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Complex networks from experimental horizontal oil–water flows: Community structure detection versus flow pattern discrimination.
- Source :
-
Physics Letters A . Apr2015, Vol. 379 Issue 8, p790-797. 8p. - Publication Year :
- 2015
-
Abstract
- We propose a complex network-based method to distinguish complex patterns arising from experimental horizontal oil–water two-phase flow. We first use the adaptive optimal kernel time–frequency representation (AOK TFR) to characterize flow pattern behaviors from the energy and frequency point of view. Then, we infer two-phase flow complex networks from experimental measurements and detect the community structures associated with flow patterns. The results suggest that the community detection in two-phase flow complex network allows objectively discriminating complex horizontal oil–water flow patterns, especially for the segregated and dispersed flow patterns, a task that existing method based on AOK TFR fails to work. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03759601
- Volume :
- 379
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- Physics Letters A
- Publication Type :
- Academic Journal
- Accession number :
- 100946723
- Full Text :
- https://doi.org/10.1016/j.physleta.2014.09.004