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From the 2 of 27 linked papers with an AI index.

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20242026
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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…

physics.flu-dyn2024

Machine-learned flow estimation with sparse data -- exemplified for the rooftop of a UAV vertiport

Chang Hou, Luigi Marra, Guy Y. Cornejo Maceda +9

We propose a physics-informed data-driven framework for urban wind estimation. This framework validates and incorporates the Reynolds number independence for flows under various wo…

physics.flu-dyn2024

Measuring time-resolved heat transfer fluctuations on a heated-thin foil in a turbulent channel airflow

Antonio Cuéllar, Enrico Amico, Jacopo Serpieri +4

We present an experimental setup to perform time-resolved convective heat transfer measurements in a turbulent channel flow with air as the working fluid. We employ a heated thin f…

physics.flu-dyn2024

Some effects of limited wall-sensor availability on flow estimation with 3D-GANs

Antonio Cuéllar, Andrea Ianiro, Stefano Discetti

In this work we assess the impact of the limited availability of wall-embedded sensors on the full 3D estimation of the flow field in a turbulent channel with Reτ = 200. The estim…

physics.flu-dyn2024

Three-dimensional generative adversarial networks for turbulent flow estimation from wall measurements

Antonio Cuéllar, Alejandro Güemes, Andrea Ianiro +3

Different types of neural networks have been used to solve the flow sensing problem in turbulent flows, namely to estimate velocity in wall-parallel planes from wall measurements.…