2 papers
physics.flu-dyn2024
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…
physics.flu-dyn2024
Minimizing Nature's Cost: Exploring Data-Free Physics-Informed Neural Network Solvers for Fluid Mechanics Applications
Abdelrahman Elmaradny, Ahmed Atallah, Haithem Taha
In this paper, we present a novel approach for fluid dynamic simulations by harnessing the capabilities of Physics-Informed Neural Networks (PINNs) guided by the newly unveiled pri…