Localized Meshfree Methods for Solving 3D-Helmholtz Equation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32845
Localized Meshfree Methods for Solving 3D-Helmholtz Equation

Authors: Reza Mollapourasl, Majid Haghi

Abstract:

In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: Radial basis functions, Hermite finite difference, Helmholtz equation, stability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39

References:


[1] S. Britt, S. Tsynkov, and E. Turkel, “Numerical simulation of time-harmonic waves in inhomogeneous media using compact high order schemes,” Communications in Computational Physics, vol. 9, no. 3, p. 520–541, 2011.
[2] I. Babuˇska, F. Ihlenburg, E. T. Paik, and S. A. Sauter, “A generalized finite element method for solving the helmholtz equation in two dimensions with minimal pollution,” Computer Methods in Applied Mechanics and Engineering, vol. 128, no. 3, pp. 325–359, 1995. (Online). Available: https://www.sciencedirect.com/science/article/pii/004578259500890X
[3] G. Fasshauer, A. Khaliq, and D. Voss, “Using meshfree approximation for multi-asset American options,” Journal of the Chinese Institute of Engineers, vol. 27, no. 4, pp. 563 – 571, 2004.
[4] L. Ballestra and G. Pacelli, “Computing the survival probability density function in jump-diffusion models: A new approach based on radial basis functions,” Engineering Analysis with Boundary Elements, vol. 35, no. 9, pp. 1075 – 1084, 2011.
[5] M. Dehghan, M. Abbaszadeh, and A. Mohebbi, “The numerical solution of nonlinear high dimensional generalized benjamin-bona-mahony-burgers equation via the meshless method of radial basis functions,” Computers & Mathematics with Applications, vol. 68, no. 3, pp. 212 – 237, 2014. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0898122114002314
[6] A. Mohebbi, M. Abbaszadeh, and M. Dehghan, “The use of a meshless technique based on collocation and radial basis functions for solving the time fractional nonlinear schr¨odinger equation arising in quantum mechanics,” Engineering Analysis with Boundary Elements, vol. 37, no. 2, pp. 475 – 485, 2013. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0955799712002299
[7] M. Dehghan and A. Shokri, “A numerical method for solution of the two-dimensional sine-gordon equation using the radial basis functions,” Mathematics and Computers in Simulation, vol. 79, no. 3, pp. 700 – 715, 2008. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0378475408001778
[8] R. Mollapourasl, A. Fereshtian, and M. Vanmaele, “Radial basis functions with partition of unity method for American options with stochastic volatility,” Computational Economics, Sep 2017. (Online). Available: https://doi.org/10.1007/s10614-017-9739-8
[9] R. Mollapourasl, A. Fereshtian, H. Li, and X. Lu, “RBF-PU method for pricing options under the jump-diffusion model with local volatility,” Journal of Computational and Applied Mathematics, vol. 337, pp. 98–118, 2018. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0377042718300232
[10] T. Driscoll and B. Fornberg, “Interpolation in the limit of increasingly flat radial basis functions,” Computers & Mathematics with Applications, vol. 43, no. 3, pp. 413 – 422, 2002. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0898122101002954
[11] B. Fornberg and E. Lehto, “Stabilization of RBF-generated finite difference methods for convective pdes,” Journal of Computational Physics, vol. 230, no. 6, pp. 2270 – 2285, 2011. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0021999110006789
[12] V. Shankar, “The overlapped radial basis function-finite difference (RBF-FD) method: A generalization of RBF-FD,” Journal of Computational Physics, vol. 342, pp. 211 – 228, 2017. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0021999117303169
[13] R. Mollapourasl, M. Haghi, and A. Heryudono, “Numerical simulation of convection-diffusion-reaction equation and its application with radial basis function in finite difference mode,” Journal of Computational Finance, vol. 23, no. 5, pp. 33 – 73, 2020.
[14] R. Hardy, “Multiquadric equations of topography and other irregular surfaces,” Journal of Geophysical Research, vol. 76, no. 8, pp. 1905 – 1915, 1971.
[15] E. Kansa, “Multiquadrics-A scattered data approximation scheme with applications to computational fluid-dynamics-I: surface approximations and partial derivative estimates,” Computers & Mathematics with Applications, vol. 19, no. 8, pp. 127 – 145, 1990.
[16] M. Dehghan and A. Shokri, “Numerical solution of the nonlinear Klein-Gordon equation using radial basis functions,” Journal of Computational and Applied Mathematics, vol. 230, no. 2, pp. 400 – 410, 2009.
[17] H.-Y. Hu, Z.-C. Li, and A.-D. Cheng, “Radial basis collocation methods for elliptic boundary value problems,” Computers & Mathematics with Applications, vol. 50, no. 1, pp. 289 – 320, 2005.
[18] G. Fasshauer, Meshfree Approximation Methods with Matlab. Singapore: World Scientific Publishing Co, 2007.
[19] M. Buhmann, Radial basis functions: theory and implementations. New York: Cambridge University Press, 2003.
[20] N. Flyer, B. Fornberg, V. Bayona, and G. A. Barnett, “On the role of polynomials in RBF-FD approximations: I. Interpolation and accuracy,” Journal of Computational Physics, vol. 321, pp. 21 – 38, 2016. (Online). Available: http://www.sciencedirect.com/science/article/pii/S0021999116301632
[21] H. Wendland, Scattered Data Approximation, ser. Cambridge Monographs on Applied and Computational Mathematics. New York: Cambridge University Press, 2005, no. 17.
[22] E. Larsson, E. Lehto, A. Heryudono, and B. Fornberg, “Stable computation of differentiation matrices and scattered node stencils based on Gaussian radial basis functions,” SIAM Journal on Scientific Computing, vol. 35, no. 4, pp. A2096–A2119, 2013. (Online). Available: https://doi.org/10.1137/120899108
[23] B. Fornberg, E. Lehto, and C. Powell, “Stable calculation of Gaussian-based RBF-FD stencils,” Computers & Mathematics with Applications, vol. 65, no. 4, pp. 627 – 637, 2013. (Online).Available: http://www.sciencedirect.com/science/article/pii/S0898122112006529
[24] W. Zongmin, “Hermite-Birkhoff interpolation of scattered data by radial basis functions,” Approximation Theory and its Applications, vol. 8, no. 2, pp. 1–10, Jun 1992. (Online). Available: https://doi.org/10.1007/BF02836101
[25] F. J. Narcowich and J. D. Ward, “Generalized hermite interpolation via matrix-valued conditionally positive definite functions,” Math. Comput., vol. 63, pp. 661–688, 1994.