Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows

7 May 2021

Papers citing "Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows"

5 / 5 papers shown

Title
Node Assigned physics-informed neural networks for thermal-hydraulic system simulation: CVH/FL module Jeesuk Shin Cheolwoong Kim Sunwoong Yang Minseo Lee S. J. Kim J. Jeon 27 0 0 23 Apr 2025
Comparison of CNN-based deep learning architectures for unsteady CFD acceleration on small datasets Sangam Khanal Shilaj Baral Joongoo Jeon AI4CE 66 1 0 06 Feb 2025
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality Joogoo Jeon Jean Rabault Joel Vasanth Francisco Alcántara-Ávila Shilaj Baral Ricardo Vinuesa AI4CE 51 5 0 25 Jul 2024
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning J. Jeon Juhyeong Lee Ricardo Vinuesa S. J. Kim AI4CE 8 25 0 14 Jun 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 111 355 0 05 Oct 2021