HiLiftAeroML: A High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics

Abstract:HiLiftAeroML is, to our knowledge, the first open high-fidelity computational fluid dynamics dataset dedicated to high-lift aircraft aerodynamics. It contains 1,800 simulations spanning 180 variants of the NASA Common Research Model high-lift configuration and ten angles of attack from $4^\circ$ to $22^\circ$. Each case was generated with a GPU-accelerated explicit wall-modeled large-eddy simulation approach on solution-adapted grids of 300--500 million cells, covering attached, separated, and post-stall flow conditions. Comparisons with wind-tunnel measurements for reference landing configurations show good agreement in integrated loads and sectional pressures, with grid adaptation substantially improving drag and pitching-moment predictions. The CC-BY-4.0 release includes geometries, time-averaged surface and volume fields, integrated loads, validation material, and deterministic benchmark splits. Initial GeoTransolver and Transolver baselines, evaluated on the complete native surface and volume support of every held-out case rather than on a sampled subset, reconstruct the fields well for several interpolation and held-out-geometry tests, while high-angle separated flow, limited-data training, and out-of-distribution flow-regime shifts remain substantially harder. The dataset and baselines provide a common resource for developing and assessing data-driven models for realistic high-lift aerodynamics.

70 pages. v2: expanded with GeoTransolver and Transolver baselines, native-support evaluation, updated CFD and data-quality documentation, computational-cost analysis, and public score-reproduction artifacts and checkpoints (this https URL)

Fluid Dynamics (physics.flu-dyn); Machine Learning (cs.LG)

arXiv:2605.19565 [physics.flu-dyn]

(or arXiv:2605.19565v2 [physics.flu-dyn] for this version)