Abstract

This work continues a line of work on developing partially explicit methods for multiscale problems. In our previous works, we considered linear multiscale problems where the spatial heterogeneities are at the subgrid level and are not resolved. In these works, we have introduced contrast-independent, partially explicit time discretizations for linear equations. The contrast-independent, partially explicit time discretization divides the spatial space into two components: contrast dependent (fast) and contrast independent (slow) spaces defined via multiscale space decomposition. Following this decomposition, temporal splitting was proposed, which treats fast components implicitly and slow components explicitly. The space decomposition and temporal splitting are chosen such that they guarantees stability, and we formulated a condition for the time stepping. This condition was formulated as a condition on slow spaces. In this paper, we extend this approach to nonlinear problems. We propose a splitting approach and derive a condition that guarantees stability. This condition requires some type of contrast-independent spaces for slow components of the solution. We present numerical results and show that the proposed methods provide results similar to implicit methods with a time step that is independent of the contrast.

Highlights

  • The work continues our earlier work on linear problems, where we proposed temporal splitting and associated spatial decomposition that guarantees stability

  • We introduce two spatial spaces, the first accounting for spatial features related to fast time scales and the second for spatial features related to “slow” time scales

  • Wherein the first equation solves for fast components implicitly and the second equation solves for slow components explicitly

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Summary

Introduction

Nonlinear problems arise in many applications, and they are typically described by some nonlinear partial differential equations. In many applications, these problems have multiscale nature and contain multiple scales and high contrast. Examples include nonlinear porous media flows (Richards’ equations, Forchheimer flow and so on; see [1,2]), where the media properties contain many spatial scales and high contrast. Due to high contrast in the media properties, these processes occur on multiple time scales. Due to a disparity of time scales, special temporal discretizations are often sought, which is the main goal of the paper in the context of multiscale problems

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