Robust and Efficient Modular Grad-Div Stabilization
For computational fluid dynamics researchers, this provides a robust and efficient way to add grad-div stabilization to existing NSE codes without performance degradation.
The paper introduces two modular grad-div stabilization algorithms for Navier-Stokes equations that avoid breakdown and slowdown for large grad-div parameters, with proven stability and optimal convergence. Numerical tests confirm the theory and show benefits over fully coupled stabilization.
This paper presents two modular grad-div algorithms for calculating solutions to the Navier-Stokes equations (NSE). These algorithms add to an NSE code a minimally intrusive module that implements grad-div stabilization. The algorithms do not suffer from either breakdown (locking) or debilitating slow down for large values of grad-div parameters. Stability and optimal-order convergence of the methods are proven. Numerical tests confirm the theory and illustrate the benefits of these algorithms over a fully coupled grad-div stabilization.