Two-phase flow pattern transition behaviors on experimental established ordinal pattern networks.

Area of Science:

• Fluid Dynamics
• Complex Systems Analysis
• Network Science

Background:

• Modeling two-phase flow pattern transitions is crucial but challenging.
• Existing methods may not fully capture the complex dynamics of flow pattern changes.

Purpose of the Study:

• To investigate gas-liquid two-phase flow pattern transition dynamics.
• To analyze the topology structures of complex networks representing flow patterns.
• To identify novel metrics for detecting flow pattern transitions.

Main Methods:

• Conducting gas-liquid two-phase flow experiments in a vertical pipe.
• Establishing ordinal pattern complex networks from flow fluctuation signals.
• Applying K-core decomposition and network homology persistence analysis.

Main Results:

• The decay rate of K-core size is sensitive to flow conditions and indicates transitions.
• Network homology persistence (maximum persistence, persistence entropy) reflects oscillatory behaviors.
• Established complex networks effectively represent different flow patterns.

Conclusions:

• K-core decomposition decay rate is a potential metric for flow pattern transition identification.
• Network persistence analysis aids in understanding oscillatory behaviors during transitions.
• This network-based approach offers a novel method for analyzing two-phase flow systems.