Bound-preserving and entropy stable enriched Galerkin methods for nonlinear hyperbolic equations

TL;DR

This paper introduces novel bound-preserving and entropy-stable limiting techniques for enriched Galerkin methods applied to nonlinear hyperbolic equations, ensuring stability, conservation, and accuracy.

Contribution

It develops and analyzes new limiters tailored for enriched Galerkin discretizations to enforce stability and maximum principles in nonlinear hyperbolic problems.

Findings

Limiters prevent violations of constraints.

Methods preserve optimal accuracy for smooth solutions.

Numerical results confirm stability and effectiveness.

Abstract

In this paper, we develop monolithic limiting techniques for enforcing nonlinear stability constraints in enriched Galerkin (EG) discretizations of nonlinear scalar hyperbolic equations. To achieve local mass conservation and gain control over the cell averages, the space of continuous (multi-)linear finite element approximations is enriched with piecewise-constant functions. The resulting spatial semi-discretization has the structure of a variational multiscale method. For linear advection equations, it is inherently stable but generally not bound preserving. To satisfy discrete maximum principles and ensure entropy stability in the nonlinear case, we use limiters adapted to the structure of our locally conservative EG method. The cell averages are constrained using a flux limiter, while the nodal values of the continuous component are constrained using a clip-and-scale limiting strategy for antidiffusive element contributions. The design and analysis of our new algorithms build on recent advances in the fields of convex limiting and algebraic entropy fixes for finite element methods. In addition to proving the claimed properties of the proposed approach, we conduct numerical studies for two-dimensional nonlinear hyperbolic problems. The numerical results demonstrate the ability of our limiters to prevent violations of the imposed constraints, while preserving the optimal order of accuracy in experiments with smooth solutions.