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Multi-scale symbolic time reverse analysis of gas–liquid two-phase flow structures

Author

Listed:
  • Hongmei Wang

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China)

  • Lusheng Zhai

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China)

  • Ningde Jin

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China)

  • Youchen Wang

    (School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China)

Abstract

Gas–liquid two-phase flows are widely encountered in production processes of petroleum and chemical industry. Understanding the dynamic characteristics of multi-scale gas–liquid two-phase flow structures is of great significance for the optimization of production process and the measurement of flow parameters. In this paper, we propose a method of multi-scale symbolic time reverse (MSTR) analysis for gas–liquid two-phase flows. First, through extracting four time reverse asymmetry measures (TRAMs), i.e. Euclidean distance, difference entropy, percentage of constant words and percentage of reversible words, the time reverse asymmetry (TRA) behaviors of typical nonlinear systems are investigated from the perspective of multi-scale analysis, and the results show that the TRAMs are sensitive to the changing of dynamic characteristics underlying the complex nonlinear systems. Then, the MSTR analysis is used to study the conductance signals from gas–liquid two-phase flows. It is found that the multi-scale TRA analysis can effectively reveal the multi-scale structure characteristics and nonlinear evolution properties of the flow structures.

Suggested Citation

  • Hongmei Wang & Lusheng Zhai & Ningde Jin & Youchen Wang, 2017. "Multi-scale symbolic time reverse analysis of gas–liquid two-phase flow structures," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(01), pages 1-22, January.
    • Handle: RePEc:wsi:ijmpcx:v:28:y:2017:i:01:n:s0129183117500073
    DOI: 10.1142/S0129183117500073
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