Aerospace

Fluid / CFD - Airfoil RANS

Parametric airfoil RANS flow-field dataset - compact and ML-pipeline friendly, the go-to starting point for learning fluid surrogates.

CFD Benchmark / Multi-Scenario

Multiphysics benchmark for computational fluid dynamics covering internal/external flows and thermal convection - includes transient and steady-state data.

CFD/Computational Fluid Dynamics

A computational fluid dynamics dataset hosted on HuggingFace, focusing on wind-related fluid simulation data for CFD researchers and engineers.

CFD/Computational Fluid Dynamics

A comprehensive benchmark dataset for training and evaluating neural PDE solvers, containing six standard tasks on regular grids, structured grids, and irregular geometries, used for unified evaluation in the ICML 2024 paper Transolver.

CFD

A dataset of 2000 steady-state CFD simulations for a liquid-cooled dual-chip pin-fin cold plate, accompanied by a POD-NN surrogate model and code to reproduce all figures in the associated paper.

CFD

A physics simulation dataset accompanying the GeoPT paper, covering 5 downstream tasks including aerodynamic simulations, with metadata on mesh sizes, variables, and train/test splits.

Automotive Aerodynamics / Large-Scale CFD

MIT's large-scale automotive aerodynamics dataset: 8,000 parametric car geometries with CFD flow fields, meshes and aerodynamic coefficients.

Aerodynamics / Design Optimization Solver

Open-source CFD and adjoint solver with built-in aerodynamic shape optimization, widely used for airfoil/aircraft analysis and gradient-driven design.

Aerodynamic Design / Surrogate Model

Airfoil aerodynamic simulation and surrogate study: large parametric CFD datasets of NACA airfoils plus FNO/DeepONet surrogate comparison.

Automotive Aerodynamics / Drag Prediction

Train surrogates on high-fidelity LES data for millisecond drag-coefficient (Cd) prediction, enabling digitalization and aero optimization of vehicle external flow.

Flow Control / Turbulent Drag Reduction

An open-source reinforcement learning platform for flow control that couples six CFD solver backends with dozens of pre-configured environments; trained policies transfer zero-shot to a wing and cut skin-friction drag substantially.

Fourier Neural Operator / Beginner Tutorial

Systematic FNO from theory to code - for engineers and researchers wanting neural operators as PDE surrogates.

CFD

Proposes a geometry-aware anisotropic boundary correction method using neural operators as an efficient alternative to traditional CFD solvers for aerodynamic simulation, improving physical modeling near solid boundaries.

CFD

TM4FF introduces a physics-constrained operator learning framework combining Transformer attention with Mamba state-space models for accurate flow field prediction and denoising.

CFD

Proposes periodic Fourier Neural Mapping (p-FNM), a neural-operator framework for rapid prediction of unsteady pressure distributions on turbine rotor blades, targeting aeroelastic analysis in turbomachinery.

CFD

Proposes p-FNM, a neural-operator framework using periodic Fourier mapping to predict unsteady pressure distributions and aeroelastic loads on turbine rotor blades, reducing high-fidelity CFD computational costs.

CFD

Proposes a non-intrusive correction method using VAE latent space adaptation to reduce discrepancies between CFD predictions and experiments for open tip clearance flow in compressor cascades, trained on 166 parametrically sampled CFD total pressure loss fields.

CFD/Fluid

A periodic physics-informed neural network (P-PINN) framework is proposed for solving parametric periodic flows and analyzing finite-amplitude aeroelastic responses in a purely physics-driven manner.

Frontier Paper

Proposes a physics-attention mechanism that projects meshes onto learnable physical-state tokens, improving efficiency and accuracy of PDE solving on large industrial geometries.