no code implementations • 27 Jul 2023 • Florian Heyder, Juan Pedro Mellado, Jörg Schumacher
In this work, we present a parametrization for a dry convective boundary layer based on a generative adversarial network.
no code implementations • 26 Feb 2022 • Sandeep Pandey, Philipp Teutsch, Patrick Mäder, Jörg Schumacher
A combined convolutional autoencoder-recurrent neural network machine learning model is presented to analyse and forecast the dynamics and low-order statistics of the local convective heat flux field in a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at Prandtl number ${\rm Pr}=7$ and Rayleigh number ${\rm Ra}=10^7$.
no code implementations • 27 Jan 2021 • Florian Heyder, Jörg Schumacher
The reservoir is subsequently fed by the data and results in predictions of future flow states.
no code implementations • 26 Oct 2020 • Philipp P. Vieweg, Janet D. Scheel, Jörg Schumacher
Turbulent convection processes in nature are often found to be organized in a hierarchy of plume structures and flow patterns.
Fluid Dynamics Solar and Stellar Astrophysics
no code implementations • 28 Jan 2020 • Sandeep Pandey, Jörg Schumacher
Reservoir computing is applied to model the large-scale evolution and the resulting low-order turbulence statistics of a two-dimensional turbulent Rayleigh-B\'{e}nard convection flow at a Rayleigh number ${\rm Ra}=10^7$ and a Prandtl number ${\rm Pr}=7$ in an extended domain with an aspect ratio of 6.