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E-raamat: Mathematics of Two-Dimensional Turbulence

, (Université de Cergy-Pontoise)
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"This book deals with basic problems and questions, interesting for physicists and engineers working in the theory of turbulence. Accordingly Chapters 3-5 (which form the main part of this book) end with sections, where we explain the physical relevance of the obtained results. These sections also provide brief summaries of the corresponding chapters. In Chapters 3 and 4, our main goal is to justify, for the 2D case, the statistical properties of fluid's velocity"--

"This book is dedicated to the mathematical study of two-dimensional statistical hydrodynamics and turbulence, described by the 2D Navier-Stokes system with a random force. The authors' main goal is to justify the statistical properties of a fluid's velocity field u(t,x) that physicists assume in their work. They rigorously prove that u(t,x) converges, as time grows, to a statistical equilibrium, independent of initial data. They use this to study ergodic properties of u(t,x) - proving, in particular, that observables f(u(t,.)) satisfy the strong law of large numbers and central limit theorem. They also discuss the inviscid limit when viscosity goes to zero, normalising the force so that the energy of solutions stays constant, while their Reynolds numbers grow to infinity. They show that then the statistical equilibria converge to invariant measures of the 2D Euler equation and study these measures. The methods apply to other nonlinear PDEs perturbed by random forces"--

Muu info

Presents recent progress in two-dimensional mathematical hydrodynamics, including rigorous results on turbulence in space-periodic fluid flows.
Preface ix
1 Preliminaries
1(35)
1.1 Function spaces
1(4)
1.2 Basic facts from measure theory
5(17)
1.3 Markov processes and random dynamical systems
22(14)
Notes and comments
35(1)
2 Two-dimensional Navier-Stokes equations
36(65)
2.1 Cauchy problem for the deterministic system
36(22)
2.2 Stochastic Navier-Stokes equations
58(4)
2.3 Navier-Stokes equations perturbed by a random kick force
62(7)
2.4 Navier-Stokes equations perturbed by spatially regular white noise
69(18)
2.5 Existence of a stationary distribution
87(6)
2.6 Appendix: some technical proofs
93(8)
Notes and comments
99(2)
3 Uniqueness of stationary measure and mixing
101(72)
3.1 Three results on uniqueness and mixing
104(11)
3.2 Dissipative RDS with bounded kicks
115(11)
3.3 Navier-Stokes system perturbed by white noise
126(15)
3.4 Navier-Stokes system with unbounded kicks
141(4)
3.5 Further results and generalisations
145(14)
3.6 Appendix: some technical proofs
159(9)
3.7 Relevance of the results for physics
168(5)
Notes and comments
169(4)
4 Ergodicity and limiting theorems
173(38)
4.1 Ergodic theorems
173(9)
4.2 Random attractors and stationary distributions
182(20)
4.3 Dependence of a stationary measure on the random force
202(7)
4.4 Relevance of the results for physics
209(2)
Notes and comments
210(1)
5 Inviscid limit
211(34)
5.1 Balance relations
211(7)
5.2 Limiting measures
218(23)
5.3 Relevance of the results for physics
241(4)
Notes and comments
244(1)
6 Miscellanies
245(24)
6.1 3D Navier-Stokes system in thin domains
245(6)
6.2 Ergodicity and Markov selection
251(13)
6.3 Navier-Stokes equations with very degenerate noise
264(5)
Appendix
269(24)
A.1 Monotone class theorem
269(1)
A.2 Standard measurable spaces
270(1)
A.3 Projection theorem
271(1)
A.4 Gaussian random variables
271(3)
A.5 Weak convergence of random measures
274(1)
A.6 The Gelfand triple and Yosida approximation
275(2)
A.7 Ito formula in Hilbert spaces
277(5)
A.8 Local time for continuous Ito processes
282(1)
A.9 Krylov's estimate
283(2)
A.10 Girsanov's theorem
285(1)
A.11 Martingales, submartingales, and supermartingales
286(2)
A.12 Limit theorems for discrete-time martingales
288(1)
A.13 Martingale approximation for Markov processes
289(2)
A.14 Generalised Poincare inequality
291(1)
A.15 Functions in Sobolev spaces with a discrete essential range
292(1)
Solutions to selected exercises 293(11)
Notation and conventions 304(3)
References 307(12)
Index 319
Sergei Kuksin is a Professor in the Centre Mathématiques Laurent Schwartz at École Polytechnique in Palaiseau, France. Armen Shirikyan is a professor in the mathematics department at the University of Cergy-Pontoise (UCP), France, and served as the Head of Department from April 2008 to August 2012. He gained his PhD from Moscow State University in 1995 and his Habilitation thesis from the University of Paris-Sud in 2003. His current research interests are related to the ergodic theory for randomly forced equations of mathematical physics and controllability of nonlinear PDEs.