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Within the framework of one-dimensional Laval-Dubrulle-Nazarenko type model for the Lagrangian acceleration in developed turbulence studied in the work [A.K. Aringazin and M.I. Mazhitov, cond-mat/0305186] we focus on the effect of…

统计力学 · 物理学 2007-05-23 A. K. Aringazin

This text describes a method to simultaneously reconstruct flow states and determine particle properties from Lagrangian particle tracking (LPT) data. LPT is a popular measurement strategy for fluids in which particles in a flow are…

流体动力学 · 物理学 2023-11-16 Ke Zhou , Samuel J. Grauer

We have developed a new experimental technique to measure the Lagrangian velocity of tracer particles in a turbulent flow, based on ultrasonic Doppler tracking. This method yields a direct access to the velocity of a single particule at a…

流体动力学 · 物理学 2009-11-07 N. Mordant , P. Metz , O. Michel , J. -F. Pinton

The equation for the fluid velocity gradient along a Lagrangian trajectory immediately follows from the Navier-Stokes equation. However, such an equation involves two terms that cannot be determined from the velocity gradient along the…

流体动力学 · 物理学 2023-06-21 Xiaolong Zhang , Maurizio Carbone , Andrew D. Bragg

We study the evolution of turbulent puffs by means of high-resolution numerical simulations. Puffs are bunches of passive particles released from an initially spherical distribution at regular time intervals of the order of the Kolmogorov…

流体动力学 · 物理学 2015-09-29 Stefano Bianchi , Luca Biferale , Antonio Celani , Massimo Cencini

Tracers in a turbulent flow separate according to the celebrated $t^{3/2}$ Richardson--Obukhov law, which is usually explained by a scale-dependent effective diffusivity. Here, supported by state-of-the-art numerics, we revisit this…

流体动力学 · 物理学 2015-06-05 Rehab Bitane , Jérémie Bec , Holger Homann

We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a…

混沌动力学 · 物理学 2017-04-05 Michael Lindner , Reik V. Donner

We recently proposed a method for estimation of states and parameters in stochastic differential equations, which included intermediate time points between observations and used the Laplace approximation to integrate out these intermediate…

概率论 · 数学 2025-04-01 Uffe Høgsbro Thygesen

The Navier-Stokes equations generate an infinite set of generalized Lyapunov exponents defined by different ways of measuring the distance between exponentially diverging perturbed and unperturbed solutions. This set is demonstrated to be…

流体动力学 · 物理学 2021-04-14 Itzhak Fouxon , Joshua Feinberg , Petri Käpylä , Michael Mond

Turbulent flows are strongly chaotic and unpredictable, with a Lyapunov exponent that increases with the Reynolds number. Here, we study the chaoticity of the Surface Quasi-geostrophic system, a two-dimensional model for geophysical flows…

流体动力学 · 物理学 2025-07-28 V. J. Valadão , F. De Lillo , S. Musacchio , G. Boffetta

We propose a unified framework to study the turbulent transport problem from the perspective of nonequilibrium statistical mechanics. By combining Krarichnan's turbulence thermalization assumption and Ruelle's recent work on nonequilibrium…

统计力学 · 物理学 2021-06-15 Yuanran Zhu

We study the Lagrangian velocity and acceleration statistics of light particles (micro-bubbles in water) in homogeneous isotropic turbulence. Micro-bubbles with a diameter of 340 microns and Stokes number from 0.02 to 0.09 are dispersed in…

流体动力学 · 物理学 2012-05-30 Julian Martinez Mercado , Vivek N. Prakash , Yoshiyuki Tagawa , Chao Sun , Detlef Lohse

Deformation of material lines drives transport and dissipation in many industrial and natural flows. Here we report an exact Eulerian formula for the stretching rate of a material line, also known as the topological entropy, in a prototype…

流体动力学 · 物理学 2024-12-16 Amal Manoharan , Sai Subramanian , Ashwin Joy

This work is concerned with the stability properties of linear stochastic differential equations with random (drift and diffusion) coefficient matrices, and the stability of a corresponding random transition matrix (or exponential…

概率论 · 数学 2019-05-02 Adrian N. Bishop , Pierre Del Moral

The Lagrangian statistics of heavy particles and of fluid tracers transported by a fully developed turbulent flow are investigated by means of high resolution direct numerical simulations. The Lagrangian velocity structure functions are…

混沌动力学 · 物理学 2007-05-23 Jeremie Bec , Luca Biferale , Massimo Cencini , Alessandra S. Lanotte , Federico Toschi

Dense granular flows are often unstable and form inhomogeneous structures. Although significant advances have been recently made in understanding simple flows, instabilities of such flows are often not understood. We present experimental…

软凝聚态物质 · 物理学 2009-10-02 Tamas Borzsonyi , Robert E. Ecke , Jim N. McElwaine

We study the chaoticity and the predictability of a turbulent flow on the basis of high-resolution direct numerical simulations at different Reynolds numbers. We find that the Lyapunov exponent of turbulence, which measures the exponential…

流体动力学 · 物理学 2017-08-09 G. Boffetta , S. Musacchio

We analytically evaluate the large deviation function in a simple model of classical particle transfer between two reservoirs. We illustrate how the asymptotic large time regime is reached starting from a special propagating initial…

统计力学 · 物理学 2015-06-16 Upendra Harbola , Christian Van den Broeck , Katja Lindenberg

Understanding and predicting the dynamical properties of systems involving dry friction is a major concern in physics and engineering. It abounds in many mechanical processes, from the sound produced by a violin to the screeching of chalk…

概率论 · 数学 2023-05-16 Josselin Garnier , Ziyu Lu , Laurent Mertz

The breakup of inertial, solid aggregates in an incompressible, homogeneous and isotropic three-dimensional turbulent flow is studied by means of a direct numerical simulation, and by a Lagrangian tracking of the aggregates at varying…

流体动力学 · 物理学 2022-11-08 Graziano Frungieri , Matthaus U. Baebler , Luca Biferale , Alessandra Sabina Lanotte