Machine-learning-based spatio-temporal super resolution reconstruction of turbulent flows

Deep learning methods for super-resolution reconstruction of turbulent flows

(2020) Bo Liu et al.   PHYSICS OF FLUIDS

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

(2020) Maziar Raissi et al.   SCIENCE

Assessment of supervised machine learning methods for fluid flows

(2020) Kai Fukami et al.   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies of various shapes

(2020) Kazuto Hasegawa et al.   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Reconstructing the time evolution of wall-bounded turbulent flows from non-time-resolved PIV measurements

(2020) C. Vamsi Krishna et al.   Physical Review Fluids

Special issue on machine learning and data-driven methods in fluid dynamics

(2020) Steven L. Brunton et al.   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data

(2020) Kai Fukami et al.   PHYSICS OF FLUIDS

Probabilistic neural networks for fluid flow surrogate modeling and data recovery

(2020) Romit Maulik et al.   Physical Review Fluids

Super-resolution reconstruction of turbulent flows with machine learning

(2019) Kai Fukami et al.   JOURNAL OF FLUID MECHANICS

Predictions of turbulent shear flows using deep neural networks

(2019) P. A. Srinivasan et al.   Physical Review Fluids

Synthetic turbulent inflow generator using machine learning

(2019) Kai Fukami et al.   Physical Review Fluids

Machine Learning for Fluid Mechanics

(2019) Steven L. Brunton et al.   Annual Review of Fluid Mechanics

Data-driven prediction of unsteady flow over a circular cylinder using deep learning

(2019) Sangseung Lee et al.   JOURNAL OF FLUID MECHANICS

Nonlinear mode decomposition with convolutional neural networks for fluid dynamics

(2019) Takaaki Murata et al.   JOURNAL OF FLUID MECHANICS

Perspective on machine learning for advancing fluid mechanics

(2019) M. P. Brenner et al.   Physical Review Fluids

Turbulence Modeling in the Age of Data

(2018) Karthik Duraisamy et al.   Annual Review of Fluid Mechanics

Subgrid modelling for two-dimensional turbulence using neural networks

(2018) R. Maulik et al.   JOURNAL OF FLUID MECHANICS

Network structure of two-dimensional decaying isotropic turbulence

(2016) Kunihiko Taira et al.   JOURNAL OF FLUID MECHANICS

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

(2016) Julia Ling et al.   JOURNAL OF FLUID MECHANICS

A fast immersed boundary method using a nullspace approach and multi-domain far-field boundary conditions

(2007) Tim Colonius et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING