Simulations of Particle-Laden Flows with Large Dispersed-Phase Size Disparities Using Highly Scalable Parallel Adaptive Methods
Linfeng Jiang, Enrico Calzavarini, Dominik Krug

TL;DR
This paper introduces a scalable computational framework combining lattice Boltzmann and immersed boundary methods on adaptive grids to simulate complex multiphase flows with large size disparities efficiently.
Contribution
It develops a novel parallel adaptive method that accurately and efficiently simulates particle-laden flows with large size differences, validated against benchmarks.
Findings
Accurately captures hydrodynamic interception in quiescent flow.
Reproduces theoretical collision efficiency scaling law.
Successfully simulates bubble-particle interactions in turbulence.
Abstract
The numerical simulation of multiphase flows involving dispersed components with large scale disparities, such as the collisions between millimeter-sized bubbles and micron-sized mineral particles in flotation, poses a significant computational challenge. Accurately resolving the thin boundary layers of finite-size objects while tracking massive numbers of small particles within a large turbulent domain is often prohibitively expensive on uniform grids. To address this, we present a parallel scalable computational framework that couples the lattice Boltzmann method with the immersed boundary method on a dynamically adaptive octree grid. A key algorithm is developed for the efficient parallel host-cell searching, which significantly accelerates the tracking of Lagrangian points on distributed unstructured grids. The accuracy and robustness of the code are rigorously validated against…
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