Abstract
Gas–liquid two-phase flows are widely encountered in many industrial applications, and the evolutionary dynamics of the flow patterns are fundamental knowledge for the establishment of the two-phase controlling system. In this work, we propose a symbolic complex network-based method for identifying the evolutionary dynamics of the gas–liquid two-phase flow system. First, we establish a series of symbolic networks with the derived gas–liquid two-phase flow symbolic series. Then we suggest a symbolic network index, which is the number of enumerated elementary cycles, to reveal the periodic oscillation properties of various gas–liquid flow patterns. In addition, we estimate the symbolic network average degree C and average shortest path length L to reveal the evolutionary dynamics of the flow patterns. The results suggest that our developed method is efficient for detecting the dynamics of the two-phase flow system, which can be further applied to other complex fluid systems.
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