51 citations · 109 across the 9 of their papers we have counts for
8 papers · 1 filter
Assessment of non-intrusive sensing in wall-bounded turbulence through explainable deep learning
A. Cremades, R. Freibergs, S. Hoyas +3
In this work we present a framework to explain the prediction of the velocity fluctuation at a certain wall-normal distance from wall measurements with a deep-learning model. For t…
Instantaneous convective heat transfer at the wall: a depiction of turbulent boundary layer structures
Firoozeh Foroozan, Andrea Ianiro, Stefano Discetti +1
We demonstrate the ability to experimentally measure fluctuations of the convective heat transfer coefficient at the wall in a turbulent boundary layer. For this, we measure two-di…
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…
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.…
Machine learning flow control with few sensor feedback and measurement noise
R. Castellanos, G. Y. Cornejo Maceda, I. de la Fuente +3
A comparative assessment of machine learning (ML) methods for active flow control is performed. The chosen benchmark problem is the drag reduction of a two-dimensional Kármán vorte…
Predicting the near-wall region of turbulence through convolutional neural networks
A. G. Balasubramanian, L. Guastoni, A. Güemes +5
Modelling the near-wall region of wall-bounded turbulent flows is a widespread practice to reduce the computational cost of large-eddy simulations (LESs) at high Reynolds number. A…