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A fully-convolutional neural-network model is used to predict the streamwise velocity fields at several wall-normal locations by taking as input the streamwise and spanwise wall-shear-stress planes in a turbulent open channel flow. The…

Fluid Dynamics · Physics 2020-08-26 L. Guastoni , M. P. Encinar , P. Schlatter , H. Azizpour , R. Vinuesa

The objective of this study is to assess the capability of convolution-based neural networks to predict wall quantities in a turbulent open channel flow. The first tests are performed by training a fully-convolutional network (FCN) to…

Two models based on convolutional neural networks are trained to predict the two-dimensional velocity-fluctuation fields at different wall-normal locations in a turbulent open channel flow, using the wall-shear-stress components and the…

Fluid Dynamics · Physics 2020-06-23 L. Guastoni , A. Güemes , A. Ianiro , S. Discetti , P. Schlatter , H. Azizpour , R. Vinuesa

Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. As a first step towards a data-driven wall-model, a…

This paper is focused on the fundamental mechanism(s) of viscoelastic turbulence that lead to polymer induced turbulent drag reduction phenomenon. A great challenge in this problem is the computation of viscoelastic turbulent flows, since…

Fluid Dynamics · Physics 2011-11-18 Vassilios Dallas , J. Christos Vassilicos , Geoffrey F. Hewitt

Friction drag from a turbulent fluid moving past or inside an object plays a crucial role in domains as diverse as transportation, public utility infrastructure, energy technology, and human health. As a direct measure of the shear-induced…

Fluid Dynamics · Physics 2023-10-19 Esther Lagemann , Steven L. Brunton , Christian Lagemann

Estimation of near-wall turbulence in channel flow from outer observations is investigated using adjoint-variational data assimilation. We first consider fully resolved velocity data, starting at a distance from the wall. By enforcing the…

Fluid Dynamics · Physics 2025-04-09 Mengze Wang , Tamer A. Zaki

Fully-convolutional neural networks (FCN) were proven to be effective for predicting the instantaneous state of a fully-developed turbulent flow at different wall-normal locations using quantities measured at the wall. In Guastoni et al.…

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 to identify the fluid-compliant material interface. Focus is…

Fluid Dynamics · Physics 2021-11-03 Amir Esteghamatian , Joseph Katz , Tamer A. Zaki

We experimentally investigate the flow of a viscoelastic fluid in a parallel shear geometry at low Reynolds number. As the flow becomes unstable via a nonlinear subcritical instability, velocimetry measurements show non-periodic…

Fluid Dynamics · Physics 2017-07-26 Boyang Qin , Paulo E. Arratia

I shortly describe the main results on elastically driven instabilities and elastic turbulence in viscoelastic inertia-less flows with curved streamlines. Then I describe a theory of elastic turbulence and prediction of elastic waves at…

Fluid Dynamics · Physics 2022-06-08 V. Steinberg

Mathematical models and numerical simulations offer a non-invasive way to explore cardiovascular phenomena, providing access to quantities that cannot be measured directly. In this study, we start with a one-dimensional multiscale blood…

Machine Learning · Computer Science 2026-04-09 Giulia Bertaglia , Raffaella Fiamma Cabini

In this paper, the prediction capabilities of recurrent neural networks are assessed in the low-order model of near-wall turbulence by Moehlis {\it et al.} (New J. Phys. {\bf 6}, 56, 2004). Our results show that it is possible to obtain…

The pressure strain correlation plays a critical role in the Reynolds stress transport modelling. Accurate modelling of the pressure strain correlation leads to proper prediction of turbulence stresses and subsequently the other terms of…

Fluid Dynamics · Physics 2021-03-02 J P Panda , H V Warrior

The majority of practical flows, particularly those flows in applications of importance to transport, distribution and climate, are turbulent and as a result experience complex three-dimensional motion with increased drag compared with the…

Fluid Dynamics · Physics 2015-03-17 B. J. McKeon , A. S. Sharma , I. Jacobi

As an experimental model to mimic the flow of bio-fluids in the cell and the flow in tiny blood capillaries, we study the co-moving shear flow of dilute polymeric solutions. An inflection point shear flow profile is created by parallel…

Fluid Dynamics · Physics 2025-10-09 Jimreeves David M

The transition to turbulence in a plane Poiseuille flow of dilute polymer solutions is studied by direct numerical simulations of a FENE-P fluid. A range of Reynolds number ($Re$) in $2000 \le Re \le 5000$ is studied but with the same level…

Fluid Dynamics · Physics 2023-11-07 Alexia Martinez Ibarra , Jae Sung Park

We report detailed quantitative studies of elastic turbulence in a curvilinear channel flow in a dilute polymer solution of high molecular weight polyacrylamide in a high viscosity water-sugar solvent. Detailed studies of the average and…

Chaotic Dynamics · Physics 2015-05-30 Yonggun Jun , Victor Steinberg

Direct numerical simulations (DNS) of turbulent channel flows up to $Re_{\tau} \approx 1000$ are conducted to investigate the three-dimensional (consisting of streamwise wavenumber, spanwise wavenumber and frequency) spectrum of wall…

Fluid Dynamics · Physics 2022-03-14 Bowen Yang , Zixuan Yang

This paper employs an input-output based approach to analyze convective velocities and the transport of fluctuations in turbulent channel flows. The convective velocity for a fluctuating quantity associated with streamwise-spanwise…

Fluid Dynamics · Physics 2021-11-16 Chang Liu , Dennice F. Gayme
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