NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design

Mouadh Yagoubi, David Danan, Milad Leyli-abadi, Jean-Patrick Brunet, Jocelyn Ahmed Mazari, Florent Bonnet, maroua gmati, Asma Farjallah, Paola Cinnella, Patrick Gallinari, Marc Schoenauer

Keywords: Geometric Deep Learning · Hybridization · Benchmark · PDE · CFD

Abstract: The integration of machine learning (ML) techniques for addressing intricate physics problems is increasingly recognized as a promising avenue for expediting simulations. However, assessing ML-derived physical models poses a significant challenge for their adoption within industrial contexts. This competition is designed to promote the development of innovative ML approaches for tackling physical challenges, leveraging our recently introduced unified evaluation framework known as Learning Industrial Physical Simulations (LIPS). Building upon the preliminary edition held from November 2023 to March 20241, this iteration centers on a task fundamental to a well-established physical application: airfoil design simulation, utilizing our proposed AirfRANS dataset. The competition evaluates solutions based on various criteria encompassing ML accuracy, computational efficiency, Out-Of-Distribution performance, and adherence to physical principles. Notably, this competition represents a pioneering effort in exploring ML-driven surrogate methods aimed at optimizing the trade-off between computational efficiency and accuracy in physical simulations. Hosted on the Codabench platform, the competition offers online training and evaluation for all participating solutions.

Competition Timeline:

Warm-up phase : July 1st - August 4th
Development phase: August 5th - October 14th
Final phase: October 15th - October 31st

Website: https://ml-for-physical-simulation-challenge.irt-systemx.fr/airfoil-challenge-neurips2024

Primary Contact Email: [e-mail]

Participant Contact Email: [e-mail]

Workshop Format: Hybrid (Vancouver + some online speakers)

Preferred Timezone: UTC+1

Submission Number: 21