A numerical study of compact approximations based on flat integrated radial basis functions for second-order differential equations. (November 2016)

• Record Type: Journal Article
• Authors: Tien, C.M.T.; Mai-Duy, N.; Tran, C.-D.; Tran-Cong, T.
• Is Part Of: Computers & mathematics with applications. Volume 72:issue 9(2016)
• Page Start: 2364
• Page End: 2387
• Publication Date: 2016-11
• Subjects: RBF -- Integrated RBF -- Shape parameter -- Ill-conditioning -- ODE -- PDE; Electronic data processing -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.28541
• DOI: 10.1016/j.camwa.2016.09.001
• Languages: English
• ISSNs: 0898-1221

Abstract

Abstract: In this paper, we propose a simple but effective preconditioning technique to improve the numerical stability of Integrated Radial Basis Function (IRBF) methods. The proposed preconditioner is simply the inverse of a well-conditioned matrix that is constructed using non-flat IRBFs. Much larger values of the free shape parameter of IRBFs can thus be employed and better accuracy for smooth solution problems can be achieved. Furthermore, to improve the accuracy of local IRBF methods, we propose a new stencil, namely Combined Compact IRBF (CCIRBF), in which (i) the starting point is the fourth-order derivative; and (ii) nodal values of first- and second-order derivatives at side nodes of the stencil are included in the computation of first- and second-order derivatives at the middle node in a natural way. The proposed stencil can be employed in uniform/nonuniform Cartesian grids. The preconditioning technique in combination with the CCIRBF scheme employed with large values of the shape parameter are tested with elliptic equations and then applied to simulate several fluid flow problems governed by Poisson, Burgers, convection–diffusion, and Navier–Stokes equations. Highly accurate and stable solutions are obtained. In some cases, the preconditioned schemes are shown to be several orders of magnitude more accurate than those without preconditioning.