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Complex networks from multivariate time series for characterizing nonlinear dynamics of two-phase flow patterns

Gao Zhong-Ke Jin Ning-De Yang Dan Zhai Lu-Sheng Du Meng

Complex networks from multivariate time series for characterizing nonlinear dynamics of two-phase flow patterns

Gao Zhong-Ke, Jin Ning-De, Yang Dan, Zhai Lu-Sheng, Du Meng
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  • Abstract views:  1826
  • PDF Downloads:  1211
  • Cited By: 0
Publishing process
  • Received Date:  11 January 2012
  • Accepted Date:  22 February 2012
  • Published Online:  20 June 2012

Complex networks from multivariate time series for characterizing nonlinear dynamics of two-phase flow patterns

  • 1. School of Electrical Engineering & Automation, Tianjin University, Tianjin 300072, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 61104148, 50974095, 41174109), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110032120088), and the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2011ZX05020-006).

Abstract: We use finite element analysis method to optimize and design a new curve half-ring conductance sensor for gas-liquid two-phase flow system. Then we carry out gas-liquid two-phase flow experiment in multiphase flow loop facility, and use the designed sensor to measure multivariate time series corresponding to different flow patterns. According to the measured signals, we construct complex networks from multivariate time series for different flow patterns by a network inference method. Through investigating the community structures of the constructed networks, we find that different communities correspond to different flow patterns and the network statistics in community can be used to effectively characterize the dynamic behavior of different flow patterns. In this regard, our method can be a powerful tool for identifying flow patterns and uncovering the nonlinear dynamics governing the evolution of different flow patterns.

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