Entropy damping and Bulk Viscosity based artificial compressibility methods on dynamically distorting grids

Abstract

Artificial Compressibility Methods (ACM) rely on an artificial equation that links the pressure and velocity fields to model incompressible flows. These hyperbolic/parabolic equations can rapidly converge to a ‘nearly’ divergence-free flow field in contrast to the methods based on the elliptic pressure Poisson equation. We compare the computational efficacy of two ACMs, namely, the Bulk Viscosity ACM (BVACM) and Entropically Damped Artificial Compressibility (EDAC) recently proposed in the literature. The methods implemented in the in-house high-order finite difference solver, COMPSQUARE, are validated for the test cases of a 2D doubly periodic shear layer (DPSL), a 3D Taylor Green Vortex (TGV), and 2D/3D NACA0012 airfoil pitching about the quarter chord. The efficacy of these methods was also tested on static and dynamic grids using conservative metrics. Although both ACMs yield competitive results, the divergence of the velocity field is found to be more prominent in the highly unsteady regions. BVACM resulted in (a) a superior divergence-free velocity field and (b) $20-38\text{\%}$ higher maximum stable time than the EDAC, thereby increasing the computational speed. A higher value of the bulk viscosity coefficient, $A$, although ensures a stringent divergence-free velocity field, is shown to have minimal effect on the flow statistics and reduce the maximum stable time step. The parabolic–hyperbolic nature of the governing equations and the lack of dual time-stepping in BVACM and EDAC ensures that both these methods are highly scalable on massively parallel architectures. Since the energy equation is no longer required to compute the velocity field, both EDAC and BVACM approaches are found to be $8-10\text{\%}$ faster than the weakly compressible Navier–Stokes simulations under the low-Mach number limit.