Emerging trends in machine learning for computational fluid dynamics

Emerging trends in machine learning for computational fluid dynamics

28 November 2022

Ricardo Vinuesa

Steve Brunton

Papers citing "Emerging trends in machine learning for computational fluid dynamics"

8 / 8 papers shown

Title
Navigation in a simplified Urban Flow through Deep Reinforcement Learning Federica Tonti Jean Rabault Ricardo Vinuesa 13 3 0 26 Sep 2024
AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics Neil Ashton Danielle C. Maddix Samuel Gundry Parisa M. Shabestari AI4CE 38 2 0 30 Jul 2024
DeltaPhi: Learning Physical Trajectory Residual for PDE Solving Xihang Yue Linchao Zhu Yi Yang AI4CE 34 1 0 14 Jun 2024
A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty A. Agrawal P. Koutsourelakis AI4CE 9 15 0 05 Jul 2023
Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil Rahul Sundar Dipanjan Majumdar Didier Lucor Sunetra Sarkar PINN AI4CE 25 6 0 23 Jun 2023
Predictive Limitations of Physics-Informed Neural Networks in Vortex Shedding Pi-Yueh Chuang L. Barba PINN 26 10 0 31 May 2023
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 98 353 0 05 Oct 2021
Data-driven discovery of intrinsic dynamics D. Floryan M. Graham AI4CE 85 71 0 12 Aug 2021