Link-wise Artificial Compressibility Method

TL;DR

The paper introduces a link-wise reformulation of the Artificial Compressibility Method (LW-ACM) for incompressible flows, leveraging lattice Boltzmann techniques to improve computational efficiency and reduce memory usage.

Contribution

It presents a novel LW-ACM approach that combines lattice Boltzmann advantages with finite difference simplicity, requiring no high-order moments or kinetic expansions.

Findings

LW-ACM achieves similar speed to optimized LBM.

Memory demand is significantly lower than LBM.

Numerical results show high stability and accuracy.

Abstract

The Artificial Compressibility Method (ACM) for the incompressible Navier-Stokes equations is (link-wise) reformulated (referred to as LW-ACM) by a finite set of discrete directions (links) on a regular Cartesian mesh, in analogy with the Lattice Boltzmann Method (LBM). The main advantage is the possibility of exploiting well established technologies originally developed for LBM and classical computational fluid dynamics, with special emphasis on finite differences (at least in the present paper), at the cost of minor changes. For instance, wall boundaries not aligned with the background Cartesian mesh can be taken into account by tracing the intersections of each link with the wall (analogously to LBM technology). LW-ACM requires no high-order moments beyond hydrodynamics (often referred to as ghost moments) and no kinetic expansion. Like finite difference schemes, only standard Taylor expansion is needed for analyzing consistency. Preliminary efforts towards optimal implementations have shown that LW-ACM is capable of similar computational speed as optimized (BGK-) LBM. In addition, the memory demand is significantly smaller than (BGK-) LBM. Importantly, with an efficient implementation, this algorithm may be one of the few which is compute-bound and not memory-bound. Two- and three-dimensional benchmarks are investigated, and an extensive comparative study between the present approach and state of the art methods from the literature is carried out. Numerical evidences suggest that LW-ACM represents an excellent alternative in terms of simplicity, stability and accuracy.