ayz2/superwing_processed

SuperWing (processed)

This is a processed, downsampled derivative of SuperWing, 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 SuperWing. Total size is 0.70 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   (packed in shards/*.tar, see below)
volume_collated/          volume
  manifest.json
  norm_stats_volume*.npz
  samples/<stem>.npy   (packed in shards/*.tar, see below)
RELEASE.json              downsampling factors, columns and row totals

This dataset has ~29k samples per tree, so the per-sample files are packed into ~5 GB uncompressed tar shards to stay within Hub file-count limits. The member paths are relative to the dataset root, so this reproduces the per-sample layout above:

cd <download dir>
for f in collated/shards/*.tar volume_collated/shards/*.tar; do tar -xf "$f"; done

<tree>/shards/index.json maps each stem to its shard. A single sample can be pulled with tar -xf <shard> <tree>/samples/<stem>.npy.

Columns

Surface (collated, 7 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

Dropped from this release: rho, T.

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	cp	pressure coefficient

Dropped from this release: rho_tilde, layer.

Downsampling

tree	samples	row factor	rows (release)	rows (collated source)
collated	28,856	1/1	1.215e+09	1.215e+09
volume_collated	28,294	1/3	2.394e+10	7.182e+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: 23,111 samples
• val: 5,745 samples

Source dataset and preprocessing

SuperWing

What it is. 28 856 transonic solutions over 4239 kinked (double-swept) wing planforms, each at up to eight operating conditions. 56 design variables per wing (7 planform, 18 spanwise, 20 CST section coefficients, 11 operating). The only wall-resolved and structured-mesh campaign here.

Generation. ADflow (MDOLab), steady compressible RANS with Spalart-Allmaras in a fully turbulent setting (no transition model). Structured O-mesh hyperbolically extruded from the surface: 249 circumferential × 41/125 spanwise (inner/outer) × 81 wall-normal layers at y⁺ ≈ 1 (the release ships the inner 70 layers). Solution strategy is 3w multigrid, 500 cycles on coarse levels then up to 3000 on the fine mesh, approximate Newton-Krylov until the total residual drops below 1e-8, then Newton-Krylov to 1e-10.

Parameters. Mach 0.75–0.90, Re fixed at 2.0e7, T∞ = 300 K ⇒ U∞ ≈ 260–313 m/s (derived from a = 347 m/s), AoA 2–12°. The release carries no dimensional quantity at all — no density, no p∞, no viscosity — which is why Reynolds number is unavailable as a normalization scale for this campaign.

Cost. "The simulations are conducted on the 160-core high-performance computing cluster at Tsinghua University for over four months", i.e. ≈ 4.6e5 core-hours for the campaign and ≈ 16 core-hours per case (derived from the wall time, not published per case). Released as 26.7 GB of compressed surface data plus 3.2 TB of volume.

Processing. The surface release is a single dense array, (28856, 9, 44096) float64 (~92 GB), in [sample, channel, point] layout with raw channel order x, y, z, ρ̃, Cp, Cfx, Cfy, Cfz, T̃; the 44 096 cell centres are fixed per wing geometry. The builder transposes to [44096, 9], reorders channels into the shared contract [x, y, z, cp, cfx, cfy, cfz, rho, T], and row-shuffles. Cp/Cf are already coefficients, so no conversion. The raw frame is chord = +x, span = z, vertical = +y with +y the suction side — established by an upper/lower surface pairing test binned on chord × span, then checked for 100% sign agreement with the released CFD lift coefficient — so SuperWing carries the same ORIENT permutation as WindsorML (x ← x, y ← −z, z ← y), which puts negative Cp on the +z side of a lifting wing. The volume arrives as 46 shards of (n, 8, 3086720) float64 (5.72 TB) with freestream-normalized channels x, y, z, ρ̃, p̃, Ṽx, Ṽy, Ṽz. Its topology is undocumented upstream and was recovered here: 3 086 720 = 44 096 × 70, i.e. the surface cells extruded through 70 wall-normal layers in 13 structured blocks, layer-major within a block, with the blocks in a different order in the volume array than in the surface array. The grading is exponential (median wall distance 9e-7 at layer 0 to 6.5 at layer 69), so half of all volume points lie within 0.0085 chord of the wall, and layer 0 is the surface field — its density matches the surface file bit-for-bit. A layer column is therefore carried in the output ([x, y, z, ux, uy, uz, cp, rho_tilde, layer], 9 cols) so that wall-distance thinning is a filter over the collated array rather than a re-read of the raw shards. Volume Cp is recovered as (p̃ − 1)/(½γM²) with γ = 1.4, reproducing the surface Cp column to 4e-8; velocity is kept non-dimensional (u/U∞) since no dimensional scale is shipped. The alignment of each shard to its samples is asserted by un-shuffling the paired surface file and matching the 44 096 layer-0 rows (a wrong offset gives a positional discrepancy of 3.13 against 1.1e-6 for the correct one). One upstream defect: shard 32 is byte-identical to shard 31 (same published checksum), so 562 samples have no volume data and the volume tree holds 28 294 of 28 856. Crop margins are x: 0.25/0.75 L_x, z: 0.15/0.02 L_z, with the thin-axis (y) half-width at 0.20 max(L_x, L_z) — the streamwise reference, not L_y, or the slab clips the shock off the suction side — keeping 81.4–83.8%. Surface Cf is pruned at 3σ per sample on all three components (1 272 434 176 → 1 214 523 900 rows, −4.55%); the removed rows concentrate at the wing tip and aft chord and the pruning is a normalization trade, recorded in collated/pruned_cf.json with a keep-mask so the volume's alignment gate still works. Splits are geometry-grouped 80/20 (23 111/5745).

Citation

TODO: this work, and the upstream dataset's citation.