Assessing the Sensitivity of Hybrid RANS-LES Simulations to Mesh Resolution, Numerical Schemes and Turbulence Modelling within an Industrial CFD Process

2018-01-0709

04/03/2018

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Event
WCX World Congress Experience
Authors Abstract
Content
A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity. The overall correlation from CFD to the wind-tunnel was still very good with only 1 drag count difference for the A1 & Q3 and 6 drag counts for the TT and A4. The lift correlation was poorer and is the subject of continued research, in particular into the generation of high-quality low y+ meshes and improved turbulence modelling. This paper demonstrates the challenges of finding the optimum setup for hybrid RANS-LES simulations and the large number of influencing parameters.
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DOI
https://doi.org/10.4271/2018-01-0709
Pages
11
Citation
Ashton, N., Unterlechner, P., and Blacha, T., "Assessing the Sensitivity of Hybrid RANS-LES Simulations to Mesh Resolution, Numerical Schemes and Turbulence Modelling within an Industrial CFD Process," SAE Technical Paper 2018-01-0709, 2018, https://doi.org/10.4271/2018-01-0709.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0709
Content Type
Technical Paper
Language
English