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Spatial Profiles in the Singular Solutions of the 3D Euler Equations and Simplified Models


Liu, Pengfei (2017) Spatial Profiles in the Singular Solutions of the 3D Euler Equations and Simplified Models. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9V9862G.


The partial differential equations (PDE) governing the motions of incompressible ideal fluid in three dimensional (3D) space are among the most fundamental nonlinear PDEs in nature and have found a lot of important applications. Due to the presence of super-critical non-linearity, the fundamental question of global well-posedness still remains open and is generally viewed as one of the most outstanding open questions in mathematics. In this thesis, we investigate the potential finite-time singularity formation of the 3D Euler equations and simplified models by studying the self-similar spatial profiles in the potentially singular solutions.

In the first part, we study the self-similar singularity of two 1D models, the CKY model and the HL model, which approximate the dynamics of the 3D axisymmtric Euler equations on the solid boundary of a cylindrical domain. The two models are both numerically observed to develop self-similar singularity. We prove the existence of a discrete family of self-similar profiles for the CKY model, using a combination of analysis and computer-aided verification. Then we employ a dynamic rescaling formulation to numerically study the evolution of the spatial profiles for the two 1D models, and demonstrate the stability of the self-similar singularity. We also study a singularity scenario for the HL model with multi-scale feature.

In the second part, we study the self-similar singularity for the 3D axisymmetric Euler equations. We first prove the local existence of a family of analytic self-similar profiles using a modified Cauchy-Kowalevski majorization argument. Then we use the dynamic rescaling formulation to investigate two types of initial data with different leading order properties. The first initial data correspond to the singularity scenario reported by Luo and Hou. We demonstrate that the self-similar profiles enjoy certain stability, which confirms the finite-time singularity reported by Luo and Hou. For the second initial data, we show that the solutions develop singularity in a different manner from the first case, which is unknown previously. The spatial profiles in the solutions become singular themselves, which means that the solutions to the Euler equations develop singularity at multiple spatial scales.

In the third part, we propose a family of 3D models for the 3D axisymmetric Euler and Navier-Stokes equations by modifying the amplitude of the convection terms. The family of models share several regularity results with the original Euler and Navier-Stokes equations, and we study the potential finite-time singularity of the models numerically. We show that for small convection, the solutions of the inviscid model develop self-similar singularity and the profiles behave like travelling waves. As we increase the amplitude of the velocity field, we find a critical value, after which the travelling wave self-similar singularity scenario disappears. Our numerical results reveal the potential stabilizing effect the convection terms.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Euler Equations, Finite-time Singularity, Self-similar, Simplified Models
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Applied And Computational Mathematics
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Hou, Thomas Y.
Thesis Committee:
  • Hou, Thomas Y. (chair)
  • Bruno, Oscar P.
  • Meiron, Daniel I.
  • Owhadi, Houman
Defense Date:22 August 2016
Non-Caltech Author Email:pengfeiliuc (AT)
Record Number:CaltechTHESIS:09092016-000915850
Persistent URL:
Liu, Pengfei0000-0002-6714-7387
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9920
Deposited By: Pengfei Liu
Deposited On:19 Sep 2016 21:43
Last Modified:04 Oct 2019 00:14

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