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README.md

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+---
+license: cc-by-sa-4.0
+pretty_name: WindsorML (processed)
+tags: [cfd, aerodynamics, point-cloud, physics, surrogate-modeling]
+size_categories: [10B<n<100B]
+---
+
+# WindsorML (processed)
+
+> **This is a processed, downsampled derivative of WindsorML, not the original dataset.** Fields were converted to a common frame and non-dimensionalization, rows were randomly subsampled and some columns were dropped (details below). For the original data, see the upstream source.
+
+A preprocessed, downsampled release of WindsorML. Total size is 0.72 TB. Every sample is a float32 point cloud `[n_points, n_cols]` stored as `.npy`, in a common frame and non-dimensionalization shared across the campaigns of this release.
+
+## 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`, 9 columns):
+
+| col | name | meaning |
+|---|---|---|
+| 0 | `x` | position |
+| 1 | `y` | position |
+| 2 | `z` | position |
+| 3 | `cp` | pressure coefficient |
+| 4 | `cf_x` | skin-friction coefficient |
+| 5 | `cf_y` | skin-friction coefficient |
+| 6 | `cf_z` | skin-friction coefficient |
+| 7 | `cp_var` | pressure-coefficient variance |
+| 8 | `yPlus` | wall y+ |
+
+**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) |
+
+## Downsampling
+
+| tree | samples | row factor | rows (release) | rows (collated source) |
+|---|---|---|---|---|
+| `collated` | 350 | 1/1 | 7.935e+08 | 7.935e+08 |
+| `volume_collated` | 350 | 1/3 | 2.472e+10 | 7.417e+10 |
+
+**Rows within each file are in random order**: they were permuted when the files were written. The release keeps the first `n // factor` rows of each collated sample, which is a uniform random subsample of the mesh points. For the same reason, **any contiguous window `arr[s:s+k]` is a uniform random crop**, so `np.load(..., mmap_mode='r')` plus a slice is the intended access pattern. The shipped `norm_stats*.npz` were computed on the full collated trees and remain valid for the subsample.
+
+## Splits
+
+The volume tree uses the surface splits (keyed by stem).
+
+- `train`: 280 samples
+- `val`: 70 samples
+
+## Source dataset and preprocessing
+
+### WindsorML
+
+**What it is.** 355 variants of the Windsor body (a squareback automotive reference geometry),
+released as time-averaged wall-modelled LES. It is the only campaign here with no RANS branch
+anywhere in the closure.
+
+**Generation.** Genuine **WMLES** with the constant-coefficient **Vreman** SGS model and an
+equilibrium wall model imposed as a shear-stress constraint with the outer state probed at a
+fixed 1.5Δ off the wall. Compressible and *explicit*: nominally fourth-order finite differences
+with SSP-RK3 time stepping on Cartesian octree grids (unstructured tree-of-cubes, leaf cubes of
+4³ or 8³ cells) with an immersed-boundary geometry representation, in Volcano ScaLES. Baseline
+grid 275 M cells at 0.75 mm minimum spacing. Fields are time-averaged.
+
+**Parameters.** U∞ = 40 m/s, Re = 2.9e6 on body length (1.044 m); pitching-moment reference
+length 0.6375 m (wheelbase), reference frontal area 0.112 m² for the baseline geometry.
+
+**Cost.** One AWS `g5.48xlarge` node per case (8 × NVIDIA A10G), ~2 min to mesh and ~28 h to
+solve = 224 GPU-hours per case, ≈ 7.8e4 GPU-hours for the campaign.
+
+**Processing.** 350 of the 355 runs are present. The surface file stores fields on *points*
+and already ships dimensionless coefficients, so no dynamic-pressure conversion is applied:
+`[x, y, z, cp, cfx, cfy, cfz, cpvar, yPlus]` (9 cols). The **native frame is rotated relative
+to every other campaign** — x is streamwise, **y is vertical** (floor at y ≈ 0) and z is the
+lateral/width axis — so WindsorML carries an `ORIENT` signed permutation
+(`x ← x, y ← −z, z ← y`) applied to positions, to the surface Cf vector and to the volume
+velocity vector, mapping it into the shared loader frame. The volume is a 21 GB base64/zlib
+inline VTU per run (~325 M points / 291 M hexahedra) whose fields live on *cells* with no
+stored centroids, so cell centres are computed explicitly; one read costs ~227 s and ~36 GB
+RSS. Crop margins in native axes are `[0.5, 0.0, 0.75]/[2.0, 0.5, 0.75] L`
+(stream/vertical/width, never extending below the floor), keeping ~79% of cells. Volume output
+`[x, y, z, ux, uy, uz, p]`, 74.2e9 cells total. One caveat worth recording: the volume tree
+stores pressure in Pa against a solver reference that matches no documented ambient; regressing
+wall-adjacent volume pressure on the paired surface Cp gives q = 1016.6 and p∞ = 37 340.5 at
+R² = 0.88, and these fitted values (not measured ones) are what the unified physical
+normalization uses for this campaign. Splits: random 80/20 (280/70).
+
+## Citation
+
+TODO: this work, and the upstream dataset's citation.

RELEASE.json

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+{
+  "dataset": "windsorml",
+  "row_order": "shuffled; any contiguous window is a uniform subsample",
+  "collated": {
+    "factor": 1,
+    "columns": [
+      "x",
+      "y",
+      "z",
+      "cp",
+      "cf_x",
+      "cf_y",
+      "cf_z",
+      "cp_var",
+      "yPlus"
+    ],
+    "columns_dropped": [],
+    "n_samples": 350,
+    "rows_source": 793529952,
+    "rows_release": 793529952,
+    "bytes_release": 28567123072,
+    "source": "/mnt/ceph/users/azhou/data/windsorml/collated"
+  },
+  "volume_collated": {
+    "factor": 3,
+    "columns": [
+      "x",
+      "y",
+      "z",
+      "ux",
+      "uy",
+      "uz",
+      "p"
+    ],
+    "columns_dropped": [],
+    "n_samples": 350,
+    "rows_source": 74172250746,
+    "rows_release": 24724083473,
+    "bytes_release": 692274382044,
+    "source": "/mnt/ceph/users/azhou/data/windsorml/volume_collated"
+  }
+}

collated/manifest.json

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