Oil–water two-phase flow pattern analysis with ERT based measurement and multivariate maximum Lyapunov exponent  

作　　者：谭超 王娜娜 董峰 

机构地区：[1]Tianjin Key Laboratory of Process Measurement and Control (School of Electrical Engineering and Automation,Tianjin University)

出　　处：《Journal of Central South University》2016年第1期240-248,共9页中南大学学报（英文版）

基　　金：Projects(61227006,61473206) supported by the National Natural Science Foundation of China;Project(13TXSYJC40200) supported by Science and Technology Innovation of Tianjin,China

摘　　要：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.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.

关 键 词：oil-water two-phase flow flow patterns electrical resistance tomography （ERT） multivariate time-series multivariate maximum Lyapunov exponent correlation dimension 

分 类 号：O359[理学—流体力学]