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Physics-informed neural networks (PINNs) for fluid mechanics: a review

Acta mechanica Sinica, 2021-12, Vol.37 (12), p.1727-1738

English ed., 2021

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Operator learning for predicting multiscale bubble growth dynamics

The Journal of chemical physics, 2021-03, Vol.154 (10), p.104118-104118

2021

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Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks

Journal of fluid mechanics, 2021-03, Vol.915, Article A102

2021

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Dense motion estimation of particle images via a convolutional neural network

Experiments in fluids, 2019-04, Vol.60 (4), p.1-16, Article 73

2019

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Motion estimation under location uncertainty for turbulent fluid flows

Experiments in fluids, 2018-01, Vol.59 (1), p.1-17, Article 8

2018

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A proposal on centralised and distributed optimisation via proportional–integral–derivative controllers (PID) control perspective

IET cyber-systems and robotics, 2023-12, Vol.5 (4), p.n/a

2023

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Computational investigation of blood cell transport in retinal microaneurysms

PLoS computational biology, 2022-01, Vol.18 (1), p.e1009728-e1009728

2022

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Filtering enhanced tomographic PIV reconstruction based on deep neural networks

IET cyber-systems and robotics, 2020-03, Vol.2 (1), p.43-52

2020

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NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

Journal of computational physics, 2021-02, Vol.426 (C), p.109951, Article 109951

2021

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Segmentation of cardiac tissues and organs for CCTA images based on a deep learning model

Frontiers in physics, 2023-08, Vol.11

2023

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AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images

Translational vision science & technology, 2022-08, Vol.11 (8), p.7-7

2022

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Physics-Informed Neural Networks for Heat Transfer Problems

Journal of heat transfer, 2021-06, Vol.143 (6)

2021

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DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks

Journal of computational physics, 2021-07, Vol.436 (C), p.110296, Article 110296

2021

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A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data

Computer methods in applied mechanics and engineering, 2022-04, Vol.393, p.114778, Article 114778

2022

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System identification and model predictive control of vortex shedding behind a rotating cylinder

2016 35th Chinese Control Conference (CCC), 2016, p.5099-5105

2016

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Physics-Informed Neural Networks Enhanced Particle Tracking Velocimetry: An Example for Turbulent Jet Flow

IEEE transactions on instrumentation and measurement, 2024, Vol.73, p.1-9

2024

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Particle Image Velocimetry Based on a Deep Learning Motion Estimator

IEEE transactions on instrumentation and measurement, 2020-06, Vol.69 (6), p.3538-3554

2020

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Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

Proceedings of the National Academy of Sciences - PNAS, 2021-03, Vol.118 (13)

2021

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Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network architecture

Energy conversion and management, 2022-01, Vol.252, p.115063, Article 115063

2022

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DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks

IEEE transactions on instrumentation and measurement, 2022, Vol.71, p.1-16

2022

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Recurrent graph optimal transport for learning 3D flow motion in particle tracking

Nature machine intelligence, 2023-05, Vol.5 (5), p.505-517

2023

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NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

Journal of computational physics, 2020-11, Vol.426

2020

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LAFlowNet: A dynamic graph method for the prediction of velocity and pressure fields in left atrium and left atrial appendage

Engineering applications of artificial intelligence, 2024-10, Vol.136, p.108896, Article 108896

2024

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A deep learning model for efficient end-to-end stratification of thrombotic risk in left atrial appendage

Engineering applications of artificial intelligence, 2023-11, Vol.126, p.107187, Article 107187

2023

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Flow reconstruction over a SUBOFF model based on LBM-generated data and physics-informed neural networks

Ocean engineering, 2024-09, Vol.308, p.118250, Article 118250

2024

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Physics-informed neural networks (PINNs) for fluid mechanics: a review

Operator learning for predicting multiscale bubble growth dynamics

Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks

Dense motion estimation of particle images via a convolutional neural network

Motion estimation under location uncertainty for turbulent fluid flows

A proposal on centralised and distributed optimisation via proportional–integral–derivative controllers (PID) control perspective

Computational investigation of blood cell transport in retinal microaneurysms

Filtering enhanced tomographic PIV reconstruction based on deep neural networks

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

Segmentation of cardiac tissues and organs for CCTA images based on a deep learning model

AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images

Physics-Informed Neural Networks for Heat Transfer Problems

DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks

A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data

System identification and model predictive control of vortex shedding behind a rotating cylinder

Physics-Informed Neural Networks Enhanced Particle Tracking Velocimetry: An Example for Turbulent Jet Flow

Particle Image Velocimetry Based on a Deep Learning Motion Estimator

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network architecture

DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks

Recurrent graph optimal transport for learning 3D flow motion in particle tracking

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

LAFlowNet: A dynamic graph method for the prediction of velocity and pressure fields in left atrium and left atrial appendage

A deep learning model for efficient end-to-end stratification of thrombotic risk in left atrial appendage

Flow reconstruction over a SUBOFF model based on LBM-generated data and physics-informed neural networks

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