PINNs for Parametric Incompressible Newtonian Flows
Palavras-chave:
PINNs, Incompressible Flows, Parametric PDEsResumo
In this paper we demonstrate the application of Physics-Informed Neural Networks (PINNs) for learning
the solution of the parametric steady incompressible Navier-Stokes equations for multiple flow regimes for the
well-known channel-driven cavity flow problem, given only the geometry and boundary conditions.
