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Nonlinear analysis of gas-water/oil-water two-phase flow in complex networks [electronic resource] / Zhong-Ke Gao, Ning-De Jin, Wen-Xu Wang.

Gao, Zhong-Ke, author.; Jin, Ning-De, author.; Wang, Wen-Xu, author.
2014
TA357.5.M84
Available Online
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Title
Nonlinear analysis of gas-water/oil-water two-phase flow in complex networks [electronic resource] / Zhong-Ke Gao, Ning-De Jin, Wen-Xu Wang.
Author
Gao, Zhong-Ke, author.
ISBN
9783642383731 electronic book
3642383734 electronic book
9783642383724
3642383726
DOI
https://doi.org/10.1007/978-3-642-38373-1
Published
Heidelberg : Springer, 2014.
Copyright
©2014
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-642-38373-1 doi
Call Number
TA357.5.M84
Dewey Decimal Classification
532/.56
Summary
Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination with complex network theory. We systematically carried out gas-water/oil-water two-phase flow experiments for measuring the time series of flow signals which is studied in terms of the mapping from time series to complex networks. Three network mapping methods were proposed for the analysis and identification of flow patterns, i.e. Flow Pattern Complex Network (FPCN), Fluid Dynamic Complex Network (FDCN) and Fluid Structure Complex Network (FSCN). Through detecting the community structure of FPCN based on K-means clustering, distinct flow patterns can be successfully distinguished and identified. A number of FDCNs under different flow conditions were constructed in order to reveal the dynamical characteristics of two-phase flows. The FDCNs exhibit universal power-law degree distributions. The power-law exponent and the network information entropy are sensitive to the transition among different flow patterns, which can be used to characterize nonlinear dynamics of the two-phase flow. FSCNs were constructed in the phase space through a general approach that we introduced. The statistical properties of FSCN can provide quantitative insight into the fluid structure of two-phase flow. These interesting and significant findings suggest that complex networks can be a potentially powerful tool for uncovering the nonlinear dynamics of two-phase flows.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Jin, Ning-De, author.
Wang, Wen-Xu, author.
Series
SpringerBriefs in applied sciences and technology. Multiphase flow.
Available in Other Form
Nonlinear analysis of gas-water/oil-water two -phase flow in complex networks
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Definition of flow patterns
The experimental flow loop facility and data acquisition
Community detection in flow pattern complex network
Nonlinear dynamics in fluid dynamic complex network
Gas-water fluid structure complex network
Oil-water fluid structure complex network
Directed weighted complex network for characterizing gas-liquid slug flow
Markov transition probability-based network for characterizing horizontal gas-liquid two-phase flow
Recurrence network for characterizing bubbly oil-in-water flows
Conclusions.

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