157 citations · 211 across the 10 of their papers we have counts for
18 papers
Inverse Problems with Diffusion Models: A MAP Estimation Perspective
Sai Bharath Chandra Gutha, Ricardo Vinuesa, Hossein Azizpour
Inverse problems have many applications in science and engineering. In Computer vision, several image restoration tasks such as inpainting, deblurring, and super-resolution can be…
Characteristics of active and inactive motions in high-Reynolds-number turbulent boundary layers
Rahul Deshpande, Ricardo Vinuesa, Ivan Marusic
Wall-scaled (attached) eddies play a significant role in the overall drag experienced in high-Reynolds-number turbulent boundary layers (TBLs). This study aims to delve into the un…
Active flow control of a turbulent separation bubble through deep reinforcement learning
Bernat Font, Francisco Alcántara-Ávila, Jean Rabault +2
The control efficacy of classical periodic forcing and deep reinforcement learning (DRL) is assessed for a turbulent separation bubble (TSB) at on the upstream region be…
Linear and nonlinear Granger causality analysis of turbulent duct flows
Barbara Lopez-Doriga, Marco Atzori, Ricardo Vinuesa +3
This research focuses on the identification and causality analysis of coherent structures that arise in turbulent flows in square and rectangular ducts. Coherent structures are fir…
Perspectives on predicting and controlling turbulent flows through deep learning
Ricardo Vinuesa
The current revolution in the field of machine learning (ML) is leading to many interesting developments in a wide range of areas, including fluid mechanics. Here we review recent…
Optimizing Flow Control with Deep Reinforcement Learning: Plasma Actuator Placement around a Square Cylinder
Mustafa Z Yousif, Kolesova Paraskovia, Yifang Yang +5
The present study proposes an active flow control (AFC) approach based on deep reinforcement learning (DRL) to optimize the performance of multiple plasma actuators on a square cyl…