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Related papers: Non-Markovian Closure Models for Large Eddy Simula…

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A closure model is presented for large-eddy simulation (LES) based on the three-dimensional variational data assimilation algorithm. The approach aims at reconstructing high-fidelity kinetic energy spectra in coarse numerical simulations by…

Fluid Dynamics · Physics 2024-07-02 Sagy Ephrati , Arnout Franken , Erwin Luesink , Paolo Cifani , Bernard Geurts

In this work, we present a localized form of the dynamic eddy viscosity model for computationally efficient and accurate simulation of the turbulent flows governed by Euler equations. In our framework, we determine the dynamic model…

Fluid Dynamics · Physics 2018-10-04 Sk. Mashfiqur Rahman , Omer San

A new tuning-free subgrid-scale model, termed `locally-averaged scale-dependent dynamic' (LASDD) model, is developed and implemented in large-eddy simulations (LESs) of stable boundary layers. The new model dynamically computes the…

Atmospheric and Oceanic Physics · Physics 2016-08-16 Sukanta Basu , Fernando Porté-Agel

The hydrodynamics of thin films is typically described using phenomenological models whose connection to the microscopic particle dynamics is a subject of ongoing research. Existing methods based on density functional theory provide a good…

Soft Condensed Matter · Physics 2024-03-20 Michael te Vrugt , Leon Topp , Raphael Wittkowski , Andreas Heuer

In this article we detail the use of machine learning for spatiotemporally dynamic turbulence model classification and hybridization for the large eddy simulations (LES) of turbulence. Our predictive framework is devised around the…

Fluid Dynamics · Physics 2019-05-15 Romit Maulik , Omer San , Jamey D. Jacob , Christopher Crick

MHD turbulence is likely to play an important role in several astrophysical scenarios where the magnetic Reynolds is very large. Numerically, these cases can be studied efficiently by means of Large Eddy Simulations, in which the…

High Energy Astrophysical Phenomena · Physics 2020-03-25 Federico Carrasco , Daniele Viganò , Carlos Palenzuela

In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations…

Atmospheric and Oceanic Physics · Physics 2016-12-23 Georg A. Gottwald , Daan T. Crommelin , Christian L. E. Franzke

Recent advances in learning dynamical systems from data have shown significant promise. However, many existing methods assume access to the full state of the system -- an assumption that is rarely satisfied in practice, where systems are…

Machine Learning · Computer Science 2026-03-10 Thibault Monsel , Onofrio Semeraro , Lionel Mathelin , Guillaume Charpiat

The results of large eddy simulation (LES) using three sub-grid scale models, namely: constant coefficient Smagorinsky, dynamic Smagorinsky, and a dynamic Clark model, for rotating stratified turbulence in the absence of forcing using…

Fluid Dynamics · Physics 2023-08-17 Kiran Jadhav , Rahul Agrawal , Abhilash J. Chandy

We present a methodology to determine the best turbulence closure for an eddy-permitting ocean model through measurement of the error-landscape of the closure's subgrid spectral transfers and flux. We apply this method to 6 different…

Fluid Dynamics · Physics 2015-06-05 Jonathan Pietarila Graham , Todd Ringler

Rotating turbulent flows form a challenging test case for large-eddy simulation (LES). We, therefore, propose and validate a new subgrid-scale (SGS) model for such flows. The proposed SGS model consists of a dissipative eddy viscosity term…

Fluid Dynamics · Physics 2019-04-30 Maurits H. Silvis , H. Jane Bae , F. Xavier Trias , Mahdi Abkar , Roel Verstappen

We provide a simple hypocoercivity analysis for the effective Mori-Zwanzig equation governing the time evolution of noise-averaged observables in a stochastic dynamical system. Under the hypocoercivity framework mainly developed by…

Mathematical Physics · Physics 2021-09-14 Yuanran Zhu

Over the last years, supervised learning (SL) has established itself as the state-of-the-art for data-driven turbulence modeling. In the SL paradigm, models are trained based on a dataset, which is typically computed a priori from a…

Fluid Dynamics · Physics 2022-12-23 Marius Kurz , Philipp Offenhäuser , Andrea Beck

Turbulence is the most important, ubiquitous, and difficult problem of classical physics. Feynman viewed it as essentially unsolved, without a rigorous mathematical basis to describe the statistical dynamics of this most complex of fluid…

Fluid Dynamics · Physics 2024-07-16 Jorgen S. Frederiksen , Vassili Kitsios , Terence J. O'Kane

Numerical simulations of turbulent flows are well known to pose extreme computational challenges due to the huge number of dynamical degrees of freedom required to correctly describe the complex multi-scale statistical correlations of the…

Fluid Dynamics · Physics 2025-02-27 Giulio Ortali , Alessandro Gabbana , Nicola Demo , Gianluigi Rozza , Federico Toschi

We continue a previous work in which {\em a priori} estimates were derived on subgrid stress and subgrid flux for filtering schemes used in the turbulence modelling method of Large-Eddy Simulation (LES). The estimates were derived there as…

chao-dyn · Physics 2008-02-03 Gregory L. Eyink

We present a framework based on the generalized lattice-Boltzmann equation using multiple relaxation times with forcing term for eddy capturing simulation of wall bounded turbulent flows. Due to its flexibility in using disparate relaxation…

Computational Physics · Physics 2009-11-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

Filtered budgets for anelastic turbulence and a general expression of the turbulent sensible heat flux are derived for a multicomponent fluid with an arbitrary equation of state. A family of subgrid-scale closures is then found under the…

Fluid Dynamics · Physics 2026-01-26 Thomas Dubos

The issue of the parameterization of small scale (``subgrid'') turbulence is addressed in the context of passive scalar transport. We focus on the Kraichnan advection model which lends itself to the analytical investigation of the closure…

Chaotic Dynamics · Physics 2009-11-10 M. Martins Afonso , A. Celani , R. Festa , A. Mazzino

We present an overview of recent works on the statistical description of turbulent flows in terms of probability density functions (PDFs) in the framework of the Lundgren-Monin-Novikov (LMN) hierarchy. Within this framework, evolution…

Fluid Dynamics · Physics 2013-03-19 R. Friedrich , A. Daitche , O. Kamps , J. Lülff , M. Voßkuhle , M. Wilczek