Staggered discontinuous Galerkin methods for the incompressible Navier–Stokes equations: Spectral analysis and computational results

• Published in: Numerical linear algebra with applications Vol. 25; no. 5; pp. e2151:1 - n/a
• Main Authors: Dumbser, M., Fambri, F., Furci, I., Mazza, M., Serra‐Capizzano, S., Tavelli, M.
• Format: Journal Article
• Language: English
• Published: Oxford Wiley Subscription Services, Inc 01.10.2018
• Subjects: Approximation; Computational fluid dynamics; Conjugate gradient method; Convergence; Fluid flow; Galerkin method; generating function; GLT analysis; high‐order staggered finite element schemes; Incompressible flow; incompressible Navier–Stokes equations; Iterative methods; Linear systems; Mathematical analysis; matrix sequence; multilevel; Navier-Stokes equations; Numerical analysis; Numerical methods; Preconditioning; Solvers; Spectra; spectral analysis; spectral symbol; staggered semi‐implicit discontinuous Galerkin schemes; Toeplitz matrices (block
• ISSN: 1070-5325; 1099-1506; 1099-1506
• DOI: 10.1002/nla.2151

Summary The goal of this paper is to create a fruitful bridge between the numerical methods for approximating PDEs in fluid dynamics and the (iterative) numerical methods for dealing with the resulting large linear systems. Among the main objectives are the design of new, efficient iterative solvers and a rigorous analysis of their convergence speed. The link we have in mind is either the structure or the hidden structure that the involved coefficient matrices inherit, both from the continuous PDE and from the approximation scheme; in turn, the resulting structure is used for deducing spectral information, crucial for the conditioning and convergence analysis and for the design of more efficient solvers. As a specific problem, we consider the incompressible Navier–Stokes equations; as a numerical technique, we consider a novel family of high‐order, accurate discontinuous Galerkin methods on staggered meshes, and as tools, we use the theory of Toeplitz matrices generated by a function (in the most general block, the multilevel form) and the more recent theory of generalized locally Toeplitz matrix sequences. We arrive at a somehow complete picture of the spectral features of the underlying matrices, and this information is employed for giving a forecast of the convergence history of the conjugate gradient method, together with a discussion on new and more advanced techniques (involving preconditioning, multigrid, multi‐iterative solvers). Several numerical tests are provided and critically illustrated in order to show the validity and the potential of our analysis.