activity
20202026
most citedFrom coarse wall measurements to turbulent velocity fields through deep learning

132 citations · 329 across the 25 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

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★ 5 cited

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 estima…

physics.flu-dyn2024★ 23 cited

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.…

physics.data-an2024★ 3 cited

A meshless method to compute the proper orthogonal decomposition and its variants from scattered data

Iacopo Tirelli, Miguel Alfonso Mendez, Andrea Ianiro +1

Complex phenomena can be better understood when broken down into a limited number of simpler "components". Linear statistical methods such as the principal component analysis and i…

physics.flu-dyn2024★ 7 cited

Actuation manifold from snapshot data

Luigi Marra, Guy Y. Cornejo Maceda, Andrea Meilán-Vila +5

We propose a data-driven methodology to learn a low-dimensional manifold of controlled flows. The starting point is resolving snapshot flow data for a representative ensemble of ac…