2 citations · 3 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2024★ 2 cited
DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics
Neil Ashton, Charles Mockett, Marian Fuchs +9
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…
physics.flu-dyn2024★ 1 cited
WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
Neil Ashton, Jordan B. Angel, Aditya S. Ghate +6
This paper presents a new open-source high-fidelity dataset for Machine Learning (ML) containing 355 geometric variants of the Windsor body, to help the development and testing of…