Search Results - "Cai, Shengze"

Physics-informed neural networks (PINNs) for fluid mechanics: a review by Cai, Shengze, Mao, Zhiping, Wang, Zhicheng, Yin, Minglang, Karniadakis, George Em

“…Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier–Stokes equations (NSE), we…”
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Dense motion estimation of particle images via a convolutional neural network by Cai, Shengze, Zhou, Shichao, Xu, Chao, Gao, Qi

“…In this paper, we propose a supervised learning strategy for the fluid motion estimation problem (i.e., extracting the velocity fields from particle images)…”
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Motion estimation under location uncertainty for turbulent fluid flows by Cai, Shengze, Mémin, Etienne, Dérian, Pierre, Xu, Chao

“…In this paper, we propose a novel optical flow formulation for estimating two-dimensional velocity fields from an image sequence depicting the evolution of a…”
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DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks by Liang, Jiaming, Cai, Shengze, Xu, Chao, Chen, Tehuan, Chu, Jian

“…Particle tracking velocimetry (PTV) is a powerful technique for global and nonintrusive flow field measurement, which shows a great potential to improve the…”
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A proposal on centralised and distributed optimisation via proportional–integral–derivative controllers (PID) control perspective by Liu, Jiaxu, Chen, Song, Cai, Shengze, Xu, Chao

“…Motivated by the excellent performance of proportional–integral–derivative controllers (PIDs) in the field of control, the authors injected the philosophy of…”
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Computational investigation of blood cell transport in retinal microaneurysms by Li, He, Deng, Yixiang, Sampani, Konstantina, Cai, Shengze, Li, Zhen, Sun, Jennifer K, Karniadakis, George E

“…Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in…”
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Filtering enhanced tomographic PIV reconstruction based on deep neural networks by Liang, Jiaming, Cai, Shengze, Xu, Chao, Chu, Jian

“…Tomographic particle image velocimetry (Tomo‐PIV) has been successfully applied in measuring three‐dimensional (3D) flow field in recent years. Such technology…”
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Segmentation of cardiac tissues and organs for CCTA images based on a deep learning model by Cai, Shengze, Lu, Yunxia, Li, Bowen, Gao, Qi, Xu, Lei, Hu, Xiuhua, Zhang, Longjiang

“…Accurate segmentation of cardiac tissues and organs based on cardiac computerized tomography angiography (CCTA) images has played an important role in…”
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AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images by Zhang, Qian, Sampani, Konstantina, Xu, Mengjia, Cai, Shengze, Deng, Yixiang, Li, He, Sun, Jennifer K, Karniadakis, George Em

“…Accurate segmentation of microaneurysms (MAs) from adaptive optics scanning laser ophthalmoscopy (AOSLO) images is crucial for identifying MA morphologies and…”
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System identification and model predictive control of vortex shedding behind a rotating cylinder by Cai, Shengze, Xu, Chao

“…In this paper we present an approach for modeling and control of the unsteady flow over a circular cylinder at a low Reynolds number (Re = 60). Actuation is…”
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NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations by Jin, Xiaowei, Cai, Shengze, Li, Hui, Karniadakis, George Em

“…•NSFnets involve the VP and VV formulations of the Navier-Stokes equations.•NSFnets can directly simulate and sustain turbulence at Reτ∼1,000.•A study on the…”
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DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks by Cai, Shengze, Wang, Zhicheng, Lu, Lu, Zaki, Tamer A., Karniadakis, George Em

“…•DeepONets can learn the electroconvection operator using a small number of data.•DeepONets achieve high accuracy at 1000X speed for the unseen testing…”
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A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data by Lu, Lu, Meng, Xuhui, Cai, Shengze, Mao, Zhiping, Goswami, Somdatta, Zhang, Zhongqiang, Karniadakis, George Em

“…Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for…”
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Physics-Informed Neural Networks Enhanced Particle Tracking Velocimetry: An Example for Turbulent Jet Flow by Cai, Shengze, Gray, Callum, Karniadakis, George Em

“…Particle image velocimetry (PIV) and particle tracking velocimetry (PTV) are important flow visualization technologies for measuring global velocity fields in…”
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Neural Observer With Lyapunov Stability Guarantee for Uncertain Nonlinear Systems by Chen, Song, Cai, Shengze, Chen, Tehuan, Xu, Chao, Chu, Jian

“…In this article, we propose a novel nonlinear observer based on neural networks (NNs), called neural observers, for observation tasks of linear time-invariant…”
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Particle Image Velocimetry Based on a Deep Learning Motion Estimator by Cai, Shengze, Liang, Jiaming, Gao, Qi, Xu, Chao, Wei, Runjie

“…Particle image velocimetry (PIV), as a common technology for analyzing the global flow motion from images, plays a significant role in experimental fluid…”
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Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease by Cai, Shengze, Li, He, Zheng, Fuyin, Kong, Fang, Dao, Ming, Karniadakis, George Em, Suresh, Subra

“…Understanding the mechanics of blood flow is necessary for developing insights into mechanisms of physiology and vascular diseases in microcirculation. Given…”
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PIDNODEs: Neural ordinary differential equations inspired by a proportional–integral–derivative controller by Wang, Pengkai, Chen, Song, Liu, Jiaxu, Cai, Shengze, Xu, Chao

“…Neural Ordinary Differential Equations (NODEs) are a novel family of infinite-depth neural-net models through solving ODEs and their adjoint equations. In this…”
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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 by Osorio, Julian D., Wang, Zhicheng, Karniadakis, George, Cai, Shengze, Chryssostomidis, Chrys, Panwar, Mayank, Hovsapian, Rob

“…•A modified version of the Deep Operator Network was proposed.•Deep Operator Network accurately predicts state-of-charge and efficiency of the…”
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Recurrent graph optimal transport for learning 3D flow motion in particle tracking by Liang, Jiaming, Xu, Chao, Cai, Shengze

“…Flow visualization technologies such as particle tracking velocimetry are broadly used for studying three-dimensional turbulent flow in natural and industrial…”
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