Multivariate multiscale complex network analysis of vertical upward oil-water two-phase flow in a small diameter pipe

High water cut and low velocity vertical upward oil-water two-phase flow is a typical complex system with the features of multiscale, unstable and non-homogenous. We first measure local flow information by using distributed conductance sensor and then develop a multivariate multiscale complex networ...

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Bibliographic Details
Published in:Scientific reports 2016-02, Vol.6 (1), p.20052-20052, Article 20052
Main Authors: Gao, Zhong-Ke, Yang, Yu-Xuan, Zhai, Lu-Sheng, Dang, Wei-Dong, Yu, Jia-Liang, Jin, Ning-De
Format: Article
Language:English
Subjects:
639/766/530/2801
639/766/530/2803
Behavior
Conductance
Entropy
Experiments
Flow pattern
Humanities and Social Sciences
multidisciplinary
Multiphase flow
Oil
Science
Sensors
Time series
Velocity
Water flow
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Summary:High water cut and low velocity vertical upward oil-water two-phase flow is a typical complex system with the features of multiscale, unstable and non-homogenous. We first measure local flow information by using distributed conductance sensor and then develop a multivariate multiscale complex network (MMCN) to reveal the dispersed oil-in-water local flow behavior. Specifically, we infer complex networks at different scales from multi-channel measurements for three typical vertical oil-in-water flow patterns. Then we characterize the generated multiscale complex networks in terms of network clustering measure. The results suggest that the clustering coefficient entropy from the MMCN not only allows indicating the oil-in-water flow pattern transition but also enables to probe the dynamical flow behavior governing the transitions of vertical oil-water two-phase flow.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep20052