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

arXiv:2605.19565 · physics.flu-dyn, cs.LG · Submitted 2026-05-19 · Read on arXiv

physics.flu-dyn, cs.LG

Submitted: 2026-05-19

Updated: 2026-09-25

Terminology

• Fidelity — 83× in this paper · explained in 2 episodes
• Computational Fluid Dynamics — 57× in this paper
• Angle of Attack — 28× in this paper
• Adaptation — 14× in this paper · explained in 1 episode
• Accuracy — 13× in this paper · explained in 1 episode
• Generalization — 12× in this paper · explained in 13 episodes
• Large Eddy Simulation — 7× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Convective Time Units — 5× in this paper
• NASA Common Research Model — 5× in this paper
• Adam — 4× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Wall-Modeled Large Eddy Simulation — 3× in this paper
• AI surrogate models — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• AI Foundation Model — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Dynamic Modeling — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Mean Aerodynamic Chord — 1× in this paper
• Neural Surrogates — 1× in this paper · explained in 2 episodes
• Root Mean Square — 1× in this paper
• Texas Advanced Computing Center — 1× in this paper
• While Reynolds-Averaged Navier-Stokes — 1× in this paper
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• AB-UPT for Automotive and Aerospace Applications
• AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
• Fluid Intelligence: A Forward Look on AI Foundation Models in Computational Fluid Dynamics
• AB-UPT: Scaling Neural CFD Surrogates for High-Fidelity Automotive Aerodynamics Simulations via Anchored-Branched Universal Physics Transformers
• DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations
• BlendedNet++: A dataset and benchmark for field-resolved aerodynamics and inverse design of blended wing body aircraft
• X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation
• Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes
• Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary Domains
• SuperWing: a comprehensive transonic wing dataset for data-driven aerodynamic design

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