Artificial Compressibility Approaches in Flux Reconstruction for Incompressible Viscous Flow Simulations
Will Trojak, Nagabhushana Rao Vadlamani, James Tyacke and, Freddie Witherden, Antony Jameson

TL;DR
This paper compares artificial compressibility methods for incompressible flow simulations using flux reconstruction, highlighting the strengths and limitations of EDAC and hyperbolised ACM across different flow scenarios.
Contribution
It provides a detailed comparison of EDAC and hyperbolised ACM methods within flux reconstruction, revealing their performance and stability characteristics in various flow regimes.
Findings
EDAC improves divergence reduction linearly as compressibility decreases
EDAC performs well on Taylor-Green vortex but causes early transition in complex flows
Hyperbolised ACM can be beneficial but increases setup complexity
Abstract
Several competing artificial compressibility methods for the incompressible flow equations are examined using the high-order flux reconstruction method. The established artificial compressibility method (ACM) of \citet{Chorin1967} is compared to the alternative entropically damped (EDAC) method of \citet{Clausen2013}, as well as an ACM formulation with hyperbolised diffusion. While the former requires the solution to be converged to a divergence free state at each physical time step through pseudo iterations, the latter can be applied explicitly. We examine the sensitivity of both methods to the parameterisation for a series of test cases over a range of Reynolds numbers. As the compressibility is reduced, EDAC is found to give linear improvements in divergence whereas ACM yields diminishing returns. For the Taylor--Green vortex, EDAC is found to perform well; however on the more…
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Taxonomy
TopicsFluid Dynamics and Turbulent Flows · Computational Fluid Dynamics and Aerodynamics · Model Reduction and Neural Networks
