5 papers
HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics
Neil Ashton, Adam Clark, Liam Heidt +11
This paper describes the first-ever open-source high-fidelity CFD dataset of a high-lift aircraft for the purpose of AI surrogate model development. The dataset is composed of 1800…
Fluid Intelligence: A Forward Look on AI Foundation Models in Computational Fluid Dynamics
Neil Ashton, Johannes Brandstetter, Siddhartha Mishra
Driven by the advancement of GPUs and AI, the field of Computational Fluid Dynamics (CFD) is undergoing significant transformations. This paper bridges the gap between the machine…
A Benchmarking Framework for AI models in Automotive Aerodynamics
Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian +5
In this paper, we introduce a benchmarking framework within the open-source NVIDIA PhysicsNeMo-CFD framework designed to systematically assess the accuracy, performance, scalabilit…
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…
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…