activity
20202022
most citedFlow over an espresso cup: Inferring 3D velocity and pressure fields from tomographic background oriented schlieren videos via physics-informed neural networks

349 citations · 562 across the 5 of their papers we have counts for

collaborators

7 papers

physics.flu-dyn20221 cited

GotFlow3D: Recurrent Graph Optimal Transport for Learning 3D Flow Motion in Particle Tracking

Jiaming Liang, Chao Xu, Shengze Cai

Flow visualization technologies such as particle tracking velocimetry (PTV) are broadly used in understanding the all-pervasiveness three-dimensional (3D) turbulent flow from natur…

eess.IV2021

AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images

Qian Zhang, Konstantina Sampani, Mengjia Xu +5

Microaneurysms (MAs) are one of the earliest signs of diabetic retinopathy (DR), a frequent complication of diabetes that can lead to visual impairment and blindness. Adaptive opti…

physics.flu-dyn202172 cited

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

Shengze Cai, Zhiping Mao, Zhicheng Wang +2

Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier-Stokes equations (NSE), we still cannot incorporate…

physics.flu-dyn2021349 cited

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

Shengze Cai, Zhicheng Wang, Frederik Fuest +3

Tomographic background oriented schlieren (Tomo-BOS) imaging measures density or temperature fields in 3D using multiple camera BOS projections, and is particularly useful for inst…

physics.comp-ph2020140 cited

Operator learning for predicting multiscale bubble growth dynamics

Chensen Lin, Zhen Li, Lu Lu +3

Simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investiga…

physics.comp-ph2020

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

Shengze Cai, Zhicheng Wang, Lu Lu +2

Electroconvection is a multiphysics problem involving coupling of the flow field with the electric field as well as the cation and anion concentration fields. For small Debye lengt…