Sharp inf-sup estimate for the Stokes equation in tight domains with periodic pillars and some numerical implications
Provides a theoretical explanation and practical solution for a computational bottleneck in simulating microfluidic devices like DLD arrays.
The paper identifies that the stagnation of iterative solvers for Stokes flow in dense pillar arrays is due to a fundamental degradation of the inf-sup constant scaling as m^{-1} with pillar density m. They propose an adaptively scaled Augmented Lagrangian method that overcomes this issue, validated by numerical experiments.
The predictive simulation of fluid dynamics in densely packed microfluidic devices, such as Deterministic Lateral Displacement (DLD) arrays, is severely bottlenecked by the stagnation of standard iterative solvers. In this paper, we reveal that this failure is not an algorithmic artifact, but fundamentally rooted in the pre-asymptotic degradation of the pressure-velocity coupling stability. By rigorously analyzing periodic pillar geometries in this generalized lattice framework, we prove that the continuous Ladyzhenskaya-Babuška-Brezzi (LBB) condition, also called the inf-sup constant, deteriorates exactly as $m^{-1}$ up to a positive multiplicative constant, where $m$ is the pillar density (the number of pillars per unit length). This causes a severe a priori error amplification and extreme ill-conditioning in Schur complement of the saddle point system. To overcome this theoretical limit, we propose a parameter-free, adaptively scaled Augmented Lagrangian (AL) stabilization strategy. Extensive numerical experiments on both standard square and highly asymmetric DLD arrays validate our theoretical bounds and demonstrate the robustness of the proposed AL method.