Stable difference methods for block-oriented adaptive grids

TL;DR

This paper introduces a stable block-oriented adaptive mesh refinement scheme using SBP finite difference methods, improving flexibility and stability at interfaces with minimal accuracy loss, demonstrated on Schrödinger and advection equations.

Contribution

It develops a stable SBP-SAT interface treatment for adaptive grids, allowing more flexible configurations with reduced interface complexity and maintaining overall accuracy.

Findings

Stable discretizations for complex grid configurations.

Numerical simulations show minimal accuracy loss at interfaces.

Effective adaptive mesh organization for multi-variable problems.

Abstract

In this paper, we present a block-oriented scheme for adaptive mesh refinement based on summation-by-parts (SBP) finite difference methods and simultaneous-approximation-term (SAT) interface treatment. Since the order of accuracy at SBP-SAT grid interfaces is lower compared to that of the interior stencils, we strive at using the interior stencils across block-boundaries whenever possible. We devise a stable treatment of SBP-FD junction points, i.e. points where interfaces with different boundary treatment meet. This leads to stable discretizations for more flexible grid configurations within the SBP-SAT framework, with a reduced number of SBP-SAT interfaces. Both first and second derivatives are considered in the analysis. Even though the stencil order is locally reduced close to numerical interfaces and corner points, numerical simulations show that the locally reduced accuracy does not severely reduce the accuracy of the time propagated numerical solution. Moreover, we explain how to organize the grid and how to automatically adapt the mesh, aiming at problems of many variables. Examples of adaptive grids are demonstrated for the simulation of the time-dependent Schr\"odinger equation and for the advection equation.