Dynamic analysis on topological properties of the complex network of gas-liquid two-phase flow

The pattern of gas-liquid two-phase flow has always been a stress topic since it plays an important role on flow and heat transfer performance. Therefore, the study of flow pattern is always an important subject of two-phase flow. This paper focus on an experiment that obtains pressure signals of gas-liquid two phase flow, which are used for constructing a complex network of gas-liquid two-phase differential pressure fluctuation, recording undulate flow pressure information to compute the dynamics statistics. The compute results reveal that occurrence probability of the degree numbers of top 15 nodes is extremely higher than other ones; therefore they are the key factors of flow characteristic. Otherwise, the network possesses a high clustering coefficient, small average path length and big node degree that reflected it has long-range correlation and shot-range correlation. Also, these dynamics statistics manifested the large network with many small groups. This paper verifies a typical feature of gas-liquid two-phase flow that it brings fluctuant differential pressure from a totally new perspective, providing a reliable reference of the internal laws of different flow pattern and trend. We also achieve good identification of flow pattern in gas-liquid two-phase flow based on complex network theory.