4.7 Article

Prediction of turbulent heat transfer using convolutional neural networks

Related references

Note: Only part of the references are listed.
Review Mechanics

Turbulence Modeling in the Age of Data

Karthik Duraisamy et al.

ANNUAL REVIEW OF FLUID MECHANICS, VOL 51 (2019)

Article Engineering, Mechanical

Dense motion estimation of particle images via a convolutional neural network

Shengze Cai et al.

EXPERIMENTS IN FLUIDS (2019)

Article Mechanics

Super-resolution reconstruction of turbulent flows with machine learning

Kai Fukami et al.

JOURNAL OF FLUID MECHANICS (2019)

Article Mechanics

Deep learning of vortex-induced vibrations

Maziar Raissi et al.

JOURNAL OF FLUID MECHANICS (2019)

Article Mechanics

Subgrid modelling for two-dimensional turbulence using neural networks

R. Maulik et al.

JOURNAL OF FLUID MECHANICS (2019)

Article Computer Science, Interdisciplinary Applications

Model identification of reduced order fluid dynamics systems using deep learning

Z. Wang et al.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS (2018)

Article Engineering, Mechanical

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

Pedro M. Milani et al.

JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME (2018)

Article Thermodynamics

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

C. Sotgiu et al.

INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER (2018)

Review Green & Sustainable Science & Technology

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

Tabish Alam et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)

Article Physics, Fluids & Plasmas

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

Jin-Long Wu et al.

PHYSICAL REVIEW FLUIDS (2018)

Article Multidisciplinary Sciences

Deep learning for universal linear embeddings of nonlinear dynamics

Bethany Lusch et al.

NATURE COMMUNICATIONS (2018)

Article Engineering, Mechanical

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

Julia Ling et al.

JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME (2017)

Article Engineering, Mechanical

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

Yong Lee et al.

EXPERIMENTS IN FLUIDS (2017)

Article Engineering, Multidisciplinary

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

Jean Rabault et al.

MEASUREMENT SCIENCE AND TECHNOLOGY (2017)

Article Multidisciplinary Sciences

Mastering the game of Go without human knowledge

David Silver et al.

NATURE (2017)

Review Green & Sustainable Science & Technology

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

Ralph Kristoffer B. Gallegos et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)

Article Physics, Fluids & Plasmas

Searching for turbulence models by artificial neural network

Masataka Gamahara et al.

PHYSICAL REVIEW FLUIDS (2017)

Article Mechanics

A neural network approach for the blind deconvolution of turbulent flows

R. Maulik et al.

JOURNAL OF FLUID MECHANICS (2017)

Article Engineering, Aerospace

Machine-Learning-Augmented Predictive Modeling of Turbulent Separated Flows over Airfoils

Anand Pratap Singh et al.

AIAA JOURNAL (2017)

Article Mechanics

Deep earning in fluid dynamics

J. Nathan Kutz

JOURNAL OF FLUID MECHANICS (2017)

Article Computer Science, Interdisciplinary Applications

Machine learning strategies for systems with invariance properties

Julia Ling et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2016)

Article Computer Science, Interdisciplinary Applications

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

Eric J. Parish et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2016)

Article Multidisciplinary Sciences

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

David Silver et al.

NATURE (2016)

Article Mechanics

Closed-loop separation control using machine learning

N. Gautier et al.

JOURNAL OF FLUID MECHANICS (2015)

Article Mechanics

Analysis of coherent structures in Rayleigh-Benard convection

Sangro Park et al.

JOURNAL OF TURBULENCE (2015)

Article Multidisciplinary Sciences

Human-level control through deep reinforcement learning

Volodymyr Mnih et al.

NATURE (2015)

Review Multidisciplinary Sciences

Deep learning

Yann LeCun et al.

NATURE (2015)

Article Mechanics

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

Junghoon Lee et al.

PHYSICS OF FLUIDS (2015)

Review Green & Sustainable Science & Technology

A comprehensive review on passive heat transfer enhancements in pipe exchangers

S. Liu et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2013)

Review Green & Sustainable Science & Technology

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

H. E. Ahmed et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2012)

Article Mechanics

On the near-wall characteristics of acceleration in turbulence

K. Yeo et al.

JOURNAL OF FLUID MECHANICS (2010)

Article Mechanics

Eulerian and Lagrangian statistics in stably stratified turbulent channel flows

Kyongmin Yeo et al.

JOURNAL OF TURBULENCE (2009)

Article Thermodynamics

A turbulent-wake estimation using radial basis function neural networks

M Hocevar et al.

FLOW TURBULENCE AND COMBUSTION (2005)

Article Thermodynamics

Surface heat-flux fluctuations in a turbulent channel flow up to Reτ=1020 with Pr=0.025 and 0.71

H Abe et al.

INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW (2004)

Article Mechanics

Integral space-time scales in turbulent wall flows

M Quadrio et al.

PHYSICS OF FLUIDS (2003)

Article Computer Science, Interdisciplinary Applications

Neural networks based subgrid scale modeling in large eddy simulations

F Sarghini et al.

COMPUTERS & FLUIDS (2003)

Article Computer Science, Interdisciplinary Applications

Neural network modeling for near wall turbulent flow

M Milano et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2002)

Article Engineering, Mechanical

Three-dimensional swirl flow velocity-field reconstruction using a neural network with radial basis functions

J Pruvost et al.

JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME (2001)