Coarse large-eddy simulations in a transitional wake flow with flow models under location uncertainty. (30th May 2018)

• Record Type: Journal Article
• Authors: Chandramouli, Pranav; Heitz, Dominique; Laizet, Sylvain; Mémin, Etienne
• Is Part Of: Computers & fluids. Volume 168(2018)
• Page Start: 170
• Page End: 189
• Publication Date: 2018-05-30
• Subjects: Large-eddy simulation -- Cylinder wake flow; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2018.04.001
• Languages: English
• ISSNs: 0045-7930

Abstract

Highlights: Large-eddy simulations are performed on a coarse mesh for cylinder wake at Re = 3900. Models under location uncertainty are compared with more conventional models. A detailed analysis investigating model performance is provided. Models under location uncertainty reproduce the main features of the flow. Abstract: The focus of this paper is to perform coarse-grid large-eddy simulation (LES) using recently developed sub-grid scale (SGS) models of cylinder wake flow at Reynolds number (Re) of 3900. As we approach coarser resolutions, a drop in accuracy is noted for all LES models but more importantly, the numerical stability of classical models is called into question. The objective is to identify a statistically accurate, stable sub-grid scale (SGS) model for this transitional flow at a coarse resolution. The proposed new models under location uncertainty (MULU) are applied in a deterministic coarse LES context and the statistical results are compared with variants of the Smagorinsky model and various reference data-sets (both experimental and Direct Numerical Simulation (DNS)). MULU are shown to better estimate statistics for coarse resolution (at 0.46% the cost of a DNS) while being numerically stable. The performance of the MULU is studied through statistical comparisons, energy spectra, and sub-grid scale (SGS) contributions. The physics behind the MULU are characterised and explored using divergence and curl functions. The additional terms present (velocity bias) in the MULU are shown to improve model performance. The spanwise periodicity observed at low Reynolds is achieved at this moderate Reynolds number through the curl function, in coherence with the birth of streamwise vortices.