### Regularisation and Long-Time Behaviour of Random Systems

Schenke A (2020)
Bielefeld: Universität Bielefeld.

Bielefelder E-Dissertation | Englisch

1.11 MB
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Abstract / Bemerkung
In this work, we study several different aspects of systems modelled by partial differential equations (PDEs), both deterministic and stochastically perturbed. The thesis is structured as follows:

Chapter I gives a summary of the contents of this work and illustrates the main results and ideas of the rest of the thesis.

Chapter II is devoted to a new model for the flow of an electrically conducting fluid through a porous medium, the tamed magnetohydrodynamics (TMHD) equations. After a survey of regularisation schemes of fluid dynamical equations, we give a physical motivation for our system. We then proceed to prove existence and uniqueness of a strong solution to the TMHD equations, prove that smooth data lead to smooth solutions and finally show that if the onset of the effect of the taming term is deferred indefinitely, the solutions to the tamed equations converge to a weak solution of the MHD equations.

In Chapter III we investigate a stochastically perturbed tamed MHD (STMHD) equation as a model for turbulent flows of electrically conducting fluids through porous media. We consider both the problem posed on the full space $\R^{3}$ as well as the problem with periodic boundary conditions. We prove existence of a unique strong solution to these equations as well as the Feller property for the associated semigroup. In the case of periodic boundary conditions, we also prove existence of an invariant measure for the semigroup.

The last chapter deals with the long-time behaviour of solutions to SPDEs with locally monotone coefficients with additive L\'{e}vy noise. Under quite general assumptions, we prove existence of a random dynamical system as well as a random attractor. This serves as a unifying framework for a large class of examples, including stochastic Burgers-type equations, stochastic 2D Navier-Stokes equations, the stochastic 3D Leray-$\alpha$ model, stochastic power law fluids, the stochastic Ladyzhenskaya model, stochastic Cahn-Hilliard-type equations, stochastic Kuramoto-Sivashinsky-type equations, stochastic porous media equations and stochastic $p$-Laplace equations.
Jahr
2020
Page URI
https://pub.uni-bielefeld.de/record/2941476

### Zitieren

Schenke A. Regularisation and Long-Time Behaviour of Random Systems. Bielefeld: Universität Bielefeld; 2020.
Schenke, A. (2020). Regularisation and Long-Time Behaviour of Random Systems. Bielefeld: Universität Bielefeld. doi:10.4119/unibi/2941476
Schenke, A. (2020). Regularisation and Long-Time Behaviour of Random Systems. Bielefeld: Universität Bielefeld.
Schenke, A., 2020. Regularisation and Long-Time Behaviour of Random Systems, Bielefeld: Universität Bielefeld.
A. Schenke, Regularisation and Long-Time Behaviour of Random Systems, Bielefeld: Universität Bielefeld, 2020.
Schenke, A.: Regularisation and Long-Time Behaviour of Random Systems. Universität Bielefeld, Bielefeld (2020).
Schenke, Andre. Regularisation and Long-Time Behaviour of Random Systems. Bielefeld: Universität Bielefeld, 2020.
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