A deep learning approximation of non-stationary solutions to wave kinetic equations

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Detail(s)

Original languageEnglish
Pages (from-to)213-226
Journal / PublicationApplied Numerical Mathematics
Volume199
Online published23 Dec 2022
Publication statusPublished - May 2024

Abstract

We present a deep learning approximation, stochastic optimization based, method for wave kinetic equations. To build confidence in our approach, we apply the method to a Smoluchowski coagulation equation with multiplicative kernel for which an analytic solution exists. Our deep learning approach is then used to approximate the non-stationary solution to a 3-wave kinetic equation corresponding to acoustic wave systems. To validate the neural network approximation, we compare the decay rate of the total energy with previously obtained theoretical results. A finite volume solution is presented and compared with the present method.

Research Area(s)

  • 3-wave equation, Deep learning, Function approximation, Partial differential equations, Stochastic optimization, Wave turbulence

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