Your browser doesn't support javascript.
loading
Asymptotic Self-Similar Blow-Up Profile for Three-Dimensional Axisymmetric Euler Equations Using Neural Networks.
Wang, Y; Lai, C-Y; Gómez-Serrano, J; Buckmaster, T.
Afiliação
  • Wang Y; Department of Geosciences, Princeton University, Princeton, New Jersey 08544, USA.
  • Lai CY; Department of Geosciences, Princeton University, Princeton, New Jersey 08544, USA.
  • Gómez-Serrano J; Department of Mathematics, Brown University, Kassar House, 151 Thayer Street, Providence, Rhode Island 02912, USA.
  • Buckmaster T; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Gran Via de les Corts Catalanes, 585, 08007, Barcelona, Spain.
Phys Rev Lett ; 130(24): 244002, 2023 Jun 16.
Article em En | MEDLINE | ID: mdl-37390436
Whether there exist finite-time blow-up solutions for the 2D Boussinesq and the 3D Euler equations are of fundamental importance to the field of fluid mechanics. We develop a new numerical framework, employing physics-informed neural networks, that discover, for the first time, a smooth self-similar blow-up profile for both equations. The solution itself could form the basis of a future computer-assisted proof of blow-up for both equations. In addition, we demonstrate physics-informed neural networks could be successfully applied to find unstable self-similar solutions to fluid equations by constructing the first example of an unstable self-similar solution to the Córdoba-Córdoba-Fontelos equation. We show that our numerical framework is both robust and adaptable to various other equations.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Física / Redes Neurais de Computação Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Física / Redes Neurais de Computação Idioma: En Ano de publicação: 2023 Tipo de documento: Article