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Related papers: Stochastic Geometric Mechanics for Fluid Dynamics

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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

In 1966 V.Arnold suggested a group-theoretic approach to ideal hydrodynamics in which the motion of an inviscid incompressible fluid is described as the geodesic flow of the right-invariant $L^2$-metric on the group of volume-preserving…

Symplectic Geometry · Mathematics 2018-09-05 Anton Izosimov , Boris Khesin

This work investigates variational frameworks for modeling stochastic dynamics in incompressible fluids, focusing on large-scale fluid behavior alongside small-scale stochastic processes. The authors aim to develop a coupled system of…

Fluid Dynamics · Physics 2025-03-21 Arnaud Debussche , Etienne Mémin

Predicting how much mixing occurs when a given amount of energy is injected into a Boussinesq fluid is a longstanding problem in stratified turbulence. The huge number of degrees of freedom involved in those processes renders extremely…

Fluid Dynamics · Physics 2016-12-21 Antoine Venaille , Louis Gostiaux , Joel Sommeria

Dipole-conserving fluids serve as examples of kinematically constrained systems that can be understood on the basis of symmetry. They are known to display various exotic features including glassylike dynamics, subdiffusive transport, and…

Strongly Correlated Electrons · Physics 2023-04-18 Aleksander Głódkowski , Francisco Peña-Benítez , Piotr Surówka

In this work, we introduce an effective model for both ideal and viscous fluid dynamics within the framework of kinetic field theory (KFT). The main application we have in mind is cosmic structure formation where gaseous components need to…

Statistical Mechanics · Physics 2018-11-01 C. Viermann , J. T. Schneider , R. Lilow , F. Fabis , C. Littek , E. Kozlikin , M. Bartelmann

Inhomogeneous flows and shear banding are of interest for a range of applications but have been eluding a comprehensive theoretical understanding, mostly due to the lack of a framework comparable to equilibrium statistical mechanics. Here…

Statistical Mechanics · Physics 2025-05-15 Thomas Speck

A recently introduced particle-based model for fluid dynamics with continuous velocities is generalized to model fluids with excluded volume effects. This is achieved through the use of biased stochastic multi-particle collisions which…

Soft Condensed Matter · Physics 2007-05-23 Erkan Tuzel , Thomas Ihle , Daniel M. Kroll

The stochastics two-layer quasi-geostrophic flow model is an intermediate system between the single-layer two dimensional barotropic flow model and the continuously stratified three dimensional baroclinic flow model. This model is widely…

Dynamical Systems · Mathematics 2008-10-17 Aijun Du , Jinqiao Duan , Hongjun Gao

The aim of this article is to highlight the interest to apply Differential Geometry and Mechanics concepts to chaotic dynamical systems study. Thus, the local metric properties of curvature and torsion will directly provide the analytical…

Dynamical Systems · Mathematics 2014-08-11 Jean-Marc Ginoux , Bruno Rossetto

A simple generalization of the MHD model accounting for the fluctuations of the configurations due to kinetic effects in plasmas in short times small scales is considered. The velocity of conductive fluid and the magnetic field are…

Plasma Physics · Physics 2007-10-26 D. Volchenkov , R. Lima

Microscopic heat engines operate in regimes where thermodynamic quantities fluctuate strongly, making stochastic effects an essential aspect of their performance. However, existing geometric formulations of finite-time thermodynamics…

Statistical Mechanics · Physics 2026-04-07 Gentaro Watanabe , Guo-Hua Xu , Yuki Minami

Graph neural networks (GNNs) have shown promise in learning unstructured mesh-based simulations of physical systems, including fluid dynamics. In tandem, geometric deep learning principles have informed the development of equivariant…

Stochastic gradient descent (SGD) is a key ingredient in the training of deep neural networks and yet its geometrical significance appears elusive. We study a deterministic model in which the trajectories of our dynamical systems are…

Machine Learning · Computer Science 2020-02-19 R. Fioresi , P. Chaudhari , S. Soatto

This paper introduces a global uncertainty propagation scheme for rigid body dynamics, through a combination of numerical parametric uncertainty techniques, noncommutative harmonic analysis, and geometric numerical integration. This method…

Dynamical Systems · Mathematics 2008-03-12 Taeyoung Lee , Melvin Leok , N. Harris McClamroch

Lie symmetry group method is applied to study Newtonian incompressible fluid's equations flow in turbulent boundary layers. The symmetry group and its optimal system are given, and group invariant solutions associated to the symmetries are…

Analysis of PDEs · Mathematics 2010-07-06 Mehdi Nadjafikhah , Seyed Reza Hejazi

The Lagrangian approach is natural to study issues of turbulent dispersion and mixing. We propose in this work a general Lagrangian stochastic model including velocity and acceleration as dynamical variables for inhomogeneous turbulent…

Fluid Dynamics · Physics 2020-05-01 Alessio Innocenti , Nicolas Mordant , Nick Stelzenmuller , Sergio Chibbaro

In this work, a stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the large-scale oceanic circulation. This stochastic framework arises from a decomposition of the…

Geophysics · Physics 2022-07-26 Long Li , Bruno Deremble , Noé Lahaye , Etienne Mémin

We analyze the transport properties of a low density ensemble of identical macroscopic particles immersed in an active fluid. The particles are modeled as inelastic hard spheres (granular gas). The non-homogeneous active fluid is modeled by…

Soft Condensed Matter · Physics 2017-10-17 Francisco Vega Reyes , Antonio Lasanta

Considered herein is a particular nonlinear dispersive stochastic equation. It was introduced recently in [3], as a model describing surface water waves under location uncertainty. The corresponding noise term is introduced through a…

Analysis of PDEs · Mathematics 2023-05-10 Evgueni Dinvay
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