Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow

摘要

Characterizing complex patterns arising from horizontal oil-water two-phase flows is a contemporarynand challenging problem of paramount importance. We design a new multisector conductance sensor andnsystematically carry out horizontal oil-water two-phase flow experiments for measuring multivariate signalsnof different flow patterns. We then infer multivariate recurrence networks from these experimental datanand investigate local cross-network properties for each constructed network. Our results demonstrate that ancross-clustering coefficient from a multivariate recurrence network is very sensitive to transitions among differentnflowpatterns and recovers quantitative insights into the flowbehavior underlying horizontal oil-water flows. Thesenproperties render multivariate recurrence networks particularly powerful for investigating a horizontal oil-waterntwo-phase flow system and its complex interacting components from a network perspective.