Search arXivSearch

arXiv · 2103.03474

Delayed singularity formation for the three dimensional compressible Euler equations with non-zero vorticity

Abstract

For the 3D compressible isentropic Euler equations with an initial perturbation of size $\ve$ of a rest state, if the initial vorticity is of size $\dl$ with $0<\dl\le \ve$ and $\ve$ is small, we establish that the lifespan of the smooth solutions is $T_{\dl}=O(\min\{e^\frac{1}{\ve},\frac{1}δ\})$ for the polytropic gases, and $T_{\dl}=O(\frac{1}δ)$ for the Chaplygin gases. For example, when $\dl=e^{-\f{1}{\ve^2}}$ is chosen, then $T_{\dl}=O(e^{\f{1}{\ve}})$ for the polytropic gases and $T_{\dl}=O(e^{\f{1}{\ve^2}})$ for the Chaplygin gases although the perturbations of the initial density and the divergence of the initial velocity are only of order $O(\ve)$. Our result illustrates that the time of existence of smooth solutions depends crucially on the size of the vorticity of the initial data, as long as the initial data is sufficiently close to a constant. The main ingredients in the paper are: introducing some suitably weighted energies, deriving the pointwise space-time decay estimates of solutions, looking for the good unknown instead of the velocity, and establishing the required weighted estimates on the vorticty.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fei Hou, Huicheng Yin. 2021-03-05. Delayed singularity formation for the three dimensional compressible Euler equations with non-zero vorticity. https://doi.org/10.1112/jlms.12642

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Two-layers neural networks for Schr{ö}dinger eigenvalue problems

The aim of this article is to analyze numerical schemes using two-layer neural networks with infinite width for the resolution of high-dimensional Schr{ö}dinger eigenvalue problems with smooth interaction potentials and Neumann boundary condition on the unit cube in any dimension. More precisely, any eigenfunction associated to the lowest eigenvalue of the Schr{ö}dinger operator is a unit L 2 norm minimizer of the associated energy. Using Barron's representation of the solution with a probability measure defined on the set of parameter values and following the approach initially suggested by Bach and Chizat [1], the energy is minimized thanks to a constrained gradient curve dynamic on the 2-Wasserstein space of the set of parameter values defining the neural network. We prove the existence of solutions to this constrained gradient curve. Furthermore, we prove that, if it converges, the represented function is then an eigenfunction of the considered Schr{ö}dinger operator. At least up to our knowledge, this is the first work where this type of analysis is carried out to deal with the minimization of non-convex functionals.

math.AP

Validity of Prandtl Expansion for Steady Compressible Navier-Stokes-Fourier Flows

Assume no-slip boundary conditions for the velocity field and either insulated or Dirichlet boundary conditions for the temperature field in a steady compressible fluid. In the inviscid limit $\v \rightarrow 0$, we develop a mathematical framework for the uniform-in-$\v$ remainder estimate for the linear steady compressible Navier-Stokes-Fourier equations around a Prandtl layer profile with both velocity and thermal layers, which leads to the validity of the Prandtl layer expansion.

math.AP

Long time behaviour of Mean Field Games with fractional diffusion

In this paper we study the long time behaviour of mean field games systems with fractional diffusion, modeling the case that the individual dynamics of the players is driven by independent jump processes and controlled through the drift term, while being confined by an external field in order to guarantee ergodicity. In the case of globally Lipschitz, locally uniformly convex Hamiltonian, and weakly coupled costs satisfying the Lasry-Lions monotonicity condition, we prove that there is a unique solution $(u_T,m_T)$ to the mean field game problem in $(0,T)$ and we show that, if $T$ is sufficiently large, $(u_T,m_T)$ satisfies the so-called turnpike property, namely it is exponentially close to the (unique) stationary ergodic state for any proportionally long intermediate time.

math.AP