1 citations · 1 across the 4 of their papers we have counts for
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A neural network architecture and training algorithm to predict viscoelastic stresses from vortical data
Lu Zhu, Jacob Page
Numerical simulations of elastic turbulence in parallel shear flows of polymer solutions indicate that the phenomena is associated with the formation and instability of exact coher…
Learning dynamically consistent flow reconstructions from limited observations
Lu Zhu, Jacob Page
A core inverse problem in the experimental sciences is the inference of a hidden dynamical state from sparse or indirect measurements. There is a natural opportunity for deep learn…
Significant heat transfer enhancement via polymer additives in two-dimensional sheared convection
Guanhan Li, Lu Zhu, Rich. R. Kerswell
Heat dissipation is critical in modern engineering systems. Polymer additives offer a potential route to improve fluid-based cooling. Here, we study elasticity-enhanced heat transf…
Early turbulence in viscoelastic flow past a periodic cylinder array
Lu Zhu, Rich R. Kerswell
Early turbulence in periodic cylinder arrays is of particular interest in many practical applications to enhance mixing and material/heat exchange. In this study, we reveal a new e…
Physics-informed neural network to augment experimental data: an application to stratified flows
Lu Zhu, Xianyang Jiang, Adrien Lefauve +2
We develop a physics-informed neural network (PINN) to significantly augment state-of-the-art experimental data and apply it to stratified flows. The PINN is a fully-connected deep…
Geometry of stratified turbulent mixing: local alignment of the density gradient with rotation, shear and viscous dissipation
Xianyang Jiang, Amir Atoufi, Lu Zhu +4
We introduce a geometric analysis of turbulent mixing in density-stratified flows based on the alignment of the density gradient in two orthogonal bases that are locally constructe…