| --- |
| license: cc-by-sa-4.0 |
| pretty_name: DrivAerML (processed) |
| tags: [cfd, aerodynamics, point-cloud, physics, surrogate-modeling] |
| size_categories: [10B<n<100B] |
| --- |
| |
| # DrivAerML (processed) |
|
|
| This is a processed, downsampled version of DrivAerML, not the original dataset. |
| Fields were converted to a common frame and non-dimensionalized, rows were randomly subsampled and some variables were dropped. |
| For the original data, see the original [paper](https://arxiv.org/abs/2408.11969). For dataloaders and processing details please see our [paper](https://arxiv.org/abs/2610.10398v1), or [Github](https://github.com/anthonyzhou-1/cross_domain_cfd/tree/main). |
|
|
| The original size was 2.3 TB, so both the surface and volume fields are downsampled by 3x to reach a size of 0.75 TB. |
|
|
| ## Layout |
|
|
| ``` |
| collated/ surface |
| manifest.json [{stem, n_points, n_points_source, ...}] |
| splits/{train,val}.json |
| norm_stats*.npz per-column normalization statistics |
| samples/<stem>.npy |
| volume_collated/ volume |
| manifest.json |
| norm_stats_volume*.npz |
| samples/<stem>.npy |
| RELEASE.json downsampling factors, columns and row totals |
| ``` |
|
|
| ## Columns |
|
|
| **Surface** (`collated`, 7 columns): |
|
|
| | col | name | meaning | |
| |---|---|---| |
| | 0 | `x` | position | |
| | 1 | `y` | position | |
| | 2 | `z` | position | |
| | 3 | `p` | static pressure (raw solver units; Cp = (p - p_inf) / q) | |
| | 4 | `tau_x` | wall shear stress (raw) | |
| | 5 | `tau_y` | wall shear stress (raw) | |
| | 6 | `tau_z` | wall shear stress (raw) | |
|
|
| Dropped from this release: Cp, pPrime2. |
|
|
| **Volume** (`volume_collated`, 7 columns): |
|
|
| | col | name | meaning | |
| |---|---|---| |
| | 0 | `x` | position | |
| | 1 | `y` | position | |
| | 2 | `z` | position | |
| | 3 | `ux` | velocity | |
| | 4 | `uy` | velocity | |
| | 5 | `uz` | velocity | |
| | 6 | `p` | static pressure (raw solver units; Cp = (p - p_inf) / q) | |
| |
| |
| ## Splits |
| |
| The volume tree uses the surface splits (keyed by stem). |
| |
| - `train`: 386 samples |
| - `val`: 97 samples |
| |
| Either use norm_stats_centered.npz, or norm_stats_thinned.npz. The centered stats are computed on the simulation mesh (i.e., native discretization), while the thinned stats are computed after (roughly) uniform sampling. |
| |
