Prediction of turbulent heat transfer using convolutional neural networks

Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control

(2019) Jean Rabault et al.   JOURNAL OF FLUID MECHANICS

Dense motion estimation of particle images via a convolutional neural network

(2019) Shengze Cai et al.   EXPERIMENTS IN FLUIDS

Super-resolution reconstruction of turbulent flows with machine learning

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

A turbulent heat flux prediction framework based on tensor representation theory and machine learning

(2018) C. Sotgiu et al.   INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER

Prediction model of velocity field around circular cylinder over various Reynolds numbers by fusion convolutional neural networks based on pressure on the cylinder

(2018) Xiaowei Jin et al.   PHYSICS OF FLUIDS

A comprehensive review on single phase heat transfer enhancement techniques in heat exchanger applications

(2018) Tabish Alam et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Physics-informed machine learning approach for augmenting turbulence models: A comprehensive framework

(2018) Jin-Long Wu et al.   Physical Review Fluids

Turbulence Modeling in the Age of Data

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

Deep learning of vortex-induced vibrations

(2018) Maziar Raissi et al.   JOURNAL OF FLUID MECHANICS

Subgrid modelling for two-dimensional turbulence using neural networks

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

Data-driven deconvolution for large eddy simulations of Kraichnan turbulence

(2018) R. Maulik et al.   PHYSICS OF FLUIDS

Deep learning for universal linear embeddings of nonlinear dynamics

(2018) Bethany Lusch et al.   Nature Communications

Modification of turbulence and stratification of stably stratified turbulent channel flows by finite-size particles

(2018) Juwon Jang et al.   Physical Review Fluids

PIV-DCNN: cascaded deep convolutional neural networks for particle image velocimetry

(2017) Yong Lee et al.   EXPERIMENTS IN FLUIDS

Model identification of reduced order fluid dynamics systems using deep learning

(2017) Z. Wang et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS

A Machine Learning Approach for Determining the Turbulent Diffusivity in Film Cooling Flows

(2017) Pedro M. Milani et al.   JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME

Subgrid-scale scalar flux modelling based on optimal estimation theory and machine-learning procedures

(2017) A. Vollant et al.   JOURNAL OF TURBULENCE

Performing particle image velocimetry using artificial neural networks: a proof-of-concept

(2017) Jean Rabault et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

Flags as vortex generators for heat transfer enhancement: Gaps and challenges

(2017) Ralph Kristoffer B. Gallegos et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Searching for turbulence models by artificial neural network

(2017) Masataka Gamahara et al.   Physical Review Fluids

Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data

(2017) Jian-Xun Wang et al.   Physical Review Fluids

Machine learning strategies for systems with invariance properties

(2016) Julia Ling et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A paradigm for data-driven predictive modeling using field inversion and machine learning

(2016) Eric J. Parish et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

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

Uncertainty Analysis and Data-Driven Model Advances for a Jet-in-Crossflow

(2016) Julia Ling et al.   JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Closed-loop separation control using machine learning

(2015) N. Gautier et al.   JOURNAL OF FLUID MECHANICS

Analysis of coherent structures in Rayleigh–Bénard convection

(2015) Sangro Park et al.   JOURNAL OF TURBULENCE

Human-level control through deep reinforcement learning

(2015) Volodymyr Mnih et al.   NATURE

Deep learning

(2015) Yann LeCun et al.   NATURE

Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

(2015) J. Ling et al.   PHYSICS OF FLUIDS

Modification of particle-laden near-wall turbulence: Effect of Stokes number

(2015) Junghoon Lee et al.   PHYSICS OF FLUIDS

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

Compressive sensing based machine learning strategy for characterizing the flow around a cylinder with limited pressure measurements

(2013) Ido Bright et al.   PHYSICS OF FLUIDS

An overview on heat transfer augmentation using vortex generators and nanofluids: Approaches and applications

(2012) H.E. Ahmed et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A comprehensive review on passive heat transfer enhancements in pipe exchangers

(2012) S. Liu et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

On the near-wall characteristics of acceleration in turbulence

(2010) K. YEO et al.   JOURNAL OF FLUID MECHANICS

Eulerian and Lagrangian statistics in stably stratified turbulent channel flows

(2009) Kyongmin Yeo et al.   JOURNAL OF TURBULENCE

Near-wall similarity between velocity and scalar fluctuations in a turbulent channel flow

(2009) Hiroyuki Abe et al.   PHYSICS OF FLUIDS

Application of compact neural network for drag reduction in a turbulent channel flow at low Reynolds numbers

(2008) Li Vodinh Lorang et al.   PHYSICS OF FLUIDS