most citedDrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction

17 citations · 47 across the 5 of their papers we have counts for

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physics.flu-dyn2025★ 1 cited

TripNet: Learning Large-scale High-fidelity 3D Car Aerodynamics with Triplane Networks

Qian Chen, Mohamed Elrefaie, Angela Dai +1

Surrogate modeling has emerged as a powerful tool to accelerate Computational Fluid Dynamics (CFD) simulations. Existing 3D geometric learning models based on point clouds, voxels,…

physics.flu-dyn2024★ 11 cited

Real-time and On-site Aerodynamics using Stereoscopic PIV and Deep Optical Flow Learning

Mohamed Elrefaie, Steffen Hüttig, Mariia Gladkova +3

We introduce Recurrent All-Pairs Field Transforms for Stereoscopic Particle Image Velocimetry (RAFT-StereoPIV). Our approach leverages deep optical flow learning to analyze time-re…