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Related papers: State estimation in turbulent channel flow from li…

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The success of recurrent neural networks (RNNs) has been demonstrated in many applications related to turbulence, including flow control, optimization, turbulent features reproduction as well as turbulence prediction and modeling. With this…

We combine resolvent-mode decomposition with techniques from convex optimization to optimally approximate velocity spectra in a turbulent channel. The velocity is expressed as a weighted sum of resolvent modes that are dynamically…

Fluid Dynamics · Physics 2014-05-22 R. Moarref , M. R. Jovanovic , J. A. Tropp , A. S. Sharma , B. J. McKeon

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

Fluid Dynamics · Physics 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia

We perform direct numerical simulations (DNS) of a turbulent channel flow over porous walls. In the fluid region the flow is governed by the incompressible Navier--Stokes (NS) equations, while in the porous layers the Volume-Averaged…

Fluid Dynamics · Physics 2023-07-19 Marco E. Rosti , Luca Cortelezzi , Maurizio Quadrio

This paper reviews results from the study of wall-bounded turbulent flows using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD…

Fluid Dynamics · Physics 2017-02-10 Brian F. Farrell , Dennice F. Gayme , Petros J. Ioannou

We present a direct comparison between interface-resolved and one-way-coupled point-particle direct numerical simulations (DNS) of gravity-free turbulent channel flow laden with small inertial particles, with high particle-to-fluid density…

Fluid Dynamics · Physics 2024-07-26 Pedro Costa , Luca Brandt , Francesco Picano

Supersonic turbulent channels subjected to sudden spanwise acceleration at initial friction Reynolds numbers of approximately 500 and different Mach numbers are studied through direct numerical simulations. The response to the spanwise…

Fluid Dynamics · Physics 2026-01-14 Salvador Rey Gomez

In this article we examine channel flow subject to spatially varying viscosity in the streamwise direction. The Reynolds number is imposed locally with three different ramps. The setup is reminiscent of transient channel flow, but with a…

Fluid Dynamics · Physics 2020-06-11 Victor Coppo Leite , Elia Merzari

For low enough flow rates, turbulent channel flow displays spatial modulations of large wavelengths. This phenomenon has recently been interpreted as a linear instability of the turbulent flow. We question here the ability of linear…

Fluid Dynamics · Physics 2024-06-21 P. V. Kashyap , Y. Duguet , O. Dauchot

Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct…

Fluid Dynamics · Physics 2023-12-13 Shengyu Chen , Tianshu Bao , Peyman Givi , Can Zheng , Xiaowei Jia

The ability of linear stochastic response analysis to estimate coherent motions is investigated in turbulent channel flow at friction Reynolds number Re$_\tau$ = 1007. The analysis is performed for spatial scales characteristic of…

Fluid Dynamics · Physics 2021-02-02 Pierluigi Morra , Onofrio Semeraro , Dan S. Henningson , Carlo Cossu

The effect of streamwise-traveling waves of spanwise wall velocity (StTW) on the quasi-streamwise vortices (QSV) populating the near-wall region of turbulent channels is studied via a conditional averaging technique applied to flow…

Fluid Dynamics · Physics 2022-08-23 Emanuele Gallorini , Maurizio Quadrio , Davide Gatti

The spatiotemporal dynamics of turbulent flows is chaotic and difficult to predict. This makes the design of accurate and stable reduced-order models challenging. The overarching objective of this paper is to propose a nonlinear…

Fluid Dynamics · Physics 2022-11-23 Alberto Racca , Nguyen Anh Khoa Doan , Luca Magri

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…

The large structures in the outer layer of turbulent wall flows are of great physical importance, because they contain a substantial fraction of the streamwise kinetic energy and of the Reynolds stresses. Nevertheless, the organization of…

Fluid Dynamics · Physics 2013-09-12 Juan C. del Alamo , Javier Jimenez

The characteristics of the wavenumber-frequency spectra of the rapid, slow and total wall pressure fluctuations are investigated using direct numerical simulation (DNS) of turbulent channel flow up to $\Rey_\tau\approx 1000$. For the…

Fluid Dynamics · Physics 2021-01-15 Bowen Yang , Guowei He , Zixuan Yang

A data-driven implementation of a quasi-linear approximation is presented, extending a minimal quasi-linear approximation (MQLA) (Hwang & Ekchardt, J. Fluid Mech., 2020, 894:A23) to incorporate non-zero streamwise Fourier modes. A…

Fluid Dynamics · Physics 2023-05-25 Jacob Holford , Myoungkyu Lee , Yongyun Hwang

Using high-resolution direct numerical simulations, the height and Reynolds number dependence of higher-order statistics of the energy dissipation rate and local enstrophy are examined in incompressible, fully-developed turbulent channel…

Fluid Dynamics · Physics 2011-06-28 Peter E. Hamlington , Dmitry Krasnov , Thomas Boeck , Jörg Schumacher

The study of turbulent flows calls for measurements with high resolution both in space and in time. We propose a new approach to reconstruct High-Temporal-High-Spatial resolution velocity fields by combining two sources of information that…

Fluid Dynamics · Physics 2017-07-10 Linh Van Nguyen , Jean-Philippe Laval , Pierre Chainais

State estimation is necessary in diagnosing anomalies in Water Demand Systems (WDS). In this paper we present a neural network performing such a task. State estimation is performed by using optimization, which tries to reconcile all the…

Neural and Evolutionary Computing · Computer Science 2007-11-20 J. Izquierdo , M. M. Tung , R. Perez , F. J. Martinez