%0 Conference Paper
%A John, Chelsea Maria
%A Herten, Andreas
%A Kesselheim, Stefan
%A Ruprecht, Daniel
%T Harnessing Fourier Neural Operator For Rayleigh–Bénard Convection
%I TUHH
%M FZJ-2024-04967
%D 2024
%X Rayleigh-Bénard convection, is a classic fluid dynamics problem, with applications in geophysical, astrophysical, and industrial flows. Fourier Neural Operator (FNO) leverages neural networks and Fourier analysis to efficiently model spatiotemporal dynamics in fluid systems, offering a promising avenue for accurate and scalable simulations. In this poster, first results on the application of FNO for tackling the Rayleigh-Benard convection equations is presented.
%B PhysML Workshop 2024
%C 14 May 2024 - 16 May 2024, Oslo (Norway)
Y2 14 May 2024 - 16 May 2024
M2 Oslo, Norway
%F PUB:(DE-HGF)24
%9 Poster
%R 10.34734/FZJ-2024-04967
%U https://juser.fz-juelich.de/record/1029111