2 papers
physics.flu-dyn2020
An advanced hybrid deep adversarial autoencoder for parameterized nonlinear fluid flow modelling
M. Cheng, F. Fang, C. C. Pain +1
Considering the high computation cost produced in conventional computation fluid dynamic simulations, machine learning methods have been introduced to flow dynamic simulations in r…
physics.ao-ph2020
Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network
M. Cheng, F. Fang, C. C. Pain +1
Deep learning techniques for improving fluid flow modelling have gained significant attention in recent years. Advanced deep learning techniques achieve great progress in rapidly p…