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The transport properties of a random velocity field with Kolmogorov spectrum and time correlations defined along Lagrangian trajectories are analyzed. The analysis is carried on in the limit of short correlation times, as a perturbation…

Chaotic Dynamics · Physics 2009-11-07 Piero Olla

Lagrangian measurements of tracer particle dispersion in stratified turbulence are presented from a large-scale experiment achieving both high buoyancy Reynolds numbers and low Froude numbers -- a regime characteristic of oceanic…

We consider so-called Leray regularization of the convective contributions. This gives rise to a subgrid parameterization which involves both explicit filtering and (approximate) inversion. The Leray model also arises from the…

Chaotic Dynamics · Physics 2007-05-23 Bernard J. Geurts , Darryl D. Holm

We outline a methodology for the simulation of particle-laden flows whereby the dispersed and fluid phases are two-way coupled. The drag force which couples fluid and particle momentum depends on the undisturbed fluid velocity at the…

Fluid Dynamics · Physics 2020-04-21 J. A. K. Horwitz , G. Iaccarino , J. K. Eaton , A. Mani

We present direct numerical simulation results of turbulent open channel flow at bulk Reynolds numbers up to 12000, coupled with (passive) scalar transport at Schmidt numbers up to 200. Care is taken to capture the very large scale motions…

Fluid Dynamics · Physics 2022-01-19 Michele Pinelli , Herlina Herlina , Jan G. Wissink , Markus Uhlmann

Recent theoretical progress using multiscale asymptotic analysis has revealed various possible regimes of stratified turbulence. Notably, buoyancy transport can either be dominated by advection or diffusion, depending on the effective…

Fluid Dynamics · Physics 2024-11-20 Pascale Garaud , Greg P. Chini , Laura Cope , Kasturi Shah , Colm-cille P. Caulfield

An experiment was performed using SPIV in the LMFL boundary layer facility to determine all the derivative moments needed to estimate the average dissipation rate of the turbulence kinetic energy, $\varepsilon = 2 \nu \langle s_{ij}s_{ij}…

Direct numerical simulations (DNS) are one of the main ab initio tools to study turbulent flows. However, due to their considerable computational cost, DNS are primarily restricted to canonical flows at moderate Reynolds numbers, in which…

Fluid Dynamics · Physics 2024-09-17 Arnab Moitro , Sai Sandeep Dammati , Alexei Y. Poludnenko

We study the effect of turbulence on a sedimenting layer of particles by means of direct numerical simulations. A Lagrangian model in which particles are considered as tracers with an additional downward settling velocity is integrated…

Fluid Dynamics · Physics 2020-07-08 Alessandro Sozza , Gabor Drotos , Emilio Hernández-García , Cristóbal López

We use laser-Doppler velocimetry (LDV) experiments and Reynolds-averaged Navier--Stokes (RANS) simulations to study the characteristic flow patterns downstream of a standardized clockwise swirl disturbance generator. After quantifying the…

Fluid Dynamics · Physics 2015-10-27 Diego del Olmo Díaz , Denis F. Hinz

In this note, we study the long-time dynamics of passive scalars driven by rotationally symmetric flows. We focus on identifying precise conditions on the velocity field in order to prove enhanced dissipation and Taylor dispersion in…

Analysis of PDEs · Mathematics 2023-05-30 Michele Coti Zelati , Michele Dolce , Chia-Chun Lo

We develop a stochastic model for the velocity gradients dynamics along a Lagrangian trajectory. Comparing with different attempts proposed in the literature, the present model, at the cost of introducing a free parameter known in…

Fluid Dynamics · Physics 2018-02-23 Rodrigo M. Pereira , Luca Moriconi , Laurent Chevillard

The joint probability density function (PDF) of turbulent velocity and concentration of a passive scalar in an urban street canyon is computed using a newly developed particle-in-cell Monte Carlo method. Compared to moment closures, the PDF…

Geophysics · Physics 2010-03-25 J. Bakosi , P. Franzese , Z. Boybeyi

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

Using high-fidelity numerical simulations based on a lattice Boltzmann framework, the advection-enhanced transport of a passive scalar from a prolate spheroid in simple shear flow has been thoroughly investigated across various parameters,…

Fluid Dynamics · Physics 2025-10-15 Yanxing Wang , Hui Wan , Tie Wei , Fangjun Shu

Steady statistics of a passive scalar advected by a random two-dimensional flow of an incompressible fluid is described in the range of scales between the correlation length of the flow and the diffusion scale. That corresponds to the…

Condensed Matter · Physics 2009-10-22 M. Chertkov , G. Falkovich , I. Kolokolov , V. Lebedev

We study passive scalar mixing by parallel shear flows in the presence of weak molecular diffusion. We recover the sharp uniform-in-diffusivity mixing rate for shear flows with finitely many critical points, recently proven in [1]. Our…

Analysis of PDEs · Mathematics 2026-03-11 Kyle L. Liss , Kunhui Luan

Bubbles play an important role in the transport of chemicals and nutrients in many natural and industrial flows. Their dispersion is crucial to understand the mixing processes in these flows. Here we report on the dispersion of millimetric…

Fluid Dynamics · Physics 2018-08-08 Varghese Mathai , Sander G. Huisman , Chao Sun , Detlef Lohse , Mickaël Bourgoin

Multiscale mixing efficiencies for passive scalar advection are defined in terms of the suppression of variance weighted at various length scales. We consider scalars maintained by temporally steady but spatially inhomogeneous sources,…

Fluid Dynamics · Physics 2007-05-23 Charles R. Doering , Jean-Luc Thiffeault

The emerging push of the differentiable programming paradigm in scientific computing is conducive to training deep learning turbulence models using indirect observations. This paper demonstrates the viability of this approach and presents…

Fluid Dynamics · Physics 2021-04-13 Carlos A. Michelén Ströfer , Heng Xiao