Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180
<p dir="ltr">This database corresponds to a direct numerical simulation (DNS) of an incompressible turbulent channel flow at friction Reynolds number Re_tau=u_tau*delta/nu=180, where delta = 1 m is the channel half-height, u_tau = 1 m/s is the friction velocity, and nu is the kinemat...
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2025
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| _version_ | 1849927625360801792 |
|---|---|
| author | Pablo Portero (22639367) |
| author2 | Joan Calafell (22682822) Lluís Jofre (17295445) |
| author2_role | author author |
| author_facet | Pablo Portero (22639367) Joan Calafell (22682822) Lluís Jofre (17295445) |
| author_role | author |
| dc.creator.none.fl_str_mv | Pablo Portero (22639367) Joan Calafell (22682822) Lluís Jofre (17295445) |
| dc.date.none.fl_str_mv | 2025-11-25T19:44:06Z |
| dc.identifier.none.fl_str_mv | 10.25452/figshare.plus.30636068.v1 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Direct_Numerical_Simulation_Dataset_of_Turbulent_Channel_Flow_at_Re_tau_180/30636068 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Fundamental and theoretical fluid dynamics Turbulent flows Direct Numerical Simulation Wall-bounded Turbulent Flows Machine Learning Computational Fluid Dynamics Fluid Mechanics Flow Physics |
| dc.title.none.fl_str_mv | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p dir="ltr">This database corresponds to a direct numerical simulation (DNS) of an incompressible turbulent channel flow at friction Reynolds number Re_tau=u_tau*delta/nu=180, where delta = 1 m is the channel half-height, u_tau = 1 m/s is the friction velocity, and nu is the kinematic viscosity. The flow is computed with the in-house flow solver RHEA (https://gitlab.com/ProjectRHEA/flowsolverrhea). The simulation is initialized from a parabolic velocity profile seeded with random perturbations, and advanced in time until fully developed turbulence is attained after approximately 10 large-eddy turn-over times (LETOTs), defined as t_ell = delta/u_tau. Once statistical steady-state is reached, instantaneous flow fields are sampled every Delta t/t_ell = 0.5, yielding a database of 4600 equally spaced 3D snapshots. In the present work, the released dataset comprises 1525 snapshots extracted from this sequence, while the full set can be generated using the RHEA flow solver. Data is stored separately in HDF5 files in the different LETOTs folders. Each file comprises a 3D instantaneous snapshot of the following flow fields: (i) velocity in the streamwise (u), wall-normal (v) and spanwise (w) directions, and (ii) pressure.</p><p dir="ltr">The mesh is stored in the 3d_turbulent_channel_flow-MESH.h5 file located in the mesh folder. The computational domain extends 4*pi*delta x 2*delta x 4/3*pi*delta in the streamwise (x), wall-normal (y) and spanwise (z) directions. The grid comprises 256 x 128 x 128 points, with uniform spacing in the homogeneous directions corresponding to Delta x^+ = 9 and Delta z^+ = 6, and a stretched distribution in the y-direction such that the first off-wall point is located at y^+ = 0.1 and 0.1 < Delta y^+ < 4.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_11f8cb7fd30cdb09fefdd57dc8c00cbc |
| identifier_str_mv | 10.25452/figshare.plus.30636068.v1 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30636068 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180Pablo Portero (22639367)Joan Calafell (22682822)Lluís Jofre (17295445)Fundamental and theoretical fluid dynamicsTurbulent flowsDirect Numerical SimulationWall-bounded Turbulent FlowsMachine LearningComputational Fluid DynamicsFluid MechanicsFlow Physics<p dir="ltr">This database corresponds to a direct numerical simulation (DNS) of an incompressible turbulent channel flow at friction Reynolds number Re_tau=u_tau*delta/nu=180, where delta = 1 m is the channel half-height, u_tau = 1 m/s is the friction velocity, and nu is the kinematic viscosity. The flow is computed with the in-house flow solver RHEA (https://gitlab.com/ProjectRHEA/flowsolverrhea). The simulation is initialized from a parabolic velocity profile seeded with random perturbations, and advanced in time until fully developed turbulence is attained after approximately 10 large-eddy turn-over times (LETOTs), defined as t_ell = delta/u_tau. Once statistical steady-state is reached, instantaneous flow fields are sampled every Delta t/t_ell = 0.5, yielding a database of 4600 equally spaced 3D snapshots. In the present work, the released dataset comprises 1525 snapshots extracted from this sequence, while the full set can be generated using the RHEA flow solver. Data is stored separately in HDF5 files in the different LETOTs folders. Each file comprises a 3D instantaneous snapshot of the following flow fields: (i) velocity in the streamwise (u), wall-normal (v) and spanwise (w) directions, and (ii) pressure.</p><p dir="ltr">The mesh is stored in the 3d_turbulent_channel_flow-MESH.h5 file located in the mesh folder. The computational domain extends 4*pi*delta x 2*delta x 4/3*pi*delta in the streamwise (x), wall-normal (y) and spanwise (z) directions. The grid comprises 256 x 128 x 128 points, with uniform spacing in the homogeneous directions corresponding to Delta x^+ = 9 and Delta z^+ = 6, and a stretched distribution in the y-direction such that the first off-wall point is located at y^+ = 0.1 and 0.1 < Delta y^+ < 4.</p>2025-11-25T19:44:06ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.25452/figshare.plus.30636068.v1https://figshare.com/articles/dataset/Direct_Numerical_Simulation_Dataset_of_Turbulent_Channel_Flow_at_Re_tau_180/30636068CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306360682025-11-25T19:44:06Z |
| spellingShingle | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 Pablo Portero (22639367) Fundamental and theoretical fluid dynamics Turbulent flows Direct Numerical Simulation Wall-bounded Turbulent Flows Machine Learning Computational Fluid Dynamics Fluid Mechanics Flow Physics |
| status_str | publishedVersion |
| title | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| title_full | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| title_fullStr | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| title_full_unstemmed | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| title_short | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| title_sort | Direct Numerical Simulation Dataset of Turbulent Channel Flow at Re_tau=180 |
| topic | Fundamental and theoretical fluid dynamics Turbulent flows Direct Numerical Simulation Wall-bounded Turbulent Flows Machine Learning Computational Fluid Dynamics Fluid Mechanics Flow Physics |