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Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning
Qi Gao, Shaowu Pan, Hongping Wang +2
Three-dimensional particle reconstruction with limited two-dimensional projections is an under-determined inverse problem that the exact solution is often difficult to be obtained.…
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Deep Learning Without Simulation Data
Luning Sun, Han Gao, Shaowu Pan +1
Numerical simulations on fluid dynamics problems primarily rely on spatially or/and temporally discretization of the governing equation into the finite-dimensional algebraic system…
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability
Shaowu Pan, Karthik Duraisamy
The Koopman operator has emerged as a powerful tool for the analysis of nonlinear dynamical systems as it provides coordinate transformations to globally linearize the dynamics. Wh…
Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks
Yaser Afshar, Saakaar Bhatnagar, Shaowu Pan +2
An approximation model based on convolutional neural networks (CNNs) is proposed for flow field predictions. The CNN is used to predict the velocity and pressure field in unseen fl…
On the Structure of Time-delay Embedding in Linear Models of Non-linear Dynamical Systems
Shaowu Pan, Karthik Duraisamy
This work addresses fundamental issues related to the structure and conditioning of linear time-delayed models of non-linear dynamics on an attractor. While this approach has been…