Unconditional stability and convergence analysis of novel regularization schemes for the Navier-Stokes equations

TL;DR

This paper introduces novel decoupled schemes for the Navier-Stokes equations that are unconditionally stable, efficient, and do not require pressure boundary conditions, with proven convergence and error estimates.

Contribution

The paper develops new regularization schemes based on penalty and sequential methods that ensure stability and convergence without time step restrictions.

Findings

Schemes are unconditionally stable and convergent in 2D and 3D.

High-order regularity and optimal error estimates are established.

Compared schemes demonstrate improved accuracy and efficiency over classic methods.

Abstract

In this paper, we construct novel first- and second-order decoupled schemes for the Navier-Stokes equations based on the penalty method and the sequential regularization method (SRM), respectively. These schemes do not require the boundary condition on the pressure and thus preserve the original velocity boundary conditions. By using the idea of the scalar auxiliary variable (SAV), the nonlinear terms of these schemes are treated explicitly, which improves computational efficiency while maintaining stability. It is important to note that we carefully reformulated the Navier-Stokes system to ensure convergence of the proposed scheme without any restriction on the time step. For the Penalty-SAV (P-SAV) schemes, at each time step it is only necessary to solve elliptic equations with constant coefficients. We prove the high-order stability (high-order regularities of the solution) of the schemes, and establish an unconditional (without time step constraints) global optimal error estimate in two dimensions as well as a local error estimate in three dimensions for the first-order scheme. Furthermore, to more accurately approximate the incompressibility constraint without introducing extra stiffness into the system, the sequential regularization-SAV (SR-SAV) schemes are developed, and their error estimates are provided. In addition, we compare our proposed scheme with the classic linearized projection scheme to demonstrate its accuracy and efficiency.