Soft coarse-grained particle model for particle-fluid systems--颗粒学报PARTICUOLOGY

Ye, Y., Xu, J., & Ge, W. (2024). Soft coarse-grained particle model for particle-fluid systems. Particuology, 84, 178-193. https://doi.org/10.1016/j.partic.2023.06.005

Soft coarse-grained particle model for particle-fluid systems

Yanhao Ye^{a b}, Ji Xu^{a c}, Wei Ge^{a b c *}

a State Key Laboratory of Multiphase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China
b School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
c Innovation Academy for Green Manufacture, Chinese Academy of Sciences, Beijing, 100190, China

10.1016/j.partic.2023.06.005

Volume 84, January 2024, Pages 178-193

Received 15 April 2023, Revised 21 May 2023, Accepted 2 June 2023, Available online 21 June 2023, Version of Record 29 June 2023.

E-mail: wge@ipe.ac.cn

Highlights

• Numerical measurement on the collisional force between coarse-grained particles.

• Soft-shell model for coarse-grained particles applicable to general cases.

• More statistical parameters remaining invariant before and after coarse-graining.

• Better agreement with experiments and real particle DPM simulations.

Abstract

By modeling a group of neighboring real particles as a single coarse-grained particle (CGP), discrete particle method (DPM) is now capable of simulating industrial-scale particle-fluid systems. However, a systematic approach to determine the CGP properties and develop their interaction models is still lacking, which casts uncertainty on the predictivity of the method. In this study, collisions between predefined particle groups are analyzed to construct kernel functions for modeling the CGPs and then the model parameters are determined by equating the statistical properties of the CGPs and the real particles in the physical process studied. This approach is implemented for homogeneous cooling of granular gas, then demonstrated effective in simulating experimental fluidized beds.

Graphical abstract

Keywords

Coarse-grain (CG); Discrete particle method (DPM); Fluidized bed; Multi-scale simulation

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