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  Interconnected ordinal pattern complex network for characterizing the spatial coupling behavior of gas-liquid two-phase flow

Du, M., Wei, J., Li, M.-Y., Gao, Z.-k., Kurths, J. (2023): Interconnected ordinal pattern complex network for characterizing the spatial coupling behavior of gas-liquid two-phase flow. - Chaos, 33, 6, 063108.
https://doi.org/10.1063/5.0146259

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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_29107 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_29107_2
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 ???ViewItemFull_lblCreators???:
Du, Meng 1, ???ENUM_CREATORROLE_AUTHOR???
Wei, Jie1, ???ENUM_CREATORROLE_AUTHOR???
Li , Meng-Yu 1, ???ENUM_CREATORROLE_AUTHOR???
Gao, Zhong-ke 1, ???ENUM_CREATORROLE_AUTHOR???
Kurths, Jürgen2, ???ENUM_CREATORROLE_AUTHOR???           
???ViewItemFull_lblAffiliations???:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???: The complex phase interactions of the two-phase flow are a key factor in understanding the flow pattern evolutional mechanisms, yet these complex flow behaviors have not been well understood. In this paper, we employ a series of gas–liquid two-phase flow multivariate fluctuation signals as observations and propose a novel interconnected ordinal pattern network to investigate the spatial coupling behaviors of the gas–liquid two-phase flow patterns. In addition, we use two network indices, which are the global subnetwork mutual information (⁠ ⁠) and the global subnetwork clustering coefficient (⁠ ⁠), to quantitatively measure the spatial coupling strength of different gas–liquid flow patterns. The gas–liquid two-phase flow pattern evolutionary behaviors are further characterized by calculating the two proposed coupling indices under different flow conditions. The proposed interconnected ordinal pattern network provides a novel tool for a deeper understanding of the evolutional mechanisms of the multi-phase flow system, and it can also be used to investigate the coupling behaviors of other complex systems with multiple observations.

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???ViewItemFull_lblLanguages???: eng - English
 ???ViewItemFull_lblDates???: 2023-06-052023-06-05
 ???ViewItemFull_lblPublicationStatus???: ???ViewItem_lblPublicationState_published-in-print???
 ???ViewItemFull_lblPages???: 11
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1063/5.0146259
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???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Complex Networks
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Energy
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Nonlinear Data Analysis
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???ViewItemFull_lblSourceTitle???: Chaos
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, SCI, Scopus, p3
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???ViewItemFull_lblPages???: ???lbl_noEntry??? ???ViewItemFull_lblSourceVolumeIssue???: 33 (6) ???ViewItemFull_lblSourceSequenceNo???: 063108 ???ViewItemFull_lblSourceStartEndPage???: ???lbl_noEntry??? ???ViewItemFull_lblSourceIdentifier???: ???ENUM_IDENTIFIERTYPE_CONE???: https://publications.pik-potsdam.de/cone/journals/resource/180808
???ENUM_IDENTIFIERTYPE_PUBLISHER???: American Institute of Physics (AIP)