Open AccessComplex network community structure of two-phase flow pattern and its statistical characteristics
Author(s) -
Zhong-Ke Gao,
Ningde Jin
Publication year - 2008
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.57.6909
Subject(s) - flow (mathematics) , complex network , computer science , community structure , slug flow , flow network , perspective (graphical) , cluster analysis , two phase flow , data mining , artificial intelligence , mechanics , statistics , mathematics , physics , mathematical optimization , world wide web
We extract the flow pattern complex network from the measured data. After detecting the community structure of the network through the community detection algorithm which is based on k-means clustering, we find that there are three communities in the network, which correspond to the bubble flow, slug flow and churn flow respectively, and the nodes of the network that are connected tightly between two communities correspond to the transitional flow. In this paper, from a new perspective, we not only achieve good identification of flow patterns in gas/liquid two-phase flow based on complex network theory, but also find the characteristics of flow pattern complex network that are sensitive to the flow parameters, which provide reference to the study of dynamic properties of two-phase flow.