An octree-based immersogeometric approach for modeling inertial migration of particles in channels

In this paper, we develop a scalable, adaptively refined, octree-based finite element approach with immersogeometric analysis to track inertial migration of particles in microchannels. Fluid physics is modeled using a residual-based variational multiscale method, and the particle movement is modeled as rigid body motion. A parallel, hierarchically refined octree mesh is employed as the background mesh, on which a variationally consistent immersogeometric formulation is adopted for tracking the particle motion in the fluid. Adaptations of immersogeometric analysis on an octree background mesh are developed to enable efficient searching of background element for a given surface quadrature point, as well as a distribution of surface quadrature points over processors to reduce memory overhead and better parallelize the surface assembly. An octree-based adaptive mesh refinement algorithm adapted to in-out test in the immersogeometric approach is also developed. The validation of our octree-based immersogeometric approach is carried out using a benchmark case of a sphere settling in quiescent fluid, with good agreement presented. In addition, good strong (and weak) scalability on supercomputing resources for this benchmark case up to 16,384 processes is demonstrated. The proposed method is further deployed for exploring particle migration in straight and converging-diverging channels. This example illustrates the potential of the octree-based immersogeometric approach for efficiently tracking particle motion in complex channel flows - a problem with a diverse array of applications. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper presents a scalable, adaptively refined, octree-based finite element approach with immersogeometric analysis for tracking particle migration in microchannels. The method utilizes a parallel, hierarchically refined octree mesh and variational immersogeometric formulation for efficient particle motion tracking. Good scalability and validation results are achieved for a benchmark case, demonstrating the potential of the proposed approach for tracking particle motion in complex channel flows.