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Rename P3D -> TCF (3D turbulent channel flow)

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Files changed (27) hide show
  1. README.md +7 -7
  2. TCF/rotated/TCF_test_metadata.npy +3 -0
  3. TCF/rotated/sim0_data_test_rot_x_180.h5 +3 -0
  4. TCF/rotated/sim0_data_test_rot_x_270.h5 +3 -0
  5. TCF/rotated/sim0_data_test_rot_x_270_y_270.h5 +3 -0
  6. TCF/rotated/sim0_data_test_rot_x_270_y_90.h5 +3 -0
  7. TCF/rotated/sim0_data_test_rot_x_270_z_270.h5 +3 -0
  8. TCF/rotated/sim0_data_test_rot_x_270_z_90.h5 +3 -0
  9. TCF/rotated/sim0_data_test_rot_x_90.h5 +3 -0
  10. TCF/rotated/sim0_data_test_rot_x_90_y_270.h5 +3 -0
  11. TCF/rotated/sim0_data_test_rot_x_90_y_90.h5 +3 -0
  12. TCF/rotated/sim0_data_test_rot_x_90_z_270.h5 +3 -0
  13. TCF/rotated/sim0_data_test_rot_x_90_z_90.h5 +3 -0
  14. TCF/rotated/sim0_data_test_rot_y_180.h5 +3 -0
  15. TCF/rotated/sim0_data_test_rot_y_270.h5 +3 -0
  16. TCF/rotated/sim0_data_test_rot_y_270_z_180.h5 +3 -0
  17. TCF/rotated/sim0_data_test_rot_y_90.h5 +3 -0
  18. TCF/rotated/sim0_data_test_rot_y_90_z_180.h5 +3 -0
  19. TCF/rotated/sim0_data_test_rot_z_180.h5 +3 -0
  20. TCF/rotated/sim0_data_test_rot_z_270.h5 +3 -0
  21. TCF/rotated/sim0_data_test_rot_z_270_x_270.h5 +3 -0
  22. TCF/rotated/sim0_data_test_rot_z_270_x_90.h5 +3 -0
  23. TCF/rotated/sim0_data_test_rot_z_90.h5 +3 -0
  24. TCF/rotated/sim0_data_test_rot_z_90_x_270.h5 +3 -0
  25. TCF/rotated/sim0_data_test_rot_z_90_x_90.h5 +3 -0
  26. TCF/sim0_data_test.h5 +3 -0
  27. TCF/sim0_data_train.h5 +3 -0
README.md CHANGED
@@ -30,7 +30,7 @@ We provide three benchmark datasets spanning 2D and 3D physics simulations:
30
  |---------|------|---------------|----------|-------------------|--------|
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  | **KF2D** | 2D Kolmogorov Flow | 2D | 2 (velocity) | 160×160 | [APEBench](https://github.com/Ceyron/apebench) |
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  | **MHD_64** | 3D Magnetohydrodynamics | 3D | 7 (density + velocity + magnetic) | 64×64×64 | [The Well](https://github.com/PolymathicAI/the_well) |
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- | **P3D** | 3D Periodic Channel Flow | 3D | 4 (velocity + pressure) | 96×96×96 | DNS Simulation |
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  ---
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@@ -107,7 +107,7 @@ We provide three benchmark datasets spanning 2D and 3D physics simulations:
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  ---
109
 
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- ## P3D — 3D Periodic Channel Flow
111
 
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  **Physical scenario:** Direct numerical simulation (DNS) of incompressible turbulent flow in a 3D periodic channel. The simulation resolves velocity and pressure fields at high resolution.
113
 
@@ -115,8 +115,8 @@ We provide three benchmark datasets spanning 2D and 3D physics simulations:
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  | File | Shape (velocity) | Shape (pressure) | Size | Description |
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  |------|-------------------|-------------------|------|-------------|
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- | `P3D/sim0_data_train.h5` | `(1, 180, 3, 96, 96, 96)` | `(1, 180, 1, 96, 96, 96)` | ~1.4 GB | Training |
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- | `P3D/sim0_data_test.h5` | `(1, 20, 3, 96, 96, 96)` | `(1, 20, 1, 96, 96, 96)` | ~157 MB | Test |
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  ### HDF5 Structure
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@@ -193,8 +193,8 @@ with h5py.File("Dataset/MHD_64/data/train/MHD_Ma_0.7_Ms_0.5.hdf5", "r") as f:
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  magnetic = f["t1_fields/magnetic_field"][:] # (5, 100, 64, 64, 64, 3)
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  density = f["t0_fields/density"][:] # (5, 100, 64, 64, 64)
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- # === P3D ===
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- with h5py.File("Dataset/P3D/sim0_data_train.h5", "r") as f:
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  velocity = f["velocity"][:] # (1, 180, 3, 96, 96, 96)
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  pressure = f["pressure"][:] # (1, 180, 1, 96, 96, 96)
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  ```
@@ -221,4 +221,4 @@ This dataset is released under the [MIT License](https://opensource.org/licenses
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  - **KF2D**: Generated using the [APEBench](https://github.com/Ceyron/apebench) benchmark framework
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  - **MHD_64**: Subset from [The Well](https://github.com/PolymathicAI/the_well) benchmark
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- - **P3D**: Direct numerical simulation data
 
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  |---------|------|---------------|----------|-------------------|--------|
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  | **KF2D** | 2D Kolmogorov Flow | 2D | 2 (velocity) | 160×160 | [APEBench](https://github.com/Ceyron/apebench) |
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  | **MHD_64** | 3D Magnetohydrodynamics | 3D | 7 (density + velocity + magnetic) | 64×64×64 | [The Well](https://github.com/PolymathicAI/the_well) |
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+ | **TCF** | 3D Turbulent Channel Flow | 3D | 4 (velocity + pressure) | 96×96×96 | DNS Simulation |
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  ---
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107
 
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  ---
109
 
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+ ## TCF — 3D Turbulent Channel Flow
111
 
112
  **Physical scenario:** Direct numerical simulation (DNS) of incompressible turbulent flow in a 3D periodic channel. The simulation resolves velocity and pressure fields at high resolution.
113
 
 
115
 
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  | File | Shape (velocity) | Shape (pressure) | Size | Description |
117
  |------|-------------------|-------------------|------|-------------|
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+ | `TCF/sim0_data_train.h5` | `(1, 180, 3, 96, 96, 96)` | `(1, 180, 1, 96, 96, 96)` | ~1.4 GB | Training |
119
+ | `TCF/sim0_data_test.h5` | `(1, 20, 3, 96, 96, 96)` | `(1, 20, 1, 96, 96, 96)` | ~157 MB | Test |
120
 
121
  ### HDF5 Structure
122
 
 
193
  magnetic = f["t1_fields/magnetic_field"][:] # (5, 100, 64, 64, 64, 3)
194
  density = f["t0_fields/density"][:] # (5, 100, 64, 64, 64)
195
 
196
+ # === TCF ===
197
+ with h5py.File("Dataset/TCF/sim0_data_train.h5", "r") as f:
198
  velocity = f["velocity"][:] # (1, 180, 3, 96, 96, 96)
199
  pressure = f["pressure"][:] # (1, 180, 1, 96, 96, 96)
200
  ```
 
221
 
222
  - **KF2D**: Generated using the [APEBench](https://github.com/Ceyron/apebench) benchmark framework
223
  - **MHD_64**: Subset from [The Well](https://github.com/PolymathicAI/the_well) benchmark
224
+ - **TCF**: Direct numerical simulation data
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