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We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS)…

Fluid Dynamics · Physics 2026-04-13 Ben-Rui Xu , Ao Xu

To fully evaluate a turbulent flow, Direct Numerical Simulation (DNS) is the most accurate method by far and requires considerable computational power and time; not optimum for industry standards. Developing an alternative model, providing…

Fluid Dynamics · Physics 2022-07-04 Indrajit Nandi , Saikat Saha , Sabir Subedi , Sumon Saha

A simple model accounting for the ejection of heavy particles from the vortical structures of a turbulent flow is introduced. This model involves a space and time discretization of the dynamics and depends on only two parameters: the…

Chaotic Dynamics · Physics 2009-11-13 Jeremie Bec , Raphael Chetrite

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 modelling of fluid particle accelerations in homogeneous, isotropic turbulence in terms of second-order stochastic models for the Lagrangian velocity is considered. The basis for the Reynolds model (A. M. Reynolds, \textit{Phys. Rev.…

Soft Condensed Matter · Physics 2007-05-23 A. G. Lamorgese , S. B. Pope , P. K. Yeung , B. L. Sawford

Results from Direct Numerical Simulations of particle relative dispersion in three dimensional homogeneous and isotropic turbulence at Reynolds number $Re_\lambda \sim 300$ are presented. We study point-like passive tracers and heavy…

Fluid Dynamics · Physics 2015-02-19 L. Biferale , A. S. Lanotte , R. Scatamacchia , F. Toschi

A machine learning technique is used to fit multiplicity distributions in high-energy proton-proton collisions and applied to make predictions for collisions at higher energies. The method is tested with Monte Carlo event generator events.…

High Energy Physics - Experiment · Physics 2021-08-16 E. Shokr , A. De Roeck , M. A. Mahmoud

Large-scale magnetic fields thread through the electrically conducting matter of the interplanetary and interstellar medium, stellar interiors, and other astrophysical plasmas, producing anisotropic flows with regions of…

Fluid Dynamics · Physics 2022-07-13 J. Pratt , A. Busse , W. -C. Müller

The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study turbulent dispersed flows when the computational cost of Direct Numerical Simulation (DNS) becomes too…

Fluid Dynamics · Physics 2017-06-02 Alessio Innocenti , Cristian Marchioli , Sergio Chibbaro

Turbulent cascades characterize the transfer of energy injected by a random force at large scales towards the small scales. In hydrodynamic turbulence, when the Reynolds number is large, the velocity field of the fluid becomes irregular and…

Mathematical Physics · Physics 2023-12-05 Gabriel B. Apolinário , Geoffrey Beck , Laurent Chevillard , Isabelle Gallagher , Ricardo Grande

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

A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in…

Fluid Dynamics · Physics 2023-07-19 Justin Sirignano , Jonathan F. MacArt

Perturbation Theory (PT) applied to a cosmological density field with Gaussian initial fluctuations suggests a specific hierarchy for the correlation functions when the variance is small. In particular quantitative predictions have been…

Astrophysics · Physics 2009-10-30 D. Munshi , F. Bernardeau , A. L. Melott , R. Schaeffer

The effect of turbulence on the heterogeneous (solid-fluid) reactions of solid particles is studied numerically with Direct Numerical Simulations (DNS). A simplified reaction system is used, where the solid-fluid reaction is represented by…

Fluid Dynamics · Physics 2016-07-14 Jonas Krüger , Nils E. L. Haugen , Dhrubaditya Mitra , Terese Løvås

Most turbulence models used in Reynolds-averaged Navier-Stokes (RANS) simulations are partial differential equations (PDE) that describe the transport of turbulent quantities. Such quantities include turbulent kinetic energy for eddy…

Fluid Dynamics · Physics 2022-02-18 Ruiying Xu , Xu-Hui Zhou , Jiequn Han , Richard P. Dwight , Heng Xiao

Recent advances in data-driven turbulence modeling have established tensor basis neural networks (TBNN) as a physically grounded framework for Reynolds-stress closure in Reynolds-averaged Navier-Stokes (RANS) simulations. However, their…

Fluid Dynamics · Physics 2026-04-13 Zelong Yuan , Yuzhu Pearl Li

In this paper, a three-dimensional numerical solver is developed for suspensions of rigid and soft particles and droplets in viscoelastic and elastoviscoplastic (EVP) fluids. The presented algorithm is designed to allow for the first time…

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

We recently found wall-bounded turbulence to suppress and control bipolar triboelectric charging of particles of identical material. This control is due to fluid modifying the motion of light particles. Thus, the particles' charge…

Fluid Dynamics · Physics 2024-02-15 Simon Jantač , Holger Grosshans

Reservoir computing is applied to model the large-scale evolution and the resulting low-order turbulence statistics of a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at a Rayleigh number ${\rm Ra}=10^7$ and a Prandtl number…

Fluid Dynamics · Physics 2020-11-25 Sandeep Pandey , Jörg Schumacher
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