An open-source, adaptive solver for particle-resolved simulations with both subcycling and non-subcycling methods

We present the IAMReX (incompressible flow with adaptive mesh refinement for the eXascale), an adaptive and parallel solver for particle-resolved simulations on the multi-level grid. The fluid equations are solved using a finite-volume scheme on the block-structured semi-staggered grids with both subcycling and non-subcycling methods. The particle-fluid interaction is resolved using the multidirect forcing immersed boundary method. The associated Lagrangian markers used to resolve fluid-particle interface only exist on the finest-level grid, which greatly reduces memory usage. The volume integrals are numerically calculated to capture the free motion of particles accurately, and the repulsive potential model is also included to account for the particle–particle collision. We demonstrate the versatility, accuracy, and efficiency of the present multi-level framework by simulating fluid-particle interaction problems with various types of kinematic constraints. The cluster of monodisperse particles case is presented at the end to show the capability of the current solver in handling multiple particles. It is demonstrated that the three-level AMR (Adaptive Mesh Refinement) simulation leads to a 72.46% grid reduction compared with the single-level simulation. The source code and testing cases used in this work can be accessed at https://github.com/ruohai0925/IAMR/tree/development. Input scripts and raw postprocessing data are also available for reproducing all results.

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Institutions

Publication Details

Journal
Physics of Fluids
Published
2024-11-01
DOI
https://doi.org/10.1063/5.0236509
Citations
3
Primary Topic
Particle Dynamics in Fluid Flows
Type
article
Field-Weighted Citation Impact
1.01
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article

An open-source, adaptive solver for particle-resolved simulations with both subcycling and non-subcycling methods

Zhengping Zhu, Y. Zeng, C-Q. Li, W. Li et al.
3 citations
Physics of Fluids
Particle Dynamics in Fluid Flows
1.01
article

An open-source, adaptive solver for particle-resolved simulations with both subcycling and non-subcycling methods

Zhengping Zhu, Y. Zeng, C-Q. Li, W. Li, Mingze Tang, Xuzhu Li, Xiaokai Li
article en
3 citations

Abstract

We present the IAMReX (incompressible flow with adaptive mesh refinement for the eXascale), an adaptive and parallel solver for particle-resolved simulations on the multi-level grid. The fluid equations are solved using a finite-volume scheme on the block-structured semi-staggered grids with both subcycling and non-subcycling methods. The particle-fluid interaction is resolved using the multidirect forcing immersed boundary method. The associated Lagrangian markers used to resolve fluid-particle interface only exist on the finest-level grid, which greatly reduces memory usage. The volume integrals are numerically calculated to capture the free motion of particles accurately, and the repulsive potential model is also included to account for the particle–particle collision. We demonstrate the versatility, accuracy, and efficiency of the present multi-level framework by simulating fluid-particle interaction problems with various types of kinematic constraints. The cluster of monodisperse particles case is presented at the end to show the capability of the current solver in handling multiple particles. It is demonstrated that the three-level AMR (Adaptive Mesh Refinement) simulation leads to a 72.46% grid reduction compared with the single-level simulation. The source code and testing cases used in this work can be accessed at https://github.com/ruohai0925/IAMR/tree/development. Input scripts and raw postprocessing data are also available for reproducing all results.

Physics of FluidsVol. 36(11)
University of Science and Technology of China (CN), Hefei University of Technology (CN), Northwestern Polytechnical University (CN), Lanzhou University of Technology (CN), ShanghaiTech University (CN), Zhejiang Lab (CN), The University of Texas at Austin (US)
Openalex Percentile: Top 24%
Particle Dynamics in Fluid Flows
1.01
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