Understanding the impact of model error on data assimilation is an important practical topic.
Model error in the subgrid scale is commonly seen in various applications as a natural …

The aim of this paper is to describe a turbulence model for the particle method Smoothed
Particle Hydrodynamics (SPH). The model makes few assumptions, conserves linear and …

Abstract The Navier-Stokes-Voigt (NSV) model of viscoelastic incompressible fluid has been
recently proposed as a regularization of the 3D Navier-Stokes equations for the purpose of …

Data assimilation is a methodology to estimate weather or ocean variables by combining
(synchronizing) information from observational data with a numerical dynamical (forecast) …

We consider a general family of regularized Navier–Stokes and Magnetohydrodynamics
(MHD) models on n-dimensional smooth compact Riemannian manifolds with or without …

In this paper, we investigate the advantages of the 2D Navier–Stokes–Voight (NSV)
turbulence model for use in algorithms and explore its limits in the context of image …

Rates of convergence of solutions of various two-dimensional α-regularization models,
subject to periodic boundary conditions, toward solutions of the exact Navier–Stokes …

Inviscid regularization modeling of turbulent flow is investigated. Homogeneous, isotropic,
decaying turbulence is simulated at a range of filter widths. A coarse-graining of turbulent …

In this paper we prove the existence of an inertial manifold, ie, a globally invariant,
exponentially attracting, finite-dimensional smooth manifold, for two different subgrid-scale α …

The present work extends Kolmogorov's micro-scales to a large family of viscoplastic fluids.
The new micro-scales, combined with Gioia and Chakaborty's (2006) friction …