High-performance computational homogenization of Stokes-Brinkman flow with an Anderson-accelerated FFT method

Fluid flow problems in bi-porous media have strong implications in a variety of industrial applications, such as nuclear waste disposal and composites manufacturing. Despite various numerical solutions proposed in the literature, the prediction of dual-scale flow remains a challenging task due to the requirement of fine meshes to resolve the complex microstructures of bi-porous media. This paper introduces a new numerical solver based on fast Fourier transform (FFT) for the Stokes-Brinkman problem to predict fluid flow in bi-porous media with local anisotropy. The novel FFT solver is derived from a velocity-form of the problem, in contrast to the stress-form proposed by a recent work. The Anderson acceleration technique is applied for the first time to the Stokes-Brinkman problem, leading to a substantial (orders of magnitude) improvement of the convergence rate. A range of detailed numerical examples are provided to validate the method against the analytical and literature results. Parametric studies are also demonstrated to aid in the selection of model parameters to achieve optimum numerical performance. With a 3D unit cell of a woven textile fabric, we demonstrate that the proposed method is capable of handling high-resolution simulations with strongly heterogeneous microstructures. Combined with a parallelized implementation over high-performance computing systems, our method demonstrates a new state-of-the-art in numerical solvers for the Stokes-Brinkman problem, in terms of computation capacity.

Automated summary

This paper presents a new numerical solver based on fast Fourier transform (FFT) for predicting fluid flow in bi-porous media with local anisotropy. The solver is derived from a velocity-form of the Stokes-Brinkman problem and utilizes the Anderson acceleration technique to improve the convergence rate. Detailed numerical examples and parametric studies are provided to validate the method and demonstrate its performance. The proposed method, combined with parallelization on high-performance computing systems, represents a state-of-the-art numerical solver for the Stokes-Brinkman problem.