Complex network analysis in inclined oil--water two-phase flow |
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| Authors: | Gao Zhong-Ke and Jin Ning-De |
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| Affiliation: | School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China |
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| Abstract: | Complex networks have established themselves in recentyears as being particularly suitable and flexible for representingand modelling many complex natural and artificial systems.Oil--water two-phase flow is one of the most complex systems. Inthis paper, we use complex networks to study the inclined oil--watertwo-phase flow. Two different complex network construction methodsare proposed to build two types of networks, i.e. the flow patterncomplex network (FPCN) and fluid dynamic complex network (FDCN).Through detecting the community structure of FPCN by thecommunity-detection algorithm based on K-means clustering, usefuland interesting results are found which can be used for identifyingthree inclined oil--water flow patterns. To investigate the dynamiccharacteristics of the inclined oil--water two-phase flow, we construct48 FDCNs under different flow conditions, and find that thepower-law exponent and the network information entropy, which aresensitive to the flow pattern transition, can both characterize thenonlinear dynamics of the inclined oil--water two-phase flow. In thispaper, from a new perspective, we not only introduce a complexnetwork theory into the study of the oil--water two-phase flow but alsoindicate that the complex network may be a powerful tool for exploringnonlinear time series in practice. |
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| Keywords: | two-phase flow complex networks community structure nonlinear dynamics |
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