNVFSsjSTE0UkN4opNgZ3w9nOuMy4jX6vWh-DBP3hNod13yfa0tgYJjh2MQZkUKe-CsHbTNc-L40_aIL1sWM9dKwjoY8daxYZOjAhat3G-j-L_6Dbk9G2cptd5H6dhIgZJhNC2Q9pW4yq</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>谭超 王娜娜 董峰</creator><general>Central South University</general><general>Tianjin Key Laboratory of Process Measurement and Control(School of Electrical Engineering and Automation, Tianjin University), Tianjin 300072, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>2016</creationdate><title>Oil–water two-phase flow pattern analysis with ERT based measurement and multivariate maximum Lyapunov exponent</title><author>谭超 王娜娜 董峰</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c351t-425a1ea53597f1f63d5032c777b53be722c2031798cccd19773cf749175a9393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Engineering</topic><topic>ERT</topic><topic>Metallic Materials</topic><topic>两相流</topic><topic>多元时间序列</topic><topic>多变量时间序列</topic><topic>最大Lyapunov指数</topic><topic>水油</topic><topic>流型分析</topic><topic>测量数据</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>谭超 王娜娜 董峰</creatorcontrib><collection>维普_期刊</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Journal of Central South University</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>谭超 王娜娜 董峰</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Oil–water two-phase flow pattern analysis with ERT based measurement and multivariate maximum Lyapunov exponent</atitle><jtitle>Journal of Central South University</jtitle><stitle>J. Cent. South Univ</stitle><addtitle>Journal of Central South University of Technology</addtitle><date>2016</date><risdate>2016</risdate><volume>23</volume><issue>1</issue><spage>240</spage><epage>248</epage><pages>240-248</pages><issn>2095-2899</issn><eissn>2227-5223</eissn><abstract>Oil–water two-phase flow patterns in a horizontal pipe are analyzed with a 16-electrode electrical resistance tomography（ERT） system. The measurement data of the ERT are treated as a multivariate time-series, thus the information extracted from each electrode represents the local phase distribution and fraction change at that location. The multivariate maximum Lyapunov exponent（MMLE） is extracted from the 16-dimension time-series to demonstrate the change of flow pattern versus the superficial velocity ratio of oil to water. The correlation dimension of the multivariate time-series is further introduced to jointly characterize and finally separate the flow patterns with MMLE. The change of flow patterns with superficial oil velocity at different water superficial velocities is studied with MMLE and correlation dimension, respectively, and the flow pattern transition can also be characterized with these two features. The proposed MMLE and correlation dimension map could effectively separate the flow patterns, thus is an effective tool for flow pattern identification and transition analysis.</abstract><cop>Changsha</cop><pub>Central South University</pub><doi>10.1007/s11771-016-3067-3</doi><tpages>9</tpages></addata></record> |
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| identifier | ISSN: 2095-2899 |
| ispartof | Journal of Central South University, 2016, Vol.23 (1), p.240-248 |
| issn | 2095-2899 2227-5223 |
| language | eng |
| recordid | cdi_wanfang_journals_zngydxxb_e201601026 |
| source | Springer Nature - Complete Springer Journals; Alma/SFX Local Collection |
| subjects | Engineering ERT Metallic Materials 两相流 多元时间序列 多变量时间序列 最大Lyapunov指数 水油 流型分析 测量数据 |
| title | Oil–water two-phase flow pattern analysis with ERT based measurement and multivariate maximum Lyapunov exponent |
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