activity
20092026
most citedDeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks

217 citations · 868 across the 46 of their papers we have counts for

collaborators
Showing 2021Show all

11 papers · 1 filter

physics.flu-dyn2021★ 34 cited

Synchronization of turbulence in channel flow

Mengze Wang, Tamer A. Zaki

Synchronization of turbulence in channel flow is investigated using continuous data assimilation. The flow is unknown within a region of the channel. Beyond this region the velocit…

physics.flu-dyn2021

Simulations of turbulence over compliant walls

Amir Esteghamatian, Joseph Katz, Tamer A. Zaki

Direct numerical simulations of turbulent flow in a channel with one rigid and one viscoelastic wall are performed. An Eulerian-Eulerian model is adopted with a level-set approach…

physics.flu-dyn2021

Vorticity amplification in viscoelastic channel flows with long-wave surface distortions

Jacob Page, Tamer A. Zaki

Surface distortions to an otherwise planar channel flow introduce vorticity perturbations. We examine this scenario in viscoelastic fluids, and identify new mechanisms by which sig…

physics.flu-dyn2021

Ensemble-variational assimilation of statistical data in large eddy simulation

Vincent Mons, Yifan Du, Tamer A. Zaki

A non-intrusive data assimilation methodology is developed to improve the statistical predictions of large-eddy simulations (LES). The ensemble-variational (EnVar) approach aims to…

physics.flu-dyn2021

From limited observations to the state of turbulence: Fundamental difficulties of flow reconstruction

Tamer A. Zaki, Mengze Wang

Numerical simulations of turbulence provide non-intrusive access to all the resolved scales, although they often invoke idealizations that can compromise realism. In contrast, expe…

physics.flu-dyn2021★ 26 cited

A Lagrangian relaxation towards equilibrium wall model for large eddy simulation

Mitchell Fowler, Tamer A. Zaki, Charles Meneveau

A large eddy simulation wall model is developed based on a formal interpretation of quasi-equilibrium that governs the momentum balance integrated in the wall-normal direction. The…

physics.flu-dyn2021★ 34 cited

From wall observations to turbulence: The difficulty of flow reconstruction

Qi Wang, Mengze Wang, Tamer A. Zaki

Estimation of the initial state of turbulent channel flow from spatially and temporally resolved wall data is performed using adjoint-variational data assimilation. The accuracy of…

cs.CE2021

Optimization of a Moving Sensor Trajectory for Observing a Point Scalar Source in Turbulent Flow

Constantinos F. Panagiotou, Davide Cerizza, Tamer A. Zaki +1

We propose a strategy for optimizing a sensor trajectory in order to estimate the time dependence of a localized scalar source in turbulent channel flow. The approach leverages the…

physics.flu-dyn2021★ 29 cited

DeepONet prediction of linear instability waves in high-speed boundary layers

P. Clark Di Leoni, L. Lu, C. Meneveau +2

Deep operator networks (DeepONets) are trained to predict the linear amplification of instability waves in high-speed boundary layers and to perform data assimilation. In contrast…

physics.comp-ph2021★ 69 cited

Evolutional Deep Neural Network

Yifan Du, Tamer A. Zaki

The notion of an Evolutional Deep Neural Network (EDNN) is introduced for the solution of partial differential equations (PDE). The parameters of the network are trained to represe…

physics.flu-dyn2021★ 9 cited

Concave-wall turbulent boundary layers without and with free-stream turbulence

Jiho You, David A. Buchta, Tamer A. Zaki

Direct numerical simulations are performed to contrast turbulent boundary layers over a concave wall without and with free-stream turbulence. Adverse pressure gradient near the ons…