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This study develops invariance-embedded machine learning sub-grid-scale (SGS) stress models admitting turbulence kinetic energy (TKE) backscatter towards more accurate large eddy simulation (LES) of meso-scale turbulent hurricane boundary…

Fluid Dynamics · Physics 2025-04-22 Md Badrul Hasan , Meilin Yu , Tim Oates

Conditional elimination of degrees of freedom is shown to lead to an exact expression for the rate of turbulent energy dissipation in terms of a renormalized viscosity and a correction. The correction is neglected on the basis of a previous…

Condensed Matter · Physics 2009-10-31 C. Johnston , W. D. McComb

In this review, the methodology of large eddy simulations (LES) is introduced and applications in astrophysics are discussed. As theoretical framework, the scale decomposition of the dynamical equations for compressible neutral fluids by…

Astrophysics of Galaxies · Physics 2025-09-09 Wolfram Schmidt-Brückner

Due to the chaotic nature of turbulence, statistical quantities are often more informative than pointwise characterizations. In this work, we consider the stochastic Ladyzhenskaya-Smagorinsky equation driven by space-time Gaussian noise on…

Analysis of PDEs · Mathematics 2026-03-03 Louis Wai-Tong Fan , Ali Pakzad

Classical eddy viscosity models of turbulence add an eddy viscosity term based on the Kolmogorov-Prandtl parameterization by a turbulent length scale $l$ and a turbulent kinetic energy $k^{\prime }$. Approximations of the unknowns…

Numerical Analysis · Mathematics 2026-03-31 William Layton , Nanda Nechingal Raghunathan

Fluid turbulence is an important problem for physics and engineering. Turbulence modeling deals with the development of simplified models that can act as surrogates for representing the effects of turbulence on flow evolution. Such models…

Fluid Dynamics · Physics 2021-11-16 J P Panda

In 1-equation URANS models of turbulence the eddy viscosity is given by $\nu_{T}=0.55l(x,t)\sqrt{k(x,t)}$ . The length scale $l$ must be pre-specified and $k(x,t)$ is determined by solving a nonlinear partial differential equation. We show…

Numerical Analysis · Mathematics 2023-09-08 Rui Fang , Weiwei Han , William Layton

In wildfires, atmospheric turbulence plays a major role in the transfer of turbulent kinetic energy. Understanding how turbulence feeds back into a dynamical system is important, down to the varying small scales of fuel structures (i.e.…

Fluid Dynamics · Physics 2024-09-11 Dorianis M. Perez , Jesse M. Canfield , Rodman R. Linn , Kevin Speer

The equations in conservative form for nonlinear waves modeling on a liquid film flowing down a vertical plane have been investigated. It has been found that in the computational domain extended along the transverse axis the equations with…

Fluid Dynamics · Physics 2016-06-29 Dmitry Arkhipov , Ivan Vozhakov , Dmitry Markovich , Oleg Tsvelodub

In this paper, we study the well-posedeness at low regularity of a two-dimensional system obtained as a reduced model for micropolar fluid dynamics. At the mathematical level, the system presents a coupling between an Euler-type equation…

Analysis of PDEs · Mathematics 2026-05-14 Francesco Fanelli , Pedro Gabriel Fernández Dalgo

Physics-based closures such as eddy-viscosity and backscattering models are widely used for large-eddy simulation (LES) of geophysical turbulence for applications including weather and climate prediction. However, these closures have…

Fluid Dynamics · Physics 2026-04-14 Yifei Guan , Pedram Hassanzadeh

A large eddy simulation (LES) with an extended Smagorinsky model has been carried to investigate numerically the fully developed turbulent flow of a shear thinning fluid (n=0.75) in a stationary pipe at a simulation's Reynolds number equals…

Fluid Dynamics · Physics 2020-06-01 Mohamed Abdi , Meryem Ould-Rouiss , Abdelkader Noureddine

In supersonic and hypersonic flows, the near-wall density variation due to wall cooling poses a challenge for accurately predicting the near-wall velocity and temperature profiles using classical eddy viscosity turbulence models.…

Fluid Dynamics · Physics 2025-08-19 Zifei Yin

Machine learning-based closure models for LES have shown promise in capturing complex turbulence dynamics but often suffer from instabilities and physical inconsistencies. In this work, we develop a novel skew-symmetric neural architecture…

Machine Learning · Computer Science 2025-12-04 Toby van Gastelen , Wouter Edeling , Benjamin Sanderse

Based on the characteristics of the multi-scale and similarity at different scales in turbulent flow, we propose a scale decomposition for solving the turbulence problem of incompressible Newtonian fluid. The solution domain is decomposed…

Fluid Dynamics · Physics 2023-02-21 Shanwen Tan

In this work we introduce a well-posed mathematical model for the processes involved in the artificial circulation of water, in order to avoid eutrophication phenomena, for instance, in a lake. This novel and general formulation is based on…

Analysis of PDEs · Mathematics 2019-02-04 Francisco J. Fernández , Lino J. Álvarez-Vázquez , Aurea Martínez

We prove an estimate of total (viscous plus modelled turbulent) energy dissipation in general eddy viscosity models for shear flows. For general eddy viscosity models, we show that the ratio of the near wall average viscosity to the…

Fluid Dynamics · Physics 2022-10-12 Kiera Kean , William Layton , Michael Schneier

By analogy with the kinetic theory of gases, most turbulence modeling strate- gies rely on an eddy viscosity to model the unresolved turbulent fluctuations. How- ever, the ratio of unresolved to resolved scales - very much like a degree of…

Fluid Dynamics · Physics 2016-08-24 Marcello Righi

The analytical solutions reported in our previous paper are given as series of hypergeometric or Coulomb wave functions. By using them, we can get the Teukolsky functions analytically in a desired accuracy. For the computation, the deep…

General Relativity and Quantum Cosmology · Physics 2009-10-28 Shuhei Mano , Eiichi Takasugi

This paper puts forth two new closure models for the proper orthogonal decomposition reduced-order modeling of structurally dominated turbulent flows: the dynamic subgrid-scale model and the variational multiscale model. These models, which…

Computational Physics · Physics 2015-05-28 Zhu Wang , Imran Akhtar , Jeff Borggaard , Traian Iliescu