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We focus in this paper on the effect of the resolution of Direct Numerical Simulations (DNS) on the spatio-temporal development of the turbulence downstream of a single square grid. The aims of this study are to validate our numerical…

Fluid Dynamics · Physics 2015-10-28 S. Laizet , J. Nedić , J. C. Vassilicos

A fully-resolved direct-numerical-simulation (DNS) approach for investigating flexible bodies forced by a turbulent incoming flow is designed to study the flapping motion of a flexible flag at moderate Reynolds number. The incoming…

Fluid Dynamics · Physics 2021-08-25 Stefano Olivieri , Francesco Viola , Andrea Mazzino , Marco E. Rosti

Neural networks of simple structures are used to construct a turbulence model for large-eddy simulation (LES). Data obtained by direct numerical simulation (DNS) of homogeneous isotropic turbulence are used to train neural networks. It is…

Fluid Dynamics · Physics 2020-12-04 Satoshi Miyazaki , Yuji Hattori

Turbulent flow has been extensively studied using computational fluid dynamics (CFD) simulations since turbulent flow regime is so frequently encountered in both academic and engineering applications. The high-fidelity simulation of the…

Fluid Dynamics · Physics 2024-05-21 Minghan Chu

Accurate subgrid-scale (SGS) modeling remains a major challenge in large eddy simulation (LES), particularly for wall-bounded turbulent flows with strong near-wall anisotropy. This study proposes a novel SGS model based on Liutex theory,…

Fluid Dynamics · Physics 2025-12-18 Jiawei Chen , Yifei Yu , Chaoqun Liu

The turbulent boundary layer over a Gaussian shaped bump is computed by direct numerical simulation (DNS) of the incompressible Navier-Stokes equations. The two-dimensional bump causes a series of strong pressure gradients alternating in…

Fluid Dynamics · Physics 2021-05-19 Riccardo Balin , Kenneth E. Jansen

Direct numerical simulation (DNS) of flow in a turbulent channel with a random rough wall is performed at $Re_{\tau}=400$ and $600$. The roughness geometry corresponds to the experiments of Flack and Schultz (personal communication). The…

Fluid Dynamics · Physics 2020-10-13 R. Ma , K. Alamé , K. Mahesh

The number of steps required to exhaust a point set by iteratively removing the vertices of its convex hull is called the layer number of the point set. This article presents a short proof that the layer number of the grid…

Metric Geometry · Mathematics 2023-02-16 Travis Dillon , Narmada Varadarajan

In many engineering and industrial applications, the investigation of rotating turbulent flow is of great interest. In rotor-stator cavities, the centrifugal and Coriolis forces have a strong influence on the turbulence by producing a…

In large-eddy simulations, subgrid-scale (SGS) processes are parameterized as a function of filtered grid-scale variables. First-order, algebraic SGS models are based on the eddy-viscosity assumption, which does not always hold for…

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

Computational Physics · Physics 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw

The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant times and length scales. However, due to the dissipative nature of the Navier-Stokes equations, the long-term dynamics are expected to lie on a…

Fluid Dynamics · Physics 2025-10-15 C. Ricardo Constante-Amores , Alec J. Linot , Michael D. Graham

This article describes some common issues encountered in the use of Direct Numerical Simulation (DNS) turbulent flow data for machine learning. We focus on two specific issues; 1) the requirements for a fair validation set, and 2) the…

Direct numerical simulations (DNS) are performed to study the turbulent shear flow of an electrically conducting fluid in a cylindrical container. The flow is driven by the interaction between the radial electric currents ($I$) injected…

Fluid Dynamics · Physics 2021-04-21 Long Chen , Alban Pothérat , Ming-Jiu Ni , René Moreau

The weights of a deep neural network model are optimized in conjunction with the governing flow equations to provide a model for sub-grid-scale stresses in a temporally developing plane turbulent jet at Reynolds number $Re_0=6\,000$. The…

Fluid Dynamics · Physics 2023-03-23 Jonathan F. MacArt , Justin Sirignano , Jonathan B. Freund

Large-Eddy Simulations (LES) of two-phase turbulent flows exhibit quantitative differences in particle statistics if compared to Direct Numerical Simulations (DNS) which, in the context of the present study, is considered the exact…

Fluid Dynamics · Physics 2012-05-04 F. Bianco , S. Chibbaro , C. Marchioli , M. V. Salvetti , A. Soldati

We report on recent progress in the physical and numerical modeling of compressible two-phase flows that involve phase transition between the liquid and gaseous state of the fluid. The high-speed dynamics of cavitation bubbles is studied in…

Fluid Dynamics · Physics 2014-02-14 Stefan Hickel

We provide a rigorous analysis of the self-similar solution of the temporal turbulent boundary layer, recently proposed in [2], in which a body force is used to maintain a statistically steady turbulent boundary layer with periodic boundary…

Fluid Dynamics · Physics 2024-06-17 Andrew Wynn , Saeed Parvar , Joseph O Connor , Sylvain Laizet

In this paper we overcome a key problem in an otherwise highly potential approach to study turbulent flows, ODTLES (One-Dimensional Turbulence Large Eddy Simulation). From a methodological point of view, ODTLES is an approach in between…

Fluid Dynamics · Physics 2018-06-06 Christoph Glawe , Juan A. Medina M. , Heiko Schmidt

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

Fluid Dynamics · Physics 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem
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