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 …

In order to improve the dynamics and stability of the POD-Galerkin models of strongly-stiff
systems, an α-like regularization is suggested and assessed in the present article. In this …

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 …

It was recently proven in Case et al.(2010)[2] that, under mild restrictions, grad-div stabilized
Taylor–Hood solutions of Navier–Stokes problems converge to the Scott–Vogelius solution …

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 …

State-of-the-art global ocean circulation models used in climate studies are only passing the
edge of becoming “eddy-permitting” or barely eddy-resolving. Such models commonly suffer …

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