Repeated Richardson extrapolation applied to the two-dimensional Laplace equation using triangular and square grids

• Published in: Applied mathematical modelling Vol. 37; no. 7; pp. 4661 - 4675
• Main Authors: Marchi, C.H., Araki, L.K., Alves, A.C., Suero, R., Gonçalves, S.F.T., Pinto, M.A.V.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-04-2013
• Subjects: Dirichlet problem; Discretization; Discretization error; Errors; Extrapolation; Finite volume; Laplace equation; Mathematical analysis; Mathematical models; Order of accuracy; Richardson extrapolation; Triangular grid; Two dimensional; Verification; Triangular grid; Richardson extrapolation; Verification; Finite volume; Discretization error; Order of accuracy
• ISSN: 0307-904X
• DOI: 10.1016/j.apm.2012.09.071

The focus of this work is to verify the efficiency of the Repeated Richardson Extrapolation (RRE) to reduce the discretization error in a triangular grid and to compare the result to the one obtained for a square grid for the two-dimensional Laplace equation. Two different geometries were employed: the first one, a unitary square domain, was discretized into a square or triangular grid; and the second, a half square triangle, was discretized into a triangular grid. The methodology employed used the following conditions: the finite volume method, uniform grids, second-order accurate approximations, several variables of interest, Dirichlet boundary conditions, grids with up to 16,777,216 nodes for the square domain and up to 2097,152 nodes for the half square triangle domain, multigrid method, double precision, up to eleven Richardson extrapolations for the first domain and up to ten Richardson extrapolations for the second domain. It was verified that (1) RRE is efficient in reducing the discretization error in a triangular grid, achieving an effective order of approximately 11 for all the variables of interest for the first geometry; (2) for the same number of nodes and with or without RRE, the discretization error is smaller in a square grid than in a triangular grid; and (3) the magnitude of the numerical error reduction depends on, among other factors, the variable of interest and the domain geometry.