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This paper presents results for a set of parameterised periodic hill geometries using the hybrid RANS-LES approach based on the Spalart-Allmaras improved delayed-detached eddy simulation (IDDES). These results are compared with data from direct numerical simulations. The dataset is intended to be used for data-driven Reynolds-averaged Navier-Stokes (RANS) closure modelling for aerodynamic shape optimisation. As a demonstration, the IDDES data for the baseline geometry is used for turbulent mean flow reconstruction with the \(k-\omega \) shear stress transport model. Flow reconstruction results demonstrate considerable improvements compared to the baseline RANS model.

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A Hybrid RANS-LES Dataset for Data-Driven Turbulent Mean Flow Reconstruction

  • 会议论文

  • 发表日期：

    2025年

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  • Omid Bidar,
  • Sean R Anderson,
  • Ning Qin

摘要

This paper presents results for a set of parameterised periodic hill geometries using the hybrid RANS-LES approach based on the Spalart-Allmaras improved delayed-detached eddy simulation (IDDES). These results are compared with data from direct numerical simulations. The dataset is intended to be used for data-driven Reynolds-averaged Navier-Stokes (RANS) closure modelling for aerodynamic shape optimisation. As a demonstration, the IDDES data for the baseline geometry is used for turbulent mean flow reconstruction with the \(k-\omega \) shear stress transport model. Flow reconstruction results demonstrate considerable improvements compared to the baseline RANS model.