A Lattice Boltzmann Front-Tracking Interface Capturing Method based on Neural Network for Gas-Liquid Two-Phase Flow-Reference-Cited by-同舟云学术

A Lattice Boltzmann Front-Tracking Interface Capturing Method based on Neural Network for Gas-Liquid Two-Phase Flow

Published:2023-01-02 Issue:1 Volume:37 Page:49-66
ISSN:1061-8562
Container-title:International Journal of Computational Fluid Dynamics
language:en
Short-container-title:International Journal of Computational Fluid Dynamics

Author:

Lai Bozhen¹,Ke Zhaoqing¹,Wang Zhiqiang¹,Zhu Ronghua¹,Gao Ruifeng¹,Mao Yu¹,Zhang Ying¹

Affiliation:

1. School of Advanced Manufacturing, Nanchang University, Nanchang, People’s Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Energy Engineering and Power Technology,Condensed Matter Physics,Aerospace Engineering,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618562.2023.2246398

Reference50 articles.

1. Capturing of interface topological changes in two-phase gas–liquid flows using a coupled volume-of-fluid and level-set method (VOSET)

2. A continuum method for modeling surface tension

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4. Boosting the aerodynamic properties of vibrating-mesh nebulized polymeric nanosuspensions

5. Machine Learning for Fluid Mechanics

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