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The non--static generalized Langevin equation and its corresponding Fokker--Planck equation for the position of a viscous fluid particle were solved in closed form for a time dependent external force. Its solution for a constant external…

Statistical Mechanics · Physics 2018-05-08 Wilmer Olivares-Rivas , Pedro J. Colmenares

The interaction of fluids with surface-mounted obstacles in canopy flows leads to strong turbulence that dominates dispersion and mixing in the neutrally stable atmospheric surface layer. This work focuses on intermittency in the Lagrangian…

Fluid Dynamics · Physics 2021-03-01 Ron Shnapp

As most mathematically justifiable Lagrangian coherent structure detection methods rely on spatial derivatives, their applicability to sparse trajectory data has been limited. For experimental fluid dynamicists and natural scientists…

Fluid Dynamics · Physics 2024-11-20 Nikolas O. Aksamit , Alex P. Encinas-Bartos , George Haller , David E. Rival

We outline a statistical theory of turbulence based on the Lagrangian formulation of fluid motion. We derive a hierarchy of evolution equations for Lagrangian N-point probability distributions as well as a functional equation for a suitably…

Fluid Dynamics · Physics 2007-05-23 R. Friedrich

Fluid deformation controls myriad processes in random flows including mixing and dispersion, stress development in complex fluids, colloid transport and deposition, droplet breakup and emulsification, fluid-structure interaction, chemical…

Fluid Dynamics · Physics 2026-05-07 Daniel Lester , Marco Dentz

Non-spherical particles transported by turbulent flow have a rich dynamics that combines their translational and rotational motions. Here, the focus is on small, heavy, inertial particles with a spheroidal shape fully prescribed by their…

Fluid Dynamics · Physics 2023-08-02 Sofia Allende , Jeremie Bec

Based on geometric considerations, longitudinal and transverse Lagrangian velocity increments are introduced as components along, and perpendicular to, the displacement of fluid particles during a time scale {\tau}. It is argued that these…

Chaotic Dynamics · Physics 2015-06-22 Emmanuel Leveque , Aurore Naso

Spontaneous stochasticity is a modern paradigm for turbulent transport at infinite Reynolds numbers. It suggests that tracer particles advected by rough turbulent flows and subject to additional thermal noise, remain non-deterministic in…

Fluid Dynamics · Physics 2023-06-21 André Luís Peixoto Considera , Simon Thalabard

We study the transport of a passive tracer particle in a steady strongly mixing flow with a nonzero mean velocity. We show that there exists a probability measure under which the particle Lagrangian velocity process is stationary. This…

Probability · Mathematics 2007-05-23 Tomasz Komorowski , Grzegorz Krupa

The Euler and Navier-Stokes fluid mechanics equations are derived using a modified statistical mechanical approach using theory taken from the Chapman-Enskog perturbation analysis used to support the lattice Boltzmann method. Additional…

Fluid Dynamics · Physics 2021-07-06 Charles Cook

Experimental measurements of properties of the large-scale circulation (LSC) in turbulent convection of a fluid heated from below in a cylindrical container of aspect ratio one are presented and used to test a model of diffusion in a…

Fluid Dynamics · Physics 2009-11-13 Eric Brown , Guenter Ahlers

We suggested a one-fluid model of a turbulent dilute suspension which accounts for the ``two-way'' fluid-particle interactions by $k$-dependent effective density of suspension and additional damping term in the Navier-Stokes equation. We…

Chaotic Dynamics · Physics 2007-05-23 Victor S. L'vov , Anna Pomyalov

The transition from laminar to turbulent fluid motion occurring at large Reynolds numbers is generally associated with the instability of the laminar flow. On the other hand, since the turbulent flow characteristically appears in the form…

Fluid Dynamics · Physics 2013-09-27 Sergei F. Chekmarev

We consider a fluid governed by the randomly forced 2D Navier-Stokes system. It is assumed that the force is bounded, acts directly only on a small number of Fourier modes, and satisfies some natural decomposability and observability…

Analysis of PDEs · Mathematics 2024-11-18 Vahagn Nersesyan , Deng Zhang , Chenwan Zhou

Based on direct numerical simulations with point-like inertial particles, with Stokes numbers, $\textrm{St}=0, 0.5$, $3$, and $6$, transported by homogeneous and isotropic turbulent flows, we present in this letter for the first time…

Fluid Dynamics · Physics 2022-06-27 A. Fuchs , M. Obligado , M. Bourgoin , M. Gibert , P. D. Mininni , J. Peinke

When studying the dynamics of incompressible fluids in bounded domains the only available data often provide average flow rate conditions on portions of the domain's boundary. In engineering applications a common practice to complete these…

Computational Engineering, Finance, and Science · Computer Science 2025-12-15 Luca Crugnola , Christian Vergara

In the context of instanton method for stochastic system this paper purposes a modification of the arclength parametrization of the Hamilton's equations allowing for an arbitrary instanton speed. The main results of the paper are: (i) it…

Fluid Dynamics · Physics 2020-05-20 L. S. Grigorio

We investigate the statistics of a vector Manakov soliton in the presence of additive Gaussian white noise. The adiabatic perturbation theory for Manakov soliton yields a stochastic Langevin system which we analyze via the corresponding…

Chaotic Dynamics · Physics 2007-05-23 S. A. Derevyanko , J. E. Prilepsky , D. A. Yakushev

We characterize the behavior of stochastic Navier-Stokes on $\mathbb{T} \times [-1,1]$ with Navier boundary conditions at high Reynolds number when initialized near Couette flow subject to small additive stochastic forcing. We take additive…

Analysis of PDEs · Mathematics 2026-03-03 Ryan Arbon , Jacob Bedrossian

Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini