mlsanityData to 7 Oct 2026

DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics

arXiv 2408.11969 ↗First posted 21 Aug 2024physics.flu-dyn cs.CE cs.LGcited by 33

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Abstract (arXiv)

Machine Learning (ML) has the potential to revolutionise the field of automotive aerodynamics, enabling split-second flow predictions early in the design process. However, the lack of open-source training data for realistic road cars, using high-fidelity CFD methods, represents a barrier to their development. To address this, a high-fidelity open-source (CC-BY-SA) public dataset for automotive aerodynamics has been generated, based on 500 parametrically morphed variants of the widely-used DrivAer notchback generic vehicle. Mesh generation and scale-resolving CFD was executed using consistent and validated automatic workflows representative of the industrial state-of-the-art. Geometries and rich aerodynamic data are published in open-source formats. To our knowledge, this is the first large, public-domain dataset for complex automotive configurations generated using high-fidelity CFD.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Aug 2024.

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Citing papers per year: 2024: 1; 2025: 13; 2026: 19.

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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. 2025DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulationscited by 26
  3. 2024X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulationcited by 20
  4. 2025GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformercited by 20
  5. 2026Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometriescited by 20
  6. 2025CarBench: A Comprehensive Benchmark for Neural Surrogates on High-Fidelity 3D Car Aerodynamicscited by 10
  7. 2026GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Trainingcited by 8
  8. 2025FLARE: Fast Low-rank Attention Routing Enginecited by 6
  9. 2025A Benchmarking Framework for AI models in Automotive Aerodynamicscited by 4
  10. 2025AB-UPT for Automotive and Aerospace Applicationscited by 4
  11. 2025Point-wise Diffusion Models for Physical Systems with Shape Variations: Application to Spatio-temporal and Large-scale systemcited by 2
  12. 2025A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamicscited by 2
21 more
  1. 2025Accelerating Transient CFD through Machine Learning-Based Flow Initializationcited by 1
  2. 2026RETO: A Rotary-Enhanced Transformer Operator for High-Fidelity Prediction of Automotive Aerodynamicscited by 1
  3. 2026ShardTensor: Domain Parallelism for Scientific Machine Learningcited by 1
  4. 2025Learning Nonlinear Responses in PET Bottle Buckling with a Hybrid DeepONet-Transolver Frameworkcited by 0
  5. 2025Towards Multi-Fidelity Scaling Laws of Neural Surrogates in CFDcited by 0
  6. 2025GLOBE: Accurate and Generalizable PDE Surrogates using Domain-Inspired Architectures and Equivariancescited by 0
  7. 2026WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamicscited by 0
  8. 2026Towards a Foundation-Model Paradigm for Aerodynamic Prediction in Three-dimensional Designcited by 0
  9. 2026M3: Reframing Training Measures for Discretized Physical Simulationscited by 0
  10. 2026Physics Transformer: Tailoring Transformer for General PDE Predictioncited by 0
  11. 2026Large language models for partial differential equation workflowscited by 0
  12. 2026The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamicscited by 0
  13. 2026FLARE++: Low-rank attention with dynamic attention routingcited by 0
  14. 2026PhysicsBench: A Unified Leaderboard for Generative and Predictive Models in Engineering Design and Simulationcited by 0
  15. 2026FSAN: Flow State Attention Network for Aerodynamic Predictioncited by 0
  16. 2026Distance-Aware Attention and Wall-Distance Expert Routing for Transformer-Based 3D Flow Predictioncited by 0
  17. 2026HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Predictioncited by 0
  18. 2026Does Transolver really need a Transformer?cited by 0
  19. 2026PhysFieldBench: Can Multimodal Models Understand Physical Fields?cited by 0
  20. 2026CANTO: CAD-Native Transformer Operators for AI-Aided Engineeringcited by 0
  21. 2026Cross-Domain Pretraining for Steady-State Neural CFD Surrogatescited by 0