4 papers
Deep Reinforcement Learning Discovers a Novel Control Algorithm for Mitigating Flow-Induced Vibrations in Underactuated Tandem Cylinders
Hussam Sababha, Mohammed Daqaq
This study presents the first experimental implementation of deep reinforcement learning (DRL) for the active real-time suppression of flow-induced vibrations in simultaneously vib…
Deep Reinforcement Learning in Action: Real-Time Control of Vortex-Induced Vibrations
Hussam Sababha, Bernat Font, Mohammed Daqaq
This study showcases an experimental deployment of deep reinforcement learning (DRL) for active flow control (AFC) of vortex-induced vibrations (VIV) in a circular cylinder at a hi…
Casting Computational Fluid Mechanics into a Convex Quadratic Optimization Framework
Hussam Sababha, Haithem Taha, Mohammed Daqaq
We employ the principle of minimum pressure gradient to transform problems in unsteady computational fluid dynamics (CFD) into a convex optimization framework subject to linear con…
A Variational Computational-based Framework for Unsteady Incompressible Flows
H. Sababha, A. Elmaradny, H. Taha +1
Advancements in computational fluid mechanics have largely relied on Newtonian frameworks, particularly through the direct simulation of Navier-Stokes equations. In this work, we p…