Computing hydrodynamic interactions in confined doubly-periodic geometries in linear time

TL;DR

This paper introduces a fast, spectrally-accurate method for calculating hydrodynamic interactions among particles in confined doubly-periodic geometries, enabling large-scale simulations with linear computational complexity.

Contribution

It develops a linearly-scaling, GPU-accelerated solver combining FFT and Chebyshev methods for confined geometries, improving efficiency and accuracy over previous approaches.

Findings

Solver scales linearly with particle number

Can simulate up to a million particles in less than a second

Dense suspension of microrollers maintains structure but moves slower in slit channels

Abstract

We develop a linearly-scaling variant of the Force Coupling Method [K. Yeo and M. R. Maxey, J. Fluid Mech. 649, 205-231 (2010)] for computing hydrodynamic interactions among particles confined to a doubly-periodic geometry with either a single bottom wall or two walls (slit channel) in the aperiodic direction. Our spectrally-accurate Stokes solver uses the Fast Fourier Transform (FFT) in the periodic $xy$ plane and Chebyshev polynomials in the aperiodic $z$ direction normal to the wall(s). We decompose the problem into two problems. The first is a doubly-periodic subproblem in the presence of particles (source terms) with free-space boundary conditions in the $z$ direction, which we solve by borrowing ideas from a recent method for rapid evaluation of electrostatic interactions in doubly-periodic geometries [O. Maxian, R. P. Pel\'aez, L. Greengard and A. Donev, J. Chem. Phys. 154, 204107 (2021)]. The second is a correction subproblem to impose the boundary conditions on the wall(s). Instead of the traditional Gaussian kernel, we use the exponential of a semicircle kernel to model the source terms (body force) due to the presence of particles, and provide optimum values for the kernel parameters that ensure a given hydrodynamic radius with at least two digits of accuracy and rotational and translational invariance. The computation time of our solver, which is implemented in graphical processing units, scales linearly with the number of particles, and allows computations with about a million particles in less than a second for a sedimented layer of colloidal microrollers. We find that in a slit channel, a driven dense suspension of microrollers maintains the same two-layer structure as above a single wall, but moves at a substantially lower collective speed due to increased confinement.