Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow

Gao Zhongke; Zhang Xinwang; Jin Ningde; Marwan Norbert; Kurths Jürgen

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Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow

Gao Zhongke 1 * #,Zhang Xinwang 2,Jin Ningde 2,Marwan Norbert 3,Kurths Jürgen 4

1. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China;Potsdam Institute for Climate Impact Research, Potsdam 14473, Germany;Department of Physics, Humboldt University, Berlin 12489, Germany

2. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China

3.Potsdam Institute for Climate Impact Research, Potsdam 14473, Germany

4.Potsdam Institute for Climate Impact Research, Potsdam 14473, Germany;Department of Physics, Humboldt University, Berlin 12489, Germany;Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, UK

*Correspondence author

#Submitted by

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Funding: none

Opened online: 2 August 2013

Accepted by: none

Citation: Gao Zhongke,Zhang Xinwang,Jin Ningde.Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow[OL]. [ 2 August 2013] http://en.paper.edu.cn/en_releasepaper/content/4553013

Characterizing complex patterns arising from horizontal oil-water two-phase flows is a contemporary and challenging problem of paramount importance. We design a new multi-sector conductance sensor and systematically carry out horizontal oil-water two-phase flow experiments for measuring multivariate signals of different flow patterns. We then infer multivariate recurrence networks from these experimental data and investigate local cross-network properties for each constructed network. Our results demonstrate that local cross-clustering coefficient from a multivariate recurrence network is very sensitive to transitions among different flow patterns and recovers quantitative insights into the flow behavior underlying horizontal oil-water flows. These properties render multivariate recurrence networks particularly powerful for investigating a horizontal oil-water two-phase flow system and its complex interacting components from a network perspective.

Keywords:Multivariate recurrence network; Cross-clustering coefficient; Horizontal oil-water flows; Experiments

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