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An innovative \textit{deep learning} approach has been adopted to formulate the eddy-viscosity for large eddy simulation (LES) of wall-bounded turbulent flows. A deep neural network (DNN) is developed which learns to evaluate the…

Fluid Dynamics · Physics 2019-05-31 Anikesh Pal

A previously developed modeling procedure for large eddy simulations (LESs) is extended to allow physical space implementations for inhomogeneous flows. The method is inspired by the well-established theoretical analyses and numerical…

Fluid Dynamics · Physics 2022-10-28 Guangrui Sun , J. Andrzej Domaradzki

We propose a supervised-machine-learning-based wall model for coarse-grid wall-resolved large-eddy simulation (LES). Our consideration is made on LES of turbulent channel flows with a first grid point set relatively far from the wall…

Fluid Dynamics · Physics 2021-06-18 Naoki Moriya , Kai Fukami , Yusuke Nabae , Masaki Morimoto , Taichi Nakamura , Koji Fukagata

In the Large Eddy Simulation (LES) framework for modeling a turbulent flow, when the large scale velocity field is defined by low-pass filtering the full velocity field, a Taylor series expansion of the full velocity field in terms of the…

Fluid Dynamics · Physics 2012-10-09 Balasubramanya T. Nadiga , Freddy Bouchet

In this paper, the results of an international collaborative test case relative to the production of a Direct Numerical Simulation and Lagrangian Particle Tracking database for turbulent particle dispersion in channel flow at low Reynolds…

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

Fluid Dynamics · Physics 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

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

In this work, we will present a physically consistent theory to derive the governing equations of the Large Eddy Simulation (LES) framework based on first principles rather than the motivation to conduct computationally affordable…

Fluid Dynamics · Physics 2021-10-13 Max Okraschevski , Sven Hoffmann , Katharina Stichling , Rainer Koch , Hans-Joerg Bauer

High Reynolds Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of…

Large-eddy simulation developments and validations are presented for an improved simulation of turbulent internal flows. Numerical methods are proposed according to two competing criteria: numerical qualities (precision and spectral…

Fluid Dynamics · Physics 2008-01-15 Jérôme Boudet , Joëlle Caro , L. Shao , Emmanuel Lévêque

A large eddy simulation (LES) with an extended Smagorinsky model has been carried to investigate numerically the fully developed turbulent flow of a shear thinning fluid (n=0.75) in a stationary pipe at a simulation's Reynolds number equals…

Fluid Dynamics · Physics 2020-06-01 Mohamed Abdi , Meryem Ould-Rouiss , Abdelkader Noureddine

In dilute turbulent particle-laden flows, such as atmospheric dispersion of pollutants or virus particles, the dynamics of tracer-like to low inertial particles are significantly altered by the fluctuating motion of the carrier fluid phase.…

Fluid Dynamics · Physics 2024-06-19 Josh Williams , Uwe Wolfram , Ali Ozel

One of the greatest challenges to using large-eddy simulations (LES) in engineering applications is the large number of grid points required near walls. To mitigate this issue, researchers often couple LES with a simplified model of the…

Fluid Dynamics · Physics 2016-11-15 Alexandre Marques , Qiqi Wang , Johan Larsson , Gregory Laskowski , Sanjeeb Bose

Turbulent flow across an in-line array of tube-banks with transverse and longitudinal pitch PT /D = 2.67, and PL /D = 2.31, has been simulated successfully by Large Eddy Simulation (LES) based on the dynamic Smagorinsky subgrid scale model…

Fluid Dynamics · Physics 2016-05-30 C. Jin , I. Potts , D. C. Swailes , M. W. Reeks

In the present paper, we apply the framework of volume-filtering for particle-laden flows, to large eddy simulations (LES) of wall-bounded flows leading to a new perspective on wall-modeled LES (WMLES) that we refer to as volume-filtered…

Fluid Dynamics · Physics 2025-04-29 Max Hausmann , Berend van Wachem

A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence…

Fluid Dynamics · Physics 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

Recent developments in vortex particle methods for simulating three-dimensional incompressible flows are presented. A lightweight, dynamic Large-Eddy Simulation model is tested, featuring a dynamic procedure that relies solely on Lagrangian…

Fluid Dynamics · Physics 2026-01-13 Flavio A. C. Martins , Alexander van Zuijlen , Carlos J. Simao Ferreira

We investigate the ability of 4D Particle Tracking Velocimetry measurements at high particle density to explore intermittency and irreversibility in a turbulent swirling flow at various Reynolds numbers. For this, we devise suitable tools…

Lagrangian averaging plays an important role in the analysis of wave--mean-flow interactions and other multiscale fluid phenomena. The numerical computation of Lagrangian means, e.g. from simulation data, is however challenging. Typical…

Fluid Dynamics · Physics 2023-04-26 Hossein A. Kafiabad , Jacques Vanneste

Time-varying vector fields produced by computational fluid dynamics simulations are often prohibitively large and pose challenges for accurate interactive analysis and exploration. To address these challenges, reduced Lagrangian…

Machine Learning · Computer Science 2022-04-11 Mengjiao Han , Sudhanshu Sane , Chris R. Johnson