Construction of the radial basis function finite difference methods and their application to problems with arbitrary domain

Authors
Abstract
In this paper we, obtain the weight of radial basis finite difference formula for some differential operators. These weights are used to obtain the local truncation error in powers of the inter-node distance and the shape parameter of radial basis functions. We show that for each difference formula, there is a value of the shape parameter for which RBF-FD formulas are more accurate than the corresponding standard FD formulas. We apply these formulas for Poisson equation with irregular domains and show that the proposed method can be used as a fully meshfree methods.
Keywords

1. Fasshauer G.E. (2007). Meshfree Approximation Methods with MATLAB, World Scientific Publishing Co., Singapore.

2. Bayona, V., et al. (2010). RBF-FD formulas and convergence properties, Journal of Computational Physics, 229 (22), 8281-8295.

3. Golbabai, A. and Mohebianfar E. (2017). A new method for evaluating options based on multiquadric RBF-FD method, Applied Mathematics and Computation, 308, 130-141.

4. Davydov, O. and Dang T.O. (2011). On the optimal shape parameter for Gaussian radial basis function finite difference approximation of the Poisson equation, Computers & Mathematics with Applications, 62 (5), 2143-2161.

5. Flyer, N., Gregory A.B. and Louis J.W. (2016). Enhancing finite differences with radial basis functions: experiments on the Navier–Stokes equations, Journal of Computational Physics, 316, 39-62.

6. Barfeie, M., Soheili, A.R. and Arab Ameri M. (2013). Application of variational mesh generation approach for selecting centers of radial basis functions collocation method, Engineering Analysis with Boundary Elements, 37(12), 1567-1575.

7. Bayona, V., Miguel M. and Manuel K. (2012). Gaussian RBF-FD weights and its corresponding local truncation errors, Engineering Analysis with Boundary Elements, 36(9), 1361-1369.

8. Bayona V., Moscoso M., Carretero M., Kindelan M. (2010). RBF-FD formulas and convergence properties, Journal of Computational Physics, 229(82), 81–95.

9. Soleymani, F., Barfeie M. and Khaksar Haghani F. (2018). Inverse multi-quadric RBF for computing the weights of FD method: Application to American options, Communications in Nonlinear Science and Numerical Simulation, 64, 74-88.

10. Wright G.B., Fornberg B., (2006). Scattered node compact finite difference-type formulas generated from radial basis functions, Journal of Computational Physics, 212, 99-123.

11. Wang, J.G., and Liu G.R. (2002). On the optimal shape parameters of radial basis functions used for 2-D meshless methods, Computer Methods in Applied Mechanics and Engineering, 191(23), 2611-2630.

12. S. Sabermahani, Y. Ordokhani, S.A. Yousefi, Numerical approach based on fractional-order Lagrange polynomials for solving a class of fractional differential equations, Comp. Appl. Math., 37 (2018), 3846-386

13. S. Sabermahani, Y. Ordokhani, S.‑A. Yousefi, Fractional‑order Fibonacci‑hybrid functions approach for solving fractional delay differential equations, Engineering with Computers, 36 (2020), 795-806.

14. S. Sabermahani, Y. Ordokhani, S.A. Yousefi, Fractional-order general Lagrange scaling functions and their applications, BIT Numerical Mathematics, 60 (2020), 101-128.

15. S. Sabermahani, Y. Ordokhani, S.A. Yousefi, Two-dimensional Müntz–Legendre hybrid functions: theory and applications for solving fractional-order partial differential equations, Computational and Applied Mathematics, 39 (2020), Art. ID: 111.