Abstract:
The main subject of this thesis is to analyse various discretisations schemes for the stochastic Navier-Stokes equations on bounded two and three dimensional domains.
The motivation for this numerical analysis is twofold: First this is an important model problem which combines algebraic constraints, non-Lipschitz nonlinearity, and stochastic forcing. The methods developed for this model problem may be applied to a wide range of nonlinear stochastic partial differential equations driven by a Wiener noise. Second, these methods may be used in applications. Such a system has been introduced to better understand turbulence phenomena, well posedness of the deterministic problem and random fluctuations in hydrodynamic models. It may be used to model relevant physical phenomena, such as turbulence.
In the first part of this thesis, we address the finite element based approximation of weak martingale solutions in two and three dimensions, i.e., a system consisting of a filtered probability space, a Wiener process on it, and a solution to the equations. The discretisation is conceived such that all the elements of the system are constructed using continuous perturbations of the discrete iterates, and convergence without rates for subsequences of approximating solutions is proved. Moreover we show the same convergence properties for a scheme which uses general random variables to approximate the time increments of the stochastic forcing. In the two-dimensional case, thanks to a local monotonicity argument, the same scheme with Wiener process increments is shown to produce iterates that converge towards the unique strong solution.
In the second part of this thesis, we study the convergence properties of projection based splitting schemes applied to the unsteady stochastic Stokes equations. In this simplified setting, we observe that the Lagrange multiplier affects the convergence behavior of the scheme, due to its irregularity This motivates the introduction of a new discretisation scheme, which is stable under this irregularity. Finite element discretisations are also considered, and their convergence proved.
In the third part of the thesis, we consider implicit Euler based approximation schemes for the two-dimensional stochastic Navier-Stokes equations with periodic boundary conditions, and study convergence with rates. Due to the non-Lipschitz character of the nonlinearity, we prove convergence only on a set with probability arbitrarily close to one for the proposed schemes in a general setting. However, for additive noise we show convergence on the whole realisation space for the time discretisation. Finite element approximations for the corresponding time discretisations are considered, and convergence analysed.
All the parts are concluded with simulations to illustrate the convergence results, and compare the efficiency of the different discretisations.