Vorticity-based polynomial adaptation for moving and deforming domains. (15th December 2021)

• Record Type: Journal Article
• Authors: Ghoreishi, Ramin; Vermeire, Brian C.
• Is Part Of: Computers & fluids. Volume 231(2021)
• Publication Date: 2021-12-15
• Subjects: Polynomial adaptation -- Arbitrary Lagrangian–Eulerian -- Flux reconstruction -- Load balancing; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2021.105160
• Languages: English
• ISSNs: 0045-7930

Abstract

Abstract: This paper introduces a novel non-dimensional vorticity-based polynomial adaptation indicator for moving and deforming domains using a high-order unstructured spatial discretization. We verify the utility of this approach when applied to the Arbitrary Lagrangian–Eulerian (ALE) form of the compressible Navier–Stokes equations for a range of applications on moving and deforming domains. Specifically, we verify the ALE implementation by performing simulations of an Euler Vortex (EV), and then, illustrate the accuracy and efficiency of the adaptation routine by performing simulations of flow over an oscillating circular cylinder with two different flow settings, dynamic stall of a 2D NACA 0012 airfoil undergoing heaving and pitching motions, shallow dynamic stall of a 3D SD 7003 airfoil undergoing heaving and pitching motions, and flow over a Vertical Axis Wind Turbine (VAWT) composed of two NACA 0012 airfoils. Results demonstrate that the non-dimensional vorticity indicator can track regions of interest, such as vortices and boundary layers, and yields a significant reduction in degrees of freedom when paired with polynomial adaptation. Highlights: A non-dimensional vorticity-based adaptation indicator is introduced for polynomial adaptation. Polynomial adaptation is carried out for moving and deforming domains. Dynamic load balancing is used to increase the efficiency of the adaptation. The flux reconstruction spatial discretization is used. Results demonstrate that adaptation yields a significant speedup over simulations with uniform polynomial degree.