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Proper Generalized Decomposition method for incompressible Navier-Stokes equations with a spectral discretization

Abstract : Proper Generalized Decomposition (PGD) is a method which consists in looking for the solution to a problem in a separate form. This approach has been increasingly used over the last few years to solve mathematical problems. The originality of this work consists in the association of PGD with a spectral collocation method to solve transfer equations as well as Navier-Stokes equations. In the first stage, the PGD method and its association with spectral discretization is detailed. This approach was tested for several problems: the Poisson equation, the Darcy problem, Navier-Stokes equations (the Taylor Green problem and the lid-driven cavity). In the Navier-Stokes problems, the coupling between velocity and pressure was performed using a fractional step scheme and a PN--PN-2 discretization. For all problems considered, the results from PGD simulations were compared with those obtained by a standard solver and/or with the results found in the literature. The simulations performed showed that PGD is as accurate as standard solvers. PGD preserves the spectral behavior of the errors in velocity and pressure when the time step or the space step decreases. Moreover, for a given number of discretization nodes, PGD is faster than the standard solvers.
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Antoine Dumon, Cyrille Allery, Amine Ammar. Proper Generalized Decomposition method for incompressible Navier-Stokes equations with a spectral discretization. Applied Mathematics and Computation, Elsevier, 2013, 219 (15), pp.8145-8162. ⟨10.1016/j.amc.2013.02.022⟩. ⟨hal-01062396⟩



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