mlsanityData to 7 Oct 2026

AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics

arXiv 2407.20801 ↗First posted 30 Jul 2024physics.flu-dyn cs.CE cs.LGcited by 13

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Abstract (arXiv)

The development of Machine Learning (ML) methods for Computational Fluid Dynamics (CFD) is currently limited by the lack of openly available training data. This paper presents a new open-source dataset comprising of high fidelity, scale-resolving CFD simulations of 500 geometric variations of the Ahmed Car Body - a simplified car-like shape that exhibits many of the flow topologies that are present on bluff bodies such as road vehicles. The dataset contains simulation results that exhibit a broad set of fundamental flow physics such as geometry and pressure-induced flow separation as well as 3D vortical structures. Each variation of the Ahmed car body were run using a high-fidelity, time-accurate, hybrid Reynolds-Averaged Navier-Stokes (RANS) - Large-Eddy Simulation (LES) turbulence modelling approach using the open-source CFD code OpenFOAM. The dataset contains boundary, volume, geometry, and time-averaged forces/moments in widely used open-source formats. In addition, the OpenFOAM case setup is provided so that others can reproduce or extend the dataset. This represents to the authors knowledge, the first open-source large-scale dataset using high-fidelity CFD methods for the widely used Ahmed car body that is available to freely download with a permissive license (CC-BY-SA).

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 22 of its 85 references that are in the map. First posted on arXiv 30 Jul 2024.

Builds on

22 of 85 references.

References · 22

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10 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 7.

13 papers.

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  1. 2025AB-UPT: Scaling Neural CFD Surrogates for High-Fidelity Automotive Aerodynamics Simulations via Anchored-Branched Universal Physics Transformerscited by 49
  2. 2026Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometriescited by 20
  3. 2025CarBench: A Comprehensive Benchmark for Neural Surrogates on High-Fidelity 3D Car Aerodynamicscited by 10
  4. 2025A Benchmarking Framework for AI models in Automotive Aerodynamicscited by 4
  5. 2025MSPT: Efficient Large-Scale Physical Modeling via Parallelized Multi-Scale Attentioncited by 3
  6. 2025NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysiscited by 0
  7. 2025ChannelFlow-Tools: A Configuration-Driven Pipeline for Generating Machine-Learning-Ready Datasets of 3D Obstructed Channel Flowscited by 0
  8. 2026WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamicscited by 0
  9. 2026M3: Reframing Training Measures for Discretized Physical Simulationscited by 0
  10. 2026MENO: Memory-Efficient Neural Operatorcited by 0
  11. 2026CANTO: CAD-Native Transformer Operators for AI-Aided Engineeringcited by 0
  12. 2026SHIFT-Truck: A High-Fidelity Aerodynamics Dataset and Benchmark for Pickup Truckscited by 0
1 more
  1. 2026Cross-Domain Pretraining for Steady-State Neural CFD Surrogatescited by 0