Numerical and convergence analysis of the stochastic Lagrangian averaged Navier-Stokes equations

Jad Doghman (1) , Ludovic Goudenège (1)

1 Fédération de Mathématiques de CentraleSupélec

The primary emphasis of this work is the development of a finite element based space-time discretization for solving the stochastic Lagrangian averaged Navier-Stokes (LANS-α) equations of incompressible fluid turbulence with multiplicative random forcing, under nonperiodic boundary conditions within a bounded polygonal (or polyhedral) domain of R^d , d ∈ {2, 3}. The convergence analysis of a fully discretized numerical scheme is investigated and split into two cases according to the spacial scale α, namely we first assume α to be controlled by the step size of the space discretization so that it vanishes when passing to the limit, then we provide an alternative study when α is fixed. A preparatory analysis of uniform estimates in both α and discretization parameters is carried out. Starting out from the stochastic LANS-α model, we achieve convergence toward the continuous strong solutions of the stochastic Navier-Stokes equations in 2D when α vanishes at the limit. Additionally, convergence toward the continuous strong solutions of the stochastic LANS-α model is accomplished if α is fixed.

Mots clés: stochastic Lagrangian averaged Navier-Stokes; stochastic Navier-Stokes; finite element; Euler method

Domaines: Mécanique des fluides [physics.class-ph]; Modélisation et simulation; Analyse numérique [cs.NA]; Equations aux dérivées partielles [math.AP]; Probabilités [math.PR]

Jad Doghman, Ludovic Goudenège. Numerical and convergence analysis of the stochastic Lagrangian averaged Navier-Stokes equations. Journal of Computational and Applied Mathematics, 2022, ⟨10.1016/j.cam.2022.114446⟩. ⟨hal-03406041v3⟩