Advances in Multiphase Flows: Numerical, Experimental, and AI+ Methodologies

Dear Colleagues,

Multiphase flow has wide applications in numerous fields, including chemical engineering, aerospace engineering, petroleum engineering, power engineering, geology, food processing, and environmental engineering. It refers to the movement of two or more phases of matter (i.e., solid, liquid, or gas) together in a system. Understanding multiphase flow is essential for optimizing the efficiency of industrial processes and minimizing environmental impacts.

The behavior of multiphase flow is highly dependent on the properties of the fluids and the flow conditions, such as density, viscosity, and velocity, in the simultaneous flow of two or more phases. It is complex to study and requires advanced analytical tools, computational models, and experimental techniques. In the meantime, fluid mechanics and data-driven methods have gradually been well integrated. Prevalent data-driven methods such as deep learning (DL) and reinforcement learning (RL) could solve many traditionally challenging problems from new perspectives with exceptional efficiencies. However, the challenges of applying data-driven methods to multiphase flow lie in many aspects, such as the lack of high-fidelity datasets (numerical or experimental) and difficulties in creating versatile models and analytical solutions. There is also ongoing research into developing advanced materials/structures and technologies for controlling multiphase flow in different industrial applications. Therefore, multiphase flow is an important study area with significant implications and continuous interest in scientific fields.

This Special Issue aims to gather the recent developments and advancements in the field of multiphase flow. Particular interest is paid to the integration of different methodologies, including analytical, numerical, experimental, and artificial intelligence (AI) techniques. We also welcome papers discussing the challenges and opportunities in a broader field of fluid dynamics, not restricted to multiphases. The findings can contribute to better understanding, prediction, modeling, controlling, and optimization by providing new or improved insights.

In this Special Issue, original research papers, review articles, and perspectives are welcome. Research areas may include (but are not limited to) the following:

• Two-phase and three-phase flows including gas–liquid, liquid–liquid, gas–solid, or gas–solid–liquid;
• Multiphase flow modeling and CFD;
• Multiphase turbulence;
• Theoretical and mathematical modeling;
• Numerical methods for simulation and optimization;
• AI techniques in fluid dynamics research;
• Multiphase flow measurement and instrumentation;
• Experimental techniques for flow characterization;
• Flow visualization;
• Flow regime transitions and flow pattern prediction;
• Heat and mass transfer in multiphase flows;
• Mixing and separation in multiphase flows;
• Multiphase flow in porous media;
• Multiphase flow in microchannels and nanochannels;
• Microfluidic devices and systems;
• Multiphase flow in viscous and non-Newtonian fluids;
• Flows in complex geometries with complex boundary conditions;
• Fluid–structure interaction in multiphase flow;
• Bubbly flows in fluidized beds;
• Bubble and drop dynamics;
• Interaction of gases, liquids, and solids;
• Interface dynamics and interfacial instabilities;
• Rheology of multiphase flows;
• Reactive flows;
• Cavitating and boiling flows with phase transition;
• Plasma in dielectrics;
• Atomization;
• Multiphase flow in industrial applications.

We look forward to receiving your contributions, and hope this Special Issue will provide a platform for researchers to share their work and exchange knowledge and ideas.

Dr. Mingming Ge
Dr. Bin Ji
Prof. Dr. Desheng Zhang
Guest Editors

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