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Related papers: Grid-based calculation of Lagrangian mean

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Lagrangian averaging plays an important role in the analysis of wave--mean-flow interactions and other multiscale fluid phenomena. The numerical computation of Lagrangian means, e.g. from simulation data, is however challenging. Typical…

Fluid Dynamics · Physics 2023-04-26 Hossein A. Kafiabad , Jacques Vanneste

Lagrangian averaging is a valuable tool for the analysis and modelling of multiscale processes in fluid dynamics. The numerical computation of Lagrangian (time) averages from simulation data is challenging, however. It can be carried out by…

Fluid Dynamics · Physics 2024-12-23 Abhijeet Minz , Lois E. Baker , Hossein A. Kafiabad , Jacques Vanneste

A computationally efficient model is introduced to account for the sub-grid scale velocities of tracer particles dispersed in statistically homogeneous and isotropic turbulent flows. The model embeds the multi-scale nature of turbulent…

Fluid Dynamics · Physics 2015-06-18 I. M. Mazzitelli , F. Toschi , A. S. Lanotte

Geophysical flows are typically composed of wave and mean motions with a wide range of overlapping temporal scales, making separation between the two types of motion in wave-resolving numerical simulations challenging. Lagrangian filtering…

Fluid Dynamics · Physics 2025-10-15 Lois E. Baker , Hossein A. Kafiabad , Cai Maitland-Davies , Jacques Vanneste

This paper deals with the state estimation of non-linear and non-Gaussian systems with an emphasis on the numerical solution to the Bayesian recursive relations. In particular, this paper builds upon the Lagrangian grid-based filter (GbF)…

Signal Processing · Electrical Eng. & Systems 2026-02-20 Jindřich Duník , Jan Krejčí , Jakub Matoušek , Marek Brandner , Yeongkwon Choe

This paper proposes stochastic models for the analysis of ocean surface trajectories obtained from freely-drifting satellite-tracked instruments. The proposed time series models are used to summarise large multivariate datasets and infer…

Applications · Statistics 2017-03-16 Adam M. Sykulski , Sofia C. Olhede , Jonathan M. Lilly , Eric Danioux

Numerical simulations of the air in the atmosphere and water in the oceans are essential for numerical weather prediction. The state-of-the-art for performing these fluid simulations relies on an Eulerian viewpoint, in which the fluid…

Fluid Dynamics · Physics 2025-08-12 Philip Caplan , Otis Milliken , Toby Pouler , Zeyi Tong , Col McDermott , Sam Millay

We propose a defiltering method of turbulent flow fields for Lagrangian particle tracking using machine learning techniques. Numerical simulation of Lagrangian particle tracking is commonly used in various fields. In general, practical…

Fluid Dynamics · Physics 2024-11-21 Tomoya Oura , Koji Fukagata

Spurious numerical mixing is a frequent phenomenon in ocean models. In this paper, we present an efficient and robust methodology that defines the vertical grid motion so that this mixing is reduced. This motion is defined as the solution…

Computational Physics · Physics 2026-05-27 Andreas Alexandris-Galanopoulos , George Papadakis

The aim of the present paper is to introduce and to discuss inconsistencies errors that may arise when Eulerian and Lagrangian models are coupled for the simulations of turbulent poly-dispersed two-phase flows. In these hydrid models, two…

Fluid Dynamics · Physics 2011-04-07 Sergio Chibbaro , Jean-Pierre Minier

This paper describes a method for deriving approximate equations for irrotational water waves. The method is based on a 'relaxed' variational principle, i.e., on a Lagrangian involving as many variables as possible. This formulation is…

Classical Physics · Physics 2020-02-20 Didier Clamond , Denys Dutykh

The immersed boundary (IB) method is an approach to fluid-structure interaction that uses Lagrangian variables to describe the structure and Eulerian variables to describe the fluid. Explicit time stepping schemes for the IB method require…

Numerical Analysis · Mathematics 2017-04-06 Robert D. Guy , Bobby Philip , Boyce E. Griffith

In this chapter, we illustrate the advantage of variational principles for modeling water waves from an elementary practical viewpoint. The method is based on a `relaxed' variational principle, i.e., on a Lagrangian involving as many…

Fluid Dynamics · Physics 2019-12-16 Didier Clamond , Denys Dutykh

The generalized Langrangian mean theory provides exact equations for general wave-turbulence-mean flow interactions in three dimensions. For practical applications, these equations must be closed by specifying the wave forcing terms. Here…

Atmospheric and Oceanic Physics · Physics 2009-11-13 Fabrice Ardhuin , Nicolas Rascle , Kostas Belibassakis

Semi-Lagrangian solvers for the Vlasov system offer noiseless solutions compared to Lagrangian particle methods and can handle larger time steps compared to Eulerian methods. In order to reduce the computational complexity of the…

Numerical Analysis · Mathematics 2025-10-24 Nils Schild , Mario Raeth Klaus Hallatschek , Katharina Kormann

We construct sub-grid scale models of incompressible fluids by considering expectations of semi-martingale Lagrangian particle trajectories. Our construction is based on the Lagrangian decomposition of flow maps into mean and fluctuation…

Mathematical Physics · Physics 2025-04-15 Theo Diamantakis , Ruiao Hu

We consider the assimilation of Lagrangian data into a primitive equations circulation model of the ocean at basin scale. The Lagrangian data are positions of floats drifting at fixed depth. We aim at reconstructing the four-dimensional…

Optimization and Control · Mathematics 2009-11-13 Maëlle Nodet

Non-spherical particles transported by an anisotropic turbulent flow preferentially align with the mean shear and intermittently tumble when the local strain fluctuates. Such an intricate behaviour is here studied for inertialess,…

Soft Condensed Matter · Physics 2022-12-27 Lorenzo Campana , Mireille Bossy , Jeremie Bec

A variational method is used to derive a self-consistent macro-particle model for relativistic electromagnetic kinetic plasma simulations. Extending earlier work [E. G. Evstatiev and B. A. Shadwick, J. Comput. Phys., vol. 245, pp. 376-398,…

Computational Physics · Physics 2014-04-22 A. B. Stamm , B. A. Shadwick , E. G. Evstatiev

We present the first method to directly use a learned continuous Lagrangian to forecast the dynamics of systems governed by partial differential equations, exploiting the inherent conservative structure to achieve stable long-range…

Machine Learning · Computer Science 2026-05-11 Lyra Zhornyak , Eric Forgoston , M. Ani Hsieh
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