Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow

Unsupervised deep learning for super-resolution reconstruction of turbulence

(2021) Hyojin Kim et al.   JOURNAL OF FLUID MECHANICS

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

Deep unsupervised learning of turbulence for inflow generation at various Reynolds numbers

(2020) Junhyuk Kim et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Time-series learning of latent-space dynamics for reduced-order model closure

(2020) Romit Maulik et al.   PHYSICA D-NONLINEAR PHENOMENA

Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

(2020) S. Ashwin Renganathan et al.   PHYSICS OF FLUIDS

Data-driven recovery of hidden physics in reduced order modeling of fluid flows

(2020) Suraj Pawar et al.   PHYSICS OF FLUIDS

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

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

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

CNN-LSTM based reduced order modeling of two-dimensional unsteady flows around a circular cylinder at different Reynolds numbers

(2020) Kazuto Hasegawa et al.   FLUID DYNAMICS RESEARCH

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

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

(2020) Kai Fukami et al.   JOURNAL OF FLUID MECHANICS

A novel method of low-dimensional representation for temporal behavior of flow fields using deep autoencoder

(2019) Noriyasu Omata et al.   AIP Advances

Spatio-temporal proper orthogonal decomposition of turbulent channel flow

(2019) Srikanth Derebail Muralidhar et al.   JOURNAL OF FLUID MECHANICS

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

A deep learning enabler for nonintrusive reduced order modeling of fluid flows

(2019) S. Pawar et al.   PHYSICS OF FLUIDS

Modal Analysis of Fluid Flows: Applications and Outlook

(2019) Kunihiko Taira et al.   AIAA JOURNAL

Nonlinear mode decomposition with convolutional neural networks for fluid dynamics

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

Prediction of turbulent heat transfer using convolutional neural networks

(2019) Junhyuk Kim et al.   JOURNAL OF FLUID MECHANICS

Data-driven discovery of coordinates and governing equations

(2019) Kathleen Champion et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Perspective on machine learning for advancing fluid mechanics

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

Non-intrusive reduced-order modeling for fluid problems: A brief review

(2019) Jian Yu et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING

Numerical evidence of logarithmic regions in channel flow at Reτ=8000

(2018) Yoshinobu Yamamoto et al.   Physical Review Fluids

Modeling of transitional channel flow using balanced proper orthogonal decomposition

(2008) Miloš Ilak et al.   PHYSICS OF FLUIDS