Multirate partially explicit scheme for multiscale flow problems

TL;DR

This paper introduces a multirate partially explicit scheme for multiscale flow problems with high-contrast coefficients, enabling efficient and stable simulations by combining implicit and explicit methods with adaptive time stepping.

Contribution

The work develops a novel multirate splitting scheme with multiscale subspaces and adaptive refinement, improving efficiency and stability for high-contrast multiscale flow simulations.

Findings

The scheme achieves contrast-independent stability.

Adaptive local temporal refinement enhances computational efficiency.

Numerical tests confirm the method's effectiveness.

Abstract

For time-dependent problems with high-contrast multiscale coefficients, the time step size for explicit methods is affected by the magnitude of the coefficient parameter. With a suitable construction of multiscale space, one can achieve a stable temporal splitting scheme where the time step size is independent of the contrast. Consider the parabolic equation with heterogeneous diffusion parameter, the flow rates vary significantly in different regions due to the high-contrast features of the diffusivity. In this work, we aim to introduce a multirate partially explicit splitting scheme to achieve efficient simulation with the desired accuracy. We first design multiscale subspaces to handle flow with different speed. For the fast flow, we obtain a low-dimensional subspace with respect to the high-diffusive component and adopt an implicit time discretization scheme. The other multiscale subspace will take care of the slow flow, and the corresponding degrees of freedom are treated explicitly. Then a multirate time stepping is introduced for the two parts. The stability of the multirate methods is analyzed for the partially explicit scheme. Moreover, we derive local error estimators corresponding to the two components of the solutions and provide an upper bound of the errors. An adaptive local temporal refinement framework is then proposed to achieve higher computational efficiency. Several numerical tests are presented to demonstrate the performance of the proposed method.