2021
DOI: 10.1007/s10884-020-09939-z
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Strange Attractors for Oberbeck–Boussinesq Model

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Cited by 6 publications
(4 citation statements)
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“…This property implies that semiflows can generate all structurally stable dynamics (up to orbital topological equivalency). Among the systems enjoying UDA, there are a number of fundamental ones: quasilinear parabolic equations 26 , 36 , time-continuous and time-recurrent neural networks 37 , a large class of reaction-diffusion systems with heterogeneous sources 9 , generalized Lotka-Volterra system 38 , Oberbeck-Boussinesq model 39 . Also, the Euler equations on multidimensional manifolds exhibit similar properties 32 .…”
Section: Methodsmentioning
confidence: 99%
“…This property implies that semiflows can generate all structurally stable dynamics (up to orbital topological equivalency). Among the systems enjoying UDA, there are a number of fundamental ones: quasilinear parabolic equations 26 , 36 , time-continuous and time-recurrent neural networks 37 , a large class of reaction-diffusion systems with heterogeneous sources 9 , generalized Lotka-Volterra system 38 , Oberbeck-Boussinesq model 39 . Also, the Euler equations on multidimensional manifolds exhibit similar properties 32 .…”
Section: Methodsmentioning
confidence: 99%
“…In more flexible spaces than the Euclidean 3-dimensional one, let us mention the work [TdL21] of Torres de Lizaur who constructed an embedding of any smooth flow into the time-dependent evolution of the Euler PDE on high-dimensional Riemannian manifolds. See also [Vak21] for other embedding results in the context of the Oberbeck-Boussinesq model of the Navier-Stokes equations (on 2-dimensional domains) with external parameters (a space-dependent external force and heat source).…”
Section: Contributions To the State Of The Art On Complexity Of Stead...mentioning
confidence: 99%
“…The main idea to simplify the formula (31) for G i is as follows. Suppose that the kinks oscillate at certain fixed points Xj , i.e., X i (t) = Xi + Xi (t), (32) where Xi are new unknowns.…”
Section: Hopfield Systemmentioning
confidence: 99%
“…Such approach was used for finite dimensional systems (see [28]), but it can be extended on infinite dimensional evolution equations. This RVF approach is developed by first P. Poláčik to prove existence of non-trivial large time behaviour for quasilinear parabolic equations (see [29,30]) and developed in [12,24] for reaction-diffusion systems, in [18] for neural networks and in [31] for weakly compressible Navier-Stokes equations.…”
Section: Appendix Realisation Of Vector Fields (Rvf)mentioning
confidence: 99%