1 citations · 1 across the 1 of their papers we have counts for
2 papers
physics.flu-dyn2026★ 1 cited
Collapse of turbulence in optimised curved pipe flow
Eman Bagheri, Stefan Becker, Philipp Schlatter
The increased friction caused by turbulence is a significant contributor to energy consumption in the fluid-transport and piping industries. Here we describe a passive approach to…
physics.flu-dyn2024
Fully convolutional networks for velocity-field predictions based on the wall heat flux in turbulent boundary layers
L. Guastoni, A. G. Balasubramanian, F. Foroozan +6
Fully-convolutional neural networks (FCN) were proven to be effective for predicting the instantaneous state of a fully-developed turbulent flow at different wall-normal locations…