Monotonicity-preserving finite element schemes with adaptive mesh refinement for hyperbolic problems

TL;DR

This paper evaluates monotonicity-preserving finite element schemes with adaptive mesh refinement for hyperbolic problems, comparing linear and nonlinear stabilization methods in terms of accuracy and computational efficiency.

Contribution

It extends and assesses monotonicity-preserving schemes to hierarchical octree AMR, introduces a new shock detection criterion, and analyzes the cost-effectiveness of nonlinear stabilization.

Findings

Nonlinear schemes can be cost-effective on sufficiently refined meshes.

Refining around shocks is more effective than sharper shock capturing terms.

The new graph Laplacian-based shock detector outperforms the Kelly estimator.

Abstract

This work is focused on the extension and assessment of the monotonicity-preserving scheme in [3] and the local bounds preserving scheme in [5] to hierarchical octree adaptive mesh refinement (AMR). Whereas the former can readily be used on this kind of meshes, the latter requires some modifications. A key question that we want to answer in this work is whether to move from a linear to a nonlinear stabilization mechanism pays the price when combined with shock-adapted meshes. Whereas nonlinear (or shock-capturing) stabilization leads to improved accuracy compared to linear schemes, it also negatively hinders nonlinear convergence, increasing computational cost. We compare linear and nonlinear schemes in terms of the required computational time versus accuracy for several steady benchmark problems. Numerical results indicate that, in general, nonlinear schemes can be cost-effective for sufficiently refined meshes. Besides, it is also observed that it is better to refine further around shocks rather than use sharper shock capturing terms, which usually yield stiffer nonlinear problems. In addition, a new refinement criterion has been proposed. The proposed criterion is based on the graph Laplacian used in the definition of the stabilization method. Numerical results show that this shock detector performs better than the well-known Kelly estimator for problems with shocks or discontinuities.