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Flows Over Periodic Hills of Parameterized Geometries

A Dataset for Data-Driven Turbulence Modeling From Direct Simulations


For data-driven turbulence modeling, we need benchmark data from systematically and continuously varied flow conditions (e.g., Reynolds number and geometry) with maximum coverage in the parameter space. To this end, we perform direct numerical simulations of flows over periodic hills with varying slopes, resulting in a family of flows over periodic hills which ranges from incipient to mild and massive separations.

The details are provided in the paper below:

Notes on data format:

  • Mean flow data are provided in coarse meshes (comparable to those used in RANS simulations) as OpenFOAM cases.
  • The same data on the original DNS meshes are also provided as ASCII files.
  • The data include (and only include)
    • mean pressure field,
    • mean velocities fields, and
    • second order statistics of velocities (i.e., the Reynolds stress fields)
    • mean dissipation rate (only for data uploaded on April 15, 2021 or later)
  • Note: instantaneous data and higher order statistics are not saved during our simulations; these data would require very large storage spaces.

Dataset Presented in CAF Paper Above

Scheme

Note: Data for α=3 is present missing.

Dataset

Additional data uploaded on April 15, 2021:

  • Dr. Laizet added a new database with 27 simulations (Reynolds=5600, 3 different heights, 3 different streamwise extents and 3 different hill shapes). For details see: pehill_new_DNS_database/README

Additiional dataset

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