Preconditioning steady-state Navier-Stokes equations with random data

Powell, Catherine E. and Silvester, David J. (2012) Preconditioning steady-state Navier-Stokes equations with random data. SIAM Journal on Scientific Computing (submitted). (Submitted)

[thumbnail of powel_silvester_ns.pdf] PDF
powel_silvester_ns.pdf

Download (1MB)

Abstract

We consider the numerical solution of the steady-state Navier--Stokes equations with uncertain data. Specifically, we treat the case of uncertain viscosity, which results in a flow with an uncertain Reynolds number. After linearization, we apply a stochastic Galerkin finite element method, combining standard inf-sup stable Taylor--Hood approximation on the spatial domain (on highly stretched grids), with orthogonal polynomials in the stochastic parameter. This yields a sequence of non-symmetric saddle-point problems with Kronecker product structure. The novel contribution of this study lies in the construction of efficient block triangular preconditioners for these discrete systems, for use with GMRES. Crucially, the preconditioners are robust with respect to the discretization and statistical parameters, and we exploit existing deterministic solvers based on the so-called Pressure Convection-Diffusion and Least-Squares Commutator approximations.

Item Type: Article
Uncontrolled Keywords: Navier--Stokes equations, random data, stochastic Galerkin method, finite elements, mixed approximation, preconditioning, multigrid, uncertainty quantification.
Subjects: MSC 2010, the AMS's Mathematics Subject Classification > 35 Partial differential equations
MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis
Depositing User: Dr C.E. Powell
Date Deposited: 19 Mar 2012
Last Modified: 20 Oct 2017 14:13
URI: https://eprints.maths.manchester.ac.uk/id/eprint/1792

Actions (login required)

View Item View Item