Deep learning at scale for subgrid modeling in turbulent flows

1 October 2019

Papers citing "Deep learning at scale for subgrid modeling in turbulent flows"

4 / 4 papers shown

Title
Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows Kai Fukami K. Fukagata Kunihiko Taira AI4CE 16 104 0 26 Jan 2023
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors Mathis Bode AI4CE 25 4 0 28 Oct 2022
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data Mathis Bode M. Gauding Dominik Goeb Tobias Falkenstein H. Pitsch AI4CE 25 17 0 28 Oct 2022
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS Data Pranshu Pant A. Farimani AI4CE 11 12 0 21 Oct 2020