activity
20182024
most citedUnsteady aerodynamic effects in small-amplitude pitch oscillations of an airfoil

56 citations · 128 across the 13 of their papers we have counts for

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17 papers · 1 filter

physics.flu-dyn2022

The effect of wing-tip vortices on the flow around a NACA0012 wing

Siavash Toosi, Adam Peplinski, Philipp Schlatter +1

The goal of the present work is to perform a systematic study of the formation of wing-tip vortices and their interaction with and impact on the surrounding flow in more details. O…

physics.flu-dyn20222 cited

Predicting the temporal dynamics of turbulent channels through deep learning

Giuseppe Borrelli, Luca Guastoni, Hamidreza Eivazi +2

The success of recurrent neural networks (RNNs) has been demonstrated in many applications related to turbulence, including flow control, optimization, turbulent features reproduct…

physics.flu-dyn2022

On the generation and destruction mechanisms of arch vortices in urban fluid flows

Eneko Lazpita, Álvaro Martínez-Sánchez, Adrián Corrochano +3

Studying and interpreting the different flow patterns present in urban areas is becoming essential since they help develop new approaches to fight climate change through an improve…

physics.flu-dyn2021

Towards adaptive simulations of turbulent wings at high Reynolds numbers

F. Mallor, Á. Tanarro, N. Offermans +3

Adaptive mesh refinement (AMR) in the high-order spectral-element method code Nek5000 is demonstrated and validated with well-resolved large-eddy simulations (LES) of the flow past…

physics.flu-dyn20217 cited

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…

physics.flu-dyn202022 cited

Convolutional-network models to predict wall-bounded turbulence from wall quantities

L. Guastoni, A. Güemes, A. Ianiro +4

Two models based on convolutional neural networks are trained to predict the two-dimensional velocity-fluctuation fields at different wall-normal locations in a turbulent open chan…