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Published June 1, 2024 | Published
Journal Article

Sensitivity analysis of wall-modeled large-eddy simulation for separated turbulent flow

  • 1. ROR icon California Institute of Technology

Abstract

In this study, we conduct a parametric analysis to evaluate the sensitivities of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS) models, mesh resolution, wall boundary conditions and mesh anisotropy. While such investigations have been conducted for attached/flat-plate flow configurations, systematic studies specifically targeting turbulent flows with separation are notably sparse. To bridge this gap, our study focuses on the flow over a two-dimensional Gaussian-shaped bump at a moderately high Reynolds number, which involves smooth-body separation of a turbulent boundary layer under pressure-gradient and surface-curvature effects. In the simulations, the no-slip condition at the wall is replaced by three different forms of boundary condition based on the thin boundary layer equations and the mean wall-shear stress from high-fidelity numerical simulation to avoid the additional complexity of modeling the wall-shear stress. Various statistics, including the mean separation bubble size, mean velocity profile, and dissipation from SGS model, are compared and analyzed. The results reveal that capturing the separation bubble strongly depends on the choice of SGS model. While simulations approach grid convergence with resolutions nearing those of wall-resolved LES meshes, above this limit, the LES predictions exhibit intricate sensitivities to mesh resolution. Furthermore, both wall boundary conditions and the anisotropy of mesh cells exert discernible impacts on the turbulent flow predictions, yet the magnitudes of these impacts vary based on the specific SGS model chosen for the simulation.

    Copyright and License

    © 2024 Elsevier.

    Acknowledgement

    This work was supported by National Science Foundation (NSF) grant No. 2152705. Computer time was provided by the Discover project at Pittsburgh Supercomputing Center through allocation PHY230012 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by NSF grants No. 2138259, No. 2138286, No. 2138307, No. 2137603, and No. 2138296. The authors sincerely thank Dr. Ali Uzun and Dr. Mujeeb Malik for generously sharing their DNS data. We also extend special gratitude to Dr. Meng Wang for his invaluable help.

    Contributions

    Di Zhou: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. H. Jane Bae: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – review & editing.

    Data Availability

    Data will be made available on request.

    Conflict of Interest

    The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: H. Jane Bae reports financial support was provided by National Science Foundation. H. Jane Bae reports equipment, drugs, or supplies was provided by Pittsburgh Supercomputing Center.

    Additional details

    Created:
    June 26, 2024
    Modified:
    June 26, 2024