p7physics.flu-dyn

physics.flu-dyn

8 papers

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

Romit Maulik, Bethany Lusch, Prasanna Balaprakash

2002.00470

Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network

M. Cheng, F. Fang, C. C. Pain, I. M. Navon

2004.00707

The Adjoint Petrov-Galerkin Method for Non-Linear Model Reduction

Eric J. Parish, Christopher Wentland, Karthik Duraisamy

1810.03455

Learning to Control PDEs with Differentiable Physics

Philipp Holl, Vladlen Koltun, Nils Thuerey

2001.07457

Machine Learning for Fluid Mechanics

Steven Brunton, Bernd Noack, Petros Koumoutsakos

1905.11075

Deep Learning of Vortex Induced Vibrations

Maziar Raissi, Zhicheng Wang, Michael S. Triantafyllou, George Em Karniadakis

1808.08952

MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar

2005.01463

Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks

Yaser Afshar, Saakaar Bhatnagar, Shaowu Pan, Karthik Duraisamy, Shailendra Kaushik

1905.13166